GMD - Preprints

GMD - Preprints
Preprints
The following lists only preprints without a corresponding final revised paper.
Manuscripts in open discussion
Revised manuscript not (yet) submitted
Revised manuscript under review for GMD
Revised manuscript accepted for GMD
Manuscript withdrawn or not accepted
Please choose a category.
Please change your selection of category and/or time.
23 Apr 2026
The one-Layer Antarctic model for Dynamical Downscaling of Ice–ocean Exchanges (LADDIE) version 2.0
Erwin Lambert, Franka Jesse, and Constantijn J. Berends
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The future contribution of Antarctica to sea-level rise is strongly dependent on the melting of floating ice shelves by the underlying ocean. Here, we present version 2 of the two-dimensional ocean model LADDIE. We evaluate the model by comparing it to three-dimensional ocean models and satellite observations, showing good performance at low computational cost. With this open-source model, we hope to contribute to the evolution toward more realistic melting in ice sheet model simulations.
Hide
23 Apr 2026
A Generalized Framework for Multi-Parameter Optimization of Numerical Wind–Wave Model: Application to Typhoon Waves near Taiwan Island
Zongyu Li, Shuiqing Li, Jinrui Chen, Yuan Kong, Yong Fang, Jiageng Han, Pei Zhu, and Po Hu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Accurate prediction of extreme ocean waves is crucial for coastal safety, yet numerical models often struggle during severe storms. We developed an automated method to adjust key model settings together, rather than one by one, using observations from typhoon events. Tests show that this approach clearly improves wave height predictions and reduces systematic errors. The method is transparent, efficient, and can be applied to many Earth system models to better simulate hazardous conditions.
Hide
23 Apr 2026
Evolving beyond collapse: An adaptive particle batch smoother for cryospheric data assimilation
Kristoffer Aalstad, Esteban Alonso-González, Norbert Pirk, Sebastian Westermann, Clarissa Willmes, and Ruitang Yang
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
AdaPBS is a new algorithm to combine observations with cryospheric numerical models. AdaPBS is an iterative algorithm that automatically adjusts computing effort to the task, allowing the implementation of early stopping strategies. We tested AdaPBS at multiple sites with different models, matching or outperforming standard methods, when compared against more complex (computationally expensive) algorithms.
Hide
23 Apr 2026
Improving the CLASSIC (v1.8) Snow Model to Better Simulate Arctic Snowpacks
Mickaël Lalande, Alexandre Roy, Libo Wang, Diana Verseghy, Vincent Vionnet, Florent Dominé, and Christophe Kinnard
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study enhances a snow model for Arctic environments by improving the heat exchanges within the snowpack and at its interfaces, revising the compaction scheme, and adding consideration of blowing snow sublimation losses. Simulations at ten Arctic, mid-latitude, and Alpine sites show significant reductions in simulated soil and snow temperature biases and improved simulated snow depth and density, which are key features to improve simulated energy, water, and carbon budgets in the Arctic.
Hide
22 Apr 2026
A wind-farm wake-turbulence parameterization for the WRF model (EWP v2.0)
Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We improve how weather models represent the turbulence generated by wind turbines within and behind wind farms. Rather than adding this turbulence only at grid squares with turbine locations, the new method transports it through the wake as it moves downwind. Tests against high-resolution simulations of an idealised wind farm showed better agreement in wake turbulence and more accurate reductions in wind speed, providing a more realistic picture of wake effects across the wind farm.
Hide
22 Apr 2026
EnsAI: An Emulator for Atmospheric Chemical Ensembles
Michael Sitwell
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
EnsAI is a newly developed artificial intelligence based program for efficiently generating ensembles of atmospheric chemical concentrations that can be used in assimilation and emissions inversions systems. Ensemble-based data assimilation methods are widely used for assimilation and emissions inversions, but are usually very computationally demanding. Once trained, EnsAI can run thousands of times faster than the physics-based models when run on graphics processing units.
Hide
22 Apr 2026
DCU-accelerated 3DVAR data assimilation with automatic differentiation for WRF-Chem
Hancheng Ye, Zengliang Zang, Wei You, Yiwen Hu, Ning Liu, and Yi Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Our study pioneers a PyTorch-based atmospheric assimilation system that leverages automatic differentiation and Deep Computing Unit acceleration to achieve order-of-magnitude speedups while establishing a direct pathway for future integration with deep learning.
Hide
21 Apr 2026
Transferable Hourly Ozone Forecasting with Transformers
Sindhu Vasireddy, Michael Langguth, and Martin Schultz
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study evaluates a transformer model for hourly air quality forecasting using past pollution, weather, and anthropogenic metadata (emissions, land use). It outperforms Copernicus Atmosphere Monitoring Service forecasts, especially in urban regions, with lower bias and improved stability. Trained in Germany, it transfers to South Korea with minimal adaptation, preserving geochemical relationships and showing strong cross-regional generalization.
Hide
21 Apr 2026
Predicting Forecast Errors with Diffusion Model for Uncertainty Quantification in Wind Speed Nowcasting
Yanwei Zhu, Aitor Atencia, Markus Dabernig, Yong Wang, and Shuyan Zhou
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The study proposes a diffusion-based framework for uncertainty quantification in wind speed nowcasting by learning forecast error distributions. By randomly generating errors and adding them to a physics-based wind nowcast, multiple forecast scenarios can be produced. The results improve forecast accuracy and provide reliable estimates of forecast uncertainty.
Hide
21 Apr 2026
Machine learning significantly improves the simulation of hourly-to-yearly scale cloud nuclei concentration and radiative forcing in polluted atmosphere
Jingye Ren, Songjian Zou, Honghao Xu, Guiquan Liu, Zhe Wang, Anran Zhang, Chuanfeng Zhao, Min Hu, Dongjie Shang, Lizi Tang, Ru-Jin Huang, Yele Sun, and Fang Zhang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
In this study, a new framework of cloud condensation nuclei (CCN) prediction in polluted region has been developed and it achieves well prediction of hourly-to-yearly scale across North China Plain. The study reveals the machine learning model can largely reduce the uncertainty in simulating cloud radiative forcing, illustrating the high sensitivity of climate forcing to changes in CCN. This improvement of our new model would be helpful to aerosols climate effect assessment in models.
Hide
21 Apr 2026
LFD (v1.0): Latent-Compression-Free Generative Diffusion with Geological Priors and Geophysical Regularization for Implicit Structural Modeling
Zhixiang Guo, Xinming Wu, Yimin Dou, Hui Gao, and Guillaume Caumon
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We present a fast way to generate subsurface structure models from seismic surveys while honoring known horizons and faults. Instead of compressing the data into a hidden representation, our method works directly with the original model values and applies geological constraints during generation. Tests on synthetic and real surveys show more realistic structures and efficient prediction, producing a 512 by 512 model in 1.56 seconds on an NVIDIA H20 graphics processing unit.
Hide
21 Apr 2026
Task aggregation as a strategy to optimize Earth System Model workflows in HPC: assessing real scenarios with EC-Earth
Pablo Goitia, Manuel G. Marciani, Miguel Castrillo, and Mario C. Acosta
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Earth System Model workflows commonly run on highly congested high-performance computing platforms, meaning that each individual workflow task potentially faces lengthy waiting times in the queues of the schedulers. In this work, we evaluate the task aggregation approach in EC-Earth3 workflows to reduce the queue times and, consequently, the total execution time. The results show an increase of up to 23.04 % in the actual simulated years per day, with queuing times reduced by up to 12.33 times.
Hide
20 Apr 2026
Development of the CCPP-Based GEFS-Aerosols Component in the Unified Forecast System for Subseasonal Prediction (UFS-Chem v1.0)
Li Zhang, Haiqin Li, Georg A. Grell, Partha S. Bhattacharjee, Gonzalo A. Ferrada, Benjamin W. Green, Shan Sun, Ligia Bernardet, Anders Jensen, Barry Baker, Li Pan, Jian He, Jordan Schnell, Ravan Ahmadov, Samuel Trahan, Dustin Swales, Anning Cheng, Fanglin Yang, Rebecca H. Schwantes, Brian C. McDonald, Dominikus Heinzeller, and Shobha Kondragunta
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Based on the operational Global Ensemble Forecast System-Aerosols at the National Centers for Environmental Prediction, we developed an upgraded system using the Common Community Physics Package framework that allows aerosol particles to directly influence radiation and cloud formation, including how precipitation removes particles from the atmosphere. Evaluation against observations and reanalysis data demonstrates improved forecast skill for weather and subseasonal prediction.
Hide
20 Apr 2026
Hybrid implicit–explicit XFEM simulation of injection-induced seismicity: resolving multi-scale rupture nucleation and dynamics
Mohammad Sabah, Mauro Cacace, Inga Berre, Iman R. Kivi, and Hannes Hofmann
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We developed a new way to simulate earthquakes triggered by fluid injection deep underground. These events involve both slow pressure build-up and rapid fault movement, which are difficult to capture together. Our method combines two calculation approaches and switches between them when needed. It reproduces earthquake behavior accurately while reducing computing time by up to seventy percent, making it more practical for assessing risks in energy and storage projects.
Hide
20 Apr 2026
Accelerating 3D Magnetotelluric Forward Modelling with Domain Decomposition and Order-Reduction Methods
Luis Tao, Alba Muixí, Sergio Zlotnik, Fabio Ivan Zyserman, Juan Carlos Afonso, and Pedro Diez
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We present a new approach for performing 3D magnetotelluric forward simulations more efficiently. Conventional methods become increasingly demanding as model resolution increases. Our approach combines numerical techniques that reduce problem size and computational cost. Tests on benchmark examples and a real-world case demonstrate speed-ups of over 90% with acceptable loss of accuracy, enabling high-resolution simulations within practical time frames.
Hide
17 Apr 2026
GLIDE-SOL: A GPU-accelerated Global Lightweight Infrastructure for Diagnostic Environmental Modeling with SOLWEIG
Andrea Zonato, Harsh G. Kamath, Naveen Sudharsan, Luca Monaco, Jonas Kittner, Luise Wolf, Matthias Andreas Demuzere, Ariane Middel, Benjamin Bechtel, and Massimo Milelli
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Cities need fast, reliable heat-stress maps to plan cooling measures and protect people. We built an automated workflow that gathers global public data, runs an outdoor comfort model much faster on graphics processing units, and adds simple corrections for wind and night-time warming. Tested in Dortmund against many sensors, errors fell from about ten to under three degrees Celsius.
Hide
16 Apr 2026
The Ice Sheet State and Parameter Estimator (ICESEE) Library (v1.0.0): Ensemble Kalman Filtering for Ice Sheet Models
Brian Kyanjo, Talea L. Mayo, and Alexander A. Robel
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We developed ICESEE, an open-source tool that helps scientists combine observations with physics-based models to better understand how ice sheets change over time. It improves estimates of current conditions and also helps identify hard-to-measure factors such as friction beneath the ice. Our tests indicate that it works efficiently on large computing systems and can be used with multiple models, making it useful for more reliable long-term studies of ice-sheet change and sea-level rise.
Hide
14 Apr 2026
Enhancing Data-Driven Weather Forecasting via Gated Relative Position Encoding and Spatial-Aware Feed-Forward Network
Leyi Wang, Duo Zhang, Jerry Zhijian Yang, Baoxiang Pan, Dazhi Xi, and Xiaoyu Huang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We built a new artificial intelligence model to forecast the weather, designed to better understand air movement and how landscapes shape atmospheric motions. We trained this model on historical data to predict future conditions. Our tool proved highly accurate at predicting weather up to three days in advance. It also outperforms top models over land area. Our method requires significantly less resources. It paves the way for more efficient and more accurate daily weather forecasts worldwide.
Hide
14 Apr 2026
Modeling thermodynamically consistent phase transitions in multi-component assemblages: An entropy method for geodynamic models
Ranpeng Li, Juliane Dannberg, Rene Gassmöller, and Robert Myhill
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Deep inside Earth, the minerals that make up rocks transform into different phases under high temperature and pressure. These transformations change rock density, affecting how material moves and how Earth’s interior evolves. We developed a new method to better model these effects in computer simulations. Our results show that even small density differences can lead to large changes in rising plumes and sinking slabs, which are key processes linked to volcanoes and earthquakes.
Hide
14 Apr 2026
UKCM2-LL: a new low-resolution GC5 configuration with constrained climate sensitivity – methodology and development
John W. Rostron, Alejandro Bodas-Salcedo, David M. H. Sexton, Colin G. Jones, Edward W. Blockley, Till Kuhlbrodt, Jane P. Mulcahy, Tamzin E. Palmer, Saloua Peatier, Mark A. Ringer, Steven T. Rumbold, Benjamin M. Sanderson, Yongming Tang, and Martin R. Willet
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The Met Office’s latest weather and climate model warms very strongly in response to increases in carbon dioxide. We created a modified version of the model with a more moderate warming response by adjusting key model parameters, using both automated methods and expert judgement. The new model matches historical temperatures more closely and is better suited for studies of long‑term climate, but has reduced overall accuracy when simulating the baseline climate.
Hide
14 Apr 2026
CMIP7 Data Request: co-created guidance for the production of CMIP7 data [v1.2.2.3]
Chloe Mackallah, Martin Juckes, James Anstey, Beth Dingley, Charlotte Pascoe, Gaëlle Rigoudy, Marie-Pierre Moine, Tomas Lovato, Alison Pamment, Martin Schupfner, Michio Kawamiya, Tommi Bergman, Charles Koven, Eleanor O'Rourke, Briony Turner, Daniel Ellis, and Matthew Mizielinski
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This paper describes the creation of a new set of output data requirements for upcoming global climate model experiments performed for CMIP7, an international climate modelling activity. Experts from the community helped to co-create a database that describes which data should be produced, and the scientific justifications behind these choices. It supports growing climate research and policy needs by linking experiments and variables to scientific objectives and real‑world applications.
Hide
13 Apr 2026
ShyBFM v1.0: unstructured grid advection-diffusion-reaction modelling for coastal biogeochemical processes
Jacopo Alessandri, Giulia Bonino, Tomas Lovato, Momme Butenschön, Lorenzo Mentaschi, Giorgia Verri, Ivan Federico, and Nadia Pinardi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Coastal seas are strongly shaped by complex coastlines, shallow depths, and inputs from rivers, which influence marine life and water quality. This study introduces a new high-resolution modelling system that combines ocean circulation and marine ecosystem processes on unstructured grids. Applied to the northern Adriatic Sea, the model realistically captures seasonal changes in key biogeochemical variables, offering improved tools to support coastal environmental management.
Hide
10 Apr 2026
Representation of the nitrogen cycle and its coupling with the carbon cycle in ISBA (SURFEX v9) the land surface model: evaluation using two Free-Air CO
Enrichment experiment sites
Jeanne Decayeux, Bertrand Decharme, Romain Darnajoux, and Christine Delire
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The article describes the implementation of the nitrogen cycle in the land surface model ISBA. The model is evaluated using Free Air CO
Enrichment experiments. A comparison with a multi-model analysis shows that the nitrogen model version performs better than the carbon-only version, notably a reduced sensitivity to elevated CO
, and smaller C stocks. We also present a detailed analysis of the simulated N dynamics in the soil.
Hide
09 Apr 2026
GOFS16: an operational global ocean analysis and forecasting system at eddy-resolving resolution
Simona Masina, Andrea Cipollone, Doroteaciro Iovino, Stefania Ciliberti, Rita Lecci, Sergio Cretí, Vladyslav Lyubartsev, Giovanni Coppini, and Emanuela Clementi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The paper presents GOFS16, an eddy-resolving global operational ocean and sea ice forecasting system which provides 6-day forecasts of three-dimensional temperature, salinity, currents, sea level, and sea ice properties. The system assimilates satellite and in situ observations using a 3D variational data assimilation scheme. Validation is conducted routinely using global and regional metrics. Results indicate that GOFS16 performs within the expected range of skill for current global systems.
Hide
09 Apr 2026
Meso-NH-ISO v1.0: a water stable isotopes scheme in the non-hydrostatic mesoscale atmospheric model Meso-NH. Application to a 2D West African squall line
Christelle Barthe, Françoise Vimeux, Camille Risi, and Sören François
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We implemented water stable isotopes in the non-hydrostatic mesoscale atmospheric model Meso-NH. We validated this isotopic version (Meso-NH-ISO) with a simulation of a well-documented squall line in the Sahel region. In future works, simulations with Meso-NH-ISO will be done on real cases of cyclones or squall lines. The goal is to better interpret and quantify isotopic observations on the field in terms of atmospheric processes that drive development and intensity of those thunderstorms.
Hide
08 Apr 2026
A new Earth Observation–based WRF configuration for urban regional climate simulations over Paris
Iraklis Kyriakidis, Vasileios Pavlidis, Maria Gkolemi, Zina Mitraka, Nektarios Chrysoulakis, Josipa Milovac, Jesus Fernandez, and Eleni Katragkou
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study introduces a novel approach to incorporating city-specific Earth Observation (EO) data into an urban canopy model named BEP-BEM integrated in WRF. We highlight the added value given by BEP-BEM in the representation of the urban processes compared to a slab urban bulk approach. The implementation of the EO data improved specific aspects of the model performance.
Hide
08 Apr 2026
ORACLE-lite (v3.0): A reduced-complexity module for simulating organic aerosol formation and evolution in long term chemistry-climate simulations
Alexandra P. Tsimpidi and Vlassis A. Karydis
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We developed a simplified representation of organic aerosol formation and evolution for long-term climate simulations. Organic aerosol affects air quality, human health, and climate but is difficult to model due to its complexity. Our approach preserves the key physical and chemical processes while reducing computational cost by about 14%. The model reproduces observed global patterns reasonably well, enabling more efficient and reliable studies of long-term changes in air pollution and climate.
Hide
08 Apr 2026
TIPMIP-OCEAN experimental protocol phase 1: Tipping dynamics of the AMOC
Didier Swingedouw, Laura Jackson, Aixue Hu, Anastasia Romanou, Nicole C. Laureanti, Wilbert Weijer, Sina Loriani, Bette Otto-Bliesner, Ayako Abe-Ouchi, Lucas Almeida, Alessio Bellucci, Reyk Börner, Gokhan Danabasoglu, Donovan P. Dennis, Marion Devilliers, Sybren Drijfhout, Jonathan Donges, Friederike Fröb, Thomas L. Frölicher, Guillaume Gastineau, Heiko Goelzer, Chuncheng Guo, Urs Hofmann, Anna Höse, Colin Jones, Torben Koenigk, Ann Kristin Klose, Valerio Lembo, Jose Licon-Salaiz, Ken Mankoff, Virna Meccia, Irina Melnikova, Oliver Mehling, Laurie Menviel, Juliette Mignot, Jon I. Robson, Gavin A. Schmidt, Robin Smith, Yuchen Sun, Irene Trombini, Matteo Willeit, Richard Wood, Fanghua Wu, Lin Zhaohui, and Ricarda Winkelmann
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study presents a plan for climate model experiments to better understand how changes in freshwater in the North Atlantic affect major ocean currents. We designed coordinated simulations to test their response to warming, added freshwater, and possible recovery after weakening. Comparing results across models and past climate evidence helps improve confidence in projections and assess risks of large ocean circulation changes.
Hide
07 Apr 2026
Simulating the impacts of utility-scale photovoltaic installations with a physically based coupled WRF-PV model
Yiran Chen, Jiming Jin, Yimin Liu, Jannik Heusinger, Jesús Carrera, and Zeyu Zhou
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Solar power plants are expanding rapidly worldwide, but their impacts on local climate remain uncertain. In this study, we developed a coupled model that explicitly represents interactions between solar panels, land surface, and the atmosphere. Simulations show that large solar farms can cool the land surface while warming the air near the ground, reduce incoming shortwave radiation, and shift rainfall toward more extreme events.
Hide
07 Apr 2026
Optimization of the Fast Layer Transmittance Algorithm in RTTOV v13.1 for Strong Water Vapor Absorption Channels of the FY-3F HIRAS-II Instrument Using LBLRTM v12.11
Panxiang Zhang, Peng Zhang, Gang Ma, Rui Li, Lu Lee, Wenguang Bai, and Chengli Qi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
To enhance atmospheric transmittance accuracy in strong water vapor absorption bands, this study proposes an optimized scheme for the fast transmittance algorithm applied to the Hyperspectral Infrared Atmospheric Sounder-II. It introduces a transmittance threshold for sample selection and a weighted least squares regression with transmittance weighting. Validation against line-by-line models and observations shows significant improvements in forward model accuracy and stability at 6.7 μm.
Hide
02 Apr 2026
Convolution Based Techniques for Computing Self Attraction and Loading in MOM6
Anthony Chen, He Wang, Brian Arbic, and Robert Krasny
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Self Attraction and Loading (SAL) is an important force that affects many oceanic motions, including tides. Computing SAL is challenging and ocean models neglected to include the impacts of SAL for a long time. Recent work has proposed a method for incorporating the effects of SAL, but the method has several limitations that limit the accuracy. This work proposes an alternative method. Tests of this new method in an ocean model indicate that it reduces the amount of error in the modeled tides.
Hide
01 Apr 2026
SLUCM+BEM (v2.0): implementing a prognostic indoor temperature scheme for application to global cities
Yuya Takane, Yukihiro Kikegawa, Zhiwen Luo, Hiroyuki Kusaka, and Sue Grimmond
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We developed and released the single-layer urban canopy model coupled with building energy model v2. This incorporates a new scheme enabling dynamic changes in indoor temperature. This allows the model to be applied not only to air-conditioned conditions but also to non-air-conditioned scenarios, making it applicable to all seasons and cities worldwide. This upgrade facilitates the assessment of climate change adaptation measures for both outdoor and indoor environments.
Hide
01 Apr 2026
SeapoPym v0.1: Implementation of the SEAPODYM low and mid trophic levels in Python with a flexible optimisation framework
Jules Victor Lehodey, Alexandre Mignot, Alexandre Ganachaud, Sarah Albernhe, and Simon Nicol
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Marine zooplankton transfer energy from microscopic algae to fish and larger predators. Understanding their distribution helps predict how oceans respond to climate change. We developed SeapoPym, a freely available model that simulates zooplankton using ocean temperature and plant productivity. This tool lets scientists test biological hypotheses and estimate parameters from observations.
Hide
31 Mar 2026
Evaluating the radiative fidelity of PALM (v25.04) in high-resolution: impact of diverse urban morphology and vegetation on short-wave radiation
Jelena Radović, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jakub Jura, Pavel Krč, Hynek Řezníček, and Jaroslav Resler
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
In this experiment, the Parallelized Large-Eddy Simulation Model (PALM)’s performance in simulating incoming and outgoing short-wave radiation in a densely built, highly heterogeneous urban environment was validated. In particular, we assessed whether the micro-scale model realistically resolves the effects of three-dimensional urban morphology and vegetation on short-wave radiation, including its propagation, shading, reflection, and attenuation within the simulated domain.
Hide
31 Mar 2026
Design and Implementation of a Newtonian Relaxation Scheme in the NOAA GFDL Sea Ice Model (SIS2)
Dmitry S. Dukhovskoy, Theresa Cordero, Katherine Hedstrom, Michael Alexander, Michael Jacox, Robert Hallberg, Matthew Harrison, and Jessie Liu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
A method for improving sea ice simulations by adjusting ice cover and thickness using observations or analysis data has been implemented in a regional sea ice model. Tests show improved representation of ice along the edges and within the ice-covered area. This suggests the method can provide more accurate initial conditions for forecasts, which is important for predicting ocean, sea ice, and ecosystem conditions in polar regions.
Hide
31 Mar 2026
Precipitation Nowcasting Based on Convolutional LSTM with Spatio-Temporal Information Transformation Using Multi-Meteorological Factors
Dufu Liu, Feihu Huang, Peng Zheng, Xiaomeng Huang, Xi Wu, Xia Yuan, Jiafeng Zheng, Xiaojie Li, and Jing Hu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Due to the limitations of past data-based models and the high cost of numerical weather prediction computing, accurately forecasting precipitation proximity remains challenging. A dual encoder-decoder framework is proposed to enhance short-term forecasting and reduce underestimation in extreme precipitation by using spatio-temporal information conversion equations and adaptive weighted gradient loss. Demonstrates better accuracy than existing deep learning methods in precipitation datasets.
Hide
31 Mar 2026
Optimizing WRF physics for multi-decadal simulation of near-surface climate over arid Xinjiang, China
Yang Xu, Liang Zhang, Mengxin Bai, Shenzhen Tian, and Zhixin Hao
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 8 comments)
Short summary
Short summary
We compared many model configurations to identify a reliable setup for long-term climate simulation in arid Xinjiang, China. Dozens of options were tested over six decades for temperature, rainfall, wind, humidity, radiation, and pressure. Performance depends strongly on how atmospheric and land processes are combined. We recommend a balanced configuration to support climate studies and high-quality data products in dry, complex terrain.
Hide
30 Mar 2026
Evaluation and improvement of CAMS-derived CCN number concentrations using in-situ measurements
Yannick Emanuel Anders, Karoline Block, Mira Pöhlker, and Johannes Quaas
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Particles in the atmosphere can trigger the formation of cloud droplets, affecting cloud properties and climate. This study evaluates a new global dataset of these particles with measurements from 25 sites around the world. The variability in time and space and their conditional formation behaviour is analysed. The authors identify systematic biases and introduce a simple correction based on observations that greatly improves the dataset’s accuracy.
Hide
27 Mar 2026
GEE-DisALEXI: Cloud-Based Implementation of the DisALEXI Model for Evapotranspiration Monitoring Using Google Earth Engine
Yun Yang, Martha Anderson, Charles Morton, Yanghui Kang, Feng Gao, Weina Duan, Hui Liu, John Volk, and Christopher Hain
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Evapotranspiration (ET) describes how water moves from land to the atmosphere and is key to understanding crops, ecosystems, and drought. We developed a cloud-based system that uses satellite data to map ET at high resolution over large areas. This approach makes it easier to monitor water use, support farmers, and improve drought detection, helping better manage water resources.
Hide
27 Mar 2026
A Raster–Vector Framework for Multi-Scale Hydrological–Hydraulic Modeling Across Large Domains
Mohamed Amine Berkaoui, Mohamed Saadi, François Colleoni, Ngo Nghi Truyen Huynh, Ahmad Akhtari, Kevin Larnier, Hélène Roux, and Pierre-André Garambois
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We present an integrated hydrological–hydraulic (H&H) modeling framework that combines grid-based hydrology with vector-based river routing, leveraging sub-grid information derived from high-resolution topography. This approach improves the representation of river networks and drainage areas across spatial resolutions, reducing errors and spatial distortions associated with regular grid discretization, and leading to more stable streamflow simulations across scales.
Hide
25 Mar 2026
The 4-mode Modal Aerosol Module in C++ (MAM4xx) v1.0: Representing Prognostic Aerosols in a Global Cloud-System Resolving Atmosphere Model for GPU Exascale Computing
Jerome D. Fast, Balwinder Singh, Oscar Diaz-Ibarra, Jeff Johnson, Chandru Dhandapani, Brian Gaudet, Taufiq Hassan, Meng Huang, Jaelyn Litzinger, James Overfelt, Kyle Pressel, Michael Schmidt, Shuaiqi Tang, Adam C. Varble, Hui Wan, Mingxuan Wu, Kai Zhang, and Po-Lun Ma
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We ported a prognostic representation of aerosols to C++ and integrated it into an Earth system model that runs on powerful GPU supercomputers. The code conversion approach keeps the same detailed physics as the Fortran version, was carefully tested, and results show that new code produces aerosol simulations consistent with real‑world data over the central U.S. in spring 2016. Future work will optimize the code for GPUs so to reduce the overall computational time.
Hide
25 Mar 2026
New classes of climate model emulators to improve paleoclimate reconstructions
Auguste Gaudin and Myriam Khodri
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Reconstructing past climate variability requires computationally efficient models able to capture the behaviour of complex climate systems. We develop a suite of climate model emulators that improve the representation, reconstruction, and prediction of spatial climate variability compared to traditional approaches. Results highlight the importance of predictability-oriented representations and nonlinear dynamical memory for scalable emulators suited to paleoclimate data assimilation frameworks.
Hide
24 Mar 2026
Sensitivity of Arctic mixed-phase cloud simulations to ice microphysical modifications in the WDM6 scheme of WRF (v4.3.1)
Hyun-Joon Sung, Kyo-Sun Sunny Lim, Song-You Hong, JiHoon Shin, Baek-Min Kim, and Ji-Hun Choi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Arctic clouds containing both liquid droplets and ice crystals are difficult to simulate. We tested how ice-related changes in a weather model, designed for temperate regions, perform in the Arctic. Ice crystal shape is the dominant factor: spherical crystals nearly eliminate cloud ice, shifting it to snow. Changes producing moderate effects in temperate regions cause extreme responses in the Arctic, showing model improvements must be tested across different climates.
Hide
24 Mar 2026
Advancing the Capabilities for Efficient Hurricane-Centric Simulations with the Atmospheric Model ICON
Fabian Senf and Roxana Cremer
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Computer models for hurricane prediction are becoming increasingly detailed but require substantial computing resources. We developed a flexible approach that follows hurricanes as they move, applying high-resolution simulations only where needed. This method reduces computing costs by factors of 13–175 while achieving resolutions down to 300 meters. The approach enables more efficient hurricane research and improved understanding of tropical dynamics.
Hide
24 Mar 2026
DDA-BNN v1.0: A Morphology-Aware Surrogate Model for the Optical Properties of Black Carbon–Containing Particles
Payton Beeler, Sam Donald, and Laura Fierce
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 4 comments)
Short summary
Short summary
We developed a surrogate model to predict how black carbon particles absorb and scatter light based on their size, shape, and mixing with other aerosol species. The model was trained on detailed physics simulations and also estimates uncertainty caused by limited training data and unresolved internal structures. It outperformed common simplified particle assumptions, especially for scattering, and can help target new simulations to improve predictions of black carbon’s radiative effects.
Hide
24 Mar 2026
LaScape 1.0: An open-source module for three-dimensional thermo-mechanical and landscape evolution modeling
Yun Luo, Jianfeng Yang, Boris J. P. Kaus, Anton Popov, Shaohui Liu, Xiaoping Yuan, and Liang Zhao
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The quantitative interaction between tectonics and landscape remains incompletely understood. We developed a novel 3D numerical tool coupling tectonic and surface processes, enabling the investigation of their dynamic interplay. We test different tectonic scenarios, such as oceanic subduction and continental collision, with coupled tectonic-landscape evolution, which sheds light on how deep processes shape surface topography and vice versa, advancing our understanding of Earth system evolution.
Hide
24 Mar 2026
TRAILS – A novel framework for time-height-resolved attribution of long-range transported wildfire smoke
Johanna Roschke, Benedikt Gast, Martin Radenz, Albert Ansmann, Patric Seifert, George McCosh, and Heike Kalesse-Los
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This research introduces a new method that combines model simulations with satellite observations to attribute the influence of wildfire smoke on an airmass. By dynamically determining the height of smoke plumes, we overcome a key limitation of earlier fixed reception-height approaches. This advancement is crucial for improving our understanding of how wildfire emissions influence cloud formation and the broader Earth's climate system.
Hide
23 Mar 2026
Regularisation of the 4DEnVar Data Assimilation method for Calibration of Land Surface Models
Natalie Douglas, Simon Beylat, Tristan Quaife, Philippe Peylin, Nina Raoult, and Ross Bannister
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study investigates a statistical method, called 4DEnVar, to calibrate uncertain land surface model parameters against observations. This method is easy to use but can lead to unphysical parameter values. The study explores the causes of this while proposing a simple way to overcome the problem. We show that the 4DEnVar method exhibits considerable versatility by applying the method to two different land surface models, under different settings, to calibrate photosynthetic parameters.
Hide
20 Mar 2026
HTAP3-OPNS: Ozone, PM, Nitrogen and Sulphur Deposition – multi-model experiments to support the revision of the CLRTAP Gothenburg Protocol
Tim Butler, Tabish Ansari, Claudio A. Belis, Elisa Bergas-Masso, Willem van Caspel, Hilde Fagerli, Johannes Flemming, Marta Garcia Vivanco, Paul Griffiths, Douglas S. Hamilton, Coralina Hernandez Trujillo, Lena Höglund-Isaksson, Vincent Huijnen, Matthew Kasoar, Johannes W. Kaiser, Gerbrand Koren, Zbigniew Klimont, Florian Lindl, Aura Lupascu, Mariano Mertens, Martijn Schaap, Steven T. Turnock, Oliver Wild, Philipp Weiss, Jacek Kaminski, Rosa Wu, and Terry Keating
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Air pollution travels across continents, meaning emissions in one region can affect air quality far away. To better understand this, scientists from many groups are planning to run coordinated computer simulations of the atmosphere. By comparing results across models and emission scenarios, the planned study will show how pollution moves between regions and which sources matter most, helping governments design more effective air quality policies.
Hide
20 Mar 2026
Benchmarking a new urban scheme in the ORCHIDEE v2.2 land surface model
Morgane Lalonde, Sophie Bastin, Ludovic Oudin, Pedro Felipe Arboleda-Obando, and Agnès Ducharne
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Some climate models still represent cities as if they were natural ground. For one of these models, we built a new way to represent cities. The update includes how reflective surfaces are, building height, stored heat, and how much ground is sealed. The novelty is to treat sealed ground not only at the surface, but also below it. Tested at twenty urban sites, the new version better represents exchanges of energy between the ground and the air, supporting more reliable urban climate studies.
Hide
20 Mar 2026
Stochastic perturbation of inputs to parametrisation schemes machine-learnt from high-resolution model variability
Helena Reid and Cyril Julien Morcrette
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
Atmospheric models used for weather and climate benefit from representing the random effects of processes that are too small to be resolved by the model. Here, very detailed simulations are used to learn about the amount of variability that would be expected in a coarser model. We then use machine learning techniques to predict that fine-scale variability and show that including these predictions improve some idealised simulations over the tropical ocean.
Hide
18 Mar 2026
Integrating Ozone–vegetation Damage Schemes into SSiB4/TRIFFID: Evaluation of Six Parameterizations and Refinement of Ozone Decay Process Across Plant Functional Types
Lingfeng Li, Bo Qiu, Siwen Zhao, Xin Miao, Chaorong Chen, Jiuyi Chen, Yueyang Ni, Xin Huang, Haishan Chen, and Weidong Guo
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Ground-level ozone can harm plant photosynthesis, but models describe these effects in different ways. In this study, we implemented six ozone damage schemes in a land surface model and compared their behaviour within a unified framework. We also improved one scheme by using observations of leaf lifespan to better represent how ozone stress accumulates and recovers in plants. This work helps identify key differences among schemes and supports the development of more realistic models.
Hide
18 Mar 2026
The CMIP6-downscaled CORDEX-Southeast Asia (SEA) ensemble: evaluation and benchmarking for megacities of SEA
Phuong Loan Nguyen, Lisa V. Alexander, Thanh Ngo-Duc, Faye Cruz, Jerasorn Santisirisomboon, Liew Juneng, Donaldi S. Permana, Jing Xiang Chung, Julie Mae Dado, John L. McGregor, Grace Redmond, Tse Wai Po, Fredolin Tangang, Tan Phan-Van, Son C. H. Truong, Marcus Thatcher, Long Trinh-Tuan, Ummu Ma’rufah, Jennifer Tibay, Giovanni Di Virgilio, and Stephen White
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
We introduce an ensemble of climate models that simulate Southeast Asia's future climate for 1960–2100. We (1) showed how well these models simulate observed climate by comparison with multiple observations, (2) applied a standardized benchmarking framework to model outputs to select a subset of models for further dynamical downscaling at kilometre-scale over megacities of SEA. These international efforts can help guide climate model design and the use and interpretation of climate projections.
Hide
17 Mar 2026
CMIP6 data usage: Lessons learned from more than 200 million downloads
Juliette Lavoie, Aude Carreric, Alistair Duffey, Giovanni Chellini, and Elisa Ziegler
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The Coupled Model Intercomparison Project (CMIP) is a large collaborative project to better understand the Earth’s climate system. The data produced through this project is downloaded by users around the world. In this paper, we analyze the patterns of downloads and the usage of this massive dataset. From this analysis, we make some recommendations for future data production and usage tracking.
Hide
17 Mar 2026
PLSTM-Reg v1.0: A regional physics-encoded LSTM model for simulating reservoir operations under data scarcity
Bin Yu, Yanan Chen, and Yi Zheng
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 7 comments)
Short summary
Short summary
We introduce a deep learning approach that extracts shared operating patterns from diverse, data-rich reservoirs and transfers this knowledge to limited-data areas, yielding skillful simulations of storage and release. Using satellite observations, the model also reconstructs historical behavior in no-data systems. Together, these advances provide a scalable foundation for addressing pressing data gaps in reservoir operations and better supporting large-scale and long-term water management.
Hide
17 Mar 2026
DeepMelt-GL v1: A neural network emulator of ice-shelf melt rates for use in ocean models which partially resolve ice-shelf cavities
Helen Ockenden, Clara Burgard, Pierre Mathiot, Christoph Kittel, Achille Gellens, Cécile Agosta, and Nicolas C. Jourdain
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Since numerical computing is expensive, climate models must decide between having a high spatial resolution or running for long time periods. Here, we develop a simple neural network to emulate small-scale processes occurring beneath Antarctic ice shelves, which allows sub-shelf melt and ice-ocean interactions to be included in global ocean models which can run for multiple centuries. This neural network will help us to understand how ocean circulation may change in the future.
Hide
16 Mar 2026
Process-based evaluation of green roof models for assessment of heat mitigation efficacy in WRF (v4.3.1) and EnergyPlus (v8.6.0)
Maria Martinez Mendoza, Alireza Saeedi, James A. Voogt, and E. Scott Krayenhoff
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Green roofs can help cool cities, but models must represent them accurately to quantify this potential. Yet few studies evaluate green roof models against real data. We evaluated two versions of EcoRoof, the green roof module in EnergyPlus, and a green roof option for WRF using measurements from London, Ontario. EcoRoof generally matched observed heat fluxes, surface temperature, and soil moisture, while WRF overestimated heat and underestimated cooling.
Hide
13 Mar 2026
Implementation and Evaluation of an Observation-Constrained Secondary Organic Aerosol Parameterization in MOZART–GOCART Chemistry in WRF-Chem
Rajmal Jat, Akash Sagar Vispute, Sachin D. Ghude, Rajesh Kumar, Vinayak Sinha, Baerbel Sinha, Gaurav Govardhan, Zhining Tao, Prafull P. Yadav, Sandeep Wagh, Sreyashi Debnath, Aditi Rathore, and Madhavan Rajeevan
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
This study developed a simplified and computationally efficient secondary organic aerosol parameterization in the MOZART–GOCART scheme within WRF-Chem using volatile organic compound observations in Delhi. This parameterization was evaluated for a period with severe pollution influenced by crop residue burning. Results show that the approach improves the model’s ability to reproduce organic aerosols and fine particulate matter while remaining much faster than more complex chemical schemes.
Hide
13 Mar 2026
Global fully coupled climate-aerosol CMA-CPSv4: aerosol simulation performance
Mengzhe Zheng, Tongwen Wu, Yixiong Lu, Weihua Jie, Yiming Liu, Xiaoge Xin, Jie Zhang, He Zhao, Xindan Zhang, and Jiajie Yang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The dynamic evolution and interactions of aerosols are first incorporated into the China Meteorological Administration Climate Prediction System version 4 (CMA-CPSv4). This paper evaluates the prediction system's simulation performance for aerosols. The results show that the CMA-CPSv4 reasonably simulates the spatial distribution of aerosols. The reasonable simulation of aerosols is fundamental for studying the impact of aerosols on climate prediction in our next work.
Hide
12 Mar 2026
Development of the TCWA2 Bulk Cloud Microphysics Scheme and Its Integration with a Dual-Polarization Radar Operator for Forecasting Applications
Tzu-Chin Tsai, Jen-Ping Chen, Zhiquan Liu, Siou-Ying Jiang, Rong Kong, Ying-Jhang Wu, Junmei Ban, Ling-Feng Hsiao, Yu-Shuang Tang, Pao-Liang Chang, and Jing-Shan Hong
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Weather radars observe rain and ice inside clouds, but models often cannot fully use this information because their cloud physics schemes do not describe the particle properties needed to simulate radar signals. This study develops a new cloud microphysics scheme directly linked to a radar operator that uses the same particle information. Tests using an idealized and a real case show that TCWA2 can reproduce observed radar features, supporting improved radar-based weather forecasting.
Hide
12 Mar 2026
Phenomena and Processes: A New MJO Diagnostic Framework using Moisture Mode Theory as the Testbed
Chun-Hao Chang, Kai-Chih Tseng, and Eric D. Maloney
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
This study developed a unified Madden-Julian Oscillation (MJO) diagnostic framework that bridges the gap between two existed types of diagnostics (i.e. phenomenological diagnostics and process-oriented diagnostics). Utilizing this framework, we can attribute simulated MJO biases in general circulation models (GCMs) to specific physical processes.
Hide
12 Mar 2026
Code accessibility and code quality across phases of the models of the Coupled Model Intercomparison Project
Michael García-Rodríguez, Javier Rodeiro-Iglesias, and Juan A. Añel
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We studied how accessible and reliable the computer code behind major climate models has been over time. By reviewing different phases of the Coupled Model Intercomparison Project, we found improvements in transparency and coding practices, but also gaps that limit reproducibility. Our work suggests practical steps to make future climate research more open, traceable, and trustworthy for scientists and society.
Hide
11 Mar 2026
CESM2/CARMA Cloud and CARMA Aerosol Model Descriptions
Yunqian Zhu, Cheng-Cheng Liu, Charles Bardeen, Lu Wang, Simone Tilmes, Ilaria Quaglia, Christopher M. Maloney, Francis Vitt, and Owen Brian Toon
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
The Community Aerosol and Radiation Model for Atmospheres (CARMA) is a sectional microphysical model widely used to study the formation of aerosols and clouds. This paper presents an update to the CARMA model algorithms since Toon et al. 1988, with a focus on the newly developed CARMA Cloud model.
Hide
11 Mar 2026
Deploying Machine Learning components coupled to Earth System Models with OASIS3-MCT (v6) and Eophis (v1.1)
Alexis Barge, Julien Le Sommer, Andrea Storto, and Sophie Valcke
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Scientists use programs, called Earth System Models, to study and predict climate. These models are based on physical theories but can be completed with AI tools. However, combining these tools with traditional models is difficult due to their different nature. Our research introduces a new method that connects these AI tools with existing climate models. We tested this method by integrating it with an ocean model. This work should help scientists explore new ways of making climate predictions.
Hide
11 Mar 2026
Assimilation of ground based lidar and ceilometer observations of aerosols from the European E-Profile network into ECMWF's Integrated Forecasting System (IFS-COMPO, CY49R1)
Michael Kahnert, Melanie Ades, Mickaël Bacles, Johannes Flemming, Vincent Guidard, Alexander Haefele, Robin J. Hogan, Samuel Rémy, and Eric Sauvageat
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides quality-controlled information related to air quality and health. We explore the possibility to constrain the CAMS global forecasting model by use of ground-based observations of laser light backscattered by particulate matter. We find that the vertical distribution of particulate matter can be predicted more faithfully with this approach, which can have implications for air quality forecasts provided by CAMS to end users.
Hide
11 Mar 2026
Validation of the ALARO1-SFX (CY43T2) regional climate model over Belgium across different resolutions
Wout Dewettinck, Hans Van de Vyver, Daan Degrauwe, Rafiq Hamdi, Michiel Van Ginderachter, Bert Van Schaeybroeck, Kwinten Van Weverberg, Kobe Vandelanotte, Steven Caluwaerts, and Piet Termonia
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study assesses an updated version of the ALARO regional climate model over Belgium at multiple resolutions, by using long-term climate simulations. Incorporating the land surface model SURFEX and simulating at higher resolutions led to improved simulation of temperature, precipitation, and extreme rainfall events. These findings support the value of high-resolution modelling for better representing local climate extremes and informing adaptation measures.
Hide
10 Mar 2026
Process-based upgrades to the WRF multi-layer green-roof scheme (WRF-MLGR v2.0) and evaluation against field observations
Alireza Saeedi, Maria Martinez Mendoza, Eric Scott Krayenhoff, James Voogt, Andrea Zonato, Sylvie Leroyer, and Claudia Wagner-Riddle
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Green roofs can help cool cities, but models must represent how heat and water move through soil and plants correctly. We improved the green roof part of the WRF multi-layer weather model by adding more realistic descriptions of evaporation, heat storage, and plant water uptake. When tested against real measurements from a roof in London, Ontario, Canada, the updated model more accurately matched observed ground heat and latent heat fluxes.
Hide
10 Mar 2026
Conservation of Heat in the Coupled Arctic Prediction System (CAPS v1.1): Comprehensive model evaluation based on the MOSAiC observations
Chao-Yuan Yang, Fengguan Gu, Jiping Liu, Annette Rinke, Hu Yang, and Xiaoxu Shi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Accurately exchanging energy between the atmosphere and the ocean-ice systems through surface heat fluxes is crucial for climate modelling. We present an improved version of Coupled Arctic Prediction System (CAPS) by revising flux coupling for conservation of heat. Our results show that the model with improved flux coupling can better simulate sea ice conditions during the period of Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC).
Hide
10 Mar 2026
Observation operator and detection limits for MODIS and VIIRS Fire Radiative Power products
Mikhail Sofiev and Rostislav Kouznetsov
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Satellites can observe fires globally, but sensitivity of instruments in space is limited: they miss small fires and cannot see through clouds. We analyzed the MODIS and VIIRS fire observations and obtained their sensitivity to small fires, which depends on the resolution of the instrument, timing of the observation (day or night), and details of the data processing. We developed a procedure for comparing fire model predictions with satellite observations accounting for their limited sensitivity
Hide
10 Mar 2026
GeoSIRR 1.0: Conversational Geological Cross-Section Modeling Using Large Language Models
Denis Anikiev, Juan Esteban Mosquera, Korhan Ayranci, Judith Bott, and Umair Bin Waheed
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Geological cross sections are essential for understanding the Earth’s subsurface, but they are usually slow to create manually. We developed GeoSIRR 1.0, a new framework that converts plain geological descriptions into consistent cross section models using generative artificial intelligence. The approach allows interactive refinement through conversation and helps bridge expert geological reasoning with digital modeling for faster exploration, education, and scenario testing.
Hide
10 Mar 2026
EnviFlux (v1.0): a simplified surface flux inversion tool based on four-dimensional variational data assimilation (4D-Var)
Ross Noel Bannister
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 7 comments)
Short summary
Short summary
EnviFlux is a low-cost data assimilation tool to estimate trace gas fluxes at the Earth's surface. Data assimilation ideas are often first studied with "toy models", but none exists for flux estimation, hence the purpose of EnviFlux.
EnviFlux is described, and then used to show how model error and bias can influence the inferred surface flux features. This is done in two scenarios, one with no prior knowledge of a source/sink pair, and another with prior knowledge in a more realistic situation.
Hide
09 Mar 2026
CEDDAR v1.0.2: Bridging physics and generative modelling for regional precipitation with controllable diffusion-based downscaling
Thea Quistgaard, Tanja Denager, Raphael J. M. Schneider, Jesper R. Christiansen, Simon Stisen, and Peter L. Langen
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We present a generative modelling framework for kilometre-scale precipitation downscaling that combines machine learning with physics-informed design. The model produces daily ensembles, not just single realisations. Using a structured evaluation setup across spatial, probabilistic, and climatological metrics, we show that realistic detail does not guarantee correct climatology and statistics, demonstrating key trade-offs which must be addressed cleanly for reliable impact and risk assessment.
Hide
09 Mar 2026
Python-Fortran Hybrid Programming for Deep Incorporation of AI and Physics Modeling and Data Assimilation (Hf2pMDA_1.0)
Xianrui Zhu, Zikuan Lin, Shaoqing Zhang, Zebin Lu, Songhua Wu, Xiangyun Hou, Zhisheng Xiao, Zhicheng Ren, Jiangyu Li, Jing Xu, Yang Gao, Rixu Hao, Xiaolin Yu, and Mingkui Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
Deep integration of Artificial intelligence (AI) algorithms and traditional scientific models is crucial for progress, but Fortran-based scientific codes and Python-based AI are difficult to combine. We develop a Python–Fortran hybrid procedure that enables mutual invocation of AI and scientific modules. Applied to climate and weather models, it supports strongly coupled data assimilation and high-precision prediction, promoting future advances in both AI and scientific modeling.
Hide
06 Mar 2026
High-resolution mapping of air quality across Europe: an ensemble machine and deep learning framework integrating multi-scale spatial predictors (CHROMAP v1.0)
Antoine Guion, Alicia Gressent, Gaël Descombes, Yassine Janati, Elsa Real, Anthony Ung, Frédérik Meleux, Simone Schucht, and Augustin Colette
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
This article presents CHROMAP, a high-resolution air quality mapping model based on the fusion of data from deterministic models, in-situ and satellite observations, and spatial proxies using an ensemble of ML and DL algorithms. Yearly estimates of the SOMO35 indicator and the average concentrations of NO
, PM2.5, PM10, and O
are produced and evaluated for the 2013-2023 period at a spatial resolution of 500 meters over the European domain.
Hide
06 Mar 2026
All-sky ATMS radiance data assimilation with MPAS-JEDI
Junmei Ban, Zhiquan Liu, Byoung-Joo Jung, Ivette Hernandez Banos, Benjamin Ruston, and Andrew Collard
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The assimilation of all-sky radiances in MPAS–JEDI, the data assimilation system for the Model for Prediction Across Scales–Atmosphere (MPAS-A) based on the Joint Effort for Data Assimilation Integration (JEDI), has been extended in this study to incorporate ATMS observations. Month-long cycling experiments demonstrate consistent and encouraging improvements in dynamical, thermodynamic, and moisture-related fields resulting from the assimilation of all-sky ATMS radiances.
Hide
06 Mar 2026
A process-based modeling of soil organic matter physical properties for land surface models – Part 2 : Global land surface simulations and mineral soil compaction adjustment
Bertrand Decharme, Diane Tzanos, Lucas Hardouin, Aaron Boone, Marie Minvielle, Patrick Le Moigne, and Rémi Gaillard
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We developed a new method to represent how organic matter in soils, together with a mineral soil compaction adjustment, influences the movement of water and heat in land models. We implemented this approach in a global model and performed long-term simulations driven by weather data and global soil maps. Compared with an older empirical method, it produces more consistent soil moisture, runoff, evaporation, and ground temperature and shows closer agreement with observations.
Hide
06 Mar 2026
Implementation of the reduced complexity model InMAP at urban scale using a high-resolution WRF-Chem simulation
Diego Roberto Rojas Neisa, Alejandro Piracoca-Mayorga, Sebastián Espitia-Cano, and Ricardo Morales Betancourt
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 7 comments)
Short summary
Short summary
In this work, we explored the ability of simpler atmospheric models to analyze the effectiveness of reducing air pollutant emissions to improve air quality. We showed that, despite its simplicity, these models correctly estimate the areas where impacts will be felt the most, and therefore, can be used by decision makers to maximize the positive impacts of planned air quality improvements.
Hide
05 Mar 2026
PALM-CO
(v01): A High-Resolution Urban CO
Transport Model with Anthropogenic and Biogenic Fluxes
Linfeng Li, Jie Zheng, and Fangxin Fang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This study presents a high-resolution model that simulates how carbon dioxide moves through cities by combining human emissions and plant activity. Using detailed data for London, the model closely matches real measurements. Results show that air movement, mixing, and urban vegetation strongly shape carbon patterns, highlighting the importance of green spaces and airflow in improving urban planning and reducing emissions.
Hide
05 Mar 2026
Integrating reservoirs and lakes in the CoSWAT global hydrological model
Jose P. Teran, Celray J. Chawanda, Albert Nkwasa, Inne Vanderkelen, Jeffrey G. Arnold, and Ann Van Griensven
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Global water models help us understand how human activities and climate change affect water resources. One of them is the CoSWAT Global Model. In this study we improved this model by adding a better representations of lakes, reservoirs, and irrigation demand. Evaluation shows these changes improve river flow simulation and enable explicit assessment of lake and reservoir water balances, producing a more robust tool for global freshwater studies.
Hide
05 Mar 2026
GPU-accelerated Finite-Element Method for the Three-dimensional Unstructured Mesh Atmospheric Dynamic Framework
Leisheng Li, Ximeng Fu, Xiyu Zheng, Huiyuan Li, and Jinxi Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Scientists use irregular grid models for accurate weather simulation, which help capture details but also make the calculations slow on traditional computers. We redesigned this model for GPUs by reorganizing data and calculations. This makes the slowest parts hundreds of times faster and the whole simulation over ten times faster. This allows for higher-resolution simulations.
Hide
05 Mar 2026
Development and Preliminary Validation of an EnKF-Like Image Assimilation System for the Common Land Model
Xuesong Bai, Zhaohui Lin, Zhengkun Qin, and Juan Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
Accurate soil moisture is crucial for weather prediction, but traditional methods often miss correct spatial patterns. We addressed this by treating moisture data as cohesive images rather than isolated points. Using image processing, we optimized both the location and intensity of moisture anomalies. This approach doubled the accuracy of spatial patterns and reduced errors in China and the United States.
Hide
05 Mar 2026
An ADCP-Based Data-Driven Framework for Proxy Sediment Transport Monitoring: From Controlled Flumes to Natural Rivers
Mohammd Tanvir Haque Tuhin, Reinhard Hinkelmann, and Christoph Mudersbach
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study tests how Acoustic Doppler Current Profiler (ADCP) data can support proxy sediment-transport monitoring without labour-intensive sediment sampling. Using data from a flume and a natural river, we train and compare several machine-learning models to predict a near-bed velocity signal. The results show which ADCP features and model types work best as practical indicators of bed activity.
Hide
04 Mar 2026
New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization
Jung Choi, Jiwoo Lee, Kristin Chang, Paul A. Ullrich, Peter J. Gleckler, and Sang-Yoon Jun
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
As climate risks grow, society needs reliable predictions for the coming years and decades. We developed a framework to collectively compare climate prediction systems and examine their performances on global temperature, rainfall, and sea ice. As a complementary to traditional analyses, our new framework offers tracking evolution of model performance in simulation time, helping scientists and stakeholders better understand strengths and limits of decadal climate prediction.
Hide
04 Mar 2026
palm_csd 25.10: A processing tool for static input data in the PALM model system
Sebastian Schubert, Julian Anders, Tobias Gronemeier, Björn Maronga, and Mohamed Salim
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
We present palm_csd version 25.10, the current default preprocessing tool for generating the static input data for the building-resolving large-eddy simulation model PALM. This paper focuses on the processing of buildings, vegetation, pavement, water bodies, terrain height and land cover. We demonstrate the application of palm_csd using publicly available geodata for the city of Berlin (Germany). Common data inconsistencies and sources of uncertainty in urban geodata are discussed.
Hide
04 Mar 2026
A deep learning framework for gridding daily climate variables from a sparse station network
Alexandru Dumitrescu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
High-quality climate maps are key for flood-risk assessment. We present a deep-learning framework that maps daily temperature and precipitation from sparse weather-station data. By learning orographic effects, it delivers more accurate rainfall fields with well-calibrated uncertainty, enabling reliable monitoring of environmental change in complex terrain.
Hide
04 Mar 2026
Effects of assimilating phytoplankton carbon in marine ecosystem modelling in NEMO4.0.4-MEDUSA2.0-PDAF2.0
Yumeng Chen, Dale Partridge, and Lars Nerger
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Operational marine ecosystem forecasts traditionally rely on combining phytoplankton chlorophyll observations with model forecasts. However, using our newly developed ensemble data assimilation system, we demonstrate that assimilating phytoplankton carbon data leads to more accurate phytoplankton estimates and improves estimates of global ocean carbon.
Hide
03 Mar 2026
An Online Spectral Nudging-Based Correction System: Improving Physical Model Forecasts by Incorporating Large-Scale Circulations Derived from Machine Learning Models
Yong Su, Jincheng Wang, Xueshun Shen, Couhua Liu, Xingliang Li, Hao Jing, Jin Zhang, and Yingying Hu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 8 comments)
Short summary
Short summary
The traditional weather prediction models improve slowly, while machine learning models struggle with extreme weather and fine details. To address these gaps, we developed an online correction system that leverages a machine learning model's skillful large-scale circulation to guide a physical model. This hybrid model enhances large-scale skill while preserving small-scale features, providing a viable pathway for improving operational weather forecasting.
Hide
03 Mar 2026
A unified Hapke-HSR + MARMIT-2 soil radiative transfer model for reflectance simulation under varying moisture conditions
Anxin Ding, Han Ma, Shunlin Liang, Ziti Jiao, Alexander A. Kokhanovsky, Hanyu Shi, and Rui Xie
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 4 comments)
Short summary
Short summary
Soil reflectance strongly influences how Earth surface properties are observed from space, especially when soil moisture changes. In this study, we develop a new soil reflectance model by combining two existing physical models to better represent both dry and wet soils. The proposed model improves accuracy and stability across different soil moisture conditions and provides a more reliable basis for interpreting optical remote sensing observations and retrieving land surface parameters.
Hide
03 Mar 2026
Beyond behavioural models: equifinality and overparameterisation undermine confidence in predictions by soil organic matter models
Marijn Van de Broek and Johan Six
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Soil organic matter models are often characterised by equifinality, the phenomenon that multiple parameter sets yield similar results. This study shows that the number of identifiable parameters that can be optimised together is limited, even under data-rich conditions. As a result, overparameterised models showed a large variability when simulating future changes. Optimising only identifiable model parameters is therefore necessary to avoid this hidden uncertainty in soil organic matter models.
Hide
02 Mar 2026
Effectively Assimilate Satellite Land Surface Temperature into Offline Land Surface Models within Ensemble-based Assimilation Frameworks
Yunhao Fu, Yongjun Zheng, and Jingjia Luo
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
It is challenging to assimilate land surface temperature (LST) owing to its fast temporally varying nature. This study proposes a scheme by jointly updating the soil temperature and soil moisture. Results show marginal enhancement in LST, yet soil temperature bias over Northeast Asia (NA) drops sharply. Snow temperature and snow depth over NA, and soil moisture in the humid tropics also improve significantly. These consistent improvements demonstrate the effectiveness of the proposed scheme.
Hide
27 Feb 2026
Comprehensive Inter-comparison of Generative AI Models for Super-Resolution Precipitation Downscaling Across Hydroclimatic Regimes
Shivam Singh, Simon Michael Papalexiou, Hebatallah M. Abdelmoaty, Tom Hartvigsen, and Antonios Mamalakis
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
High-resolution precipitation is essential for hydrologic and climate-risk applications, but climate models are too coarse to resolve storm-scale structure and extremes. We compare a deterministic U-NET and two generative models (WGAN and diffusion) for 8× and 16× precipitation downscaling using ERA5-Land. All models conserve rainfall mass, but differ at fine scales: U-NET is stable yet smooths extremes, while generative models better capture variability and heavy tails with added uncertainty.
Hide
27 Feb 2026
INFLOW-AI v2.1: A Machine Learning Framework for Predicting Out-of-Sample Extreme Seasonal Flood Extents
Jessica Rapson, Elisabeth Stephens, Ross I. Maidment, and Rogerio Bonifacio
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Extreme flooding is hard to predict in regions with limited data, yet early warnings are crucial to protect lives and livelihoods. This study developed an artificial intelligence system that learns from past weather, river levels, and satellite observations to predict where severe flooding will spread months in advance. Tested and used in real time in South Sudan, the system successfully supported humanitarian planning, showing it can improve preparedness and reduce the impacts of future floods.
Hide
27 Feb 2026
Optimization of snow cover fraction parameterization in the Community Land Model: implementation and preliminary validation over Tibetan Plateau
Kai Yang, Chenghai Wang, Yang Cui, Lingyun Ai, Feimin Zhang, and Pinghan Zhaoye
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
In this study, focusing on a well-developed LSM—CLM5, we optimized the SCF parameterization scheme through considering effects of withered grass steam and topographic relief on the probability distribution and the depletion of snow, reducing the positive biases of SCF by 34 %~88 % and the surface cold biases by 1~2 ℃ in snow-affected regions over Tibetan Plateau.
Hide
26 Feb 2026
Weather and air pollution influences on solar energy performance in West Africa: A Bayesian nonlinear mixed-effects approach
Konin Pierre-Claver Kakou, Dungall Laouali, Boko Aka, and Georg Frey
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We explored how weather conditions and air pollution shape the sunlight available for solar power. Using a statistical approach that learns from prior knowledge and follows changes across different places and times, we found that these factors affect sunlight in complex ways. Our method predicted solar energy more accurately than common models, suggesting it can support better planning and smoother expansion of solar power.
Hide
25 Feb 2026
China Regional 3 km Downscaling Based on Residual Corrective Diffusion Model
Honglu Sun, Hao Jing, Zhixiang Dai, Sa Xiao, Wei Xue, Jian Sun, and Qifeng Lu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 4 comments)
Short summary
Short summary
This study represents the first application of CorrDiff, a diffusion-based model, to achieve 3 km resolution statistical downscaling over China by integrating various variables at multiple levels. Through structural improvements to CorrDiff, our methods produce forecasts that outperform the China Meteorological Administration Mesoscale Model for almost all target variables. Our results show that for radar reflectivity prediction, CorrDiff yields more realistic outputs than regression models.
Hide
24 Feb 2026
climQMBC: A package with multiple bias correction methods of GCM climatic variables at daily, monthly and annual scale, developed in Python, R and MATLAB
Sebastian Aedo-Quililongo, Cristian Chadwick, Fernando González-Leiva, and Jorge Gironás
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Global and regional climate model outputs need to be bias corrected to assess climate change impacts at local scales. Although several bias correction methods exist, none of them is perfect and users must assess the trade-off of these methods. As there are no coding packages that allow an even comparison, we developed an easy-to-use package to compare among methods, allowing users to identify the most adequate for each situation and include this analysis in their workflow.
Hide
24 Feb 2026
Benchmarking ozone stress parameterizations in CLM5: a global mechanistic assessment of thresholds and memory effects
Peng Zhou, Jieming Chou, Li Dan, Jean-François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca Buccholz, Desneiges Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan Chen, and Liwen Xing
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We assessed the impact of ozone damage representations in a land-surface model on simulations of vegetation productivity. Results varied depending on how ozone effects were triggered and how vegetation recovery was modeled. Schemes that incorporated vegetation-specific thresholds and memory effects on photosynthesis and water loss more accurately reflected spatial patterns, indicating directions for enhancing model realism and improving projections of ecosystem responses to ozone pollution.
Hide
24 Feb 2026
A Continuous Implicit Neural Representation Framework with Gradient Regularization for Sea Surface Height Reconstruction From Satellite Altimetry
Dongshuang Li, Liming Pan, Zhaoyuan Yu, and Linwang Yuan
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Satellite measurements of sea level are uneven and incomplete, which limits our ability to map the ocean surface. This study introduces a new approach that represents sea level as a smooth surface in space and time. Experiments with satellite data and simulations show that the method produces stable and detailed reconstructions, particularly in regions with strong ocean activity, and enables improved analysis of ocean dynamics.
Hide
24 Feb 2026
A Deep Learning Approach for Lake Ice Cover Forecasting
Samuel J. Johnston, Justin Murfitt, and Claude Duguay
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
The Lake Ice Forecasting using Deep Learning model produces spatially explicit forecasts, which consistently outperform the popular Freshwater Lake model. Freeze-up and break-up timing was improved to within 3–9 days with greatly enhanced spatial accuracy of forecasted ice cover patterns. This establishes the potential of data-driven methods to advance lake ice models, with implications for enhancing weather prediction, northern transportation planning, and climate change adaptation.
Hide
23 Feb 2026
Assessment of an updated polar stratospheric cloud parameterisation for the UK Earth System Model (UKESM1.1) within the UK Met Office Unified Model (v13.9) using CALIOP and MLS observations
Isabelle Sangha, Nathan Luke Abraham, Andrew Orr, Hua Lu, Michael C. Pitts, Lamont R. Poole, and Michael Weimer
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
The UK Earth System Model is updated with an improved polar stratospheric cloud scheme. The performance of the scheme is evaluated against satellite data. While the observed wave ice still fails to form in the model, the scheme improves its ability to represent different polar stratospheric cloud types and their variations. This brings the model closer to satellite observations and highlights the need for further development to capture the polar stratospheric cloud formation in mountain waves.
Hide
23 Feb 2026
An antiplane strain model for evaluating shear-margin stability (Ortholine v1.0)
Jenny Suckale and Cooper W. Elsworth
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
The widths of glaciers and ice streams can change over time, which strongly affects how much ice is lost to the ocean. Many existing models of sea-level rise neglect these width changes, but they are commonly observed and important. This paper presents a new, simple model that helps identify which physical factors govern width changes at different field sites. The model is explained step by step and tested using an Antarctic ice stream as an example.
Hide
23 Feb 2026
AstroComb(v.1.0): Non-linear, Multi-channel, Probabilistic Cyclostratigraphic Analysis
Iris Fernandes, Klaus Mosegaard, Aske L. Sørensen, Mohammad Youssof, Nicolas Thibault, and Tais W. Dahl
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
We introduce a new method to more precisely date ancient sediment layers using astronomical time cycles recorded in the rock. Unlike previous tools, it handles complex, multi-channel data without oversimplifying and gives clear estimates of dating uncertainty. This helps future research in better understand Earth’s past climate, biological changes, and geologic events with greater confidence and accuracy.
Hide
23 Feb 2026
A Self-Supervised Precipitation Forecast Verification Based on Contrastive Learning
Yanwen Wang, Shuwen Huang, Qian Li, Xuan Peng, Haoming Chen, Kefeng Zhu, Liwen Wang, and Sheng Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We developed a contrastive learning method (CLPFV) to improve the accuracy of precipitation forecast verification. The proposed method uses precipitation augmentation to simulate real-world forecast errors with gradients and then employs an improved loss function to reflect these errors in the contrastive learning. Experimental results show that the proposed method outperforms traditional and spatial verification methods across different error types and aligns better with expert judgment.
Hide
20 Feb 2026
Quantifying the impact of input data-induced dataset shift on machine learning model applications: A case study of regional reactive nitrogen wet deposition
Yan Zhang, Jiani Tan, Qing Mu, Joshua S. Fu, and Li Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Despite growing use of machine learning in environmental research, few have studied how input data affects findings. We examined the impact of input data characteristics on nitrogen deposition estimates in East and Southeast Asia. Insufficient sample size cuts accuracy by up to 12 %, while data-scarce and remote areas show up to 50 % bias due to poor training data representation. We created a transferable framework for uncertainty quantification, applicable to other data-scarce geospatial tasks.
Hide
20 Feb 2026
Implementation of the Generalized Double-Moment Scaling Normalization Method for Raindrop Size Distribution in a WRF 4.3.1 Bulk-Type Cloud Microphysics Scheme: A Case Study over the Korean Peninsula
Joonghyun Jo, Kyo-Sun Sunny Lim, Sun-Young Park, Juhee Kwon, Wonbae Bang, Hyang Suk Park, Jae-Young Byon, Hyun-Suk Kang, and Gyuwon Lee
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
This study implements the generalized double-moment scaling normalization method for raindrop size distribution in the WDM6 microphysics scheme. Numerical experiments for a convective summer rainfall event show that the modified scheme better captures precipitation cell propagation, spatial rainfall distribution, and vertical reflectivity structures compared to the original WDM6 and other bulk/bin schemes.
Hide
19 Feb 2026
mLDNDCv1.0: A Machine Learning-based Surrogate of LandscapeDNDC for Optimising Cropping Systems in Denmark
Meshach Ojo Aderele, Edwin Haas, Licheng Liu, João Serra, David Kraus, Klaus Butterbach-Bahl, and Jaber Rahimi
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
This study develops a fast, data‑driven tool to virtually test millions of ways to manage winter wheat fields in Denmark, without running slow process-based crop models each time. It finds fertilizer, residue, manure, catch crop and irrigation strategies that cut nitrogen pollution and greenhouse gases while increasing yields and soil carbon, all without using more fertilizer overall.
Hide
19 Feb 2026
Development and improvement of a nonhydrostatic spectral model using non-constant coefficient semi-implicit and vertically conservative semi-Lagrangian schemes
Hiromasa Yoshimura
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We have developed a two-dimensional x–z nonhydrostatic spectral model that achieves high computational efficiency by allowing long timesteps. The model incorporates several improvements that enhance numerical stability and accuracy. The model was tested with various cases, and good results were obtained. The model ran stably even in the case of an extremely steep mountain with an average slope of 63.4°. These improvements will be applied to a global atmospheric model in future work.
Hide
19 Feb 2026
Transport modelling for dynamic urban climate studies: MATSDA-roads v2.0
Tiancheng Ma, Denise Hertwig, Megan McGrory, Matthew Paskin, and Sue Grimmond
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
Transport impacts emissions (heat, pollutants), which needs to be represented in high-resolution urban models. We introduce the transport model MATSDA and evaluate its route finding for car journeys in London, UK. The model shows high skill at identifying major travel corridors and associated travel durations, capturing day type and time-of-day dependency (rush-hour v. off-peak). MATSDA offers dynamic human movement patterns for transport research in the context of urban climate modelling.
Hide
18 Feb 2026
Accurate and Robust Geometric Algorithms for Regridding on the Sphere
Hongyu Chen, Paul A. Ullrich, Julian Panetta, David Marsico, Moritz Hanke, Rajeev Jain, Chengzhu Zhang, and Robert L. Jacob
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Accurate data transfer between different grids is essential in climate and weather modeling. This study analyzes the geometric operations that underpin such transfers on the spherical Earth, identifies gaps and limitations in current methods, and introduces improved algorithms to ensure accuracy, reliability, and performance for next-generation modeling and data analysis systems.
Hide
18 Feb 2026
Effect of inlet turbulence on the large eddy simulation of fire plume turbulent characteristics near the ground
Yujia Sun, Qing Chen, and Guanghui Yuan
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Wildfires pose serious risks to natural environments and cities, making it essential to predict how smoke travels through the air. We studied how wind patterns affect computer models of fire spread. We simulated fires under both smooth and turbulent airflows. Our results show that while assuming smooth wind is acceptable for light breezes, it causes errors in moderate winds. Therefore, models must account for natural turbulence to accurately predict fire plume in realistic weather.
Hide
18 Feb 2026
A high-resolution coupled physical-biogeochemical model of the northeastern US continental shelf: MOM6-COBALT-NEUS25v1.0
Dalton Kei Sasaki, Cristina Schultz, and Enrique Curchitser
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
From Cape Hatteras to Nova Scotia, local communities have suffered consequences of ocean warming, with warmer-water species moving north, lobster populations struggling due to rising temperatures, and more frequent marine heat waves. We developed an ocean model that includes carbon/nutrients cycle and validated it with data from moorings, satellites, and other observations. This tool will help future studies better understand how ocean changes affect marine life and society.
Hide
16 Feb 2026
Development and validation of ARMS-gb v2.0: Extending fast radiative transfer modeling capability to all-sky conditions for ground-based microwave radiometer retrievals
Ziyue Huang, Yi-Ning Shi, Fuzhong Weng, and Jun Yang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We present an updated version of the Advanced Radiative Transfer Modeling System for ground-based sensors to better use microwave instruments in all weather. We added realistic cloud and rain effects and compared the results with six months of observations at two stations. The model accurately simulates observations in cloudy conditions. This advance can effectively improve the use of observational data and enhance weather forecasting capability.
Hide
13 Feb 2026
Ecosystem Climate Sensitivities Drive the Divergence in Aerosol-Induced Carbon Uptake Across CMIP6 Models
Zhaoyang Zhang, Meng Fan, Minghui Tao, Yunhui Tan, and Quan Wang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
In this paper, we examined the inter-model differences among five Earth System Models in simulating the impact of aerosols on plant productivity. All models showed that the impact of human-made aerosols on global plant productivity was negative, but with the divergence in the amount of reduction. We found that the divergence was mostly caused by the parameterization of model in simulating canopy photosynthesis, which determines how strongly plants react to changes in climatic factors.
Hide
13 Feb 2026
Volume of Fluid method applied to free surface boundaries in numerical geodynamic models
Timothy Stephen Gray, Paul James Tackley, and Taras Gerya
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This study introduces a new way to track Earth’s surface and other boundaries in computer models of the planet’s interior. It replaces noisy, tracer-based methods with a technique that cleanly follows surfaces while conserving volume. The approach produces smoother, more accurate results in both 2D and 3D, reduces dependence on large numbers of tracers, and supports future links between deep Earth processes, oceans, and surface environments.
Hide
12 Feb 2026
ForEdgeClim
v1.0: a 3D process-based microclimate model incorporating vertical and lateral energy fluxes to simulate forest edge-to-core transitions
Emma Van de Walle, Félicien Meunier, Steven J. De Hertog, Louise Terryn, Pieter Sanczuk, Kim Calders, Francis Wyffels, Pieter De Frenne, Michiel Stock, and Hans Verbeeck
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We present
ForEdgeClim
, a process-based model that simulates forest microclimate temperatures from edges to forest interiors. The model combines high-resolution forest structure, meteorological data, and a physically based energy balance that includes vertical and lateral radiation and heat exchange. Validation with field measurements shows that
ForEdgeClim
captures observed edge-to-core temperature gradients, supporting its use for studying forest fragmentation and climate impacts.
Hide
12 Feb 2026
Hydrological Auditing of LISFLOOD v4.1.1: Impacts of Model Setup on Water Balance Components in the Po River Basin
Francesca Moschini, Andrea Ficchì, and Alberto Pistocchi
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We evaluated how different configurations of a large-scale river basin model affect simulations of streamflow, evaporation, soil moisture, and groundwater in the Po River Basin in Italy. We tested alternative soil depths and the inclusion or removal of subsurface flow pathways, and compared results with observations and with an established long-term water balance relationship. Setups that best matched river flow often underestimated evaporation and overestimated deep groundwater recharge.
Hide
12 Feb 2026
Parameterization and Evaluation of Nonhydrostatic Effect in the Orographic Gravity Wave Drag in China Meteorological Administration Global Forecast System (CMA-GFS) v4.0 Model
Rongrong Zhang, Zhenzhen Ai, Xin Xu, Haile Xue, and Qiying Chen
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
In this study, the orographic gravity wave drag (OGWD) parameterization scheme in the CMA-GFS v4.0 model is revised to account for nonhydrostatic effects (NHE) on the surface momentum flux of subgrid-scale orographic gravity waves. Through a series of 10-day medium-range forecasts, the revised OGWD scheme is shown to significantly improve the simulation of large-scale circulation in the Northern Hemisphere (NH), especially in the high latitudes.
Hide
12 Feb 2026
Simulating SAR altimeter echoes from cryospheric surfaces with the Snow Microwave Radiative Transfer (SMRT) model version sarm-v0
Ghislain Picard, Justin Murfitt, Elena Zakharova, Pierre Zeiger, Laurent Arnaud, Jeremie Aublanc, Jack C. Landy, Michele Scagliola, and Claude Duguay
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
Radar altimeters measure ice-sheet elevation and sea-ice thickness. To improve their accuracy, we developed a model that simulates altimeter waveforms based on the physical properties of snow and sea ice. It computes the power, time, and Doppler shift of radar echoes as waves travel to the surface, interact with snow and ice, and return to the satellite. The model was verified internally, validated against other models and applied in Antarctica using in-situ snow measurements.
Hide
11 Feb 2026
Stratospheric aerosol forcing for CMIP7 (part 2): Volcanic sulfur dioxide emissions
Thomas J. Aubry, Michael Sigl, Matthew Toohey, Man Mei Chim, Magali Verkerk, Anja Schmidt, and Simon A. Carn
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We document the historical (1750–2023) volcanic sulfur dioxide emission dataset created for phase 7 of the Coupled Model Intercomparison Project, which is a set of coordinated climate model experiments run by modelling center worldwide. Our dataset underpins the stratospheric aerosol optical property dataset which will be used as input by most climate models. However, models with interactive stratospheric aerosol capability can directly input our emission dataset to run CMIP7 experiments.
Hide
11 Feb 2026
runoutSIM v1.0: An R package for regionally simulating landslide runout and connectivity using random walks
Jason Goetz
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
runoutSIM is a free R open-source software tool that helps map where landslides like debris flows might travel. It simulates, at regional scales, how far and fast material could move and whether it might reach roads, rivers, or other features. It also estimates how likely different source areas are to connect with these features – supporting hazard planning and enabling advances in modelling methods.
Hide
10 Feb 2026
Interactive Simulation of Methane and Hydrogen Soil Deposition in ECHAM5/MESSy Atmospheric Chemistry Model (EMAC) v2.55 with the new Submodel BIODEP (v1.0)
Anna Martin, Klaus Klingmüller, Benedikt Steil, Sergey Gromov, Yu-Ri Lee, Dong Yeong Chang, Nic Surawski, Jos Lelieveld, Sujong Jeong, and Andrea Pozzer
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We evaluate a new model simulating soil uptake of methane and hydrogen from the atmosphere. Coupled to an atmospheric chemistry and land surface model, it accounts for weather and soil conditions. Our results match observations, showing accurate removal depending on soil properties, temperature, moisture, and atmospheric conditions. This work improves the model’s ability to represent natural cycles of methane and hydrogen.
Hide
10 Feb 2026
EMMA-Tracker v1.0: A lifecycle-based algorithm for identifying and tracking mesoscale convective systems in observations and climate models
David Kneidinger, Armin Schaffer, and Douglas Maraun
External preprint server,
2026
Preprint under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
Mesoscale Convective Systems cause extreme weather and flash floods, yet they remain difficult to simulate in climate models. We developed the Evolution-based Mesoscale Convective System Model Assessment tool to identify these storms using standard model data. Our 27-year record for Europe shows these systems drive over 60 percent of heavy hourly rain. This benchmark allows us to evaluate climate model performance and investigate how these intense storms will change in a warming climate.
Hide
10 Feb 2026
A simple weather generator that converts statistical information from downscaled global climate models to 24-hr precipitation input for hydrological models
Rasmus Benestad
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
The paper presents a weather generator that generates sequences of daily precipitation based on two key statistical parameters. It enables the use of downscaled projections of precipitation statistics for impact studies, such as hydrological modelling.
Hide
10 Feb 2026
ICON coupled to HAM-lite 1.0 in limited-area mode: an efficient framework for targeted kilometer-scale simulations with interactive aerosols
Bernd Heinold, Philipp Weiss, Sadhitro De, Anne Kubin, Jason Müller, Fabian Senf, Philip Stier, and Ina Tegen
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
A limited-area aerosol-climate model based on ICON coupled to HAM-lite is introduced for regional studies of natural and anthropogenic aerosols and interactions with clouds and radiation. Case studies over Central Europe, the Atlantic Arctic, and Australia exemplarily show the model’s capability to capture key aerosol patterns and variability, while remaining affected by simplified emissions and chemistry. The results guide future HAM-lite development.
Hide
10 Feb 2026
BiXiao: An AI-dirven Atmospheric Environmental Forecasting Model with Non-continuous Grids
Shengxuan Ji, Yawei Qu, Cheng Yuan, Tijian Wang, Bing Liu, Lili Zhu, Huihui Zheng, Zhenfeng Qiu, and Pulong Chen
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
This study introduces BiXiao, an artificial intelligence model that forecasts air pollution by combining weather data and observations from monitoring stations. Tested in northern China, BiXiao can produce city-scale air-quality forecasts within seconds and is more accurate than traditional numerical models. The work shows how artificial intelligence can enhance environmental forecasting and support cleaner air and public health.
Hide
10 Feb 2026
Inclusion of MyAMI-derived Mg/Ca corrections to the marine carbonate system in the cGENIE.cookie Earth system model (v.0.9.90)
Markus Adloff, Terra M. Ganey, Mathis P. Hain, Michael J. Henehan, Sarah E. Greene, and Andy Ridgwell
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Seawater composition affects carbon cycling in the ocean and has changed over Earth history, requiring corrections when reconstructing past marine carbonate systems. We present a new correction scheme for the intermediate complexity Earth system model cGENIE based on the ion interaction model MyAMI. We validate the new scheme, find significant improvements over the default scheme, and discuss the relevance of accurate and consistent major ion correction in carbon cycle reconstructions.
Hide
09 Feb 2026
Scale-selective nudging with a diffusion-based filter in the variable-resolution Model for Prediction Across Scales version 8.2.2
Yiyuan Cheng and Jianping Tang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Global models can drift from observations, so we nudge them toward reanalysis. On variable-resolution unstructured meshes, standard nudging also damps small scales that shape rainfall. We introduce a diffusion filter that separates large and small spatial scales on the mesh and is fast in parallel. In a 1-year MPAS-Atmosphere run refined over East Asia, it keeps large-scale winds realistic while preserving rainfall differences between convection schemes, showing a clear trade-off.
Hide
09 Feb 2026
ClimateBenchPress (v1.0): A Benchmark for Lossy Compression of Climate Data
Tim Reichelt, Juniper Tyree, Milan Klöwer, Peter Dueben, Bryan N. Lawrence, Allison H. Baker, Sara Faghih-Naini, Torsten Hoefler, and Philip Stier
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
The growing size of datasets used in climate science makes it difficult to store, analyze, and distribute dataset. Lossy compression algorithms can significantly reduce the disk space required to store datasets, but it can be difficult to understand and compare the behavior of different compression algorithms. ClimateBenchPress provides a benchmark to standardize comparisons between lossy compression algorithms and guide development of novel algorithms specifically targeted towards climate data.
Hide
09 Feb 2026
RIME-X v1.0: Combining Simple Climate Models, Earth System Models, and Climate Impact Models into a Unified Statistical Emulator for Regional Climate Indicators
Niklas Schwind, Mahé Perrette, Edward Byers, Annika Högner, Quentin Lejeune, Tessa Möller, Zebedee Nicholls, Peter Pfleiderer, Sarah Schöngart, Michaela Werning, and Carl-Friedrich Schleussner
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
We study how regional climate and climate impact indicators may respond to different emissions scenarios. Their possible outcomes are shaped by uncertainties in future emissions, global warming, regional effects of global warming, and the chaotic climate system. We introduce RIME-X, an emulator that combines multiple tools and datasets to estimate probabilistically how any emissions path may influence regional outcomes.
Hide
09 Feb 2026
Process-Level Diagnostics of Marine Stratocumulus in TaiESM1: Insights into Parameterization Successes and Deficiencies
Yi-Hsuan Chen and Chein-Jung Shiu
External preprint server,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Many climate models struggle to represent marine stratocumulus clouds. In contrast, the Taiwan Earth System Model version 1 reproduces them realistically, yet the reasons are unclear. Using short-term forecast simulations and process-based analysis, we reveal how individual physical processes affect these clouds and identify both strengths and weaknesses in the model. This analysis framework can be applied to understand other phenomena in climate models.
Hide
09 Feb 2026
The NASA-GISS ModelE2.1-CC2 ESM: development and simulations
Anastasia Romanou, Paul Lerner, Nancy Kiang, Igor Aleinov, Maxwell Kelley, Roland Miller, Gary Russell, Reto Ruedy, Gavin Schmidt, Maria Hakuba, and Ou Wang
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
NASA GISS latest Earth System model description and evaluation paper. Major highlights is the capability to include complex interactions of the different components of the Earth System. The model compares well with observations but has shortcomings due to biases that propagate throughout the system between different components.
Hide
06 Feb 2026
DReaMIT: A Dynamical Reanalysis Framework for Modelling Surface-Based Temperature Inversions in Cold Environments
Victor Pozsgay, Nick C. Noad, Philip P. Bonnaventure, and Stephan Gruber
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Surface-based temperature inversions occur when cold air becomes trapped near the ground beneath a layer of warmer air. This study combines field data, analysis, and modelling to develop DReaMIT, a model that captures the timing and strength of inversions across northern mountain terrain. The model’s transferability beyond the valleys where it was developed makes it valuable globally to cold-region researchers for mapping and modelling permafrost and assessing climate change impacts.
Hide
05 Feb 2026
Confidence-Aware Framework for Mapping Satellite-Derived River Reaches to Gridded Routing Networks
Kaushlendra Verma and Simon Munier
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Satellite provide river observations as vector reaches, while large-scale hydrological models represent rivers on gridded routing networks. This structural mismatch limits direct data assimilation. We present a global, confidence-aware framework that assigns vector river reaches to routing pixels using geometric and hydrological consistency criteria. Results show that most routing pixels can be assigned with high confidence while preserving basin-scale drainage topology into hydrological models.
Hide
05 Feb 2026
CaMa-Flood-GPU: A GPU-based hydrodynamic model implementation for scalable global simulations
Shengyu Kang, Jiabo Yin, and Dai Yamazaki
External preprint server,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Global floods pose serious risks, but existing models are too slow for large-scale prediction. We redesigned the CaMa-Flood model for GPUs by reformulating key components such as irregular river networks, flux updates, and floodplain dynamics into highly parallel, GPU-native algorithms. The resulting CaMa-Flood-GPU runs global simulations in hours instead of days with the same accuracy, enabling larger ensembles, improved flood-risk analysis, and better preparedness worldwide.
Hide
05 Feb 2026
Interpolating station quantile biases for tropospheric ozone MDA8 bias correction
Jan Peiker, Jan Karlický, and Peter Huszár
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We introduce a novel strategy for bias correction of tropospheric ozone maxima based on parametric interpolation of quantile biases (PIQB) from stations into the model grid. Its performance is evaluated and compared to other strategies found in literature. The results show that PIQB performs very well on simulations with a relatively high horizontal resolution, preserving model-resolved features yet mitigating model errors. We conclude that PIQB is suitable for correcting future projections.
Hide
05 Feb 2026
LOAC-OCB v1.0: A model to explore terrestrial organic carbon burial along the land-to-ocean aquatic continuum
Daniela Henry-Pinilla, Núria Catalán, Biel Obrador, and Rafael Marcé
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We developed the first global model that tracks how carbon moves and is buried across rivers, lakes, floodplains, and coastal areas. This new tool links these ecosystems within a single framework, helping scientists better understand how water systems store carbon and influence the planet’s carbon balance and climate.
Hide
04 Feb 2026
AgPaDS
v1.0: A GPU-accelerated interactive Lagrangian atmospheric transport model with 3-D in situ visualization for simulating windborne dispersal of crop pathogens
Marcel Meyer, Thomas Gaiser, and Frank Ewert
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We introduce a Lagrangian atmospheric transport model (AgPaDS) that complements existing approaches by providing an efficient massively parallelized implementation and a unique option for advanced live 3-D visualization of simulation data on global scales for supporting exploratory analyses. The tool is tailored to applications in crop epidemiology and can be used to improve assessment of risks posed to food production by windborne crop disease epidemics.
Hide
04 Feb 2026
Dynamic drag partitioning in GEOS-Chem (v. 14.2.3) eliminatessource function and tuning, revealing equifinality of atmosphericdust observations
Boyan Liu, Hongquan Song, Adrian Chappell, and Zhuoli Zhou
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We studied how vegetation and soil roughness shape released dust. Conceptualising light reflected from the land surface to represent wind sheltering, we improved a global dust model. This approach removes the need for guesswork about where dust comes from and still matches observed dust in the atmosphere. It also shows that different paths can lead to similar dust levels, which encourages better ways to track how often dust is lifted. This helps guide efforts to predict dust and its impacts.
Hide
04 Feb 2026
Evaluating Extreme Precipitation Forecasts: A Threshold-Weighted, Spatial Verification Approach for Comparing an AI Weather Prediction Model Against a High-Resolution NWP Model
Nicholas Loveday and Tracy Hertneky
External preprint server,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This study introduces a verification method that accounts for differences in grid resolution when evaluating extreme event forecasts. We apply it to an artificial intelligence-based weather prediction model and a high-resolution numerical weather prediction model. Results show that, when assessed on equivalent neighborhood scales, the high resolution numerical weather prediction model only outperforms the AI system for short lead times in predicting extreme precipitation.
Hide
04 Feb 2026
TRACE-Python: Tracer-based Rapid Anthropogenic Carbon Estimation Implemented in Python (version 1.0)
Daniel E. Sandborn, Brendan R. Carter, Mark J. Warner, and Larissa M. Dias
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We present a new implementation of our method for estimation of human-created carbon dioxide in the ocean. "Tracer-based Rapid Anthropogenic Carbon Estimation" relies on transient tracer measurements to infer gas exchange and circulation. Our work implements practical and fundamental improvements increasing accessibility, flexibility, and skill of the method. We provide an updated data product of global ocean carbon inventories spanning the industrial era and a range of future projections.
Hide
03 Feb 2026
Schumpeterian disaggregation and integrated assessment: An endogenous, stock-flow consistent economy in disequilibrium for FRIDA v2.1
Martin Breda Grimeland, Benjamin Blanz, William Schoenberg, and Beniamino Callegari
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
This study develops a novel global economic model to better capture how climate change interacts with finance, innovation, employment, and public budgets. Instead of treating climate damage as a simple output loss, the model traces how rising temperatures affect investment risk, productivity, unemployment, and government spending. Large simulation ensembles show that without stronger climate action, growth slows, financial fragility rises, and welfare and debt pressures increase.
Hide
03 Feb 2026
Development of ECCO-downscaled Amundsen-Bellingshausen Sea regional simulation using MITgcm(66j)
Yoshihiro Nakayama, Shuntaro Hyogo, Yichen Lin, Taewook Park, Jinho Lee, Juistine Caillet, Gobishankar Mohan, Mattia Poinelli, Pierre Dutrieux, Kazuki Nakata, Hong Zhang, Brice Loose, and Lauren Kowalski
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We develop a regional ocean model of the Amundsen and Bellingshausen Seas in Antarctica. Differences in model setups and parameter choices often limit usability and broader scientific application, especially for non-ocean modellers. We carefully evaluate the model outputs and establish a common control experiment that can be shared and applied across studies with tracer and particle applications. This effort aims to support wide community use and improve understanding of ice–ocean interactions.
Hide
03 Feb 2026
Spectral Nudging Impacts on Precipitation Downscaling in the Conformal Cubic Atmospheric Model, version CCAM-2504: Insights from Summer 2011
Son C. H. Truong, Marcus J. Thatcher, Phuong Loan Nguyen, Lisa V. Alexander, and John L. McGregor
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
Understanding how rainfall may change in the future is vital for managing floods and water resources in Australia. We tested different ways of constraining a regional climate model so it better matched observed rainfall during the extreme 2010–11 La Niña wet event. The most effective settings produced much more realistic rainfall, increasing confidence in using the model to explore future rainfall patterns and extreme weather risks.
Hide
02 Feb 2026
Composite Sharpening by Vortex Symmetrization and Normalization of Tropical Cyclones
Andrina Caratsch, Sylvaine Ferrachat, and Ulrike Lohmann
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Tropical cyclones come in various size and shape, which smoothes out key storm features in composite analyses. To address this, we developed a compositing method that symmetrizes storms and better aligns their eyewalls and horizontal extents prior to compositing. This approach preserves small-scale features in the composites, reduces within-group variance, and enhances the power of statistical testing. The method facilitates the investigation and understanding of tropical cyclone development.
Hide
02 Feb 2026
ISeeSnow
v1.0 – a pilot study for snow avalanche model intercomparison of thickness-integrated shallow flow approaches and beyond
Anna Wirbel, Felix Oesterle, Guillaume Chambon, Thierry Faug, Johan Gaume, Julia Glaus, Stefan Hergarten, Dieter Issler, Yoichi Ito, Marco Martini, Martin Mergili, Matthias Rauter, Jörg Robl, Giorgio Rosatti, Kae Tsunematsu, Christian Tollinger, Hervé Vicari, Daniel Zugliani, and Jan-Thomas Fischer
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
We present the first extended intercomparison of snow avalanche flow simulation tools. In this pilot-study, simulation results of mainly thickness/depth-integrated shallow flow models are compared for three simple test cases representative of standard applications. This analysis serves as a first quantitative assessment of the uncertainty introduced by the different implementation workflows (e.g., numerical schemes, ad-hoc treatments, geo-data handling, curvature treatment, etc.).
Hide
30 Jan 2026
Evaluation of the LandscapeDNDC model for drained peatland forest managements, LDNDC v1.35.2 (revision 11434)
Ahmed Hasan Shahriyer, David Kraus, Tiina Markkanen, Mika Korkiakoski, Helena Rautakoski, Suvi Orttenvuori, Yao Gao, Henri Kajasilta, Rüdiger Grote, Annalea Lohila, and Tuula Aalto
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
We successfully represented hydrology and carbon cycle associated with different forestry managements (Rotational and continuous cover forestry) for a drained peatland ecosystem using the processed based model LDNDC. This provides a robust framework for investigating future management scenarios and develop forest management strategies that supports climate neutrality in peatland ecosystems.
Hide
30 Jan 2026
S2AS v1.0 and 2D polarity–volatility lumping framework v1.0: automated compound classification and scalable lumping for organic aerosol modelling
Dalrin Ampritta Amaladhasan, Dan Hassan-Barthaux, and Andreas Zuend
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
A 2-dimensional polarity–volatility framework is introduced. It enables the automated characterization of thousands of organics and their systematic lumping into adjustable sets of surrogate components. A new polarity metric based on an activity coefficient ratio is presented for use in this framework. A related molecule substructure parsing tool for input file generation is introduced. This framework enables reduced-complexity representations of near-explicit organic aerosol systems.
Hide
29 Jan 2026
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP7
Paulo Ceppi, Alejandro Bodas-Salcedo, Mark D. Zelinka, Timothy Andrews, Florent Brient, Robin Chadwick, Jonathan M. Gregory, Yen-Ting Hwang, Sarah M. Kang, Jennifer E. Kay, Thorsten Mauritsen, Tomoo Ogura, George Tselioudis, Masahiro Watanabe, Mark J. Webb, and Allison A. Wing
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
Clouds constitute a key uncertainty for climate change projections. The Cloud Feedback Model Intercomparison Project (CFMIP) aims to address this challenge by evaluating and understanding clouds and their impacts on atmospheric circulation, precipitation, and climate sensitivity. The present paper describes the CFMIP experiment protocol for the Coupled Model Intercomparison Project phase 7 (CMIP7), and discusses the accompanying science questions and opportunities for progress.
Hide
29 Jan 2026
TOAD v1.0: A Python Framework for Detecting Abrupt Shifts and Coherent Spatial Domains in Earth-System Data
Jakob Harteg, Lukas Röhrich, Kobe De Maeyer, Julius Garbe, Boris Sakschewski, Ann Kristin Klose, Jonathan F. Donges, Ricarda Winkelmann, and Sina Loriani
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Climate systems can undergo abrupt, potentially irreversible changes with major impacts on ecosystems and societies, yet consistent tools to detect these transitions across different models are lacking. We present an open-source software package for systematically detecting where and when such changes occur in climate simulations and quantifying variation in transition timing. This enables robust comparison of abrupt changes across models and contributes to assessing climate-tipping risks.
Hide
29 Jan 2026
Quantitative assessment of parameterization sensitivity and uncertainty in Noah-MP multi-physics ensemble simulations of gross primary productivity across China’s terrestrial ecosystem
Jie Lai, Anzhi Wang, Yage Liu, Lidu Shen, Yuan Zhang, Yiwei Diao, Rongrong Cai, Rongping Li, Wenli Fei, and Jiabing Wu
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This study evaluated Noah-MP performance in simulating gross primary productivity (GPP) across China and analyzed the sensitivity of key parameterization schemes. The modified two-stream radiation scheme (RAD01) shows superior performance, especially in grassland and shrubland ecosystems, while the BTR03 β-factor performs better in croplands. Surface exchange and runoff schemes systematically overestimate GPP, indicating structural biases in energy–carbon and hydro–vegetation coupling.
Hide
28 Jan 2026
A novel ALE scheme with the internal boundary for coupling tectonic and surface processes in geodynamic models
Neng Lu, Louis Moresi, Julian Giordani, and Ben Knight
EGUsphere,
2026
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study introduces a novel framework combining geodynamic and surface process models, enhancing our understanding of Earth's crust and upper mantle deformation. By integrating the codes Underworld 2 and Badlands within the Arbitrary Lagrangian-Eulerian with Internal Boundary (ALE-IB) scheme, our approach overcomes the limitations of previous methods. It maintains internal interface integrity and precise surface tracking, improving simulation fidelity.
Hide
28 Jan 2026
DeepMIP-Eocene-p2: Experimental design for Phase 2 of the early Eocene component of the the CMIP7/PMIP7 Deep-time Model Intercomparison Project (DeepMIP-Eocene)
Daniel J. Lunt, Nicky M. Wright, Bram Vaes, Ulrich Salzmann, James W. B. Rae, Thomas Hickler, David K. Hutchinson, Julia Brugger, Jiang Zhu, Sebastian Steinig, A. Nele Meckler, Gordon N. Inglis, David Evans, Agatha M. de Boer, Bette L. Otto-Bliesner, Natalie Burls, Yurui Zhang, Appy Sluijs, Tammo Reichgelt, Igor Niezgodzki, Katrin Meissner, Jean-Baptiste Ladant, Fanni D. Kelemen, Matthew Huber, David Greenwood, Mattias Green, Flavia Boscolo-Galazzo, Mauel Tobias Blau, and Michiel Baatsen
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The early Eocene, about 50 million years ago, was a super-warm period of Earth's history, with high concentrations of carbon dioxide in the atmosphere. Here, we provide a framework and experimental design for climate modellers to carry out a coordinated project, simulating this period. This is the second phase of this project, and here we provide updated maps of the Earth's mountains and ocean floor, and vegetation, to enable more accurate modelling.
Hide
27 Jan 2026
AD-MERGE 2.0: An Integrated Assessment of the Nexus Among Energy Transitions, Climate Impacts, and Adaptation Responses
Kamyar Amirmoeini, Olivier Bahn, Kelly de Bruin, Kirsten Everett, Hamed Kouchaki-Penchah, and Pierre-Olivier Pineau
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This paper presents AD-MERGE 2.0, an integrated assessment model designed to study emissions reductions and adaptation together, and to capture how decisions on one can change the benefits and costs of the other. Building on earlier versions, and by improving how the model represents both climate policy actions and climate damages, this paper provides new evidence on how regions can combine near-term protection from climate change impacts with long-term transitions toward cleaner energy systems.
Hide
27 Jan 2026
ARTEMIS version 1.0: A Reactive Transport Enhanced Rock Weathering Model with Coupled Soil Carbon and Nutrient Dynamics
Lyla L. Taylor, Rachael H. James, Ilsa Kantola, and David J. Beerling
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
Carbon capture via dissolution of CO
in water during enhanced weathering of rock dusts applied to soils is difficult to verify, largely due to retention of cations in soils over unknown timescales. The ARTEMIS reactive transport model predicts carbon capture lag times of several decades at a site in Illinois, assuming continued rock dust treatments. Our results suggest that cation retention through the whole soil column should be assessed when predicting carbon capture via enhanced weathering.
Hide
26 Jan 2026
Development of a next-generation general ocean circulation model for the Great Lakes
Meena Raju, David J. Cannon, Peter Alsip, He Wang, Jia Wang, Theresa Cordero, Robert W. Hallberg, Charles A. Stock, and Joseph A. Langan
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study developed the Modular Ocean Model version 6.0 coupled with Sea Ice Simulator version 2.0 for the Great Lakes, validated against observations and an operational model. This study also tested two vertical coordinate systems, z* and hybrid. The model reproduced lake physics with good skill. The hybrid vertical coordinate improved thermocline representation and preserved deep cold-water during stratification, demonstrating the model’s suitability for large freshwater systems.
Hide
26 Jan 2026
JCM v1.0: A Differentiable, Intermediate-Complexity Atmospheric Model
Ellen H. Davenport, J. Varan Madan, Rebecca Gjini, Jared Brzenski, Nick Ho, Tien-Yiao Hsu, Yueshan Liang, Zhixing Liu, Veeramakali Manivannan, Eric Pham, Rohith Vutukuru, Andrew I. L. Williams, Zhiqi Yang, Rose Yu, Nicholas J. Lutsko, Stephan Hoyer, and Duncan Watson-Parris
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
We introduce version 1.0 of the JAX Circulation Model (JCM), an open-source atmosphere model. JCM is written in JAX, a framework for high-performance Python code that supports automatic differentiation (automated calculation of how sensitive any program output is to any input). JCM's differentiability and modular design make it easier to train, test, and combine physical-theory-based and data-driven model components, thus providing a flexible and modern platform to facilitate climate research.
Hide
26 Jan 2026
Local weather scenarios for soil and crop models: a simple generator based on historic data sampling
Stefan Anton Albert Gasser, Julius Ansorge, Ulrich Weller, Hans-Jörg Vogel, and Sara König
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
The LocalWeatherSampler generates 20–30 year weather scenarios at daily resolution using historical weather data. Wet/dry years can be defined by threshold or via the Standardized Precipitation Index and future weather sequences can be generated tailored to specific scenarios, like extremely dry or very wet sequences. This approach enables testing and analyzing precipitation patterns and temperature trends with models that rely on realistic, daily weather data, such as soil and crop models.
Hide
26 Jan 2026
ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0)
Xiaoguang Pang, Liming Jiang, Yuxuan Wu, Xi Lu, Yi Liu, Xiaoen Li, and Tingting Yao
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Ice thickness models based on laminar flow theory often rely on conventional assumptions regarding basal sliding parameterization when studying alpine glaciers. This paper presents the Ice Thickness Model considering Sliding Law (ITMSL) model, which integrates a basal sliding law with laminar flow theory, with the objective of simulating basal sliding to enhance the accuracy of ice thickness inversion.
Hide
26 Jan 2026
MErSiM v1.0: Resolving Biases in Global Silicate Weathering Model with A Data-Driven Surface Erosion Module
Jiaxi Zhao, Yonggang Liu, and Yongyun Hu
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
By using artificial intelligence and geological measurements, we built a machine learning model that accurately shows how landscapes erode. With this module included we developed a new silicate weatherig model, named MErSiM v1.0, which corrected a major overestimation of weathering flux in models simulating Earth’s long-term carbon cycle. This revealed that Earth's natural ability to remove atmospheric carbon dioxide is profoundly weaker under intense warming than previously understood.
Hide
26 Jan 2026
Optimization of the Gaussian Dispersion Model Inversion for Estimating Facility Scale Methane Emissions in Canada
Shoma Yamanouchi, Sebastien Ars, Meghan Flood, Lawson Gillespie, Jordan Stuart, Kiran Ramlogan, and Felix Vogel
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Methane is a potent greenhouse gas. In this study, Gaussian plume model, a simple, computationally inexpensive modeling method, was used in conjunction with measurements of atmospheric methane concentrations to estimate emissions of methane from refineries and waste treatment facilities. This study also presents novel methods to improve the model, including a method to better describe the atmosphere, as well as an algorithmic way to nudge source locations to get better emission estimates.
Hide
26 Jan 2026
Comparing the MEMS v1 model performance with MCMC and 4DEnVar calibration methods over a continental soil inventory
Toni Viskari, Tristan Quaife, Fernando Fahl, Yao Zhang, and Emanuele Lugato
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
In this work we examined how different assumptions regarding soil carbon model calibration affect the resulting model performance. We found that how the litter inputs are set have a meaningful impact on the calibrated model parameters. Furthermore, two calibration methods produced parameter sets that differed meaningfully from each other but fit the validation dataset equally well. These results raise meaningful questions how we evaluate soil carbon model performance.
Hide
23 Jan 2026
Lagrangian tracking methods applied to free surface boundaries in numerical geodynamic models
Timothy Stephen Gray, Paul James Tackley, and Taras Gerya
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
This study presents a new way to model how Earth’s surface changes over time as the deep interior moves. The method tracks the surface directly, allowing clearer and more detailed results worldwide while using less computing power. It improves accuracy compared to existing approaches and makes it easier to connect deep Earth processes with oceans, climate, landscapes, and life through time.
Hide
23 Jan 2026
A novel ALE scheme with the internal boundary for true free surface simulation in geodynamic models
Neng Lu, Louis Moresi, and Julian Giordani
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
This study presents a novel scheme for simulating Earth's free surface. Traditional methods like 'Sticky Air' face limitations such as increased computational costs and marker fluctuation issues. Our approach integrates the 'Sticky Air' concept into an Arbitrary Lagrangian–Eulerian framework using an internal boundary enabling a true free surface simulation, which reduces marker noise, enhances numerical stability.
Hide
23 Jan 2026
A Preliminary Study on a Synergistic Assimilation Scheme for Multi-band Satellite Soil Moisture Data
Xuesong Bai, Zhaohui Lin, Zhengkun Qin, and Juan Li
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Accurate soil moisture data is essential for predicting weather. This study examined how observations from three satellites can be combined to improve land-surface simulations. While each satellite helps, their value changes with vegetation type. Merging these data sources gives a more reliable estimate of soil wetness, especially in central and western China. This approach strengthens soil-water monitoring and supports more dependable climate forecasting.
Hide
23 Jan 2026
G&M3D 1.0: an Interactive Framework for 3D Model Construction and Forward Calculation of Potential Fields
Dengkang Wang, Bo Chen, Kanggui Wei, Jiaxiang Peng, and Rongwen Guo
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We developed G&M3D 1.0, a user-friendly software that allows anyone to build and explore 3D models of underground structures. We tested it on a real-world salt dome in Louisiana, demonstrating its practical use for interpreting geological data. Our research aimed to create an accessible platform for both learning and professional analysis, and we achieved this by building the software with widely-used programming tools, offering it as both an open-source project and a ready-to-use application.
Hide
22 Jan 2026
Multi-season evaluation of temperature and wind in the marine boundary layer along the United States northeast coast in the High-Resolution Rapid Refresh model
Bianca Adler, Laura Bianco, David D. Turner, Joseph B. Olson, Xia Sun, Joshua Gebauer, Nicola Bodini, Stefano Letizia, and James M. Wilczak
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
Accurate operational forecasts of temperature and wind in the coastal marine boundary layer are important for a wide range of applications. Leveraging data that were collected along the U.S. northeast coast during a multi-year period for the Third Wind Forecast Improvement project, we investigated the performance of the operational forecast model and identified systematic errors in wind and temperature forecasts that are now being addressed by the model developers.
Hide
22 Jan 2026
Implementation of the ORACLE (v1.0) organic aerosol composition and evolution module into the EC-Earth3-AerChem model
Stylianos Kakavas, Stelios Myriokefalitakis, Alexandra P. Tsimpidi, Vlassis A. Karydis, and Spyros N. Pandis
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
The computationally efficient configuration of the ORACLE v1.0 module (ORACLE-lite) is implemented into the TM5-MP global chemical transport model, which represents the chemistry-transport component of the EC-Earth3-AerChem ESM. The models bias is reduced by approximately half in the standalone TM5-MP simulation and by a factor of three in EC-Earth3-AerChem when ORACLE-lite is implemented.
Hide
22 Jan 2026
Implementing methane dynamics into the LPJmL6 model
Sibyll Schaphoff, David Hötten, Christoph Müller, Dieter Gerten, Sebastian Ostberg, and Werner von Bloh
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Methane is a strong greenhouse gas. We improved a global model of vegetation, soils and water so it can better show how methane forms and moves in wetlands and rice fields. The model now captures waterlogged areas, methane creation and escape, and flood-tolerant plants. It reproduces global wetland patterns and emissions more realistically, helping scientists assess how climate and land use changes may alter future methane release.
Hide
22 Jan 2026
Turbulence-Driven Nutrient Supply Sustains Algal Growth in the Arctic: A Modeling Approach
Giulia Castellani, Karley Campbell, Sebastien Moreau, and Pedro Duarte
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
Nutrients exchange at the ocean-ice interface is a key process to supply nutrients and support sea-ice algal growth in polar regions. Such fluxes depend on the characteristics of the flow. We develop a parameterization that accounts for shifts between smooth and turbulent flow and we implement it in two sea-ice biogeochemical models. The parameterization leads to larger fluxes of nutrients that support higher production, resulting in more than double biomass accumulation.
Hide
21 Jan 2026
Process-based evaluation of ENSO simulation sensitivity to horizontal resolution in the Chinese Academy of Sciences FGOALS-f3 Climate System Model
Meng-Er Song, Lin Chen, Yongqiang Yu, Bo An, Jiuwei Zhao, and Hai Zhi
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This study evaluates how horizontal resolution affects ENSO simulation in the CAS FGOALS-f3 climate model by comparing its ~25 km and ~100 km configurations. Using a reproducible, process-based diagnostic framework, we identify the structural origins of ENSO biases and show that they stem from resolution-dependent air-sea feedbacks and high-frequency atmospheric variability. This work informs future development for the FGOALS-f3 family and serves as a reference for CMIP6/CMIP7 model evaluation.
Hide
21 Jan 2026
Ocean–atmosphere turbulent flux algorithms in Earth system models do not always converge to unique and physical solutions: analysis and potential remedy in E3SMv2
Justin Dong, Michael A. Brunke, Xubin Zeng, Carol S. Woodward, Hui Wan, and Christopher J. Vogl
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Accurately computing ocean–atmosphere turbulent fluxes, which measure the transfer of momentum, heat, and water between the Earth and its oceans, in Earth system models is important for overall model accuracy. Under certain meteorological conditions, the set of equations utilized in many Earth system models to parameterize these fluxes can have no solution or more than one solution. Modifying the equations to address these issues leads to substantial changes to the simulated turbulent fluxes.
Hide
21 Jan 2026
Including the triple isotopic composition of dissolved oxygen in the ocean into the iLOVECLIM model (version 1.1.7): development and evaluation
Emeline Clermont, Ji-Woong Yang, Didier M. Roche, and Thomas Extier
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
The triple isotopic composition of atmospheric oxygen (
17
Δ) is used to reconstruct past global biospheric productivity. We present the first implementation of the oceanic contribution (
17
ocean
) in the intermediate-complexity model iLOVECLIM. Photosynthesis, respiration, and air-sea gas exchange are represented under preindustrial conditions. Model results agree with observations, providing a future key tool to study marine biogeochemical processes and past ocean biospheric productivity.
Hide
21 Jan 2026
Cartino2D: Scalable and Automated 2D Shallow Water Rainfall-Flood Inundation Modeling up to Very High Resolution for Large Domains
Frédéric Pons, Nabil Hocini, and Pierre-André Garambois
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
Cartino 2D (C2D) enables large-scale, automated flood modeling using reference 2D complete hydraulic model Telemac2D adapted for hydrology. It features topography-aware unstructured meshing, spatial parameterization, and supports rainfall or discharge forcing. Applied across France and at high resolution in cities, it shows strong scalability and consistency, opening new paths for local to national flood risk assessment.
Hide
20 Jan 2026
A neural network-based observation operator for weather radar data assimilation
Marco Stefanelli, Žiga Zaplotnik, and Gregor Skok
External preprint server,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Weather radars provide storm intensity and location, but weather forecasting systems do not readily use them. We trained a neural network on 5 years of reflectivity radar and model output data to map model fields into radar reflectivity space, allowing forecasts to be corrected with radar data. In a major flood case, this cut errors in storm position and strength. Broadly speaking, the methodology provides a simplified solution for assimilating observations with no direct model-equivalent field.
Hide
20 Jan 2026
Km-scale regional coupled system for the Northwest European shelf for weather and climate applications: RCS-UKC4
Ségolène Berthou, Juan Maria Castillo, Vivian Fraser-Leonhardt, Sana Mahmood, Nefeli Makrygianni, Alex Arnold, Claudio Sanchez, Huw W. Lewis, Dale Partridge, Martin Best, Lucy Bricheno, Helen Davies, Douglas Clark, James R. Clark, Jeff Polton, Andrew Saulter, Chris J. Short, Jonathan Tinker, and Simon Tucker
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
The UK’s new RCS-UKC4 system combines atmosphere, ocean, waves, land, rivers, and biogeochemistry models to improve coastal weather and climate predictions. It offers better storm wave predictions, more accurate river flows, and captures rapid sea-level changes. These advances help predict multiple hazards more reliably, supporting safer communities and helping better planning.
Hide
20 Jan 2026
Assessing resolution sensitivity in coupled climate simulations with AWI-CM3
Martina Zapponini, Tido Semmler, Jan Streffing, Thomas Rackow, Lettie A. Roach, and Thomas Jung
EGUsphere,
2026
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study evaluates the impact of grid resolution on long-term present and future climate runs using the Alfred Wegener Institute global model AWI-CM3. A higher-resolution setup (35 km atmosphere, eddy-permitting/resolving ocean) improves small-scale processes and long-term variability, across variables and regions, and can capture nonlinear ocean–atmosphere interactions often missed by Coupled Model Intercomparison Project (CMIP) models. Simulation data will be made publicly available.
Hide
19 Jan 2026
Wind and turbulence evaluation of the ICON model (icon-2024.01-1) at sub-kilometer scales using Doppler lidar observations
Maike Ahlgrimm and Eileen Päschke
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
This study uses a new type of observation of wind and turbulence to investigate the accuracy with which the German weather forecasting model predicts these variables in the lowest 600 metres of the atmosphere. The model performs adequately during the day, but struggles with both wind and turbulence at night. This is important for wind energy planning and understanding how airborne particles are transported by the wind. The study suggests ways in which the model could be further improved.
Hide
16 Jan 2026
SNOWstorm (v1.0) – a deep-learning based model for near-surface winds and drifting snow in mountain environments
Manuel Saigger, Brigitta Goger, and Thomas Mölg
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
We present a new model to predict near-surface winds and wind-driven transport of snow in mountain environments at high horizontal resolution. With its deep-learning based design, it is several orders of magnitude less computationally expensive compared to traditional numerical methods, while being applicable over a wide range of topographic settings and atmospheric conditions. A first application case study in the European Alps showed good agreement with numerical simulations and observations.
Hide
15 Jan 2026
Implementation of a three-dimensional planetary boundary layer parameterization in a coupled modeling system and evaluation of "gray zone" simulations of a wind-wave event off the U.S. California Coast using observations
Eric A. Hendricks, Timothy W. Juliano, Branko Kosović, Sue Haupt, Brian J. Gaudet, and Geng Xia
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
A three-dimensional planetary boundary layer parameterization, suited for mesoscale model grid spacings of 100–1000 m with improved treatment of unresolved horizontal mixing, is added to a coupled atmosphere / wave modeling system and the first coupled simulations are executed using the parameterization. Simulations of a significant wind-wave event demonstrate that the new parameterization has similar behaviors as one-dimensional PBL parameterizations and compares well with observations.
Hide
15 Jan 2026
Stable Stream Temperature Prediction for Different Basins Using Time Series Encoding and Temporal Convolutional Networks
Lichen Su and Wei Zhao
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 6 comments)
Short summary
Short summary
The establishment of a lateral lateral water temperature prediction model with strong generalization capabilities and stable prediction results presents a major challenge. To solve this problem, the coding of time series data incorporated in a temporary convolutional network (Fumenc-TCN) was modelled. The model effectively captured multimodal features of dynamic water temperature data from complex random time series, subsequently producing stable prediction results in different river basins.
Hide
14 Jan 2026
SPIN (v1.0): A Spontaneous Synthetic Tropical Cyclone Model Empowered by NeuralGCM for Hazard Assessment
Yurong Gao and Dazhi Xi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Tropical cyclones (TCs) are among the most destructive natural hazards, and compound TC-related events can cause even greater losses. These impacts highlight the need to assess both individual and compound TC hazards. Existing statistical models neglect TC–environment interactions, while dynamical models are costly. We present a hybrid framework enabling efficient, physically realistic simulations of individual and compound TC events.
Hide
14 Jan 2026
Application of flux footprint equations from Kljun et al. (2015) to field eddy-covariance systems for footprint characteristics into flux network datasets
Xinhua Zhou, Zhi Chen, Ryan Campbell, Atefeh Hosseini, Tian Gao, Xiufen Li, Jianmin Chu, Sen Wu, Ning Zheng, and Jiaojun Zhu
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 25 comments)
Short summary
Short summary
To help environmental researchers better understand the sources of greenhouse gas measurements, we developed a practical method for field instruments to calculate the footprints. By using simplified math and efficient computing, our approach allows real-time analysis of measurement zones, which was previously too complex for on-site processing. This enables more accurate data collection worldwide, helping improve climate change monitoring and ecosystem studies.
Hide
13 Jan 2026
Comparison of two Euler equation sets in a Discontinuous Galerkin solver for atmospheric modelling (BRIDGE v0.9)
Michael Baldauf and Florian Prill
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We present an implementation of the Discontinuous Galerkin approach, a numerical solver of the Euler equations (called BRIDGE), which is in particular well suited for numerical models for weather and climate prediction and atmospheric research. Two widespread formulations of the Euler equations with different thermodynamic variables are compared by the inspection of idealised benchmark test cases to assess the properties of the Discontinuous Galerkin method.
Hide
13 Jan 2026
From Single Storms to Global Waves: A Global 2.5 km ICON Simulation of Weather and Climate
Andreas Franz Prein, Praveen Pothapakula, Christian Zeman, Morgane Lalonde, and Marius Rixen
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
We produce one of the world's most detailed global weather and climate simulations, spanning 4 years and enabling the direct representation of storms rather than approximations. This allows the capture of dangerous events such as strong wind gusts, heavy rain, and powerful tropical and mid-latitude storms anywhere on Earth. Our results show major improvements over traditional climate models, but also reveal remaining challenges in representing large, organized storm systems in the tropics.
Hide
13 Jan 2026
Surface Kinetic Energy Distributions in the North and Equatorial Atlantic Derived from Surface Drifter Observations and High-Resolution Numerical Models with Tidal Forcing
Rémi Laxenaire, Eric P. Chassignet, Xiaobiao Xu, Alan J. Wallcraft, Luna Hiron, Brian K. Arbic, Maarten C. Buijsman, Miguel Solano, and Shane Elipot
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Fast-changing currents shape surface energy and drive interior mixing of heat and salt. Because they are hard to observe globally, we use numerical models to quantify their impacts. We evaluate seven North and Equatorial Atlantic simulations with varying parameterizations, comparing modeled currents with those from observed surface buoy tracks. We show results are sensitive to model grid and seafloor resolution, tides and wind variability, with contrasting offshore and nearshore responses.
Hide
13 Jan 2026
Evaluating Modifications to Tiedtke Cumulus Parameterization for Improving Summer Precipitation Forecasts in the Nested Grid of Taiwan Global Forecast System (TGFS v1.1)
Chang-Hung Lin, Guo-Yuan Lien, and Ling-Feng Hsiao
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 12 comments)
Short summary
Short summary
This study presents a series of modifications to the Tiedtke convection scheme, aiming to improve summer rainfall predictions in the 4.8-km-resolution nested grid of the Taiwan Global Forecast System (TGFS). The modifications improve the spatial distribution of rainfall and reduce the heavy rainfall bias in five-day forecast, as demonstrated by case studies and evaluations over a two-month period.
Hide
13 Jan 2026
This is FRIDA
Cecilie Mauritzen
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This brief paper provides the context for a collection in GMD called "The FRIDA model". FRIDA integrates climate forcing, human behavior, land use, energy, resources, demography, and the economy on equal footing. It is computationally light, transparent in design, and accessible to both expert and non-expert users. The model captures cascading socioeconomic risks and systemic feedbacks, which have been identified by the IPCC as among the most urgent and uncertain climate research issues.
Hide
12 Jan 2026
A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f)
Josua Seitz, Midori Yajima, Yu Zhu, Lumnesh Swaroop Kumar Joseph, Jinyan Yang, Fabrice Lacroix, Yunpeng Luo, Andreas Schaumberger, Michael Bahn, Sönke Zaehle, and Silvia Caldararu
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This study presents a new global leaf turnover model for grasslands in the QUINCY land surface model. Land surface models often struggle to simulate grassland carbon dynamics and phenology accurately. By allowing environmental conditions to directly control leaf senescence we improve its timing as well as the accuracy of whole-season carbon dynamics across a wide range of climates and grassland ecosystems.
Hide
12 Jan 2026
Evaluation of preCICE (version 3.3.0) in an Earth System Model Regridding Benchmark
Alex Hocks and Benjamin Uekermann
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We tested the general coupling software preCICE for data mapping between atmosphere and ocean simulation meshes in Earth system modeling. In a recent benchmark, preCICE performed on par with specialized tools. Its general design and large user community make it broadly applicable across scientific domains, fostering knowledge transfer and collaboration beyond Earth system research.
Hide
12 Jan 2026
Optimisation of ICON-CLM for the EURO-CORDEX domain: developments, sensitivities, tuning
Beate Geyer, Angelo Campanale, Evgenii Churiulin, Hendrik Feldmann, Klaus Goergen, Stefan Hagemann, Ha Thi Minh Ho-Hagemann, Muhammed Muhshif Karadan, Klaus Keuler, Pavel Khain, Divyaja Lawand, Patrick Ludwig, Vera Maurer, Sergei Petrov, Stefan Poll, Christopher Purr, Emmanuele Russo, Martina Schubert-Frisius, Jan-Peter Schulz, Shweta Singh, Christian Steger, Heimo Truhetz, and Andreas Will
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Complex models in environmental science typically have a lot of tuning parameters, which has to be set by the users depending on the application. This study presents a new method of objective tuning of a huge number of parameters, by combining expert judgement with automated tuning (LiMMo). The method is successfully applied to the regional climate model ICON-CLM over Europe.
Hide
11 Jan 2026
HyperGas
1.0: A Python package for analyzing hyperspectral data for greenhouse gases from retrieval to emission rate quantification
Xin Zhang, Joannes D. Maasakkers, Tobias A. de Jong, Paul Tol, Frances Reuland, Adam R. Brandt, Eric A. Kort, Taylor J. Adams, and Ilse Aben
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Reducing emissions of greenhouse gases such as methane and carbon dioxide is essential for addressing climate change. We developed HyperGas, an open tool that uses hyperspectral satellite images to retrieve and detect greenhouse gas plumes. It helps scientists locate emission sources, estimate their strength, and examine uncertainties through an easy workflow and visual app. Our goal is to make tracking human-made emissions more accurate and accessible, supporting better climate monitoring.
Hide
11 Jan 2026
ExoCcycle v1.0.0: A Generalized Framework for Spherical Community Detection and its Application to Defining Global Ocean Basins from Multi-Field Data
Matthew Bogumil, Carolina Lithgow-Bertelloni, and Tushar Mittal
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
We have developed a python code (ExoCcycle) that automatically finds the boundaries of ocean basins (e.g., the Atlantic) at present-day, in the past, and for other planets when given limited physical or chemical global information (e.g., ocean temperature, salinity, seafloor depth). This method can be used for clustering paleoclimate measurements and constructing next generation paleo- and exoplanet climate models. ExoCcycle is also generalized for other spherical space clustering applications.
Hide
09 Jan 2026
AIM-ALPHA v1.0: A partial equilibrium model of global agriculture and land use at basin-level resolution
Ryo Totake, Hiroki Yoshida, Tomoko Hasegawa, and Shinichiro Fujimori
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Global sustainability challenges such as food security, land-use changes, and climate mitigation require integrated assessment across sectors and regions. AIM-ALPHA, a new global model, links agriculture to land-use changes at the country and basin levels to explore these interconnected issues. By resolving national differences, it reveals cross-country variations in climate mitigation impacts and highlights the importance of country-level analysis in terms of global sustainability assessments.
Hide
09 Jan 2026
A Systematic Atmospheric Parameter Optimization method to Improve ENSO Simulation in the ICON XPP Earth System Model
Dakuan Yu, Dietmar Dommenget, Holger Pohlmann, and Wolfgang A. Müller
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We developed a new method to improve how a leading climate model simulates El Niño, a major driver of global weather extremes. By testing how the model responds to small changes in key atmospheric settings, we identified which processes matter most and adjusted them systematically. This approach makes the model’s behavior closer to observations and shows a promising path for building more reliable climate predictions.
Hide
09 Jan 2026
ML-IAM v1.0: Emulating Integrated Assessment Models With Machine Learning
Yen Shin, Changyoon Lee, Eunsu Kim, Junho Myung, Kiwoong Park, Jiheun Ha, Min-Young Choi, Bomi Kim, Hyun W. Ka, Jung-Hun Woo, Alice Oh, and Haewon McJeon
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Climate policy relies on computer models that predict future emissions and energy use under different scenarios. These models take up to hours to run, limiting their use. We developed a machine learning system that replicates these models accurately in seconds. Our system generates 2,000 scenarios in 50 seconds—thousands of times faster. This enables comprehensive analysis previously impossible and makes climate projections accessible to researchers studying other environmental impacts.
Hide
08 Jan 2026
A Glass-Box Framework for Interpreting Source-Term–Related Functional Modules in a Global Deep Learning Wave Model
Ziliang Zhang, Huaming Yu, Xiaotian Dong, Jiaqi Dou, Danqin Ren, and Xin Qi
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 0 comments)
Short summary
Short summary
Deep learning models for Earth system prediction are often criticized as "black boxes" that lack physical interpretability. This study introduces a "glass box" dissection framework to analyze the internal logic of these systems. Using the OceanCastNet wave model, we demonstrate that the AI autonomously organizes its computations into modules analogous to physical source terms (wind input, dissipation, and propagation), proving that data-driven models can spontaneously learn physical laws.
Hide
08 Jan 2026
The Path to FAIR Research Models: Lessons Learned
Albert J. Kettner, Leslie Hsu, and Brandon S. Serna
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This paper reviews how two major geoscience communities, the Community Surface Dynamics Modeling System (CSDMS) and the U.S. Geological Survey (USGS), are making scientific models more FAIR: Findable, Accessible, Interoperable, and Reusable. By comparing their approaches and lessons learned, it highlights practical steps that improve openness, collaboration, and transparency in Earth system modeling.
Hide
06 Jan 2026
Approximating the universal thermal climate index using sparse regression with orthogonal polynomials
Sabin Roman, Gregor Skok, Ljupčo Todorovski, and Sašo Džeroski
External preprint server,
2026
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study aimed to improve how the Universal Thermal Climate Index, a key measure of human thermal comfort, is calculated. Existing methods use a simplified polynomial approximation that is straightforward to apply but can introduce errors. We developed a new version using sparse regression with orthogonal polynomials, which keeps computational efficiency while improving accuracy and stability. The results enable more reliable assessments of outdoor thermal comfort and climate analyses.
Hide
06 Jan 2026
Exploring the applicability of Censored Shifted Gamma Distribution (CSGD) error model to radar based rainfall nowcasts: A UK case study
Hung-Ming Lin, Li-Pen Wang, and Jen-Yu Han
EGUsphere,
2026
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
We developed a framework to improve short-term rainfall forecasts by combining radar data with rain gauge observations. This approach reduces errors and uncertainty, giving more reliable predictions of when and where rain will fall. Such improvements are valuable for flood warnings, stormwater management, and other decisions that depend on timely and accurate rainfall information.
Hide
05 Jan 2026
Parameter estimation for land-surface models using Neural Physics
Ruiyue Huang, Claire E. Heaney, and Maarten van Reeuwijk
External preprint server,
2026
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
This paper uses the Neural Physics approach to determine parameters of a simple land-surface model. We show that we can only obtain a reliable parameter estimation using soil temperature measurements at more than one depth, and that latent and sensible heat fluxes cannot be differentiated. We then apply the inverse model to real urban flux tower data and show that parameters, as well as various heat fluxes, can be reliably estimated using an observed value for the effective surface albedo.
Hide
04 Jan 2026
SDMBCv2 (v1.0): correcting systematic biases in RCM inputs for future projection
Youngil Kim and Jason Evans
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Climate models used to study future climate often contain systematic errors that affect high-resolution simulations. This study presents a new open-source tool that reduces these errors before regional climate simulations are run. By correcting multiple atmospheric variables together and at short time scales, the method improves realism and consistency in simulated climate patterns. This leads to more reliable regional projections, particularly for extreme weather events.
Hide
04 Jan 2026
Incorporating observed fire severity in refined emissions estimates for boreal and temperate forest fires in the carbon budget model CBM-CFS3 v1.2
Dan K. Thompson, Ellen Whitman, Mark Hafer, Oleksandra Hararuk, Chelene Hanes, Vinicius Manvailer Goncalves, and Ben Hudson
EGUsphere,
2026
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Emissions from forest fires are tallied in Canada's National Forest Carbon Monitoring Accounting and Reporting System. Mapped fire extents and regional carbon stock estimates are used, but a fixed and high fire severity is assumed. This paper calculates fire emissions based on mapped fire severity. Using mapped fire severity, emissions are 10 to 20% higher, with more variation in emissions per hectare. This new method compares well against independent measurements for the 2023 fires in Canada.
Hide
04 Jan 2026
GSV-SRTS: A Heterogeneous Landscape Soil-Canopy Reflectance Model Over Sloping Terrain with an Extended GSV and Stochastic Radiative Transfer Theory
Siqi Li, Guyue Hu, Shaoda Li, Ronghao Yang, Junxiang Tan, Chenghao Liu, and Jinhu Bian
EGUsphere,
2026
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
The GSV-SRTS model simulates radiative transfer for heterogeneous mountain forests, addressing slope-induced uncertainties in remote sensing. It extends stochastic theory to slopes and integrates soil spectral vectors. Validations with benchmark models and satellite data confirm its accuracy in red/NIR bands and its capability to capture canopy-terrain effects, offering a reliable tool for improved biophysical retrieval.
Hide
04 Jan 2026
Evaluation of HNO
, SO
, and NH
in the Surface Tiled Aerosol and Gaseous Exchange (STAGE) option in the Community Multiscale Air Quality Model version 5.3.2 against field-scale,
in situ
and satellite observations
Jesse O. Bash, John T. Walker, Zhiyong Wu, Ian C. Rumsey, Ben Murphy, Christian Hogrefe, Kathleen M. Fahey, Havala O. T. Pye, Matthew R. Jones, K. Wyat Appel, Mark Shephard, Najwa I. Alnsour, and Karen E. Cady-Periera
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We applied a consistent modeling approach for both field and regional scales of multi-pollutants to evaluate the air-surface exchange processes contributing to regional air quality modeling biases when evaluated against observed network and satellite ammonia concentrations. This multi-resolution approach will serve the modeling and measurement community in their future development and generalization of air-surface exchange models utilizing flux, routine network and satellite observations.
Hide
02 Jan 2026
The Normalized Interpolated Convolution from an Adaptive Subgrid (NICAS) method
Benjamin Ménétrier
EGUsphere,
2026
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
The application of very large correlation operators to vectors is an persistent challenge for variational data assimilation. It must be accurate, fast and scalable. This article proposes a new generic method that works for any model grid, relying on adaptive subgrids to achieve this goal, even with advanced correlation functions. It describes the motivations and advantages of this method and its limitations depending on a few key parameters of the problem.
Hide
29 Dec 2025
Development of AC
FIRE
version 1.0: A mesoscale model with forest canopy and fire behavior submodels
Michael Kiefer, Shiyuan Zhong, Joseph Charney, Xindi Bian, Warren Heilman, Joseph Seitz, Nicholas Skowronski, Kenneth Clark, Michael Gallagher, Matthew Patterson, Jason Cole, Eric Mueller, and Xiaolin Hu
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 12 comments)
Short summary
Short summary
We introduce a new modeling system that simulates how wildfire and forest canopies interact. Using data from a prescribed burn in the New Jersey Pine Barrens, we show that the system can reproduce fire spread and the resulting atmospheric changes. Our results demonstrate that fully dynamic fire representation improves our ability to understand and predict fire behavior in complex forest environments.
Hide
28 Dec 2025
Variational Stokes method applied to free surface boundaries in numerical geodynamic models
Timothy Stephen Gray, Paul James Tackley, and Taras Gerya
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We developed a new way to model how planetary surfaces rise and sink as the deep interior slowly flows. Existing approaches are either costly or unstable. Our method represents the surface smoothly within a fixed grid, which avoids artificial air layers and numerical problems. Tests show it matches established results while running faster and working in more realistic settings, such as loaded surfaces and global models. This makes simulations of surface evolution more reliable and accessible.
Hide
27 Dec 2025
The Fire Modeling Intercomparison Project (FireMIP) for CMIP7
Fang Li, David Lawrence, Brendan Rogers, Chantelle Burton, Huilin Huang, Yiquan Jiang, Johannes Kaiser, Matthew Kasoar, Hanna Lee, Ruby Leung, Lars Nieradzik, Aihui Wang, Daniel Ward, Ligeer Ce, Yangchun Li, Zhongda Lin, Apostolos Voulgarakis, and Yongkang Xue
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Extreme fire events are increasing, and fires are projected to rise across most regions, posing growing risks to ecosystems and society. As a key Earth system process, fire is now modeled in most Earth System Models (ESMs). FireMIP within CMIP7 will evaluate fire simulations in state‑of‑the‑art ESMs, project future fire changes, and provide quantitative, process‑based understanding of fire's role in the Earth system.
Hide
23 Dec 2025
Untangling the effects of vertical mixing schemes and convective adjustment in the Mediterranean Sea
Lucia Gualtieri, Paolo Oddo, Hans Burchard, Federica Borile, Aimie Moulin, Pietro Miraglio, Francesco Maicu, and Emanuela Clementi
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study addresses a gap in understanding how turbulent mixing closure schemes and convective adjustments interplay in the Mediterranean Sea. Coupled ocean-wave simulations were performed with different mixing parameterizations and model results were compared against Argo float observations across different space and time scales. Results show that the Generalised Length Scale closure scheme best reproduces observed mixed layer properties and variability, without needing convective adjustment.
Hide
23 Dec 2025
Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 2: Multi-year prospective and retrospective performance evaluation
Michael D. Moran, Alexandru Lupu, Verica Savic-Jovcic, Junhua Zhang, Qiong Zheng, Elisa I. Boutzis, Rabab Mashayekhi, Craig A. Stroud, Sylvain Ménard, Jack Chen, Konstantinos Menelaou, Rodrigo Munoz-Alpizar, Dragana Kornic, and Patrick M. Manseau
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Here we present an evaluation of 5 annual runs made with the Regional Air Quality Deterministic Prediction System, an operational chemical weather forecast system for North America. Measurements included NO
, O
, and PM
2.5
, 8 other gas-phase species, 7 PM
2.5
species, and 3 ions in precipitation. Routine scores were augmented by many stratified analyses, and the results point to some model components where improvements are desirable. A companion paper provides a full description of the system.
Hide
22 Dec 2025
Towards standardising output datasets using the numerical obstacle-resolving model MITRAS as an example
Vivien Voss, K. Heinke Schlünzen, David Grawe, and Karolin S. Samsel
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This work describes necessary adaptations and extensions to the post-processing of the obstacle-resolving microscale model MITRAS, with the aim of producing and publishing well-described model results that adhere to established meteorological data standards. The described process may help data producers facing similar difficulties to find ideas and solutions and addresses the need for standardisation within the urban microscale modelling community.
Hide
21 Dec 2025
Optimizing Gaussian Process Emulation and Generalized Additive Model Fitting for Rapid, Reproducible Earth System Model Analysis
Kunal Ghosh and Leighton A. Regayre
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Understanding which parts of climate models cause uncertainty requires many large computer experiments. We developed a new workflow that greatly improves the speed and efficiency of these studies. It can analyse millions of model variations up to 25 times faster without losing accuracy, allowing scientists to explore uncertainty in more detail and make climate predictions more reliable.
Hide
19 Dec 2025
Modelling wind farm effects in HARMONIE-AROME (cycle 43.2.2) – part 2: Wind turbine database and application to Europe
Jana Fischereit, Bjarke T. E. Olsen, Marc Imberger, Henrik Vedel, Kristian H. Møller, Andrea N. Hahmann, and Xiaoli Guo Larsén
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
We evaluated how operating wind farms influence the atmosphere in numerical weather prediction using two wind farm parameterizations in the HARMONIE-AROME model, applied by over 10 European weather services. Accurate yield forecasts require including both onshore and offshore turbines. Wind turbines slightly alter near-surface temperature (<1 K on average). We also present an open-access European wind turbine dataset combining multiple data sources.
Hide
19 Dec 2025
An objective dynamic multivariable weighting method for reducing uncertainty in WRF parameterization scheme selection
Tianyu Gou, Yaoyang Deng, Jun Niu, and Shaozhong Kang
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
This study proposes a new method to improve climate simulation evaluation, tackling a key model error: selecting the best parameter combinations. Our "dynamic weighting" method automatically gives more importance to hard-to-predict variables, like precipitation and wind speed. When tested in two distinct climate regions, our approach identified model settings that produced more accurate and reliable forecasts than traditional equal-weighting methods, performing well in extreme weather years.
Hide
19 Dec 2025
Interpretation and Representation in Geomodels: The POKIMON Ontology for Formalizing Geomodelling Knowledge
Imadeddine Laouici, Boyan Brodaric, Christelle Loiselet, and Gautier Laurent
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
3D geoscience models lack transparency about the interpretation process and the assumption to model and represent geological entities, limiting explainability, reproducibility, and automation. To address this, we present POKIMON, an ontology that formalizes the expert knowledge, interpretative aspects, and geological entities descriptions underlying 3D geomodelling, enhancing understanding, transparency, and knowledge-driven automation.
Hide
19 Dec 2025
MESMER v1.0.0: Consolidating the Modular Earth System Model Emulator into a Sustainable Research Software Package
Victoria M. Bauer, Mathias Hauser, Yann Quilcaille, Sarah Schöngart, Lukas Gudmundsson, and Sonia I. Seneviratne
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
MESMER is a Python-based climate emulator that provides spatially resolved realizations of multiple climate variables. Version 1.0.0 of MESMER consolidates previous emulation methods into one numerically stable, well-documented, and user-friendly software package. It can generate large ensembles of annual and monthly mean temperatures, as well as several climate extreme indicators, within minutes. The software is shared together with pre-calibrated parameters to enable broad community adoption.
Hide
19 Dec 2025
Wave effect mechanisms enhancing sea–air CO
exchange and modulating seawater carbonate–pH adaptation in the POP2–waves coupled model
Yung-Yao Lan, Huang-Hsiung Hsu, Wei-Liang Lee, and Simon Chou
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Waves and bubbles enhance CO₂ exchange between ocean and air, especially under strong winds, but most models ignore these effects. We added a wave module to CESM1.2.2, capturing impacts on solubility and diffusivity, and compared results with NOAA’s CarbonTracker (CT2022). The new model better matches global CO₂ flux patterns, reduces pH changes and
dp
CO₂ differences, and shows how wave effects reveal the ocean’s buffering capacity through the carbonate–pH system.
Hide
18 Dec 2025
A Lagrangian Particle Tracking Framework for the Super-Droplet Method: Development, Implementation, and Application of Backward and Forward Algorithms in SCALE-SDM 5.2.6-2.3.1
Chongzhi Yin, Shin-Ichiro Shima, and Chunsong Lu
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We developed a tracking tool for cloud simulations that works in two directions. It allows researchers to follow droplets forward to observe their future evolution or trace droplets backward to identify their origins. Crucially, the system records every coalescence event between droplets. This preserves the complete growth history of rain, serving as a diagnostic tool to help scientists verify the detailed physics within cloud models.
Hide
17 Dec 2025
Using a Gaussian Process Emulator to approximate the climate response patterns to greenhouse gas and aerosol forcings
Laura A. Mansfield, Peer J. Nowack, Edmund M. Ryan, Oliver Wild, and Apostolos Voulgarakis
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We present a fast machine learning emulator that predicts how Earth’s surface temperature reacts within the first five years to changes in greenhouse gases and aerosol pollutants. It is trained on carefully designed simulations from a complex climate model, but can be run much faster. Our emulator can be used to show where the climate is most sensitive to different emissions and can help explore many possible future paths, making it easier to assess the climate effects of policy choices.
Hide
17 Dec 2025
TREED (v1.0): a trait- and optimality-based eco-evolutionary vegetation model for the deep past and the present
Julian Rogger, Khushboo Gurung, Emanuel B. Kopp, William J. Matthaeus, Benjamin J. W. Mills, Benjamin D. Stocker, Taras V. Gerya, and Loïc Pellissier
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Vegetation plays a fundamental role in regulating Earth’s climate on time scales ranging from seconds to millions of years. Here, we develop and test a new vegetation model that uses evolutionary principles to predict vegetation structure, functioning and diversity under environmental conditions fundamentally different from the present. Using the model in combination with fossil data from Earth's past may help to better understand the response of vegetation systems to environmental change.
Hide
17 Dec 2025
Transfer learning-based hybrid machine learning in single-column model of AFES v4
Yuya Baba
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Machine learning is becoming a useful tool for weather and climate prediction, but it has deficiencies in long-term prediction. Hybrid machine learning incorporated in dynamical models is expected to overcome the problem. To enhance the prediction using the hybrid model, this study adopted transfer learning to the model. The transfer learning reduces model’s mean state bias, thereby enhancing its potential for improving long-term prediction.
Hide
16 Dec 2025
A hybrid framework for the spin-up and initialization of distributed coupled ecohydrological-biogeochemical models
Taiqi Lian, Ziyan Zhang, Athanasios Paschalis, and Sara Bonetti
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
We introduce a new method to define initial conditions for spatially-distributed ecohydrological models with soil biogeochemistry. By combining a simplified simulation setup with a random forest technique, we reduced the computation time for model initialization by up to 90 % while adequately reconstructing soil carbon/nutrient spatial patterns. This efficient framework is broadly applicable to other models, enhancing the reliability of large-scale simulations of carbon and nutrient cycles.
Hide
15 Dec 2025
Earth system modelling of mercury using CESM2 – Part 3: Oceanic model POP2/Hg v1.0
Mao Mao, Yujuan Wang, Peng Zhang, Ling Li, Shaojian Huang, Chen Zhou, and Yanxu Zhang
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We developed a new global ocean model to understand how mercury moves and changes in seawater. The model closely matches observed mercury patterns, providing confidence in its results. It will serve as the ocean part of a fully coupled Earth system mercury model with air, land, and river processes, improving predictions of future mercury pollution and guiding strategies to protect marine life and human health.
Hide
15 Dec 2025
MATILDA-Online v1.0.1: A Cloud-based Open-Source Workflow for Modeling Water Resources in Glacierized Catchments
Phillip Schuster, Ana-Lena Tappe, Alexander Georgi, Christoph Schneider, Mia Janzen, and Tobias Sauter
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 3 comments)
Short summary
Short summary
We present MATILDA-Online, an open-source, cloud-based modeling toolkit, to support integrated water management in glacierized mountain regions. It integrates glacier and hydrology models with open data and cloud computing. Despite data scarcity, this tool empowers local professionals, students, and researchers to generate climate impact assessments, promoting informed decision-making. Despite its accessibility, effective calibration and interpretation still require expert knowledge.
Hide
09 Dec 2025
Automatic tuning of iterative pseudo-transient solvers for modelling the deformation of heterogeneous media
Thibault Duretz, Albert de Monserrat, Rubén Sevilla, Ludovic Räss, Ivan Utkin, and Arne Spang
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Geodynamic modeling helps scientists understand how the Earth deforms. New computer methods make these simulations faster and more efficient, especially on powerful computers. They automatically adjust settings for better performance and can handle complex materials and flow types. This approach makes it easier to study large, detailed models of Earth processes.
Hide
09 Dec 2025
SWEET – Shallow Water Equation Environment for Tests v1.0
Keerthi Gaddameedi, François Hamon, Dominik Huber, Thibaut Lunet, Pedro S. Peixoto, João Guilherme Caldas Steinstraesser, Martin Schreiber, and Valentina Schüller
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
We present the open-source software SWEET, with core written in C++, dedicated to the numerical simulation of global spectral methods for the rotating shallow water equations on the biperiodic plane and on the sphere. SWEET is designed to provide a fast and efficient environment for research around time integration methods relevant to atmospheric circulation models. The software offers a versatile implementation that allows users to easily set up and run custom time-stepping schemes.
Hide
09 Dec 2025
From Reanalysis to Climatology: Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific
Duc-Trong Le, Tran-Binh Dang, Anh-Duc Hoang Gia, Duc-Hai Nguyen, Minh-Hoa Tien, Xuan-Truong Ngo, Quang-Trung Luu, Quang-Lap Luu, Tai-Hung Nguyen, Thanh T. N. Nguyen, and Chanh Kieu
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We study how and where tropical storms begin in the western North Pacific. Using many years of global weather data and a modern pattern-recognition method, we built a model that learns signals that come before storm formation and maps when and where formation is likely. It reproduces known seasonal and regional patterns and identifies key environmental cues. These results can support better risk planning and help refine climate projections.
Hide
09 Dec 2025
Operational chemical weather forecasting with the ECCC online Regional Air Quality Deterministic Prediction System version 023 (RAQDPS023) – Part 1: System description
Michael D. Moran, Verica Savic-Jovcic, Craig A. Stroud, Sylvain Ménard, Wanmin Gong, Junhua Zhang, Qiong Zheng, Jack Chen, Ayodeji Akingunola, Alexandru Lupu, Konstantinos Menelaou, and Rodrigo Munoz-Alpizar
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Canada's weather agency uses an online chemical weather forecast system to produce forecasts of key air pollutants over North America. Here we describe two recent versions of this Regional Air Quality Deterministic Prediction System (RAQDPS), including the meteorological host model, embedded chemistry module, and two downstream systems. Three simplifications to reduce run time are also described. A companion paper presents results from a comprehensive, 5-year evaluation of RAQDPS predictions.
Hide
04 Dec 2025
Sensitivity of cloud structure and precipitation to cloud microphysics schemes in ICON and implications for global km-scale simulations
Maor Sela, Philipp Weiss, and Philip Stier
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Clouds play a key role in Earth’s climate, but their representation in models remains uncertain. We use high-resolution simulations to examine how two statistical representations of cloud processes influence cloud and rain formation, and how these effects manifest in global models. We find that simulated clouds are highly sensitive to the chosen method, and that features such as rain, fog, and ice become even more variable at the global scale.
Hide
25 Nov 2025
ISARD (v1.0) : A Reproducible Geostatistical Framework for Daily Precipitation Ensemble in Mountainous Terrain
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
Traditional precipitation analysis often misrepresent seasonal totals and spatial variability of intense rainfall in mountains. This study introduces a reproducible workflow to generate a daily precipitation ensembles, conditioned on rain gauges. It outperforms standard products by better capturing seasonal totals. It also quantifies interpolation uncertainty, improving flood modeling. The open-source workflow is transferable to regions with sparse rain-gauge networks or limited radar coverage.
Hide
25 Nov 2025
AerChemMIP2 – Unraveling the role of reactive gases, aerosol particles, and land use for air quality and climate change in CMIP7
Stephanie Fiedler, Fiona M. O'Connor, Duncan Watson-Parris, Robert J. Allen, William J. Collins, Paul T. Griffiths, Matthew Kasoar, Jarmo Kikstra, Jasper F. Kok, Lee T. Murray, Fabien Paulot, Maria Sand, Steven Turnock, James Weber, Laura J. Wilcox, and Vaishali Naik
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The Aerosol and Chemistry Model Intercomparison Project phase two (AerChemMIP2) allows the community to compare results from contemporary Earth system models. AerChemMIP2 is asking modelling centres to perform experiments following the same protocol. It includes experiments for enabling new science and for tracking progress. Model output will be used for addressing research and policy questions about anthropogenic and natural drivers of climate change, and the impacts on air quality.
Hide
25 Nov 2025
Process-Oriented Evaluation of Stationary Rossby Waves and Their Impact on Surface Air Temperature Extremes in Dynamical Downscaling over North America
Koichi Sakaguchi, Seth A. McGinnis, L. Ruby Leung, Melissa S. Bukovsky, Rachel R. McCrary, Ziming Chen, Chuan-Chieh Chang, and Yanjie Li
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We evaluated Rossby waves in dynamical downscaling simulations over North America, and their connections to surface air temperature variability and heatwaves. Simulated Rossby wave propagation is distorted by flow discontinuities at lateral boundaries and by biased mean wind patterns, thereby breaking the region-specific connections between Rossby waves and surface temperature. Adjusting simulated large-scale winds to match the forcing data can reduce these biases.
Hide
24 Nov 2025
Development and Testing of Ensemble-Variational Data Assimilation Capabilities for Radar Data within JEDI coupled with FV3-LAM Model
Jun Park, Chengsi Liu, and Ming Xue
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
This study develops and tests new methods to improve weather forecasts by using radar observations within a modern data assimilation system called the Joint Effort for Data Assimilation Integration. The approach combines information from radar measurements and computer models to better describe storms. Tests with a major U.S. storm show improved prediction of rainfall and storm structure.
Hide
24 Nov 2025
Modeling of radiative transfer through cryospheric Earth system: software package SCIATRAN
Linlu Mei, Vladimir Rozanov, Alexei Rozanov, and John P. Burrows
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
As climate change causes this ice to melt, this reflective shield shrinks, accelerating global warming. We improved how the software calculates light interaction with snow and ice and then verified its accuracy against real-world measurements. This freely available tool provides scientists with a more precise way to predict the pace of climate change, helping us understand the future of our warming planet.
Hide
21 Nov 2025
Reduced Complexity Model Intercomparison Project Phase 3: Experimental protocol for coordinated constraining and evaluation of Reduced-Complexity Models
Alejandro Romero-Prieto, Marit Sandstad, Benjamin M. Sanderson, Zebedee R. J. Nicholls, Norman J. Steinert, Thomas Gasser, Camilla Mathison, Jarmo Kikstra, Thomas J. Aubry, and Chris Smith
EGUsphere,
2025
Short summary
Short summary
Reduced-complexity models are an important tool in climate science, helping us understand and estimate future climate change. We present the experimental protocol for the next phase of the reduced-complexity model intercomparison project, which aims to compare results from many such models to better understand their behaviour. This knowledge will guide how these models are developed and used in the future, including in the upcoming IPCC assessment report (AR7).
Hide
20 Nov 2025
HAMSOM-VICE v0.9: Comparison of two variable ice-ocean drag coefficient parameterizations on annual simulations of Bohai Sea ice
Libang Xu, Bin Jia, Yu Liu, Xue'en Chen, and Donglin Guo
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
We compared two methods to calculate ice-ocean drag coefficient in Bohai Sea. Results demonstrate that in the thin ice environment, the ice-bottom surface skin drag and the ice floe edge form drag are the main components. One method better predicts ice extent, the other better predicts ice season duration. Higher ice-ocean drag melts ice from below and cools water to form new ice. Our findings improve regional ice forecasts, enhancing safety for shipping and coastal industries.
Hide
20 Nov 2025
Global parameter sensitivity analysis of modelling water, energy and carbon dynamics in a temperate swamp
Oluwabamise Lanre Afolabi, Hongxing He, and Maria Strack
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 1 comment)
Short summary
Short summary
Our study completed an uncertainty analysis of a modelling experiment for multi-decade biophysical conditions (e.g., plant processes and hydrology) and carbon (C) flux simulations at a temperate swamp in Southern Ontario, Canada. The adopted uncertainty analysis technique (GLUE) improved the modelling outcomes of our study. Consequently, the findings of this research will help inform decision making on future C flux modelling experiments and peatland C management in temperate swamps.
Hide
18 Nov 2025
SIM-HOM (version 1.0): a Mechanistic Module for the formation of highly oxygenated organic molecules from Isoprene, Monoterpene and Sesquiterpene evaluated with ADCHAM (version 1.0)
Liwen Yang, Wei Nie, Mikael Ehn, Chao Yan, Lubna Dada, Yuliang Liu, Pontus Roldin, and Aijun Ding
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
SIM-HOM (Sesquiterpene, Isoprene and Monoterpene-derived Highly Oxygenated organic Molecules) is a mechanistic module that fully simulates HOM formation from key biogenic precursors, unlocking hidden chemistry that shapes clouds and climate. It captures the role of isoprene-derived products in seeding upper-troposphere clouds, quantifies low-volatility compounds driving aerosol formation, and provides quasi-molecular resolution to link gas-phase chemistry to aerosol impacts.
Hide
18 Nov 2025
Ensemble forecasts of isolated and compound wind and precipitation extremes in Europe using HC-SWG (v3.1) and MA-SWG (v1.1) Stochastic Weather Generators
Meriem Krouma and Gabriele Messori
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We present two forecasting methods for extreme precipitation and wind in Europe, using stochastic weather generators and past atmospheric patterns. One targets precipitation via weather model reforecasts; the other predicts wind from large-scale patterns. Both outperform standard weather models up to 10 days ahead, offering improved accuracy for both individual and compound extreme events.
Hide
17 Nov 2025
Implementing belowground controls on nutrient uptake in ELMv2-SPRUCE improves representation of a boreal peatland ecosystem
Yaoping Wang, Daniel M. Ricciuto, Jiafu Mao, Sören E. Weber, Verity G. Salmon, Xiaoying Shi, Xiaojuan Yang, Natalie A. Griffiths, Paul J. Hanson, Katherine Duchesneau, Camille E. Defrenne, Jeffrey M. Warren, Stephen D. Sebestyen, Keith Oleheiser, Melanie A. Mayes, and Peter E. Thornton
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
Boreal peatlands store much of the global soil carbon, a service dependent on nutrient limitation on plant productivity. This study improved a major land surface model to better represent how plants gain nitrogen and phosphorus through fine roots and mycorrhizal association. The new model more accurately captured observed carbon fluxes than the default model at an experimental site in Minnesota, and suggests shifts in nutrient uptake strategy helps peatlands stay carbon-rich under warming.
Hide
13 Nov 2025
DRYP 2.0: A hydrological model for local and regional scale across aridity gradients
Edisson Andrés Quichimbo, Michael Bliss Singer, Katerina Michaelides, and Mark O. Cuthbert
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
DRYP 2.0 is a substantially enhanced version of the DRYland water Partition model designed to improve large-scale water balance simulations. It integrates critical new capabilities for simulating ephemeral ponds/lakes, interacting hydrogeological domains, and explicit vegetation interception, while remaining computationally efficient. Tested over the Horn of Africa, DRYP 2.0 reproduces global satellite observations without calibration, advancing hydrological modelling across aridity gradients.
Hide
13 Nov 2025
Curlew
1.0: Spatio-temporal implicit geological modelling with neural fields in python
Akshay V. Kamath, Samuel T. Thiele, Marie Moulard, Lachlan Grose, Raimon Tolosana-Delgado, Michael J. Hillier, Florian Wellmann, and Richard Gloaguen
External preprint server,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We present
curlew
, an open-source Python tool for constructing 3D geological models using machine learning. It integrates diverse spatial data and structural observations into a flexible, event-based framework.
Curlew
captures complex features like folds and faults, handles uncertainty, and supports learning from sparse or unlabelled data. We demonstrate its capabilities on synthetic and real-world examples.
Hide
13 Nov 2025
Meta-modelling of carbon fluxes from crop and grassland multi-model outputs
Roland Hollós, Nándor Zrinyi, Zoltán Barcza, Gianni Bellocchi, Renáta Sándor, János Ruff, and Nándor Fodor
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
This work builds upon and extends previous multi-model ensemble studies by introducing four meta-modelling approaches to predict ecosystem-scale C fluxes. Our results show that meta-models consistently outperform both the multi-model median and the best individual process-based models, improving explained variance by up to 38.5 % and substantially reducing bias, even for challenging fluxes such as total ecosystem respiration and net ecosystem exchange.
Hide
13 Nov 2025
Improving Simulation of Earth System Variability through Weakly Coupled Ocean Data Assimilation in E3SM
Pengfei Shi, L. Ruby Leung, Zhaoxia Pu, Samson Hagos, and Karthik Balaguru
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Reliable climate prediction requires accurate initialization of the ocean state. We developed a new data assimilation system that incorporates ocean temperature and salinity observations into a fully coupled climate model. This system improves simulations of Earth system variability from years to decades, and enhances skills in simulating winter temperature and precipitation variability over the United States. The results advance more reliable and skillful climate predictions.
Hide
13 Nov 2025
Two-Phase Thermal Simulation of Matrix Acidization Using the Non-Isothermal Darcy–Brinkman–Forchheimer Model
Yuanqing Wu and Jisheng Kou
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 2 comments)
Short summary
Short summary
Our study shows how heating up acid used in oil recovery can dramatically change the way it dissolves rock underground. While the natural temperature of the rock hardly matters, hotter acid speeds up reactions and carves more efficient flow channels. Interestingly, this has the same effect as slowing down the injection speed. These insights could help the energy industry design smarter treatments to boost oil production while using less acid.
Hide
12 Nov 2025
Simulated and Observed Transport Estimates Across the Overturning in the Subpolar North Atlantic Program (OSNAP) Section
Gokhan Danabasoglu, Frederic S. Castruccio, Burcu Boza, Alice M. Barthel, Arne Biastoch, Adam Blaker, Alexandra Bozec, Diego Bruciaferri, Frank O. Bryan, Eric P. Chassignet, Yao Fu, Ian Grooms, Catherine Guiavarc'h, Hakase Hayashida, Andrew McC. Hogg, Ryan M. Holmes, Doroteaciro Iovino, Andrew E. Kiss, M. Susan Lozier, Gustavo Marques, Alex Megann, Franziska U. Schwarzkopf, Dave Storkey, Luke van Roekel, Jon Wolfe, Xiaobiao Xu, and Rong Zhang
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 16 comments)
Short summary
Short summary
A comparison of simulated and observed overturning transports across the Overturning in the Subpolar North Atlantic Program sections for the 2014–2022 period is presented. Eighteen ocean simulations participate in the study. The simulated transports are in general agreement with observations. Analyzing overturning circulations in both depth and density space together provides a more complete picture of the overturning properties. The study serves as a benchmark for evaluation of ocean models.
Hide
12 Nov 2025
Grounding-line dynamics in a Stokes ice-flow model (Elmer/Ice v9.0): Improved numerical stability allows larger time steps
A. Clara J. Henry, Thomas Zwinger, and Josefin Ahlkrona
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
To overcome time-step restrictions, we implement the Free-Surface Stabilisation Algorithm (FSSA) at the ice-ocean interface in Stokes ice-sheet simulations. In 2D experiments, a time step of 10 years is generally numerically stable and accurate, whereas a time step of 50 years is stable, but cannot fully capture grounding-line dynamics. Implementation at the ice-ocean interface increases the applicability of Stokes models and motivates future coupling with adaptive time-stepping schemes.
Hide
10 Nov 2025
Eradiate: An Accurate and Flexible Radiative Transfer Model for Earth Observation and Atmospheric Science
Vincent Leroy, Nicolae Marton, Claudia Emde, Nicolas Misk, Misael Gonzalez Almeida, Sebastian Schunke, Noelle Cremer, Ferran Gascon, and Yves Govaerts
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Eradiate is open-source software that models how light travels through Earth's atmosphere and reflects off its surface. Using computer graphics rendering technology, it simulates satellite observations by accurately representing both surface and atmosphere in a unified framework. This bridges otherwise separate scientific communities, enabling the generation of accurate synthetic reference data to improve satellite products used for pollution tracking, climate monitoring, or land use assessment.
Hide
07 Nov 2025
An improved modelling chain for bias-adjusted high-resolution climate and hydrological projections for Norway
Shaochun Huang, Wai Kwok Wong, Andreas Dobler, Sigrid Jørgensen Bakke, Stein Beldring, Ingjerd Haddeland, Hans Olav Hygen, Tyge Løvset, Stephanie Mayer, Kjetil Melvold, Irene Brox Nilsen, Gusong Ruan, Silje Lund Sørland, and Anita Verpe Dyrrdal
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This paper documents the model experiment used to generate the most updated, comprehensive and detailed climate and hydrological projections for the national climate assessment report for Norway published in October 2025. The new datasets (COR-BA-2025 and distHBV-COR-BA-2025) of these projections are openly accessible and will serve as a knowledge base for climate change adaptation to decision makers at various administrative levels in Norway.
Hide
07 Nov 2025
A highly-efficient automated optimization approach for kilometer-level resolution Earth system models on heterogeneous many-core supercomputers
Xiaojing Lv, Zhao Liu, Yuxuan Li, Shaoqing Zhang, Haohuan Fu, Xiaohui Duan, Shiming Xu, Yang Gao, Yujing Fan, Lifeng Yan, Haopeng Huang, Haitian Lu, Lingfeng Wan, Haoran Lin, Qixin Chang, Chenlin Li, Quanjie He, Yangyang Yu, Qinghui Lin, Sheng Jia, Tengda Zhao, Weiguo Liu, and Guangwen Yang
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
This study introduces a highly-efficient optimization approach that integrates automated and fine-grained optimizations for kilometer-level Earth System Models on heterogeneous many-core supercomputers. Our optimization achieves full parallel coverage for code segments exceeding 1 % of runtime. The optimized 5-km/3-km coupled model reaches 222 Simulated Days Per Day. This work signifies a pivotal advancement in ESMs, providing a robust platform for HR climate simulations.
Hide
05 Nov 2025
Assimilating Geostationary Satellite Visible Reflectance Data: developing and testing the GSI-EnKF-CRTM-Vis technique
Chong Luo, Yongbo Zhou, Yubao Liu, Wei Han, Bin Yao, and Chao Liu
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We developed a new technique to assimilate satellite visible reflectance. By testing our technique on a heavy rainfall event, we found that it significantly reduces errors in cloud water estimates and enhances light precipitation forecasts. This data assimilation also better improved thin clouds. This advancement helps increase the accuracy of weather predictions in situations where clouds and rain play a major role.
Hide
05 Nov 2025
Iterative run-time bias corrections in an atmospheric GCM (LMDZ v6.3)
Gerhard Krinner, Aude Champouillon, Juliette Blanchet, and Frédérique Chéruy
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Although the scientific community has made much progress over the last decades, climate models still do not perfectly simulate the present climate. Therefore, the model outputs are usually corrected for these errors. This article presents a method to apply successive stages of repeated error correction that lead to a better simulation of the present climate than in previous studies, in which the same correction method had been applied only once.
Hide
04 Nov 2025
Evaluating the EPICC-Model for Regional Air Quality Simulation: A Comparative Study with CAMx and CMAQ
Mengjie Lou, Qizhong Wu, Wending Wang, Huansheng Chen, Kai Cao, Xiaohan Fan, Dingyue Liang, Fenfen Yu, Jiating Zhang, Wei Wang, and Zifa Wang
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
This study compares the performance of the independently developed EPICC-Model with CAMx and CMAQ in simulating PM
2.5
and O
in China. It finds that EPICC-Model excels in simulating summer ozone peaks, accurately captures pollution characteristics in highly polluted areas, and better reproduces persistent compound pollution processes. Furthermore, this study reveals common issues among the models and directions for improvement, providing a basis for optimizing global air quality models.
Hide
03 Nov 2025
A Global High-Resolution Hydrological Model to Simulate the Dynamics of Surface Liquid Reservoirs: Application on Mars
Alexandre Gauvain, François Forget, Martin Turbet, Jean-Baptiste Clément, Lucas Lange, and Romain Vandemeulebrouck
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
In this paper, we present a global high-resolution hydrological model to investigate how water may have once flowed and accumulated on Mars. Using detailed topography, the model tracks how lakes and seas form, grow, merge, overflow, and dry out over time. It reveals how a vast northern ocean could emerge from smaller bodies of water. This approach links surface landforms to past climates, offering new perspectives on Mars' watery history and its potential habitability.
Hide
03 Nov 2025
Actionable reporting of CPU-GPU performance comparisons: Insights from a CLUBB case study
Gunther Huebler, Vincent E. Larson, John Dennis, and Sheri Voelz
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
Central processing units (CPUs) and graphics processing units (GPUs) are different devices that suit different kinds of work. Using a climate modeling component, we provide a clearer way to tell which device type is faster for a given task. This matters because runs usually use only one device type. Our results are actionable: they guide device choice, report performance gains fairly, highlight code areas to improve, and show how code structure and optimization can change conclusions.
Hide
03 Nov 2025
Benchmarking the reactive transport code SCEPTER v1.0.2
Yoshiki Kanzaki and Christopher T. Reinhard
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
The SCEPTER model has been recently developed for simulating elemental cycles in managed lands, especially soil acidity management and carbon sequestration via enhanced weathering. This paper demonstrates that the performance of SCEPTER is essentially identical to other soil hydrological and reactive transport codes through benchmark experiments. We also discussed the emerging need for a benchmarking protocol fit for the purpose of predictive modeling of soil pH management in agricultural lands.
Hide
30 Oct 2025
GEOS-Chem-hyd: enabling source-oriented sensitivity analysis with GEOS-Chem
Samuel O. Akinjole and Shannon L. Capps
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
Air pollution degrades human health and public welfare. Quantifying the impacts of diverse sources of air pollution is challenging. Simulations are helpful for understanding these complex interactions and end points. With this development, a well-regarded simulation of air pollutants may now trace where pollution from a selected source goes around the world and what happens to it chemically when it is released into the atmosphere. This augmented model may help scientists and decisionmakers.
Hide
30 Oct 2025
Version 3.0 of the Crocus snowpack model
Matthieu Lafaysse, Marie Dumont, Basile De Fleurian, Mathieu Fructus, Rafife Nheili, Léo Viallon-Galinier, Matthieu Baron, Aaron Boone, Axel Bouchet, Julien Brondex, Carlo Carmagnola, Bertrand Cluzet, Kévin Fourteau, Ange Haddjeri, Pascal Hagenmuller, Giulia Mazzotti, Marie Minvielle, Samuel Morin, Louis Quéno, Léon Roussel, Pierre Spandre, François Tuzet, and Vincent Vionnet
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This article is a comprehensive description of the 3.0 stable release of the Crocus snowpack model. It describes various new implementations since the last reference article in 2012 and a review of the available scientific evaluations and applications of the model. This provides guidance for the future of numerical snow modelling.
Hide
30 Oct 2025
ImpactETC1.0: Impact-oriented tracking of extratropical cyclones with global optimisation and track reconciliation
Niels Agertoft, Jian Su, Jonas Wied Pedersen, Ida Margrethe Ringgaard, and Morten Andreas Dahl Larsen
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Extratropical cyclones (ETCs) drive severe weather and cause significant socio-economic impacts. We present ImpactETC1.0, a framework that identifies ETC tracks and links them to local impacts, here storm surges. It uses global optimisation, BLOB analysis, and automated calibration to improve tracking quality and identify impact-relevant tracks. Applied to CERRA data, it produced longer, more consistent tracks at low cost. Results show ImpactETC1.0 enables efficient, impact-focused ETC tracking.
Hide
30 Oct 2025
T-REX: The tile-based representation of lateral exchange processes in ICON-Land
Philipp de Vrese, Tobias Stacke, Veronika Gayler, Helena Bergstedt, Clemens von Baeckmann, Melanie Thurner, Christian Beer, and Victor Brovkin
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The spatial variability in the land surface properties is often not captured by the resolution of land surface models. To overcome this limitation, most models subdivide the grid cells into fractions with homogeneous characteristics, for which the land processes are calculated separately. In reality, the fractions interact via the lateral exchange of water and heat, and the present manuscript details an approach to include these fluxes in the land component of the ICON modeling framework.
Hide
29 Oct 2025
Regional CO
and CH
inversion system using WRF-Chem (v4.4)/DART (v9.8.0) and continuous high-precision observations over the Korean Peninsula
Doyoon Kwon, Bonhoon Koo, Jooyeop Lee, Jeongwon Kim, Jaehyung Ahn, Jinkyu Hong, Eri Saikawa, Alexander Avramov, Changsub Shim, Je-Woo Hong, Daegeun Shin, Shanlan Li, Sumin Kim, and Sangwon Joo
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
We introduce a high-resolution system to estimate how much carbon dioxide and methane people emit across the Korean Peninsula. It combines a weather model with continuous ground measurements to make more accurate maps of emissions. Tested for 2020, it reduced errors by about one third to one half and agreed well with aircraft profiles for carbon dioxide. The results pinpoint where current inventories likely miss sources, supporting national monitoring and stronger climate policy.
Hide
29 Oct 2025
A food crop yield emulator for integration in the compact Earth system model OSCAR (OSCAR-crop v1.0)
Xinrui Liu, Thomas Gasser, Jianmin Ma, Junfeng Liu, Jonas Jägermeyr, Christoph Müller, Christian Folberth, Florian Zabel, Atul Jain, Wenfeng Liu, and Heidi Webber
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This paper presents a crop yield emulator for four major crops (maize, rice, soybean, and wheat). Trained on process-based crop model simulations, it captures yield responses to key drivers: atmospheric CO
, temperature, water availability, and nitrogen use. The emulator closely reproduces the behavior of complex crop models and aligns well with FAO-reported historical yields. It provides a robust and efficient method for representing agricultural outcomes in climate change impact assessments.
Hide
28 Oct 2025
copan:LPJmL: A new hybrid modelling framework for dynamic land use and agricultural management
Jannes Breier, Luana Schwarz, Hannah Prawitz, Werner von Bloh, Christoph Müller, Stephen Björn Wirth, Max Bechthold, Dieter Gerten, and Jonathan F. Donges
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We present a new modelling framework that links global vegetation and agricultural modelling with human decision-making processes in an integrated simulation approach. This makes it possible to explore how farming practices and environmental changes influence each other over time. By combining climate, land use, and social dynamics in one system, the framework opens new ways to study food security, climate adaptation strategies, and long-term impacts.
Hide
28 Oct 2025
MIPV-NWP-PINN V1.0: Development of a Multi-scale Photovoltaic Power Forecasting Framework Integrating Numerical Weather Prediction with Physics-Informed Neural Networks
Fei Zhang, Xingcai Li, Zifa Wang, Yunyun Wen, Xuyang Zhou, Zichen Wu, Zhuoran Wang, Huansheng Chen, Zhe Wang, and Xueshun Chen
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
Solar power generation depends on weather conditions and photovoltaic modules, making accurate forecasts crucial for reliable grid operation. We combined weather prediction and artificial intelligence to improve the solar power prediction at different time scales for a plant. By improving sunlight predictions and incorporating physical constraints into the model, our approach reduced errors significantly. This can help integrate clean energy into power grids safely and efficiently.
Hide
27 Oct 2025
OceanTracker 0.5: Fast Adaptable Lagrangian Particle Tracking in Structured and Unstructured Grids
Ross Vennell, Laurin Steidle, Malcolm Smeaton, Romain Chaput, and Ben Knight
External preprint server,
2025
Revised manuscript under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Ocean currents transport everything from pollution to marine larvae, but tracking millions of virtual particles to understand these movements typically requires weeks of computer processing. OceanTracker solves this bottleneck by being over ten times faster than existing tools, completing million-particle simulations in under an hour on standard computers. This speed breakthrough enables scientists to generate heat maps and analyze connectivity patterns between ocean regions.
Hide
27 Oct 2025
CLEO: The Numerical Methods of a New Superdroplet Model including a Droplet Breakup Algorithm
Clara J. A. Bayley, Ann Kristin Naumann, Florian Poydenot, Raphaela Vogel, Bjorn Stevens, and Shin-Ichiro Shima
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
We are developing a model called CLEO, a type of “Superdroplet Model” (SDM) for cloud microphysics, to try to overcome some of the issues faced by climate models which are caused by errors in cloud modelling. Here we describe the equations for cloud microphysics CLEO uses and how we solve them, such as to see how water-droplets move around and grow/shrink in the atmosphere. We also provide some demonstrations of the microphysical processes we model to show that CLEO works as intended.
Hide
24 Oct 2025
The Ocean Model for E3SM Global Applications: Omega Version 0.1.0. A New High-Performance Computing Code for Exascale Architectures
Mark R. Petersen, Xylar S. Asay-Davis, Alice M. Barthel, Carolyn Branecky Begeman, Siddhartha Bishnu, Steven R. Brus, Philip W. Jones, Hyun-Gyu Kang, Youngsung Kim, Azamat Mametjanov, Brian O’Neill, Kieran K. Ringel, Katherine M. Smith, Sarat Sreepathi, Luke P. Van Roekel, and Maciej Waruszewski
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Ocean models are used to predict currents, temperature, and salinity of the earth’s oceans, much like weather forecasting. As supercomputer hardware changes with evolving technology, models must be updated, and sometimes rewritten. Here we document Omega, a new ocean model that was designed to run on the world’s fastest supercomputers. Testing shows that Omega accurately solves the model equations, and runs efficiently on many different computer architectures, including exascale computers.
Hide
22 Oct 2025
CLEO: The Fundamental Design for High Computational Performance of a New Superdroplet Model
Clara J. A. Bayley, Tobias Kölling, Ann Kristin Naumann, Raphaela Vogel, and Bjorn Stevens
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 11 comments)
Short summary
Short summary
Cloud microphysics is a leading source of error in both regional and global climate models and this limits our ability to understand the Earth’s climate and how it is changing. However a fairly new type of model called a Superdroplet Model (SDM) may improve both regional and global models if it can be made cost-efficient enough. Hence we are introducing a novel version of SDM, called CLEO, and it's key features that make it efficient, especially on very high performance, “exascale”, computers.
Hide
21 Oct 2025
The DLR CO
-equivalent estimator FlightClim v1.0: an easy-to-use estimation of per flight CO
and non-CO
climate effects
Hannes Bruder, Robin Niclas Thor, Malte Niklaß, Katrin Dahlmann, Roland Eichinger, Florian Linke, Volker Grewe, Simon Unterstrasser, and Sigrun Matthes
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We develop an easy-to-use tool to estimate the per-flight climate effect of CO
and non-CO
emissions, based only on aircraft size as well as origin and destination airports. The implemented model results from a comparison of Multiple and Symbolic Regression approaches and exhibits a mean relative error of 21 % with respect to climate response model results. The simplified method is designed for climate footprint assessment and covers jet-powered passenger aircraft with over 20 seats.
Hide
20 Oct 2025
A novel cluster-based learning scheme to design optimal networks for atmospheric greenhouse gas monitoring (CRO
A version 1.0)
David Matajira-Rueda, Charbel Abdallah, and Thomas Lauvaux
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study presents a scheme,
Concepteur de Réseaux Optimaux d’Observations Atmosphériques
(CRO
A), for designing optimal mesoscale atmospheric monitoring networks without relying on typical inverse modeling assumptions. It leverages direct simulations of greenhouse gas concentrations to minimize the number of ground-based monitoring stations and maximize network performance through automated processing at a balanced computational cost, while being compatible with high-performance computing.
Hide
20 Oct 2025
A Hybrid Method for Winter Road Surface Temperature Prediction Using Improved LSTMs and Stacking-Based Ensemble Learning
Wanting Li, Linyi Zhou, Xianghua Wu, Miaomiao Ren, Yuanhao Guo, Kun Chen, and Huiwen Lin
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
To improve road safety during winter, we developed a model that predicts road surface temperatures using advanced deep learning and ensemble methods. By combining local pattern recognition with attention-based time modeling, our hybrid system outperformed individual models. Tested on real meteorological data, it achieved high accuracy even under sub-zero and extreme weather conditions, offering robust support for winter road management.
Hide
17 Oct 2025
AIFS 1.1.0: An update to ECMWF's machine-learned weather forecast model AIFS
Gabriel Moldovan, Ewan Pinnington, Ana Prieto Nemesio, Simon Lang, Zied Ben Bouallègue, Jesper Dramsch, Mihai Alexe, Mario Santa Cruz, Sara Hahner, Harrison Cook, Helen Theissen, Mariana Clare, Cathal O'Brien, Jan Polster, Linus Magnusson, Gert Mertes, Florian Pinault, Baudouin Raoult, Patricia de Rosnay, Richard Forbes, and Matthew Chantry
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We present the latest release of the
rtificial
ntelligence
orecasting
ystem, AIFS 1.1.0, which shows improved headline forecasting skill through an expanded dataset and enhanced training schedule. The model also incorporates hard physical constraints that facilitate training and improve rainfall prediction. Finally, we extend the set of forecasted variables to include soil conditions and energy-related fields, strengthening the operational value of AIFS.
Hide
16 Oct 2025
Stratospheric aerosol forcing for CMIP7 (part 1): Optical properties for pre-industrial, historical, and scenario simulations (version 2.2.1)
Thomas Jacques Aubry, Matthew Toohey, Sujan Khanal, Man Mei Chim, Magali Verkerk, Ben Johnson, Anja Schmidt, Mahesh Kovilakam, Michael Sigl, Zebedee Nicholls, Larry Thomason, Vaishali Naik, Landon Rieger, Dominik Stiller, Elisa Ziegler, and Isabel Smith
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
Climate forcings, such as solar radiation or anthropogenic greenhouse gases, are required to run global climate model simulations. Stratospheric aerosols, which mostly originate from large volcanic eruptions, are a key natural forcing. In this paper, we document the stratospheric aerosol forcing dataset that will feed the next generation (CMIP7) of climate models. Our dataset is very different from its predecessor (CMIP6), which might affect simulations of the 1850–2021 climate.
Hide
16 Oct 2025
Three-stream modelling of radiative transfer for the simulation of Black Sea biogeochemistry in a NEMO framework
Loïc Macé, Luc Vandenbulcke, Jean-Michel Brankart, Jean-François Grailet, Pierre Brasseur, and Marilaure Grégoire
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
In this paper, we propose a three-stream radiative transfer model and present a use case for the Black Sea. The model is able to simulate in-water irradiance and sea surface reflectance in a wide spectral range. When coupled with an ecosystem model, the simulated irradiances can be used to update water temperature and drive primary production in a consistent way. A stochastic version of this model is also proposed to inform on uncertainties in the optical properties of seawater.
Hide
16 Oct 2025
Representing Subgrid-Scale Cloud Effects in a Radiation Parameterization using Machine Learning: MLe-radiation v1.0
Katharina Hafner, Sara Shamekh, Guillaume Bertoli, Axel Lauer, Robert Pincus, Julien Savre, and Veronika Eyring
External preprint server,
2025
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Most climate models cannot resolve clouds and cloud-radiation interactions at coarse horizontal resolutions of about 100 km, which introduces uncertainties. High-resolution models resolve clouds better but are expensive to run. We use short high-resolution simulations and artificial intelligence to learn the cloud-radiation interactions without making any assumptions about the small scales. We propose a new method that significantly reduces cloud related errors.
Hide
15 Oct 2025
A Novel Method for Sea Surface Temperature Prediction using a Featural Granularity-Based and Data-Knowledge-Driven ConvLSTM Model
Mengmeng Cao, Kebiao Mao, Yibo Yan, Sayed Bateni, and Zhonghua Guo
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Accurately predicting long-term ocean temperatures is vital for climate science. We developed a new model that integrates multiple environmental variables using a novel spatiotemporal framework. Tests demonstrated consistent improvement over baseline models, delivering more accurate monthly temperature predictions up to a decade in advance.
Hide
15 Oct 2025
Evaluation of plume rise parameterizations in GEM-MACHv2 with analysis of image data using a deep convolutional neural network
Kevin M. Axelrod, Mark Gordon, Mohammad Koushafar, Jingliang Hao, Paul A. Makar, Sepehr Fathi, and Gunho Sohn
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
The is a study of the plumes that rise from smokestacks. Knowing how these plume behave helps predict downwind pollutant concentrations. We use photos over a 2-year period to investigate how these plumes rise under different conditions and compare this to a commonly used model parameterization. It is found that the equations used to model plume rise in current models do well for some condition, but these equations can over-predict the plume rise, typically during the day when it is hot.
Hide
14 Oct 2025
Two-tier MOM6 Regional Modelling Suite of the East Australian Current System
John Reilly, Chris Chapman, Courtney Quinn, Jules Kajtar, Ashley Barnes, and Neil Holbrook
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Recent advancements in regional ocean modelling allow higher resolution simulations providing improved estimates of the large-scale ocean state, while also revealing new insights into the fine-scale processes connecting the open ocean to the continental shelf seas. Our study highlights the importance of increased model resolution in regions of the ocean that are particularly turbulent while in quasi-stable circulation regions (e.g., jets), the current state-of-the-art global models do suffice.
Hide
14 Oct 2025
Implementation of predicted rime mass in the bin microphysics scheme DESCAM 3D: Heavy Snowfall event during ICE-POP 2018
Pierre Grzegorczyk, Wolfram Wobrock, Antoine Canzi, Frédéric Tridon, Gyuwon Lee, Kwonil Kim, Kyo-Sun Sunny Lim, and Céline Planche
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
This study evaluates the implementation of predicted rime mass distribution in the bin microphysics scheme DESCAM. Based on the ‘fill-in’ concept, the model allows a smooth transition between unrimed and graupel ice particle properties. The implementation is tested for a heavy snowfall event observed during the ICE-POP 2018 field campaign. The new version of DESCAM gives a better agreement with the observations with significant changes in the precipitation amount and spatial distribution.
Hide
13 Oct 2025
CarboKitten.jl – an open source toolkit for carbonate stratigraphic modeling
Johan Hidding, Emilia Jarochowska, Niklas Hohmann, Xianyi Liu, Peter Burgess, and Hanno Spreeuw
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Coral reefs and limestones hold crucial records of Earth's climate history, but scientists have lacked accessible tools to simulate how these systems form over thousands to millions of years. We developed CarboKitten, free software that models how tropical sediments and associated organisms grow under changing sea levels and environmental conditions. The program runs fast on standard computers and can test scientific theories about how these geological features preserve the Earth’s history.
Hide
13 Oct 2025
Short-Lived Halogen Sources and Chemistry in the Community Earth System Model v2 (CESM2-SLH)
Rafael Pedro Fernandez, Carlos Alberto Cuevas, Julián Villamayor, Aryeh Feinberg, Douglas E. Kinnison, Francis Vitt, Adriana Bossolasco, Javier A. Barrera, Amelia Reynoso, Orlando G. Tomazzeli, Qinyi Li, and Alfonso Saiz-Lopez
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
In this work we summarize 15 years of research and developments of short-lived halogens (SLH) using the Community Earth System Model (CESM) and present a complete description of the implementation and capabilities achieved with the new released version CESM2-SLH, including specific namelist options, input files and technical notes detailing the most important SLH updates that must be considered for the different model configurations and resolutions.
Hide
10 Oct 2025
Flood Volume Allocation Method for Flood Hazard Mapping Using River Model with Levee Scheme
Muhammad Hasnain Aslam, Yukiko Hirabayashi, Dai Yamazaki, Gang Zhao, Yuki Kita, and Do Ngoc Khanh
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
We present a simple method that turns coarse flood volume estimates into local flood depth maps by using the shape of the land and mapped levee zones. Used with a large-scale river model, it keeps total water volume consistent while spreading water realistically inside and outside levees. Tests show levees often confine water and cut flood volume by about 10–15 % for many event sizes. The method reveals place-to-place differences in protection and yields clearer hazard maps for planning.
Hide
04 Oct 2025
SWEpy: An Open-Source GPU-Accelerated Solver for Near-Field Inundation and Far-Field Tsunami Modeling
Juan Fuenzalida, Danilo Kusanovic, Joaquín Meza, Rodrigo Meneses, and Patricio Catalan
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
This study presents SWEpy, an open-source Python tool using GPUs to simulate water flows in floods and tsunamis, without the need for costly hardware or complex code. By refining methods to reduce wave spread errors, we tested it on standard cases and real events like a French dam break and a major Chilean earthquake tsunami. Results show SWEpy predicts wave heights and speeds effectively, potentially enhancing early warnings and saving lives in flood-prone areas.
Hide
01 Oct 2025
SODA4: a mesoscale ocean/sea ice reanalysis 1980–2024
Gennady A. Chepurin, James A. Carton, Luyu Sun, and Stephen G. Penny
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
Ocean reanalyses reconstruct the physical state of the ocean – its temperature, salinity, and currents – using historical observations to constrain a numerical simulation of the fluid equations of motion. This paper describes the SODA4 reanalysis, which is now able to resolve the oceanic eddy field and its interactions with the large-scale flow throughout most of the ocean. Reanalyses are key to climate research because they merge messy historical observations into a continuous climate record.
Hide
29 Sep 2025
Development and evaluation of a Sustainable Drainage System module into TEB (v 9.0) model
José Manuel Tunqui Neira, Katia Chancibault, Marie-Christine Gromaire, and Ghassan Chebbo
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We developed and evaluated a computer model that supports sustainable urban stormwater management. It simulates how green areas and drainage systems capture, store, and release rainwater, and performs well when compared with an established model. The results show it can reliably reproduce key water processes, providing a practical tool to help improve urban rainwater management.
Hide
26 Sep 2025
Ammonia Bidirectional Flux Model Tailored for Satellite Retrieval Parameter Inversions
Michael Sitwell, Mark W. Shephard, and Shailesh K. Kharol
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Bidirectional flux models give a unified model for emission and dry deposition, but few studies have been conducted in which satellite observations are used to refine the parameters in these models. A new bidirectional flux model for ammonia was developed that was designed specifically for use with satellite observations. Ammonia satellite observations were used to refine bidirectional flux model parameters, which improved the agreement of the model with ammonia surface observations.
Hide
24 Sep 2025
Leveraging JEDI for Atmospheric Composition: A unified framework for evaluating observations and model forecasts
Shih-Wei Wei, Jérôme Barré, Soyoung Ha, Cheng-Hsuan Lu, Maryam Abdi-Oskouei, Benjamin Ménétrier, and Cheng Dang
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This paper presents a flexible workflow using a unified data assimilation framework to evaluate atmospheric composition models. It enables comparison of observations with forecasts of trace gases and aerosols from different models. The system is consistent and adaptable, reducing repetitive work, supporting model validation and observation assessment, and aligning evaluation with operational data assimilation for research and practical applications.
Hide
24 Sep 2025
A sea ice free Arctic: Assessment Fast Track
abrupt-127k
experimental protocol and motivation
Louise C. Sime, Rachel Diamond, Christian Stepanek, Chris Brierley, David Schroeder, Masa Kageyama, Irene Malmierca-Vallet, Ed Blockley, Alex West, Danny Feltham, Jeff Ridley, Pascale Braconnot, Charles J. R. Williams, Xiaoxu Shi, Bette L. Otto-Bliesner, Sophia I. Macarewich, Silvana Ramos Buarque, Qiong Zhang, Allegra LeGrande, Weipeng Zheng, Dabang Jiang, Polina Morozova, Chuncheng Guo, Zhongshi Zhang, Nicholas Yeung, Laurie Menviel, Sandeep Narayanasetti, Olivia Reeves, Matthew Pollock, and Anni Zhao
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The Arctic may have lost its summer sea ice 127,000 years ago during a naturally warm period in Earth’s past. Climate models can be tested by recreating those conditions, with similar sunlight and greenhouse gas levels. Analysing the large sea ice changes in these simulations helps us understand how the Arctic might respond in the near future and improves how we test and trust our climate models.
Hide
23 Sep 2025
A Local Terrain Smoothing Approach for Stabilizing Microscale and High-Resolution Mesoscale Simulations: a Case Study Using FastEddy
(v3.0) and WRF (v4.6.0)
Eloisa Raluy-López, Domingo Muñoz-Esparza, and Juan Pedro Montávez
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
Steep terrain can cause numerical problems in weather and climate simulations. We present a new local method that smooths only the steepest areas, preserving important terrain details elsewhere. This improves numerical stability without reducing resolution across the entire map, as was common in previous global approaches. The technique is simple, fast, and effective across models and scales, helping researchers run more accurate and reliable high-resolution simulations over complex landscapes.
Hide
23 Sep 2025
The TIPMIP Earth system model experiment protocol: phase 1
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Hide
23 Sep 2025
Improvement of the Rnnmm type climate index approach with a spatio-temporal model based on the Hawkes process
Fidel Ernesto Castro Morales, Antonio Marcos Batista do Nascimento, Marina Silva Paez, Daniele Torres Rodrigues, and Carla de Moraes Apolinário
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This paper introduces a new spatio-temporal model for analyzing the Rnnmm index, based on Hawkes processes. It improves the understanding of extreme rainfall dynamics in Brazil’s Northeast region. The model is implemented in R and estimated via MCMC under a Bayesian framework.
Hide
18 Sep 2025
Pre-training for Deep Statistical Climate Downscaling: A case study within the Spanish National Adaptation Plan (PNACC)
Jose González-Abad, Maialen Iturbide, Alfonso Hernanz, and José Manuel Gutiérrez
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
We explore how deep learning can improve local climate projections by adapting a national model to regional data. By relying on a paradigm called pre-training, we showed that models can learn faster, generalize better, and produce more consistent results, even when data is limited. This helps make future climate projections more reliable and supports better planning at both national and local levels.
Hide
17 Sep 2025
The Radiative Forcing Model Intercomparison Project (RFMIP2.0) for CMIP7
Ryan Kramer, Chris Smith, and Timothy Andrews
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Natural or anthropogenic activities can cause a perturbation in Earth’s radiative energy budget known as a radiative forcing, which induces a climate response. Diagnosing radiative forcing and its uncertainty is foundational to understanding past and future climate change. Here we outline the protocol for the second iteration of the Radiative Forcing Model Intercomparison Project (RFMIP2.0), which provides a standardized method for diagnosing radiative forcing across Global Climate Models.
Hide
17 Sep 2025
Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)
Aaron S. Donahue, Elynn Wu, W. Andre Perkins, Peter M. Caldwell, Christopher S. Bretherton, Finn O. Rebassoo, and Jean-Christophe Golaz
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
This study tested using machine learning to speed up detailed simulations in the SCREAM model. By training ML models to correct a simpler version of SCREAM, some results improved, but others did not. Technical challenges were addressed, and new tools were developed. The work shows promise for making simulations more efficient, though further improvements are needed.
Hide
16 Sep 2025
MCSeg (v1.0): A Deep Learning Framework for Long-Term Large-Scale Mesoscale Convective Systems Identification and Precipitation Event Analysis
Peng Li, Zhanao Huang, Yongqiang Yu, Xi Wu, Xiaomeng Huang, and Xiaojie Li
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
Mesoscale convective systems (MCSs) are a major cause of severe weather events. Traditional MCS identification methods rely on threshold-based approaches, which are computationally inefficient. To address this limitation, we propose a novel deep learning model for automated MCS detection. Our model achieves comparable accuracy to threshold-based methods while delivering a 200× speedup in processing efficiency.
Hide
15 Sep 2025
LUCIE-3D: A three-dimensional climate emulator for forced responses
Haiwen Guan, Troy Arcomano, Ashesh Chattopadhyay, and Romit Maulik
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
LUCIE-3D is a fast machine learning climate model that simulates the atmosphere in 3D using 30 years of ERA5 data across eight levels. It takes changing CO
and optional SST to reflect ocean effects. LUCIE-3D reproduces means, variability, and long-term signals like surface warming and stratospheric cooling, and captures patterns such as equatorial Kelvin waves, the MJO, and annular modes. It trains in under five hours on four GPUs, supporting quick studies and coupled climate exploration.
Hide
15 Sep 2025
SPREADS: From Research to Operational Open-Source Data Assimilation System
Carla Cardinali, Giovanni Conti, Marcelo Guatura, Sami Saarinen, Luis Gustavo Gonçalves De Gonçalves, Jeffrey Anderson, and Kevin Raeder
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Scientists have developed research systems to test new ideas in data assimilation, but these often lack the efficiency and robustness needed for operational use. We addressed this gap with key innovations: a flexible observation database, first guess at the appropriate time, and modular, parallelised software enabling the assimilation of millions of observations.
Hide
15 Sep 2025
On moist ocean-atmosphere coupling mechanisms
Oksana Guba, Arjun Sharma, Mark A. Taylor, Peter A. Bosler, and Erika L. Roesler
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
It is important for computational Earth system models to capture interactions between the ocean and the atmosphere accurately. Because of incredible complexity of these interactions, computational models contain simplifications, which may hinder the models' capabilities. Here we focus on detailed analysis of thermodynamic interactions between the ocean and the atmosphere in computational Earth system models. We also provide a framework to show how modeling these interactions can be improved.
Hide
11 Sep 2025
PALM-meteo 2.6: Processor of PALM meteorological input data
Pavel Krč, Michal Belda, Martin Bureš, Kryštof Eben, Jan Geletič, Jelena Radović, Hynek Řezníček, and Jaroslav Resler
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
PALM is a highly versatile open-source microscale atmospheric modelling system. One of its most useful applications is modelling detailed street-level urban climate, e.g. for evaluation of climate change adaptation and mitigation measures in cities. However, to produce real-case microscale simulations, they need to be forced by real or realistic weather conditions. The presented tool enables PALM to use meteorological inputs from a large selection of meteorological models and other sources.
Hide
11 Sep 2025
OIRF-LEnKF v1.0: A Self-evolving Data Assimilation System by Integrating Incremental Machine Learning with a Localized EnKF for Enhanced PM
2.5
Chemical Component Forecasting and Analysis
Hongyi Li, Ting Yang, Lei Kong, Di Zhang, Guigang Tang, and Zifa Wang
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
Chemical transport model-based data assimilation is computationally inefficient for large ensemble sizes and offers limited improvements in forecasting PM
2.5
chemical components. This paper introduces a machine learning-based data assimilation system that facilitates rapid iterations for forecasting, assimilation, and incremental learning. Results show that our system achieves superior efficiency and accuracy in forecasting and assimilation compared to traditional data assimilation.
Hide
10 Sep 2025
Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models
Elias C. Massoud, Nathan Collier, Yaoping Wang, Jiafu Mao, Adrian Harpold, Steven A. Kannenberg, Gerbrand Koren, Mukesh Kumar, Pushpendra Raghav, Pallav Ray, Mingjie Shi, Jing Tao, Sreedevi P. Vasu, Huiqi Wang, Qing Zhu, and Forrest M. Hoffman
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
We studied how well Earth System Models simulate soil moisture and its connection to plant growth and water use. Using a model evaluation tool and real-world data, we found that models generally perform well at the surface but struggle deeper in the soil. These issues vary by region, especially in colder regions. Our results can help improve future model development and support better predictions of how ecosystems respond to a changing environment.
Hide
05 Sep 2025
Natural Methane Emissions Feedbacks in MAGICC v. 7.6
Trevor Martin Sloughter, Zebedee Nicholls, Gang Tang, Thomas Kleinen, Zhen Zhang, and Joeri Rogelj
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
High resolution models of the earth system exhibit some disagreement and uncertainty on future methane emissions from natural sources, in particular wetlands, with some studies predicting wetlands alone could be very significant sources over the 21st century. Modelling these emissions as a response to global temperature is one option for simple models to approximate the climate impact of wetlands. The effect is a small increase in overall temperatures and a widening of the uncertainty range.
Hide
04 Sep 2025
Simulation of wind and solar energy generation over California with E3SM SCREAM regionally refined models at 3.25 km and 800 m resolutions
Jishi Zhang, Jean–Christophe Golaz, Matthew Vincent Signorotti, Hsiang–He Lee, Peter Bogenschutz, Minda Monteagudo, Paul Aaron Ullrich, Robert S. Arthur, Stephen Po–Chedley, Philip Cameron–smith, and Jean–Paul Watson
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We ran a convection-permitting model with regional mesh refinement (3.25 km and 800 m) to simulate present-day wind and solar capacity factors over California, coupling it to an energy generation model. The high-resolution models captured realistic seasonal and diurnal cycles, with wind markedly better than a 25 km model and solar outperforming a 3 km operational forecast. We highlight the critical role of resolution, modeling assumptions, and data reliability in renewable energy assessment.
Hide
01 Sep 2025
Refining gravity anomaly data of coastal areas by combining XGM2019e-2159 and SRTM/GEBCO_2024 residual terrain model with forward modeling method
Yixiang Liu, Jinyun Guo, Bin Guan, Shaofeng Bian, Heping Sun, and Xin Liu
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study refines the coastal gravity anomaly model by constructing a residual terrain model using high-resolution topographic and bathymetric data. In the spatial domain, the RTM (residual terrain model) gravity forward modeling method is applied to effectively compensate for the missing high-frequency information in the XGM2019e-2159 gravity anomaly model. As a result, an RTM-corrected XGM2019e-2159 gravity anomaly model for the study area is obtained.
Hide
01 Sep 2025
A New Hybrid Framework for Digital Terrain Modeling Using Sector-Based Neighbor Selection and Neural Network Blending
Kadir Akgol and Yelda Nur Kara
EGUsphere,
2025
Preprint under review for GMD
(discussion: open, 5 comments)
Short summary
Short summary
We developed a new computer-based approach to create more accurate maps of land surfaces. By combining artificial intelligence with traditional mapping methods, our technique produces smoother and more realistic models with less manual effort. This can help engineers and planners design safer and more cost-effective projects in areas with complex terrain.
Hide
29 Aug 2025
Simultaneous versus sequential estimation of biogeochemical and physical parameters in coupled marine ecosystem models
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The parameters that control a model's behavior determine its ability to represent a system. In this work, multiple cases test how to estimate the parameters of a model with components corresponding to both the physics and the chemical and biological processes (i.e. the biogeochemistry) of the ocean. While demonstrating how to approach this problem type, the results show estimating both sets of parameters simultaneously is better than estimating the physics then the biogeochemistry separately.
Hide
29 Aug 2025
Spatialize v1.0: A Python/C++ Library for Ensemble Spatial Interpolation
Felipe Navarro, Alvaro F. Egaña, Alejandro Ehrenfeld, Felipe Garrido, María Jesús Valenzuela, and Juan F. Sánchez-Pérez
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Spatialize is an open-source Python/C++ library for Ensemble Spatial Interpolation (ESI), combining simple interpolation with geostatistics like Kriging. It uses random space partitions (Mondrian and Voronoi forests) and ensemble learning for robust, scalable spatial interpolation and uncertainty quantification. Designed for non-experts, Spatialize supports gridded and non-gridded data, automates hyperparameter search, and delivers competitive accuracy in geoscientific applications.
Hide
28 Aug 2025
Modelling diffusion, decay and ingrowth of U–Pb isotopes in zircon
Ben Steven Knight and Chris Clark
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
This study examines how high temperatures can alter the chemical record in zircon crystals used to date rock events. Using computer simulations, we model how movement of atoms, radioactive decay, and the formation of new elements interact in a zircon under changing heat conditions. Our simulation is compared with measurements from rocks in southern India to estimate temperature history of the region. The work aims to improve insights from rock dating and our understanding of Earth’s past.
Hide
27 Aug 2025
swLICOM: the multi-core version of an ocean general circulation model on the new generation Sunway supercomputer and its kilometer-scale application
Kai Xu, Maoxue Yu, Jiangfeng Yu, Jingwei Xie, Xiang Han, Jiaying Song, Mingyao Geng, Jinrong Jiang, Hailong Liu, Pengfei Wang, and Pengfei Lin
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
swLICOM represents a significant advancement in kilometer-scale resolution ocean general circulation models on heterogeneous computing architectures. Our optimization efforts addressed a series of challenges that are particularly crucial for high-resolution modeling. We use swLICOM with a horizontal resolution of 2 km to conduct a short-term simulation test. The 2-km resolution global simulation shows the high capacity of swLICOM to capture the oceanic meso- to submesoscale processes.
Hide
26 Aug 2025
A data-driven method for identifying climate drivers of agricultural yield failure from daily weather data
Lily-belle Sweet, Christoph Müller, Jonas Jägermeyr, and Jakob Zscheischler
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
This study presents a method to identify climate drivers of an impact, such as agricultural yield failure, from high-resolution weather data. The approach systematically generates, selects and combines predictors that generalise across different environments. Tested on crop model simulations, the identified drivers are used to create parsimonious models that achieve high predictive performance over long time horizons, offering a more interpretable alternative to black-box models.
Hide
20 Aug 2025
Development of a Semi-Lagrangian advection scheme in the Finite Element Model Elmer (v9.0): Application to Ice dynamics
Cyrille Mosbeux, Peter Råback, Adrien Gilbert, Julien Brondex, Fabien Gillet-Chaulet, Nicolas C. Jourdain, Mondher Chekki, Olivier Gagliardini, and Gaël Durand
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
Transport processes like rocks carried by ice flow and damage evolution – a proxy for crevasses – are key in ice sheet modeling and should occur without diffusion. Yet, standard numerical methods often blur these features. We explore a particle-based Semi-Lagrangian approach, comparing it to a Discontinuous Galerkin method, and show it can accurately simulate such transport when run at high enough resolution.
Hide
13 Aug 2025
darcyInterTransportFoam v1.0: an open-source, fully-coupled 3D solver for simulating surface water – saturated groundwater processes and exchanges
Álvaro Pardo-Álvarez, Jan H. Fleckenstein, Kalliopi Koutantou, and Philip Brunner
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
An upgraded version of a numerical solver is introduced to better capture the three-dimensional interactions between surface water and groundwater. Built using open-source software, it adds new features to handle the complexity of real environments, including the representation of subsurface geology and the simulation of diverse dynamic processes, such as solute transport and heat transfer, in both domains. A test case and a full description of the novel features are provided in this paper.
Hide
11 Aug 2025
GCAM-Europe v7.2.0: Enhancing Policy-Relevant Climate Modelling Through Spatial and Sectoral Detail
Jon Sampedro, Russell Horowitz, Clàudia Rodés-Bachs, and Dirk-Jan Van de Ven
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
GCAM-Europe is an open-access modelling tool designed to assess the impacts of climate and environmental policies across European countries. Built on a global framework, it adds detailed regional and sectoral representation for Europe, including energy, land use, water, and emissions. This allows for analysis of policy effects within and between countries, as well as global spillover effects, to support transparent, evidence-based decision-making.
Hide
08 Aug 2025
Benchmarking Photolysis Rates: Species for Earth and Exoplanets
Sophia Adams, James Manners, Nathan Mayne, Mei Ting Mak, and Eric Hebrard
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
We perform calculations of photolysis reactions using an existing model but including updated input data. These reactions are important in shaping the composition of our upper atmosphere and that of other planets, for example, controlling ozone formation and destruction. The results of our model are compared with those of previous benchmarks, and rates of various reactions provided to facilitate other researchers in developing accurate schemes to capture photolysis in planetary atmospheres.
Hide
06 Aug 2025
Computational library for the Nutrient-Unicellular-Multicellular plankton modeling framework v. 1.0
Amalia Papapostolou, Anton Vergod Almgren, Trine Frisbæk Hansen, Athanasios Kandylas, Camila Serra-Pompei, Andre William Visser, and Ken Haste Andersen
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
The Nutrient-Unicellular-Multicellular model library simulates marine plankton ecosystems, structuring predator-prey dynamics by body size. It integrates feeding strategies in single-cell plankton and copepod life stages, essential for understanding their growth, survival, and predator-prey interactions. Validated with real data, this user-friendly tool recreates ecosystems across scales, offering insights for marine ecology and biogeochemistry.
Hide
05 Aug 2025
Lateral heat fluxes amplify the aggregation error of soil temperature in non-sorted circles
Melanie A. Thurner, Xavier Rodriguez-Lloveras, and Christian Beer
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
Soil texture varies over centimeters, which is overseen by large-scale models, likely causing simulation errors. We developed a 2-dimesional geophysical soil model (DynSoM-2D) with a resolution of 10 cm and ran it with different setups at a permafrost-affected site. Using high-resolution input, DynSoM-2D simulates a warmer soil, which thaws deeper and has an extended snow-free period in summer. These changes can impact ecosystem dynamics, but have little effect on yearly soil-air heat exchange.
Hide
05 Aug 2025
BORIS-2 – a benthic ecosystem model based on allometry
Adrian Peter Martin, Noelie Benoist, Brian Bett, Anieke Brombacher, Jennifer Durden, Sophy Oliver, and Andrew Yool
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
Although seemingly inhospitable, under huge pressure and with permanent darkness, the seafloor has a diversity of organisms. They are almost entirely dependent on food sinking down through the ocean onto the seafloor. This model allows us to study how these organisms survive in this hostile environment. Making use of evidence that biological characteristics, like lifetime, vary with size and temperature, this model can simulate the fate of seafloor creatures from bacteria to large sea cucumbers.
Hide
04 Aug 2025
biogeodyn-MITgcmIS (v1): a biogeodynamical tool for exploratory climate modelling
Laure Moinat, Florian Franziskakis, Christian Vérard, Daniel N. Goldberg, and Maura Brunetti
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
We describe a new tool,
biogeodyn-MITgcmIS
, that consistently reproduces the global-scale dynamics of the ocean, atmosphere, vegetation and ice on multimillennial timescales at low computational cost. Evaluated against observations and state-of-the-art Earth system models, it includes offline coupling to models of vegetation, hydrology and a newly developed global-scale ice sheet. Using arbitrary continental configurations, it enables studies of past and present climates on Earth or exoplanets.
Hide
04 Aug 2025
Global Climate Modeling with Improved Precipitation Characteristics by Learning Physics (GRIST-MPS v1.0) from Global Storm-Resolving Modeling
Yiming Wang, Yi Zhang, Yilun Han, Wei Xue, Yihui Zhou, Xiaohan Li, and Haishan Chen
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
This work explores the use of global storm-resolving model (GSRM) simulation data to enhance global climate modeling (GCM) through a machine learning–based model physics suite. Stable multiyear climate simulations with improved precipitation characteristics are achieved by using 80-day GSRM data.
Hide
29 Jul 2025
Coupling of the Ice-sheet and Sea-level System Model (version 4.24) with hydrology model CUAS-MPI (version 0.1) using the preCICE coupling library
Daniel Abele, Thomas Kleiner, Yannic Fischler, Benjamin Uekermann, Gerasimos Chourdakis, Mathieu Morlighem, Achim Basermann, Christian Bischof, Hans-Joachim Bungartz, and Angelika Humbert
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
For accurate projections of the evolution of continental ice sheets in Greenland and Antartica, interactions between the ice and its environment must be included in simulations. For this purpose, we have implemented adapters for the ice sheet model ISSM and subglacial hydrology model CUAS-MPI for the coupling library preCICE. This simplifies the study of earth systems by allowing the models to interact with each other as well as with models of the oceans or atmosphere with very little effort.
Hide
15 Jul 2025
Biogeochemistry-Informed Neural Network (BINN) for Improving Accuracy of Model Prediction and Scientific Understanding of Soil Organic Carbon
Haodi Xu, Joshua Fan, Feng Tao, Lifen Jiang, Fengqi You, Benjamin Z. Houlton, Ying Sun, Carla P. Gomes, and Yiqi Luo
External preprint server,
2025
Revised manuscript under review for GMD
(discussion: final response, 9 comments)
Short summary
Short summary
We developed the Biogeochemistry-Informed Neural Network (BINN) which embeds a process-based model inside an AI framework so the model’s parameters can be learned from big data. BINN recovered known parameters in synthetic tests and revealed key controls when applied to about 25 000 soil profiles across the contiguous US. It operates more than 50 times faster than Bayesian approaches while reproducing similar key processes governing SOC stocks.
Hide
14 Jul 2025
A Geographically Weighted Gaussian Process Regression Emulator of the GCHP 13.0.0 Global Air Quality Model
Anthony Y. H. Wong, Sebastian D. Eastham, Erwan Monier, and Noelle E. Selin
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
We developed a fast and accurate computer tool that predicts how air pollution levels will change around the world under different climate and policy choices. Using machine learning and real model data, our tool can estimate changes in harmful fine particulate pollution in seconds instead of thousands of hours. This makes it easier for researchers and policymakers to explore future air quality and health impacts under a wide range of scenarios.
Hide
14 Jul 2025
MONKI: a three-dimensional Monte Carlo simulator of total and polarised radiation reflected by planetary atmospheres
Victor J. H. Trees, Ping Wang, Job I. Wiltink, Piet Stammes, Daphne M. Stam, David P. Donovan, and A. Pier Siebesma
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 2 comments)
Short summary
Short summary
We present MONKI (Monte Carlo KNMI), an efficient and accurate radiative transfer code written in Fortran. MONKI computes total and polarised radiances reflected and transmitted by planetary atmospheres, accounting for polarisation in all scattering orders. MONKI handles both homogeneous atmospheres and 3D cloud structures. MONKI has been validated, and produces reliable results even for planets with optically thick, strongly polarising atmospheres.
Hide
11 Jul 2025
H2CM (v1.0): hybrid modeling of global water–carbon cycles constrained by atmospheric and land observations
Zavud Baghirov, Markus Reichstein, Basil Kraft, Bernhard Ahrens, Marco Körner, and Martin Jung
EGUsphere,
2025
Discussion: final response, 7 comments
Short summary
Short summary
We introduce a new global model that links how water and carbon move through land ecosystems. By combining process knowledge with artificial intelligence that learns from observations, we model daily changes in vegetation, water and carbon cycle processes. This model outperforms both purely data-driven and traditional process models, especially in dry and tropical regions. This advance could improve current understanding of water-carbon cycle relationships.
Hide
11 Jul 2025
Rapid Evaluation Framework for the CMIP7 Assessment Fast Track
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathaniel Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Mederios, Enrico Scoccimarro, Jeremy Walton, Philip Kershaw, André L. Marquez, Malcolm J. Roberts, Eleanor O’Rourke, Elisabeth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
As Earth system models become more complex, rapid and comprehensive evaluation through comparison with observational data is necessary. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require fast analysis. This paper describes a new Rapid Evaluation Framework (REF) that was developed for the Assessment Fast Track that will be run at the Earth System Grid Federation (ESGF) to inform the community about the performance of models.
Hide
11 Jul 2025
EXSoDOS 1.0: downscaling of weather extremes shifts for ensemble climate projections using ground-based measurements, reanalysis and stochastic modelling
Hendrik Wouters, Jente Broeckx, Francisco Pereira, Boucary Dara, Afoussatou Diarra, Robin Houdmeyers, and Dirk Lauwaet
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 11 comments)
Short summary
Short summary
Predicting shifts in local extreme weather under global warming is key for climate adaptation, but climate projections lack detail. A new tool, EXSoDOS, combines ground measurements, reanalysis data, and climate models to improve estimates of extreme weather, aiding better risk planning. Tested in five regions, it accurately captures temperature, rainfall, and wind extremes including their past changes, outperforming raw model data. Results show worsening heat (stress) and precipitation by 2100.
Hide
11 Jul 2025
LUCATOOv1 – A new land use change allocation tool and its application to the planetary boundary for land system change with the LPJmL model
Arne Tobian, Sarah Cornell, Ingo Fetzer, Dieter Gerten, and Johan Rockström
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
The land use change reallocation tool LUCATOO enables the creation of future land use change scenario datasets tailored to specific requirements in model study applications. Its usability is demonstrated in the planetary boundaries interaction context. Being written in the programming language R and made openly accessible, LUCATOO can be easily adapted to be employed in contexts other than the planetary boundaries framework.
Hide
10 Jul 2025
Improvements on the BRAMS wildfire-atmosphere modelling system
Isilda Cunha Menezes, Luiz Flávio Rodrigues, Karla M. Longo, Mateus Ferreira e Freitas, Saulo R. Freitas, Rodrigo Braz, Valter Ferreira de Oliveira, Sílvia Coelho, and Ana Isabel Miranda
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
BRAMS v6.0 was enhanced by integrating crown fire spread into its coupled fire module, SFIRE, and dynamic smoke emissions. The model was applied to the 2017 Sertã wildfire in mountainous central Portugal. Simulations were validated against MERRA-2, accurately reproducing the smoke optical properties. Results show the model's ability to simulate radiative impacts, including CAPE and CIN displacement and inversion layer modifications.
Hide
10 Jul 2025
Why does the signal-to-noise paradox exist in seasonal climate predictability?
Yashas Shivamurthy, Subodh Kumar Saha, Samir Pokhrel, Mahen Konwar, and Utkarsh Verma
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 12 comments)
Short summary
Short summary
This study highlights challenges in estimating seasonal climate predictability using the "perfect model" approach, which assumes only initial conditions cause error. We find that forecasts can exceed the predicted limit, known as the Potential Predictability Limit (PPL), due to model imperfections and short-term weather influences. A new method is proposed to estimate PPL more accurately and avoid such paradoxes.
Hide
03 Jul 2025
CMIP7 Data Request: Ocean and Sea Ice Priorities and Opportunities
Baylor Fox-Kemper, Patricia DeRepentigny, Anne Marie Treguier, Christian Stepanek, Eleanor O’Rourke, Chloe Mackallah, Alberto Meucci, Yevgeny Aksenov, Paul J. Durack, Nicole Feldl, Vanessa Hernaman, Céline Heuzé, Doroteaciro Iovino, Gaurav Madan, André L. Marquez, François Massonnet, Jenny Mecking, Dhrubajyoti Samanta, Patrick C. Taylor, Wan-Ling Tseng, and Martin Vancoppenolle
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
The earth system model variables needed for studies of the ocean and sea ice are prioritized and requested.
Hide
02 Jul 2025
Resolving effects of leaf pigmentation changes and plant residue on the energy balance of winter wheat cultivation in the ORCHIDEE-CROP model
Ke Yu, Yang Su, Ronny Lauerwald, Philippe Ciais, Yi Xi, Haoran Xu, Xianglin Zhang, Nicolas Viovy, Amie Pickering, Marie Collard, and Daniel S. Goll
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Coupling crop and land surface models helps quantify the climate effects of agriculture, but lacks crop-specific management processes. We enhanced a land surface model with time-varying albedo from foliar yellowing and residue cover, improving the simulation of energy and water fluxes. Results show cooler surfaces and slightly wetter soils during residue cover, highlighting how managements improve climate mitigation and adaptation, advancing the development of climate-smart agriculture.
Hide
26 Jun 2025
Retrieval of thermodynamic profiles in the lower troposphere from GNSS radio occultation using deep learning
Matthias Aichinger-Rosenberger and Jeremiah Sjoberg
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
This paper presents a data-driven framework for retrieving atmospheric profiles from Global Navigation Satellite Systems (GNSS) radio occultation (RO). The benefit compared to standard products is its independence of external information. Profiles are validated using reanalysis and radiosonde data, with results showing accuracy comparable to standard methods. This represents a promising investigation on the applicability of such models in RO, which could advance the quality of RO products.
Hide
25 Jun 2025
Modeling PFAS in the global atmosphere – The PRIEST extension for the ICON-ART modeling framework
Hiram Abif Meza-Landero, Julia Bruckert, Ronny Petrick, Pascal Simon, Heike Vogel, Volker Matthias, Johannes Bieser, and Martin Ramacher
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
To understand how persistent hazardous industrial chemicals travel through the air and are deposited back on Earth's surface, we created a new computer model that combines meteorology and chemistry in clouds and clean air. Using the most recent global emissions data, this model represents the trajectory and changes of these chemicals, matching patterns in many areas and overlooking others. The work seeks to improve global monitoring and modeling of hazardous chemicals.
Hide
24 Jun 2025
Enhancing Extended Weather Forecasts in the TCWAGFS Model Using Deep Learning Method for SST Bias Correction
Katherine Shu-Min Li, Nadun Sinhabahu, Ben-Jei Tsuang, Fang-Chi Wu, Wan-Ling Tseng, Pei-Hsuan Kuo, Sying-Jyan Wang, Pang-Yen Liu, Jen-Her Chen, Bin-Ming Wang, Yung-Yao Lan, and Sun-Yuan Kung
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 3 comments)
Short summary
Short summary
This study underscores the transformative potential of machine learning algorithms in environmental forecasting. The superior performance of Bi-LSTM in reducing SST bias, coupled with its broader applicability in time-series analysis, makes it a valuable tool for improving the accuracy and reliability of numerical weather prediction models.
Hide
16 Jun 2025
An extension of the BROOK90 hydrological model for estimation of subdaily water and energy fluxes
Rico Kronenberg, Ivan Vorobevskii, Thi Thanh Luong, Uwe Spank, Dongkyun Kim, and Matthias Mauder
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We developed an improved model to better understand how water and energy move through natural landscapes (forest, grasslands, croplands, etc) throughout the day. By using detailed data from study-site in Germany, we tested the model and found its good agreement with micro-meteorological measurements. Unlike many other tools, this model works without needing new adjustments and offers a powerful way to study fast-changing water processes in different environments.
Hide
10 Jun 2025
The Boundary Layer Dispersion and Footprint Model: A fast numerical solver of the Eulerian steady-state advection-diffusion equation
Mark Schlutow, Ray Chew, and Mathias Göckede
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
Understanding how greenhouse gases and pollutants move through the atmosphere is crucial. A new model, the Boundary Layer Dispersion and Footprint Model (BLDFM), tracks their movement. Unlike previous models, BLDFM uses a numerical approach without simplifying assumptions. It's flexible and can be used for climate impact studies and industrial emissions monitoring. Our testing and comparison results show BLDFM's potential as a valuable research tool.
Hide
06 Jun 2025
Centroids in second-order conservative remapping schemes on spherical coordinates
Fuyuki Saito
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
A second-order conservative remapping is a common and standard method for transformation of data from one grid system to another in climate studies. The author describes a fundamental problem in the derivation of the method in spherical coordinates proposed by a pioneer study, which is left unresolved and unrealized. It has a potential to damage the remapping, however no significant impacts are expected in the past studies, because of a formulation introduced for the other objective.
Hide
02 Jun 2025
Scenario set-up and the new CMIP6-based climate-related forcings provided within the third round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3b, group I and II)
Katja Frieler, Stefan Lange, Jacob Schewe, Matthias Mengel, Simon Treu, Christian Otto, Jan Volkholz, Christopher P. O. Reyer, Stefanie Heinicke, Colin Jones, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Ryan Heneghan, Derek P. Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Dánnell Quesada Chacón, Kerry Emanuel, Chia-Ying Lee, Suzana J. Camargo, Jonas Jägermeyr, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Lisa Novak, Inga J. Sauer, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, Michel Bechtold, Robert Reinecke, Inge de Graaf, Jed O. Kaplan, Alexander Koch, and Matthieu Lengaigne
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
This paper describes the experiments and data sets necessary to run historic and future impact projections, and the underlying assumptions of future climate change as defined by the 3rd round of the ISIMIP Project (Inter-sectoral Impactmodel Intercomparison Project, isimip.org). ISIMIP provides a framework for cross-sectorally consistent climate impact simulations to contribute to a comprehensive and consistent picture of the world under different climate-change scenarios.
Hide
28 May 2025
A barycenter-based approach for the multi-model ensembling of subseasonal forecasts
Camille Le Coz, Alexis Tantet, Rémi Flamary, and Riwal Plougonven
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We reformulate multi-model ensembles by treating ensemble forecasts as discrete probability distributions and combining them using barycenters. We compare the
barycenter (equivalent to pooling) with the Wasserstein barycenter (more precisely its Gaussian approximation). Both have the same ensemble mean but differ in how they represent forecasts uncertainty. In terms of Continuous Ranked Probability Score, the Wasserstein barycenter outperforms more often while performing similarly on average.
Hide
27 May 2025
The Atlantic Ocean's Decadal Variability in mid-Holocene Simulations using Shannon's Entropy
Iuri Gorenstein, Ilana Wainer, Francesco S. R. Pausata, Luciana F. Prado, Pedro L. S. Dias, Allegra N. LeGrande, Clay R. Tabor, and William R. Peltier
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 5 comments)
Short summary
Short summary
Using a new approach based on information theory we study climate variability in the tropical and South Atlantic by examining broad patterns in ocean and rainfall data at decadal scales. Four climate models under mid‐Holocene and pre‐industrial conditions show that shifts in vegetation and dust yield varied weather responses. Our findings indicate that incorporating large-scale patterns provides a framework for understanding long-term climate behavior, offering insights for improved predictions.
Hide
26 May 2025
Contribution of physical latent knowledge to the emulation of an atmospheric physics model: a study based on the LMDZ Atmospheric General Circulation Model
Ségolène Crossouard, Soulivanh Thao, Thomas Dubos, Masa Kageyama, Mathieu Vrac, and Yann Meurdesoif
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
Current atmospheric models are limited by the computational time required for physical processes, known as physical parameterizations. To address this, we developed neural network-based emulators to replace these parameterizations in the IPSL climate model, using a simplified aquaplanet setup. We found that incorporating some physical knowledge, such as latent variables, into the learning process can improve predictions.
Hide
05 May 2025
Bakaano-Hydro (v1.1). A distributed hydrology-guided deep learning model for streamflow prediction
Confidence Duku
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
Reliable streamflow prediction is vital for managing floods, droughts, and water resources, yet remains challenging due to data limitations and complex hydrological processes. Traditional models require intensive calibration, while many machine learning methods lack physical realism. Bakaano-Hydro integrates physical hydrology with machine learning to improve interpretability, generalizability, and performance, offering a robust approach for streamflow prediction in data-scarce regions.
Hide
25 Apr 2025
A method for assessing model extensions: Application to modelling winter precipitation with a microscale obstacle-resolving meteorological model (MITRAS v4.0)
Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
A microscale, obstacle-resolving meteorological model has been extended with a snow cover and precipitation scheme making it the first model of its kind that includes rain and snow. The model allows first estimates on the influence of different city characteristics on precipitation heterogeneities. The performance of the model extension is assessed by comparing the results of different model versions. For the comparisons, threshold values were derived based on computational accuracy.
Hide
14 Apr 2025
Meteorological Landscape of Tropical Cyclone
Pascal Oettli, Keita Tokuda, Yusuke Imoto, and Shunji Kotsuki
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
A tropical cyclone is a circular air movement that emerges over warm waters of the tropical ocean and its movement is guided by complex interactions between the ocean and the atmosphere. To better understand this complexity, we adopted ideas and techniques from biology and bioinformatics, to have a fresh look at this matter. This led to the creation of "MeteoScape," a tool that calculates the probability of paths for tropical cyclones can take and visualize them in an understandable way.
Hide
08 Apr 2025
Veris: Fast & Efficient Sea-Ice Modeling in Python with GPU Acceleration
Jan P. Gärtner, Martin Losch, Markus Jochum, and Roman Nuterman
External preprint server,
2025
Revised manuscript under review for GMD
(discussion: final response, 8 comments)
Short summary
Short summary
Climate simulations help us understand the Earth systems and inform climate policies. These complex models require advanced programming and significant energy, as they run on large grids over long timescales. A key component of a climate model is its sea ice component. We present a sea ice model that simplifies development while maintaining high performance. By utilizing GPUs, our model can replace dozens to hundreds of CPUs, drastically reducing the energy usage of running climate simulations.
Hide
04 Apr 2025
TOAR-classifier v2: A data-driven classification tool for global air quality stations
Ramiyou Karim Mache, Sabine Schröder, Michael Langguth, Ankit Patnala, and Martin G. Schultz
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 6 comments)
Short summary
Short summary
The TOAR-classifier model is a data-driven tool that allows for an objective classification of air quality measuring stations as urban, rural, or suburban. Such classification is important in the analysis of air pollutant trends and regional signatures. The model is employed in the second Tropospheric Ozone Assessment Report but can also be used in other research work.
Hide
14 Mar 2025
psit 1.0: A System to Compress Lagrangian Flows
Alexander Pietak, Langwen Huang, Luigi Fusco, Michael Sprenger, Sebastian Schemm, and Torsten Hoefler
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
As meteorological models grow in complexity, the volume of output data increases, making compression increasingly desirable. However, no specialized methods currently exist for compressing data in the Lagrangian frame. To address this gap, we developed psit, a pipeline for the lossy compression of Lagrangian flow data. In most cases, psit achieves performance that is equivalent or superior to non specialized alternatives, with compression errors behaving similar to measurement inaccuracies.
Hide
13 Feb 2025
EcoPro-LSTM
𝑣0
: A Memory-based Machine Learning Approach to Predicting Ecosystem Dynamics across Time Scales in Mediterranean Environments
Mitra Cattry, Wenli Zhao, Juan Nathaniel, Jinghao Qiu, Yao Zhang, and Pierre Gentine
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
Climate change alters Mediterranean biota, affecting how they absorb and store carbon. These associated impacts arise from short- and long-term effects of rainfall, temperature, and other atmospheric forcings, which existing tools struggle to capture. This study presents a memory-integrated model combining high- and low-resolution data to track daily ecosystem responses. By analyzing past conditions, we show how earlier conditions shape plant carbon uptake and improve predictions.
Hide
06 Feb 2025
The next generation sea-ice model neXtSIM, version 2
Einar Ólason, Guillaume Boutin, Timothy Williams, Anton Korosov, Heather Regan, Jonathan Rheinlænder, Pierre Rampal, Daniela Flocco, Abdoulaye Samaké, Richard Davy, Timothy Spain, and Sean Chua
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This paper introduces a new version of the neXtSIM sea-ice model. NeXtSIM is unique among sea-ice models in how it represents sea-ice dynamics, focusing on features such as cracks and ridges and how these impact interactions between the atmosphere and ocean where sea ice is present. The new version introduces some physical parameterisations and model options detailed and explained in the paper. Following the paper's publication, the neXtSIM code will be released publicly for the first time.
Hide
03 Feb 2025
Love number computation within the Ice-sheet and Sea-level System Model (ISSM v4.24)
Lambert Caron, Erik Ivins, Eric Larour, Surendra Adhikari, and Laurent Metivier
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Editorial statement
Short summary
Presented here is a new model of the solid-Earth response to tides and mass changes in ice sheets, oceans, and groundwater, in of terms of gravity change and bedrock motion. The model is capable simulating mantle deformation including elasticity, transient and steady-state viscous flow. We detail our approach to numerical optimization, and report the accuracy of results with respect to community benchmarks. The resulting coupled system features kilometer-scale resolution and fast computation.
Hide
Editorial statement
The viscoelastic Love Numbers underlie our ability to simulate spatially variable sea-level change. They are indeed the "secret sauce" in any such modeling effort. This paper, while technical, takes us to the back of the kitchen to share how the next-generation sauce is made. The resultant Love Numbers will be used to predict sea-level changes and glacial isostatic adjustment with more realistic mantle rheologies.
Hide
16 Jan 2025
Optimizing output operations in high-resolution climate models through dynamic scheduling
Dong Wang and Xiaomeng Huang
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
This study presents a method to enhance data output efficiency in high-resolution climate models by redistributing workloads and allowing lighter tasks to temporarily store data. We use smaller communication groups and I/O aggregation for efficient data writing. A reinforcement learning agent optimizes the approach based on performance data from two models, suggesting a promising strategy to reduce data output overhead and improve model performance.
Hide
11 Nov 2024
Spy4Cast v1.0: a Python Tool for statistical seasonal forecast based on Maximum Covariance Analysis
Pablo Duran-Fonseca and Belén Rodríguez-Fonseca
Geosci. Model Dev. Discuss.,
2024
Revised manuscript not accepted
(discussion: closed, 7 comments)
Short summary
Short summary
This paper describes the first release of Spy4Cast, a python interface to run a maximum covariance analysis model to produce seasonal forecast. This API allows the user to increase automation and productivity, including determination of modes, crossvalidation hindcast and validation. It includes a visualisation module for the results as well as a preprocessing tool that can be also used for other climate variability studies.
Hide
10 Sep 2024
The new plant functional diversity model JeDi-BACH (version 1.0) in the ICON Earth System Model (version 1.0)
Pin-Hsin Hu, Christian H. Reick, Reiner Schnur, Axel Kleidon, and Martin Claussen
Geosci. Model Dev. Discuss.,
2024
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
Short summary
We introduce the new plant functional diversity model JeDi-BACH, a novel tool that integrates the Jena Diversity Model (JeDi) within the land component of the ICON Earth System Model. JeDi-BACH captures a richer set of plant trait variations based on environmental filtering and functional tradeoffs without a priori knowledge of the vegetation types. JeDi-BACH represents a significant advancement in modeling the complex interactions between plant functional diversity and climate.
Hide
30 Aug 2024
An improved hydro-biogeochemical model (CNMM-DNDC V6.0) for simulating dynamical forest-atmosphere exchanges of carbon and evapotranspiration at typical sites subject to subtropical and temperate monsoon climates in eastern Asia
Wei Zhang, Xunhua Zheng, Siqi Li, Shenghui Han, Chunyan Liu, Zhisheng Yao, Rui Wang, Kai Wang, Xiao Chen, Guirui Yu, Zhi Chen, Jiabing Wu, Huimin Wang, Junhua Yan, and Yong Li
Geosci. Model Dev. Discuss.,
2024
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Process-oriented biogeochemical models are promising tools for estimating the carbon fluxes of forest ecosystems. In this study, the hydro-biogeochemical model of CNMM-DNDC was improved by incorporating a new forest growth module derived from the Biome-BGC. The updated model was validated using the multiple-year observed carbon fluxes and showed better performance in capturing the daily dynamics and annual variations. The sensitive eco-physiological parameters were also identified.
Hide
19 Aug 2024
Model calibration and streamflow simulations for the extreme drought event of 2018 on the Rhine River Basin using WRF-Hydro 5.2.0
Andrea L. Campoverde, Uwe Ehret, Patrick Ludwig, and Joaquim G. Pinto
Geosci. Model Dev. Discuss.,
2024
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
We looked at how well the model WRF-Hydro performed during the 2018 drought event in the River Rhine basin, even though it is typically used for floods. We used the meteorological ERA5 reanalysis dataset to simulate River Rhine’s streamflow and adjusted the model using parameters and actual discharge measurements. We focused on Lake Constance, a key part of the basin, but found issues with the model’s lake outflow simulation. By removing the lake module, we obtained more accurate results.
Hide
24 Jun 2024
Evaluation of radiation schemes in the CMA-MESO model using high time-resolution radiation measurements in China: I. Long-wave radiation
Junli Yang, Weijun Quan, Li Zhang, Jianglin Hu, Qiying Chen, and Martin Wild
Geosci. Model Dev. Discuss.,
2024
Revised manuscript not accepted
(discussion: closed, 12 comments)
Short summary
Short summary
Due to the difficulties involved in the measurements of the Downward long-wave irradiance (DnLWI), the numerical weather prediction (NWP) models have been developed to obtain the DnLWI indirectly. In this study, a long-term high time-resolution (1 min) observational dataset of the DnLWI in China was used to evaluate the radiation scheme in the CMA-MESO model over various underlying surfaces and climate zones.
Hide
11 Jun 2024
Comprehensive Air Quality Model With Extensions, v7.20: Formulation and Evaluation for Ozone and Particulate Matter Over the US
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood
Geosci. Model Dev. Discuss.,
2024
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
We describe the Comprehensive Air quality Model with extensions (CAMx) and evaluate a model simulation during 2016 over nine U.S. climate zones. For ozone, the model statistically replicates measured concentrations better than most other past models and applications. For small inhalable particulates, the model replicates concentrations consistent with most other past models and applications subject to common uncertainties associated with sources, weather, and chemical interactions.
Hide
30 May 2024
A Unified System for Evaluating, Ranking and Clustering in Diverse Scientific Domains
Zengyun Hu, Xi Chen, Deliang Chen, Zhuo Zhang, Qiming Zhou, and Qingxiang Li
Geosci. Model Dev. Discuss.,
2024
Preprint withdrawn
(discussion: closed, 8 comments)
Short summary
Short summary
ERC firstly unified the evaluating, ranking, and clustering by a simple mathematic equation based on Euclidean Distance. It provides new system to solve the evaluating, ranking, and clustering tasks in SDGs. In fact, ERC system can be applied in any scientific domain.
Hide
29 Jan 2024
A Deep Learning-Based Consistency Test Approach for Earth System Models on Heterogeneous Many-Core Systems
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss.,
2024
Preprint withdrawn
(discussion: closed, 9 comments)
Short summary
Short summary
The hardware-related perturbations caused by the heterogeneous many-core architectures can blend with software or human errors, which can affect the accuracy of the model consistency verification. We develop a deep learning-based consistency test tool for ESMs on the heterogeneous systems (ESM-DCT) and evaluate it in CESM on new Sunway system. The ESM-DCT can detect the existence of software or human errors when taking hardware-related perturbations into account.
Hide
19 Jan 2024
E3SM Chemistry Diagnostics Package (ChemDyg) Version 0.1.4
Hsiang-He Lee, Qi Tang, and Michael Prather
Geosci. Model Dev. Discuss.,
2024
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The E3SM Chemistry diagnostics package (ChemDyg) is a software tool, which is designed for the global climate model (E3SM) chemistry development. ChemDyg generates several diagnostic plots and tables for model-to-model and model-to-observation comparison, including 2-dimentional contour mapping plots, diurnal and annual cycle, time-series plots, and comprehensive processing tables. This paper is to introduce the details of each diagnostics set and its required input data formats in ChemDyg.
Hide
04 Jan 2024
Improving subseasonal forecast skill in the Norwegian Climate Prediction Model using soil moisture data assimilation
Akhilesh Sivaraman Nair, François Counillon, and Noel Keenlyside
Geosci. Model Dev. Discuss.,
2024
Publication in GMD not foreseen
(discussion: closed, 9 comments)
Short summary
Short summary
This study demonstrates the importance of soil moisture (SM) in subseasonal-to-seasonal predictions. To addess this, we introduce the Norwegian Climate Prediction Model Land (NorCPM-Land), a land data assimilation system developed for the NorCPM. NorCPM-Land reduces error in SM by 10.5 % by assimilating satellite SM products. Enhanced land initialisation improves predictions up to a 3.5-month lead time for SM and a 1.5-month lead time for temperature and precipitation.
Hide
21 Nov 2023
GHOSH v1.0.0: a novel Gauss-Hermite High-Order Sampling Hybrid filter for computationally efficient data assimilation in geosciences
Simone Spada, Anna Teruzzi, Stefano Maset, Stefano Salon, Cosimo Solidoro, and Gianpiero Cossarini
Geosci. Model Dev. Discuss.,
2023
Preprint under review for GMD
(discussion: final response, 7 comments)
Short summary
Short summary
In geosciences, data assimilation (DA) combines modeled dynamics and observations to reduce simulation uncertainties. Uncertainties can be dynamically and effectively estimated in ensemble DA methods. With respect to current techniques, the novel GHOSH ensemble DA scheme is designed to improve accuracy by reaching a higher approximation order, without increasing computational costs, as demonstrated in idealized Lorenz96 tests and in realistic simulations of the Mediterranean Sea biogeochemistry
Hide
20 Nov 2023
Clustering analysis of very large measurement and model datasets on high performance computing platforms
Colin J. Lee, Paul A. Makar, and Joana Soares
Geosci. Model Dev. Discuss.,
2023
Publication in GMD not foreseen
(discussion: closed, 5 comments)
Short summary
Short summary
Clustering is an analysis technique for finding similarities within datasets. We present a new implementation of the hierarchical clustering algorithm that is able to process much larger datasets than was previously possible, by spreading the program out over many connected computers in a high-performance computing system. We show airshed maps of a high-resolution regional model output domain, and find related air pollution profiles at monitoring stations separated by thousands of kilometers.
Hide
10 Nov 2023
Updated algorithmic climate change functions (aCCF) V1.0A: Evaluation with the climate-response model AirClim V2.0
Sigrun Matthes, Simone Dietmüller, Katrin Dahlmann, Christine Frömming, Patrick Peter, Hiroshi Yamashita, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Aviation aims to reduce its climate effect by identifying alternative climate-optimized aircraft trajectories. Such routing strategies requires a dedicated meteorological service in order to inform on regions of the atmosphere where aviation non-CO
emissions have a large climate effect, e.g. by contrail formation or nitrogen-oxide (NO
)-induced ozone formation. This study presents calibration factors for individual non-CO
effects by comparing with the climate response model AirClim.
Hide
02 Nov 2023
Simulating the variations of carbon dioxide in the global atmosphere on the hexagonal grid of DYNAMICO coupled with the LMDZ6 model
Zoé Lloret, Frédéric Chevallier, Anne Cozic, Marine Remaud, and Yann Meurdesoif
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 3 comments)
Short summary
Short summary
In this study, we evaluate the performance of a new model coupling, ICO, for simulating atmospheric carbon dioxide (CO
) transport. Using an unstructured grid, our model accurately captures seasonal CO
variations at surface stations. The model exhibits comparable accuracy to a reference configuration and offers advantages in computational speed and storage. This highlights the importance of advanced modeling approaches and high-resolution grids in refining climate models.
Hide
25 Oct 2023
A deep learning method for convective weather forecasting: CNN-BiLSTM-AM (version 1.0)
Jianbin Zhang, Zhiqiu Gao, Yubin Li, and Yuncong Jiang
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 5 comments)
Short summary
Short summary
This study developed a deep learning model called CNN-BiLSTM-AM for convective weather forecasting. The results showed that the CNN-BiLSTM-AM model outperformed traditional machine learning algorithms in predicting convective weather, with higher accuracy as the forecast lead time increased. When compared to subjective forecasts by forecasters, the objective approach of the CNN-BiLSTM-AM model also demonstrated advantages in various metrics.
Hide
21 Aug 2023
Inclusion of the subgrid wake effect between turbines in the wind farm parameterization of WRF
Wei Liu, Xuefeng Yang, Shengli Chen, Shaokun Deng, Peining Yu, and Jiuxing Xing
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Assessing environmental impacts of wind farms requires an accurate parameterization of wind farms in atmospheric models, which, in our study, is improved considering the wind turbine wake. Based on an engineering wake model of a turbine, a wake superposition coefficient and an angle correction coefficient are proposed, calculated and added in the model. Sensitivity experiments reveal that, with enlarged grid size and shortened turbine spacing, the new scheme shows more advantages.
Hide
16 Aug 2023
Surrogate model-based precipitation tuning for CAM5
Xianwei Wu, Liang Hu, Lanning Wang, Haitian Lu, and Juepeng Zheng
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
In order to build an effective surrogate model for the community atmospheric model (CAM). We present a surrogate model-based parameter tuning framework for the CAM and apply it to improve the CAM5 precipitation performance and propose a multilevel surrogate model-based optimization method. We design a nonuniform parameter parameterization scheme and integrate the parameters using a parameter smoothing scheme, and the experimental results improve in four regions.
Hide
15 Aug 2023
Deep-learning statistical downscaling of precipitation in the middle reaches of the Yellow River: A Residual in Residual Dense Block based network
He Fu, Jianing Guo, Chenguang Deng, Heng Liu, Jie Wu, Zhengguo Shi, Cailing Wang, and Xiaoning Xie
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 7 comments)
Short summary
Short summary
A Residual in Residual Dense Block based network model (RRDBNet) is designed for statistical downscaling of precipitation in the middle reaches of the Yellow River. RRDBNet has a good performance on precipitation simulations, well reproducing the spatial-temporal characteristics of high-resolution precipitation. RRDBNet has substantial improvements in extreme precipitation compared with generalized linear regression model and two deep learning-based models.
Hide
29 Jun 2023
Impacts of dynamic dust sources coupled with WRF-Chem 3.9.1 on the dust simulation over East Asia
Yu Chen, Yue Zhang, Siyu Chen, Ben Yang, Huiping Yan, Jixiang Li, Chao Zhang, Gaotong Lou, Junyan Chen, Lulu Lian, and Chuwei Liu
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The numerical models seriously ignoring the aeolian erosion and dust emission process on the potential sources. Six sets of dynamic dust sources were built by combine surface bareness and topographic feature. Results show that dust sources are closely related to surface exposure and topographic characteristics, which respectively control the spatial distribution and numerical value of dynamic dust sources.
Hide
27 Jun 2023
The CO
and non-CO
climate effects of individual flights: simplified estimation of CO
equivalent emission factors
Robin N. Thor, Malte Niklaß, Katrin Dahlmann, Florian Linke, Volker Grewe, and Sigrun Matthes
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
We develop a simplied method to estimate the climate effects of single flights through CO
and non-CO
effects, exclusively based on the aircraft seat category as well as the origin and destination airports. The derived climate effect functions exhibit a mean relative error of only 15 % with respect to results from a climate response model. The method is designed for climate footprint assessments and covers most commerical airlines with seat capacities starting from 101 passengers.
Hide
27 Jun 2023
Nonparametric estimation method for river cross-sections with point cloud data from UAV photography URiver-X version 1.0 -methodology development
Taesam Lee, Jaewoo Park, Sunghyun Hwang, and Vijay Singh
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 9 comments)
Short summary
Short summary
The current study presents a novel method to demarcate the cross-section of a river channel using a very flexible regression model, called K-nearest neighbor local linear regression (KLR). The proposed method draws the cross-section automatically based on the point cloud data taken from unmanned aerial vehicles (UAVs). The proposed model can provide a further development of 4th industy innovation by employding the UAV-based photogrammetry.
Hide
26 Jun 2023
RICHARD 1.0 – Routine for the Isolation of Chemical Hotspots in Atmospheric Research Data
Christian Scharun, Roland Ruhnke, and Peter Braesicke
Geosci. Model Dev. Discuss.,
2023
Publication in GMD not foreseen
(discussion: closed, 3 comments)
Short summary
Short summary
The identification and quantification of greenhouse gas (GHG) emissions is an important task for monitoring mitigation strategies under climate change. With RICHARD 1.0, we developed a novel approach using spatiotemporal proxy data and a selection algorithm to detect GHG emission hotspots. By using a one year dataset of global climate model output we showed that RICHARD is able to determine and quantify the source strengths of GHG emission hotspots much more precisely than conventional methods.
Hide
31 May 2023
Taylor's statistical theory applied to the turbulence parameterization in the BAM-INPE global atmospheric model
Eduardo Rohde Eras, Haroldo Fraga de Campos Velho, and Paulo Yoshio Kubota
Geosci. Model Dev. Discuss.,
2023
Publication in GMD not foreseen
(discussion: closed, 3 comments)
Short summary
Short summary
The portion of the earth atmosphere closer to the ground is responsible for heat, moisture and mechanical energy transportation between the surface and the air through turbulence, been very important for weather forecast. Between many solutions used to model this turbulence, this is the first attempt to use one based on Taylor's statistical theory in a global atmospheric model, achieving good results for precipitation and energy transportation, specially in the Amazon basin region.
Hide
03 May 2023
STEMMUS-MODFLOW v1.0.0: Integrated Understanding of Soil Water and Groundwater Flow Processes: Case Study of the Maqu Catchment, north-eastern Tibetan Plateau
Lianyu Yu, Yijian Zeng, Huanjie Cai, Mengna Li, Yuanyuan Zha, Jicai Zeng, Hui Qian, and Zhongbo Su
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We developed a coupled soil water-groundwater (SW-GW) model, which is verified as physically accurate and applicable in large-scale groundwater problems. The role of vadose zone processes, coupling approach, and spatiotemporal heterogeneity of SW-GW interactions were highlighted as essential to represent the SW-GW system. Given the relevant dataset, the developed SW-GW modeling framework has the potential to portray the processes "from bedrock to atmosphere" in a physically consistent manner.
Hide
02 May 2023
A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution
Junhua Wang, Baozhu Ge, Xueshun Chen, Jie Li, Keding Lu, Yayuan Dong, Lei Kong, Zifa Wang, and Yuanhang Zhang
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
We developed a quantitative decoupling analysis (QDA) method to quantify the contributions of emissions, meteorology, chemical reactions, and their nonlinear interactions on PM
2.5
. We found the effects of adverse meteorological conditions and the importance of nonlinear interactions. This method can provide valuable information for understanding of key factors to heavy pollution, but also help the modelers to find out the sources of uncertainties in numerical models.
Hide
12 Apr 2023
Novel Deep Learning Approaches for Mapping Variation of Ground Level from Spirit Level Measurements
Fawzi Zarzoura, Mosbeh Kaloop, Pijush Samui, Jong Wan Hu, Md Shayan Sabri, and Tamer ElGharbawi
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 10 comments)
Short summary
Short summary
The study aims to map variation in ground levels based on ordinary spirit levelling (SL) measurements. New machine learning techniques were developed and compared in the current study to estimate the leveling through SL measurements. The results show the developed LSTM model outperforms CNN, RNN, and BI-LSTM in modeling ground leveling in the training and testing stages. The accuracy of mapping ground levelling through the developed LSTM model is close to 99 % in terms of model error.
Hide
27 Mar 2023
Positive semi-definite variants of CBM4 and CBM05 chemistry schemes for atmospheric composition models
Risto Matias Hänninen, Rostislav Kouznetsov, and Mikhail Sofiev
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
Chemistry transport models describe the motion of particles and gases in atmosphere, containing chemistry equations that allow reaction between different species. The widely used carbon-bond chemistry schemes are originally written in a numerically problematic form that drives some concentrations to unphysical negative values. Here the chemistry equations are re-written in a form where this problem is absent, allowing an easier integration of the equations into any chemistry transport model.
Hide
22 Mar 2023
G&M3D 1.0: an Interactive framework for 3D Model Construction and Forward Calculation of Potential Fields
Kanggui Wei, Bo Chen, and Jiaxiang Peng
Geosci. Model Dev. Discuss.,
2023
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Geological model construction and forward calculation are the basis for the analysis and interpretation of geophysical data. However, open-source tools combining flexible source model construction and efficient forward calculation of the potential fields are rare. This study develops a new MATLAB-based software – G&M3D to address these issues. The real-world forward gravity modeling over a salt dome in Vinton Dome is performed to verify the correctness and practicality of the software.
Hide
17 Mar 2023
Quantitative Sub-Ice and Marine
racing of
ntarctic
ediment
rovenance (TASP v0.1)
James W. Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin J. Siegert, and Liam Holder
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 8 comments)
Short summary
Short summary
Ice sheet models can help predict how Antarctica’s ice sheets respond to environmental change; such models benefit from comparison to geological data. Here, we use ice sheet model results, plus other data, to predict the erosion of Antarctic debris and trace its transport to where it is deposited on the ocean floor. This allows the results of ice sheet modelling to be directly and quantitively compared to real-world data, helping to reduce uncertainty regarding Antarctic sea level contribution.
Hide
01 Mar 2023
Optimized Stochastic Representation of Soil States Model Uncertainty of WRF (v4.2) in the Ensemble Data Assimilation System
Sujeong Lim, Seon Ki Park, and Claudio Cassardo
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The ensembles in the numerical weather prediction system are under-dispersed near the land surface; therefore, an inflation method is required to increase it. In this study, we perturbed soil temperature and soil moisture to represent the near-surface uncertainty. Perturbations were obtained by the optimization algorithm taking into account diurnal variations in soil states. Consequently, it indirectly inflated the temperature and water vapor mixing ratio in the planetary boundary layer.
Hide
21 Feb 2023
Assimilating the dynamic spatial gradient of a bottom-up carbon flux estimation as a unique observation in COLA (v2.0)
Zhiqiang Liu, Ning Zeng, Yun Liu, Eugenia Kalnay, Ghassem Asrar, Qixiang Cai, and Pengfei Han
Geosci. Model Dev. Discuss.,
2023
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We introduced a novel algorithm that assimilates a better a priori knowledge to improve the estimation of global surface carbon flux. The algorithm aims at separating the first-order systematic biases in the a priori "bottom-up" flux estimations out of the inversion framework from a comprehensive data assimilation perspective.
Hide
26 Jan 2023
Randomized Block Nonparametric Temporal Disaggregation of Hydrological Variables RB-NPD (version1.0) – model development
Taesam Lee and Taha B. M. J. Ouarda
Geosci. Model Dev. Discuss.,
2023
Publication in GMD not foreseen
(discussion: closed, 2 comments)
Short summary
Short summary
The current study proposed random block based nonparametric disaggregation model so that the weakness point of the existing nonparametric disaggregation models can be resolved with preserving the long-term persistence. The proposed model illustrates superior performance for disaggregating the net basin supply of the LCRR basin in the Great Lakes, which experienced the worst flood in 2011.
Hide
29 Nov 2022
Experiments with the modified Rotating Shallow Water model (modRSW, v.1.0): assessing the relevance for convective-scale data assimilation research
Thomas Kent, Luca Cantarello, Gordon Inverarity, Steven Tobias, and Onno Bokhove
Geosci. Model Dev. Discuss.,
2022
Publication in GMD not foreseen
(discussion: closed, 6 comments)
Short summary
Short summary
Data assimilation combines recent model forecasts and observations to estimate current atmospheric conditions for use as initial conditions for numerical weather prediction. We analyse the results of a series of data assimilation experiments using a simplified and inexpensive mathematical model of the atmosphere. We closely compare key properties of the models used by weather centres with our idealised setup, proving that it can help support operational data assimilation research.
Hide
08 Nov 2022
HiWaQ v1.0: A flexible catchment water quality assessment tool with compatibility for multiple hydrological model structures
Xiaoqiang Yang, Doerthe Tetzlaff, Chris Soulsby, and Dietrich Borchardt
Geosci. Model Dev. Discuss.,
2022
Preprint retracted
(discussion: closed, 1 comment)
Short summary
Short summary
We develop the catchment water quality assessment platform HiWaQ v1.0, which is compatible with multiple hydrological model structures. The nitrogen module (HiWaQ-N) and its coupling tests with two contrasting grid-based hydrological models demonstrate the robustness of the platform in estimating catchment N dynamics. With the unique design of the coupling flexibility, HiWaQ can leverage advancements in hydrological modelling and advance integrated catchment water quantity-quality assessments.
Hide
26 Sep 2022
Development of common socio-economic scenarios for climate change impact assessments in Japan
Sayaka Yoshikawa, Kiyoshi Takahashi, Wenchao Wu, Keisuke Matsuhashi, and Nobuo Mimura
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Socio-economic scenarios developed worldwide require revised versions for local assessments in Japan. Moreover, global narratives may lack important region-specific drivers, national policy perspectives, and unification of government-provided data. Therefore, we present the development of several socio-economic scenarios with changes in population and land use based on the previous study as a framework for projecting climate change impacts and adaptation assessment in Japan.
Hide
09 Sep 2022
Neural networks for data assimilation of surface and upper-air data in Rio de Janeiro
Vinícius Albuquerque de Almeida, Haroldo Fraga de Campos Velho, Gutemberg Borges França, and Nelson Francisco Favilla Ebecken
Geosci. Model Dev. Discuss.,
2022
Publication in GMD not foreseen
(discussion: closed, 6 comments)
Short summary
Short summary
The paper focuses on data assimilation for the WRF model by employing neural network. The applied supervised ML technique was designed to emulate the 3D-Var in a regional atmospheric model. The proposed technique has the potential to significantly reduce the computational effort of data assimilation. Indeed, in the worked example the neural network scheme was more 70 times faster than 3D-Var method, with similar quality for the analysis.
Hide
08 Sep 2022
Reconstruction of past exposure to natural hazards driven by historical statistics: HANZE v2.0
Dominik Paprotny and Matthias Mengel
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
Population and economic growth over past decades have increased risk posed by natural hazards. The model presented here generates high-resolution maps of land use, population and assets (exposure) from 1870 to 2020 for 42 countries. It combines multiple methods with a large database of historical statistical data to approximate past anthropogenic environment of Europe. It enables attributing losses from past disasters to climate change by removing the influence of changes in exposure.
Hide
26 Jul 2022
PVN 1.0: using dynamic PFTs and restoration scenarios to model CO2 and CH4 emissions in peatlands
Tanya Juliette Rebecca Lippmann, Monique Heijmans, Han Dolman, Ype van der Velde, Dimmie Hendriks, and Ko van Huissteden
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 1 comment)
Short summary
Short summary
To assess the impact of vegetation on GHG fluxes in peatlands, we developed a new model, Peatland-VU-NUCOM (PVN). These results showed that plant communities impact GHG emissions, indicating that plant community re-establishment is a critical component of peatland restoration. This is the first time that a peatland emissions model investigated the role of re-introducing peat forming vegetation on GHG emissions.
Hide
20 Jul 2022
Assessment of tropospheric ozone products from CAMS reanalysis and near-real time analysis using observations over Iran
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Global climate chemistry models provide our best estimation of future projection of tropospheric composition. Coarse grid boxes of these models often limit their validations to a set of observations. Current generations of the models benefit from many improvements such upgrading to a finer resolution, assimilating with a wide range of observed data, or etc. This paper assesses the capability of two state-of-the-art global models in simulating tropospheric ozone using observations over Iran.
Hide
13 Jul 2022
Mapping 3D Structure of Loose Quaternary Deposits Combining Deep Learning and Multiple-point Statistics: An example in Chencun, Northern Pearl River Delta
Weisheng Hou, Hengguang Liu, Xianhe Zhang, Xiaoming Lin, Hongwei Li, Weisheng Wu, Fan Xiao, Junyi Li, and Hui Chang
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
In this paper, a novel approach to construct the 3D Quaternary structures is proposed. Two three-dimensional model construction examples in Chencun area, Foshan City, Guangdong Province show that the algorithm proposed in this study can realize the three-dimensional reconstruction of the fine structure of Quaternary loose sediments and fracture zones.
Hide
11 Jul 2022
Data-driven Global Subseasonal Forecast Model (GSFM v1.0) for intraseasonal oscillation components
Chuhan Lu, Dingan Huang, Yichen Shen, and Fei Xin
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
As a challenge in the construction of a “seamless forecast” system, improving the prediction skills of subseasonal forecasts is a key issue for meteorologists. In this study, we developed a new subseasonal forecast model based on deep-learning. And this model performs better on the 10–30 day prediction of the intraseasonal oscillation components of meteorological elements than the CFSv2 subseasonal results to some extent.
Hide
06 Jul 2022
An Improved Method Based on VGGNet for Refined Bathymetry from Satellite Altimetry: Reducing the Errors Effectively
Xiaolun Chen, Xiaowen Luo, Ziyin Wu, Xiaoming Qin, Jihong Shang, Mingwei Wang, and Hongyang Wan
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
To combine the advantages of satellite altimetry-derived and multibeam sonar-derived bathymetry, we apply deep learning to perform multibeam sonar-based bathymetry correction for satellite altimetry bathymetry data. Specifically, we modify and improve a pretrained VGGNet neural network mode. Experiments show that the model can improve the precision.
Hide
02 Jun 2022
CLUMondo v2.0: Improved model by adaptive determination of conversion orders for simulating land system changes with many-to-many demand-supply relationships
Peichao Gao, Yifan Gao, Xiaodan Zhang, Sijing Ye, and Changqing Song
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We found that the featured function of CLUMondo – balancing demands and supplies in a many-to-many mode – relies on a parameter called conversion order, but the setting of this parameter should be improved. This parameter should be set manually according to the characteristics of each study area and based on expert knowledge, which is not feasible for users without understanding the whole, detailed mechanism. This problem has been addressed in this study with CLUMondo Version 2.0.
Hide
24 May 2022
An Improved Algorithm for Simulating the Surface Flow Dynamics based on the Flow-Path Network Model
Qianjiao Wu, Yumin Chen, Huaming Xie, Tong Xu, Jiayong Yu, and Ting Zhang
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 8 comments)
Short summary
Short summary
To solve the problems of accuracy and response efficiency of existing simulation methods, an improved algorithm was proposed to simulate the surface flow dynamics quickly and accurately. We considers the influence of terrain parameters on flow velocity to improve Manning’s equation for enhancing simulation accuracy. We also use CUDA to advance the efficiency. Experimental results show that it can quickly and accurately complete the multi-scale simulation and ensure simulation consistence.
Hide
23 May 2022
Global Sensitivity Analysis of the distributed hydrologic model ParFlow-CLM (V3.6.0)
Wei Qu, Heye Bogena, Christoph Schüth, Harry Vereecken, Zongmei Li, and Stephan Schulz
Geosci. Model Dev. Discuss.,
2022
Publication in GMD not foreseen
(discussion: closed, 5 comments)
Short summary
Short summary
We applied the global sensitivity analysis LH-OAT to the integrated hydrology model ParFlow-CLM to investigate the sensitivity of the 12 parameters for different scenarios. And we found that the general patterns of the parameter sensitivities were consistent, however, for some parameters a significantly larger span of the sensitivities was observed, especially for the higher slope and in subarctic climatic scenarios.
Hide
19 May 2022
DFN Generator v2.0: A new tool to model the growth of large-scale natural fracture networks using fundamental geomechanics
Michael John Welch, Mikael Lüthje, and Simon John Oldfield
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
This code can build geologically realistic models of natural fracture networks by simulating the nucleation, growth and interaction of fractures based on geomechanical principles. It uses the algorithm of Welch et al. (2020) to generate more realistic models of large fracture networks than stochastic techniques. It can build either implicit fracture models, explicit DFNs, or both, and will have applications in engineering and fluid flow modelling, as well as in understanding fracture evolution.
Hide
25 Apr 2022
Empirical Assessment of Normalized Information Flow for Quantifying Causal Contributions
Chin-Hsien Cheng and Simon Redfern
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
Causality is one of the foundations of scientific understanding and progress. Statistical models extrapolate historical trends into the future through statistical tools, but may still lack insight into the physical underlying processes. We have developed a method to quantify physical causal contributions between observational time series. It plugs the gap between process-based and statistical models, providing a key to unlocking and understanding causality in Earth systems science processes.
Hide
22 Apr 2022
3D geological modelling of igneous intrusions in LoopStructural v1.4.4
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev. Discuss.,
2022
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
We introduce a method to model igneous intrusions for 3D geological modelling. We use a parameterization of the intrusion body geometry that could be constrained using field observations. Using this parametrization, we simulate distance thresholds that represent the lateral and vertical extent of the intrusion body. We demonstrate the method with two case studies, and we present a comparison with Radial Basis Function interpolation using a case study of a sill complex located in NW Australia.
Hide
06 Apr 2022
Intercomparing radar data assimilation systems for ICE-POP 2018 snowfall cases
Ki-Hong Min, Kao-Shen Chung, Ji-Won Lee, Cheng-Rong You, and Gyuwon Lee
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 12 comments)
Short summary
Short summary
LETKF underestimated the water vapor mixing ratio and temperature compared to 3DVAR due to a lack of a water vapor mixing ratio and temperature observation operator. Snowfall in GWD was less simulated in LETKF. The results signify that water vapor assimilation is important in radar DA and significantly impacts precipitation forecasts, regardless of the DA method used. Therefore, it is necessary to apply observation operators for water vapor mixing ratio and temperature in radar DA.
Hide
15 Mar 2022
The development and validation of a global 1/32° surface wave-tide-circulation coupled ocean model: FIO-COM32
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
A new global surface wave-tide-circulation coupled ocean model FIO-COM32 with resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are proved to be important contributors to the significant improvements of FIO-COM32 simulations. It should be the time to merge these separated model components (surface wave, tidal current and ocean circulation) for new generation ocean model development.
Hide
10 Jan 2022
Evaluating dust emission model performance using dichotomous satellite observations of dust emission
Mark Hennen, Adrian Chappell, Nicholas Webb, Kerstin Schepanski, Matthew Baddock, Frank Eckardt, Tarek Kandakji, Jeff Lee, Mohamad Nobakht, and Johanna von Holdt
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We use 90,000 dust point source observations (DPS), identified in satellite imagery across 9 global dryland environments to develop a novel dust emission model performance assessment. We evaluate the albedo-based dust emission model (AEM), which agrees with dust emission observations, or lack of emission 71 % of the time. Modelled dust occurs 27 % of the time with no observation, caused mostly by the incorrect assumption of infinite sediment supply and lack of dynamic dust entrainment thresholds.
Hide
07 Jan 2022
Adaptive time step algorithms for the simulation of marine ecosystem models using the transport matrix method implementation Metos3D (v0.5.0)
Markus Pfeil and Thomas Slawig
Geosci. Model Dev. Discuss.,
2022
Revised manuscript not accepted
(discussion: closed, 7 comments)
Short summary
Short summary
In investigating the global carbon cycle, shortening the runtime of the simulation of marine ecosystem models is an important issue. We present methods that automatically adjust the time step during the simulation of a steady state using transport matrices. They apply always the time step as large as possible. Two methods reduced the runtime significantly, depending on the complexity of the model. An important property was that small negative concentrations were ignored during the spin-up.
Hide
17 Nov 2021
Nonparametric-based estimation method for river cross-sections with point cloud data from UAV photography URiver-X version 1.0 -methodology development
Taesam Lee and Kiyoung Sung
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
A nonparametric-based estimation technique, called the K-nearest neighbor local linear regression (KLR) model, was proposed in the current study to demarcate the cross-section of a river with a point cloud dataset from UAV photogrammetry. The results indicate that the proposed KLR model can be a suitable alternative by reproducing the critical characteristics of natural and manmade channels, including abrupt changes and small bumps, as well as the overall trapezoidal shape.
Hide
04 Nov 2021
Weaknesses in dust emission modelling hidden by tuning to dust in the atmosphere
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Hide
22 Oct 2021
CP-DSL: Supporting Configuration and Parametrization of Ocean Models with UVic (2.9) and MITgcm (67w)
Reiner Jung, Sven Gundlach, and Wilhelm Hasselbring
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
We present CP-DSL, a domain-specific language with a focus on configuration and parametrization of ocean models, which was so far not supported by domain-specific-languages. CP-DSL is designed to be model agnostic and provides a unified interface to different ocean models. We report on the DSL design, implementation, and the evaluation with scientists and research software engineers. The implementation of CP-DSL is available as open source software and a replication package is provided.
Hide
04 Oct 2021
LAPS v1.0.0: Lagrangian Advection of Particles at Sea, a Matlab program to simulate the displacement of particles in the ocean
Maxime Mouyen, Romain Plateaux, Alexander Kunz, Philippe Steer, and Laurent Longuevergne
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
LAPS is an easy to use Matlab code that allows simulating the transport of particles in the ocean without any programming requirement. The simulation is based on publicly available ocean current velocity fields and allows to output particles spatial distribution and trajectories at time intervals defined by the user. After explaining how LAPS is working, we show a few examples of applications for studying sediment transport or plastic littering. The code is available on Github.
Hide
23 Sep 2021
CycloneDetector (v1.0) – Algorithm for detecting cyclone and anticyclone centers from mean sea level pressure layer
Martin Prantl, Michal Žák, and David Prantl
Geosci. Model Dev. Discuss.,
2021
Publication in GMD not foreseen
(discussion: closed, 3 comments)
Short summary
Short summary
The purpose of our paper is to show our experiences with a new algorithm for detecting of pressure centers based only on mean sea level pressure. While other methods usually focus only on the detection of cyclones, our approach is suitable for finding anticyclones centers as well. Our method is easy to implement with only a few parameters and is based only on standard image processing algorithms. When compared to the manual analysis provided by Met Office, the agreement is around 85 % to 90 %.
Hide
01 Sep 2021
A quantitative decoupling analysis (QDA v1.0) method for the assessment of meteorological, emission and chemical contributions to fine particulate pollution
Junhua Wang, Baozhu Ge, Xueshun Chen, Jie Li, Keding Lu, Yayuan Dong, Lei Kong, Zifa Wang, and Yuanhang Zhang
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
This paper developed a novel quantitative decoupling analysis (QDA) method to quantify the contributions of emission, meteorology, chemical reaction, and their nonlinear interactions on PM
2.5
and applied it to a pollution episode in Beijing. This method can provides the researchers and policy makers with valuable information for understanding of key factors to heavy pollution, but also help the modelers to find out the sources of uncertainties among numerical models.
Hide
21 Jul 2021
Modeling perennial bioenergy crops in the E3SM land model
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 5 comments)
Short summary
Short summary
Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Hide
20 Jul 2021
An improved carbon greenhouse gas simulation in GEOS-Chem version 12.1.1
Beata Bukosa, Jenny Fisher, Nicholas Deutscher, and Dylan Jones
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Human activities led to rising levels of greenhouse gases (carbon dioxide (CO
), methane (CH
), carbon monoxide (CO)) in the atmosphere, threatening our future. We use models and measurements to predict and understand the climatological impact of these gases. Here, we describe a new simulation in the GEOS-Chem model that uses a more accurate method to simulate CO
, CH
and CO, through their chemical dependence. Relative to the original simulations our results agree better with measurements.
Hide
19 Jul 2021
Quantifying Causal Contributions in Earth Systems by Normalized Information Flow
Chin-Hsien Cheng and Simon A. T. Redfern
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 8 comments)
Short summary
Short summary
Causality is one of the foundations of scientific understanding and progress. Causality, being one of the foundations of scientific understanding and progress, continues to expand its application in various research disciplines in recent years. For Earth sciences, causation is important for evaluating, constraining, and improving climate models. Here, we explore, the conditions under which information flow works best for quantifying causality and explain why it is advantageous.
Hide
13 Jul 2021
Systematic global evaluation of accuracy of seasonal climateforecasts for monthly precipitation of JMA/MRI-CPS2 bycomparing with a statistical system using climate indices
Yuji Masutomi, Toshichika Iizumi, Key Oyoshi, Nobuyuki Kayaba, Wonsik Kim, Takahiro Takimoto, and Yoshimitsu Masaki
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
The accuracy of seasonal climate forecasts for monthly precipitation of JMA/MRI-CPS2, a dynamical seasonal climate forecast (SCF) system, is higher than that of statistical SCF (St-SCF) system using climate indices around the equator (10° S–10° N) even for six-month lead forecasts. On a global scale, the forecast accuracy of JMA/MRI-CPS2 is higher for one-month lead forecasts; however, St-SCFs were more accurate for forecasts more than two months in advance.
Hide
09 Jul 2021
A Norwegian Approach to Downscaling
Rasmus E. Benestad
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
A Norwegian approach for deriving regional climate information through downscaling is presented. It is unique and involves a different set to techniques compared to the wider community but give more robust results. We estimate the statistical properties of daily temperature and precipitation and the results are based on large sets of simulations with global climate models.
Hide
02 Jul 2021
A Parquet Cube alternative to store gridded data for data analytics and modeling
Jean-Michel Zigna, Reda Semlal, Flavien Gouillon, Ethan Davis, Elisabeth Lambert, Frédéric Briol, Romain Prod-Homme, Sean Arms, and Lionel Zawadzki
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 5 comments)
Short summary
Short summary
The Parquet Cube storage alternative presented here is compared with Pangeo and THREDDS platforms to access to gridded data for large scale processing and modeling. Stressing the 3 implementations through 3 data scientists' scenarii, this Parquet Cube Alternative appears to be a good candidate to share gridded data in a cloud environment and share them through different communities of users. This open source alternative can be enriched by additional services to subset, enrich or explore data.
Hide
02 Jun 2021
Sensitivity analysis of a data-driven model of ocean temperature
Rachel Furner, Peter Haynes, Dave Munday, Brooks Paige, Daniel C. Jones, and Emily Shuckburgh
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 9 comments)
Short summary
Short summary
Traditional weather & climate models are built from physics-based equations, while data-driven models are built from patterns found in datasets using Machine Learning or statistics. There is growing interest in using data-driven models for weather & climate prediction, but confidence in their use depends on understanding the patterns they're finding. We look at this with a simple regression model of ocean temperature and see the patterns found by the regression model are similar to the physics.
Hide
17 May 2021
Particle dry deposition algorithms in CMAQ version 5.3: characterization of critical parameters and land use dependence using DepoBoxTool version 1.0
Qian Shu, Benjamin Murphy, Jonathan E. Pleim, Donna Schwede, Barron H. Henderson, Havala O.T. Pye, Keith Wyat Appel, Tanvir R. Khan, and Judith A. Perlinger
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
We have bridged the gap between dry deposition measurement and modeling by rigorous use of box and regional transport models and field measurements, but more efforts are needed. This study highlights that deviation among deposition schemes is most pronounced for small and large particles. This study better links model predictions to available real-world observations and incrementally reduces uncertainties in the magnitude of loss processes important for the lifecycle of air pollutants.
Hide
20 Apr 2021
Integrating Agricultural Practices into the TRIPLEX-GHG Model v2.0 for Simulating Global Cropland Nitrous Oxide Emissions: Model Development and Evaluation
Hanxiong Song, Changhui Peng, Kerou Zhang, and Qiuan Zhu
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Cropland is the major hotspot for N
O emission as affected by multiple agricultural practices. Because of the varying magnitudes of N
O emissions across observation sites and periods, it is difficult to quantify the N
O budget at a large scale. A process-based biogeochemical model, TRIPLEX-GHG, was incorporated with major agricultural practices. By comparing the modeled and measured data, we found that the TRIPLEX-GHGv2.0 is capable to provide reasonable estimations of N
O flux from cropland.
Hide
29 Mar 2021
ArcticBeach v1.0: A physics-based parameterization of pan-Arctic coastline erosion
Rebecca Rolph, Pier Paul Overduin, Thomas Ravens, Hugues Lantuit, and Moritz Langer
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 8 comments)
Short summary
Short summary
Declining sea ice, larger waves, and increasing air temperatures are contributing to a rapidly eroding Arctic coastline. We simulate water levels using wind speed and direction, which are used with wave height, wave period, and sea surface temperature to drive an erosion model of a partially frozen cliff and beach. This provides a first step to include Arctic erosion in larger-scale earth system models. Simulated cumulative retreat rates agree within the same order of magnitude as observations.
Hide
17 Mar 2021
A Twenty-Year Analysis of Winds in California for Offshore Wind
Energy Production Using WRF v4.1.2
Alex Rybchuk, Mike Optis, Julie K. Lundquist, Michael Rossol, and Walt Musial
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
We characterize the wind resource off the coast of California by conducting simulations with the Weather Research and Forecasting (WRF) model between 2000 and 2019. We compare newly simulated winds to those from the WIND Toolkit. The newly simulated winds are substantially stronger, particularly in the late summer. We also conduct a refined analysis at three areas that are being considered for commercial development, finding that stronger winds translates to substantially more power here.
Hide
15 Mar 2021
The multiple linear regression modelling algorithm ABSOLUT v1.0 for weather-based crop yield prediction and its application to Germany at district level
Tobias Conradt
Geosci. Model Dev. Discuss.,
2021
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
Crop yields usually depend on weather and climate. It is possible to predict yields solely based on meteorological observations, and future yield scenarios may be calculated from climate scenarios. The ABSOLUT algorithm uses regionally distributed data to auto-adapt to the individual weather-yield relations of a certain crop in its application domain. It is presented with an example for Germany where more than 75 % of the national yield variations of major crops can be explained.
Hide
08 Mar 2021
AstroGeoVis v1.0
: Astronomical Visualizations and Scientific
Computing for Earth Science Education
Tihomir S. Kostadinov
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Here, I introduce and describe
AstroGeoVis v1.0
: open-source software that calculates the position of the Sun in the sky and produces astronomical visualizations relevant to the Earth and climate sciences. The code also calculates the amount of solar energy falling on a tilted flat solar panel. The code and the dynamically generated figures are intended for educational applications, in a wide variety of fields and levels; research use is also envisioned.
Hide
08 Feb 2021
Simulation study of a Squall line hailstorm using High-Resolution
GRAPES-Meso with a modified Double-Moment Microphysics
scheme
Zhe Li, Qijun Liu, Xiaomin Chen, Zhanshan Ma, Jiong Chen, and Yuan Jiang
Geosci. Model Dev. Discuss.,
2021
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Hailstorm is one of the severe disaster weathers for agricultural countries. Hail microphysics processes have been added in the double-moment microphysics scheme in the operational model GRAPES_Meso and a severe squall line hailstorm is simulated. Compared with the observation, simulation results can capture the basic character of this squall line hailstorm. Results imply the ability of high-resolution GRAPES_Meso on forecasting hailstorm.
Hide
28 Dec 2020
LPJmL-Med – Modelling the dynamics of the land-sea nutrient
transfer over the Mediterranean region–version 1: Model
description and evaluation
Mohamed Ayache, Alberte Bondeau, Rémi Pagès, Nicolas Barrier, Sebastian Ostberg, and Melika Baklouti
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
Land forcing is reported as one of the major sources of uncertainty limiting the capacity of marine biogeochemical models. In this study, we present the first basin-wide simulation at 1/12° of water discharge as well as nitrate (NO
) and phosphate (PO
) release into the Mediterranean from basin-wide agriculture and urbanization, by using the agro-ecosystem model (LPJmL-Med). The model evaluation against observation data, and all implemented processes are described in detail in this manuscript.
Hide
22 Dec 2020
Incorporating
15
N into the outputs of SMOKE version 4.6 as the emission
input dataset for CMAQ version 5.2.1 for assessing the role emission
sources plays in controlling the isotopic composition of NO
, NO
, and atmospheric nitrate
Huan Fang and Greg Michalski
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
A new emission input dataset that incorporates nitrogen isotopes has been developed to simulate isotope tracers in air pollution. The NO
emission from different sources simulated by Sparse Matrix Operator Kerner Emissions (SMOKE) were replicated using
15
N. The dataset is able to predict δ
15
N variations in NO
that are similar to those observed in aerosol and gases in the troposphere.
Hide
16 Dec 2020
LARGE 0.2.0: 2D numerical modelling of geodynamic problems
Nicola Creati and Roberto Vidmar
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
LARGE
(Lithosphere AsthenospheRe Geodynamic Evolution) 0.2.0 is a 2D numerical geodynamic simulation software released under the MIT license. The code can operate on single and multiprocessors computer.
LARGE
has been written in Python, while most of simulation software are written in C or Fortran, since the language is easy to understand and write. The software provides a user friendly interface and can solve complex plate tectonics problems.
Hide
23 Nov 2020
LUCI-EntEx v1.0: A GIS-based algorithm to determine stream entry
and exit points at boundaries of any given shape
Bethanna Jackson, Rubianca Benavidez, Keith Miller, and Deborah Maxwell
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
There is an increasing will to preserve nature for its own sake and to protect its benefits for future generations. Various policies encourage more sustainable land management practices to protect rivers and lakes. Separating out broad scale from local impacts is difficult, but necessary for informed land management outcomes. We present tools automatically identifying flows of water, sediment and chemicals in and out of farms, forestry blocks, etc to enable smarter future management.
Hide
29 Oct 2020
The Effects of Ocean Surface Waves on Global Forecast
in CFS Modeling System v2.0
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Xiang Li, and Yunfei Zhang
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 7 comments)
Short summary
Short summary
To better understand the effects of surface waves, we developed a coupled global atmosphere-ocean-wave system. Processes of Langmuir circulations and sea surface momentum roughness were considered. Results from a series of 7-day forecasts show the Langmuir circulations can reduce the biases of warm sea surface temperature and shallow mixed layer in the Antarctic circumpolar current during austral summer. Whereas surface roughness enables improvements to overestimated 10-m wind and wave height.
Hide
28 Oct 2020
Evaluation and climate sensitivity of the PlaSim v.17 Earth System
Model coupled with ocean model components of different complexity
Michela Angeloni, Elisa Palazzi, and Jost von Hardenberg
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
We compare the Planet Simulator, an Earth-system Model of Intermediate Complexity, using a 3D dynamical ocean, with two configurations using a simpler mixed-layer ocean. A tuning of oceanic parameters allows a reasonable mean climate in all cases. Model equilibrium climate sensitivity in abrupt CO
concentration change experiments is found to be significantly affected by the sea-ice feedbacks and by the parameterization of meridional oceanic heat transport in the mixed-layer configurations.
Hide
22 Oct 2020
Strengths and weaknesses of three Machine Learning methods for
pCO
interpolation
Jake Stamell, Rea R. Rustagi, Lucas Gloege, and Galen A. McKinley
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Using simulated surface ocean pCO
from Earth System Models, we test three Machine Learning methods (neural network, XGBoost, random forest) to discern their ability to reconstruct global coverage from sparse observations. Synthetic data means we can train based on real-world sampling patterns and then evaluate against the known full coverage result of the original simulation. ML approaches perform best in the open ocean, but struggle in regions of low sampling. XGBoost saw the best performance.
Hide
22 Oct 2020
Parallelizing a serial code: open–source module, EZ Parallel 1.0,
and geophysics examples
Jason Louis Turner and Samuel N. Stechmann
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
EZ Parallel is a Fortran Message Passing Interface library designed to allow users to easily and quickly turn their serial code into a parallel one for the purpose of obtaining simulations with higher resolutions or larger domain sizes in a shorter amount of time. In tests of the parallelized code, the strong scaling efficiency for the finite difference code is seen to be roughly 80% to 90%, which is achieved by adding roughly only 10 new lines to the serial code.
Hide
12 Oct 2020
Using a single column model (SGRIST1.0) for connecting model physics and dynamics in the Global-to-Regional Integrated forecast SysTem (GRIST-A20.8)
Xiaohan Li, Yi Zhang, Xindong Peng, and Jian Li
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
This study develops a single-column model (SGRIST1.0) to bridge the coupling of physical parameterizations and a new unstructured-mesh modeling system. The physical parameterization suite is first isolated and evaluated via SGRIST1.0 to reduce the uncertainty of physics during transfer, then the validated parameterization suite is coupled to the 3D dynamical framework. The transferred package shows reasonable behavior in the full physics-dynamics interaction.
Hide
29 Sep 2020
Development and performance optimization of a parallel
computing infrastructure for an unstructured-mesh
modelling framework
Zhuang Liu, Yi Zhang, Xiaomeng Huang, Jian Li, Dong Wang, Mingqing Wang, and Xing Huang
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
This paper describes several techniques for the parallelization and performance optimization of
an unstructured-mesh global atmospheric model. The purpose of this research is to facilitate the rapid iterative model development. These techniques are general and can be used for other parallel modeling on unstructured meshes.
Hide
11 Sep 2020
Deep-learning based climate downscaling using the super-resolution method: a case study over the western US
Xingying Huang
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 2 comments)
02 Sep 2020
Evaluating the use of Facebook's Prophet model v0.6 in forecasting
concentrations of NO
at single sites across the UK and in response
to the COVID-19 lockdown in Manchester, England
David Topping, David Watts, Hugh Coe, James Evans, Thomas J. Bannan, Douglas Lowe, Caroline Jay, and Jonathan W. Taylor
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
Time-series forecasting methods have often been used to mitigate some of the challenges associated with deploying chemical transport models. In this study we deploy and evaluate Facebook’s Prophetmodel v0.6 in predicting hourly concentrations of Nitrogen Dioxide [NO
]. et. Overall we find the Prophet model offers a relatively effective and simple way to make predictions about NO
at local levels.
Hide
13 Aug 2020
Snowpack and firn densification in the Energy Exascale Earth
System Model (E3SM) (version 1.2)
Adam M. Schneider, Charles S. Zender, and Stephen F. Price
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
We enhance the Energy Exascale Earth System Model's land
component (ELM) to better represent multi-year snow (firn) on ice sheets. Our
developments reveal ELM deficiencies regarding firn density, a fundamental
property in glaciology. To improve firn density profiles, we fine tune
ELM's snowpack parameters using statistical modeling. Our findings demonstrate
how ELM can simulate both seasonal snow and firn on ice sheets and advance a
broader effort to better predict sea level rise.
Hide
05 Aug 2020
System identification techniques for detection of teleconnections within climate models
Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
Through a cascade of physical mechanisms, a change in one location can trigger a response in a different location. These responses and the mechanisms that cause them are difficult to detect. Here we propose a method, using global climate models, to detect possible relationships between changes in one region and responses throughout the globe caused by that change. A change in the Pacific ocean is used as a test case to determine the effectiveness of the method.
Hide
29 Jul 2020
Evaluation of asymmetric Oxygen Minimum Zones in the tropical
Pacific: a basin-scale OGCM-DMEC V1.0
Kai Wang, Xiujun Wang, Raghu Murtugudde, Dongxiao Zhang, and Rong-Hua Zhang
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 5 comments)
Short summary
Short summary
We improve and evaluate a basin-scale model’s ability to simulate spatial distribution of mid-depth oxygen in the tropical Pacific that holds the world’s two largest Oxygen Minimum Zones (OMZs). We find that low oxygen levels in the mid-ocean are largely due to extremely weak physical mixing, but the asymmetric OMZs (i.e., larger OMZ to the north) are attributable to both physical and biological processes, i.e., weaker physical supply over 200-600 m and higher biological consumption below 600 m.
Hide
27 Jul 2020
Quasi-hydrostatic equations for climate models and the study on linear instability
Robert Nigmatulin and Xiulin Xu
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 27 comments)
Short summary
Short summary
We develop a 3-dimensional quasi-hydrostatic system of equations with an accurately estimated vertical velocity. Moreover, we focus on the problem of predictability of such a system of equations and the influence of different vertical velocity evaluations. It shows that the wavelengths of perturbations significantly affect stability. Thus appropriate horizontal and vertical grid sizes should be chosen for modelling. Besides, we attempt to eliminate instability by introducing pseudo-viscosities.
Hide
24 Jul 2020
Simulating interactive ice sheets in the multi-resolution AWI-ESM 1.2: A case study using SCOPE 1.0
Paul Gierz, Lars Ackermann, Christian B. Rodehacke, Uta Krebs-Kanzow, Christian Stepanek, Dirk Barbi, and Gerrit Lohmann
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 3 comments)
Short summary
Short summary
In this study, we describe the SCOPE coupler, which is used connect the ECHAM6/JSBACH/FESOM1.4 climate model to the PISM 1.1.4 ice sheet model. This system is used to simulate IPCC scenarios projected for the future, and several warm periods in the past; the mid Holocene and the Last Interglacial. Our new model allows us to simulate the ice sheet’s response to changes in the climatic conditions, providing a new avenue of investigation over the previous models, which keep the cryosphere fixed.
Hide
13 Jul 2020
Combining homogeneous and heterogeneous chemistry to model inorganic compounds concentrations in indoor environments: the H
I model (v1.0)
Eve-Agnès Fiorentino, Henri Wortham, and Karine Sartelet
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 1 comment)
15 May 2020
The impacts of uncertainties in emissions on aerosol data assimilation and short-term PM
2.5
predictions in CMAQ v5.2.1 over East Asia
Sojin Lee, Chul Han Song, Kyung Man Han, Daven K. Henze, Kyunghwa Lee, Jinhyeok Yu, Jung-Hun Woo, Jia Jung, Yunsoo Choi, Pablo E. Saide, and Gregory R. Carmichael
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 8 comments)
07 May 2020
Explainable AI for Knowledge Acquisition in Hydrochemical Time Series V1.0.0
Michael C. Thrun, Alfred Ultsch, and Lutz Breuer
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 3 comments)
Short summary
Short summary
We propose an explainable AI (XAI) framework for times series describing water quality & environmental parameters. The relationship between parameters is investigated by swarm based cluster analysis designed to find similar days within & dissimilar days between clusters. Resulting clusters define three states of water bodies & are visualized by a topographic map of high-dimensional structures. Rules generated by the XAI system explain clusters & improve the understanding of aquatic environments.
Hide
04 May 2020
From R-squared to coefficient of model accuracy for assessing "goodness-of-fits"
Charles Onyutha
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 9 comments)
Short summary
Short summary
despite its wide use in assessing model performance has several drawbacks. While taking into account the drawbacks, this paper introduces another metric (coefficient of model accuracy MCA) which is capable of assessing "goodness-of-fits". Stepwise derivation of CMA comprises an analogy to the
. Suitability of CMA for assessing model performance was demonstrated through comparison of simulations by hydrological models calibrated using CMA and other existing objective functions.
Hide
27 Apr 2020
TraceME (v1.0) – An online Traceability analysis system for Model Evaluation on land carbon dynamics
Jian Zhou, Jianyang Xia, Ning Wei, Yufu Liu, Chenyu Bian, Yuqi Bai, and Yiqi Luo
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The increase of model complexity and data volume challenges the evaluation of Earth system models (ESMs), which mainly stems from the untraceable, unautomatic, and high computational costs. Here, we built up an online Traceability analysis system for Model Evaluation (TraceME), which is traceable, automatic and shareable. The TraceME (v1.0) can trace the structural uncertainty of simulated carbon (C) storage in ESMs and provide some new implications for the next generation of model evaluation.
Hide
06 Apr 2020
Altered sub-seasonal predictability of Community Atmosphere Model 5 (CAM5) in CESM 1.2.1 by the choices of dynamical core
Ha-Rim Kim, Baek-Min Kim, Sang-Yoon Jun, and Yong-Sang Choi
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Focusing on the predictability issue closely, we compare the differences in the predictive skill of two different dynamical cores adopting the same physics. We find that the predictive skills of these two cores were significantly different, raising caution about the choice of dynamical cores in the predictability studies. We believe our study initiates a new issue regarding the identification of model uncertainties in the predictability studies.
Hide
26 Mar 2020
ConvectiveFoam1.0
: development and benchmarking of a infinite-Pr number solver
Sara Lenzi, Matteo Cerminara, Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Antonello Provenzale
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 6 comments)
11 Mar 2020
Evaluation of air quality forecasting system FORAIR_IT over Europe and Italy at high resolution for year 2017
Mario Adani, Guido Guarnieri, Lina Vitali, Luisella Ciancarella, Ilaria D'Elia, Mihaela Mircea, Maurizio Gualtieri, Andrea Cappelletti, Massimo D'Isidoro, Gino Briganti, Antonio Piersanti, Milena Stracquadanio, Gaia Righini, Felicita Russo, Giuseppe Cremona, Maria Gabriella Villani, and Gabriele Zanini
Geosci. Model Dev. Discuss.,
2020
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
The National Air Quality forecasting system FORAIR_IT may be considered a state of the art model, and as far as we know it is the first forecasting system at high spatial resolution proposed at Italian National level. FORAIR_IT may be a useful tool that the policy makers might use in order to apply extraordinary procedure to prevent/mitigate high levels of air pollution. Moreover general population might take advantage of FORAIR_IT to get used to the complexity of air quality issues.
Hide
05 Mar 2020
Dynamic Complex Network Analysis of PM
2.5
Concentrations in the UK using Hierarchical Directed Graphs (V1.0.0)
Parya Broomandi, Xueyu Geng, Weisi Guo, Jong Ryeol Kim, Alessio Pagani, and David Topping
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
As a result of our novel graph-based reduced modeling, we are able to represent high-dimensional knowledge into a causal inference and stability framework.
Hide
24 Feb 2020
Intercomparison between the Integrated Urban land Model and the
Noah Urban Canopy Model
Chunlei Meng and Junxia Dou
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 5 comments)
17 Feb 2020
UFlow 1.0: A Computer Model for Projections of Urban Sprawl
André Koscianski
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
Urban sprawl is driven by an ensemble of forces and variables that compose a complex system, difficult to predict. This paper introduces the UFlow 1.0 simulator, based on a diffusion model and a Cellular Automata structure. A procedure adjusts a matrix of coefficients, making the model sensitive to local differences of growth speed. The software can also compute reverse predictions, and the paper indicates possible adaptations with different types of input data, metrics and algorithmic rules.
Hide
03 Feb 2020
Interaction of Small-Scale Gravity Waves with the Terdiurnal Solar
Tide in the Mesosphere and Lower Thermosphere
Friederike Lilienthal, Erdal Yiğit, Nadja Samtleben, and Christoph Jacobi
Geosci. Model Dev. Discuss.,
2020
Preprint withdrawn
(discussion: closed, 8 comments)
Short summary
Short summary
Gravity waves are a small-scale but prominent dynamical feature in the Earth's atmosphere. Here, we use a mechanistic nonlinear general circulation model and implement a modern whole atmosphere gravity wave parameterization. We study the response of the atmosphere on several phase speed spectra. We find a large influence of fast travelling waves on the background dynamics in the thermosphere and also a strong dependence of the amplitude of the terdiurnal solar tide, indicating wave interactions.
Hide
27 Jan 2020
GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration
Nicholas James Leach, Zebedee Nicholls, Stuart Jenkins, Christopher J. Smith, John Lynch, Michelle Cain, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 8 comments)
Short summary
Short summary
GIR is a simple climate model designed to make exploration of the impact of greenhouse gas and aerosol emissions on the climate easy and understandable for its users. It uses an intuitive input and output structure, and the model is itself a set of only six equations. This lends the model to applications such as teaching, or as a lowest common denominator model between groups in large-scale climate assessments. It could also be used to investigate more complex models through emulation.
Hide
24 Jan 2020
Atmospheric aging of small-scale wood combustion emissions (model MECHA 1.0) – is it possible to distinguish causal effects from non-causal associations?
Ville Leinonen, Petri Tiitta, Olli Sippula, Hendryk Czech, Ari Leskinen, Juha Karvanen, Sini Isokääntä, and Santtu Mikkonen
Geosci. Model Dev. Discuss.,
2020
Revised manuscript not accepted
(discussion: closed, 7 comments)
05 Nov 2019
Enhancement and validation of a state-of-the-art global hydrological model H08 (v.bio1) to simulate second-generation herbaceous bioenergy crop yield
Zhipin Ai, Naota Hanasaki, Vera Heck, Tomoko Hasegawa, and Shinichiro Fujimori
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Reliable bioenergy crop yield simulation remains a challenge at the global scale. Here, we enhanced a state-of-the-art global hydrological model to simulate bioenergy yield. We found that unconstrained irrigation more than doubled the yield under rainfed condition, while simultaneously reducing the water-use efficiency by 29 % globally. This is the first trial to use a global hydrological model to simulate the bioenergy crop and offers an effective tool to assess the bioenergy-water relations.
Hide
17 Sep 2019
CARBON-DISC 1.0 – A coupled, process-based model of global in-stream carbon biogeochemistry
Wim Joost van Hoek, Lauriane Vilmin, Arthur H. W. Beusen, José M. Mogollón, Xiaochen Liu, Joep J. Langeveld, Alexander F. Bouwman, and Jack J. Middelburg
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
In this study we present CARBON-DISC 1.0. It couples the global water balance model PCR-GLOBWB with global carbon inputs from the Integrated Model to Assess the Global Environment (IMAGE) at a 0.5° resolution and calculates gridcell-to-gridcell transport, C transformations, C emissions, C burial and primary production on a monthly timestep and without calibration.
Hide
14 Aug 2019
Spatial and Temporal Evolution of a Lightning Diagnostic in HWRF (V3.7a)
Keren Rosado, Bin Liu, Vernon Morris, Vijay Tallapragada, and Lin Zhu
Geosci. Model Dev. Discuss.,
2019
Publication in GMD not foreseen
(discussion: closed, 3 comments)
Short summary
Short summary
The operational Hurricane Weather Research and Forecast (HWRF) model has been used to investigate the role of lightning diagnostics in the life cycle of tropical cyclones (TC). A lightning parameterization was implemented into HWRF with the motivation of using lightning forecast as a proxy for TC intensity changes. Results from this investigation show mixed results in terms of correlating lightning forecast and TC intensity forecast.
Hide
09 Aug 2019
MetSim v2.0.0: A flexible and extensible framework for the estimation and disaggregation of meteorological data
Andrew R. Bennett, Joseph J. Hamman, and Bart Nijssen
Geosci. Model Dev. Discuss.,
2019
Preprint withdrawn
(discussion: closed, 2 comments)
Short summary
Short summary
MetSim is a software package for simulating meteorologic processes, and aims to be applied in the environmental and Earth sciences. It can simulate processes such as solar and thermal radiation, specific humidity, and vapor pressure across large spatial areas in an efficient manner. This paper describes the software and analyzes it's ability to be used in large simulations. We describe how MetSim can be used and provide details on the various options that are available.
Hide
09 Jul 2019
A process-based
Sphagnum
plant-functional-type model for implementation in the TRIFFID Dynamic Global Vegetation Model
Richard Coppell, Emanuel Gloor, and Joseph Holden
Geosci. Model Dev. Discuss.,
2019
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
(1) We developed a new Sphagnum model for ecosystem exchange. (2) The model is implemented in TRIFFID which is part of the JULES land surface model. (3) Outputs compare well to empirical field data. (4) JULES can now better incorporate peatland-climate feedbacks.
Hide
02 Jul 2019
Bolchem: an On-Line Coupled Mesoscale Chemistry Model
Rita Cesari, Alberto Maurizi, Massimo D'Isidoro, Tony Christian Landi, Mihaela Mircea, Felicita Russo, Piero Malguzzi, and Francesco Tampieri
Geosci. Model Dev. Discuss.,
2019
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
This work presents the on-line coupled meteorology-chemistry transport model BOLCHEM. The paper describes the meteorological and chemical modules, and presents simulation results on the European domain for one year run. For all considered pollutants (O
, NO
, PM
10
, PM
2.5
) the model performances are close to those achieved by the current state-of-the-art model system dedicated to air quality study, e.g. Copernicus CAMS products.
Hide
21 May 2019
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model
Julien Brajard, Alberto Carrassi, Marc Bocquet, and Laurent Bertino
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 8 comments)
Short summary
Short summary
We explore the possibility of combining data assimilation with machine learning. We introduce a new hybrid method for a two-fold scope: (i) emulating hidden, possibly chaotic, dynamics and (ii) predicting its future states. Numerical experiments have been carried out using the chaotic Lorenz 96 model, proving both the convergence of the hybrid method and its statistical skills including short-term forecasting and emulation of the long-term dynamics.
Hide
13 May 2019
A dual-pass carbon cycle data assimilation system to estimate surface CO
fluxes and 3D atmospheric CO
concentrations from spaceborne measurements of atmospheric CO
Rui Han and Xiangjun Tian
Geosci. Model Dev. Discuss.,
2019
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
This manuscript mainly introduce a new version of the carbon cycle data assimilation system Tan-Tracker (v1), which uses a novel dual-pass assimilation framework and based on an advanced assimilation algorithm NLS-4DVar. Tan-Tracker (v1) aims to find more accurate surface CO
flux estimates based on satellite XCO
observations. With a more accurate surface carbon flux, Tan-Tracker (v1) can provide a new perspective on carbon budget and become a better tool for carbon cycle research.
Hide
06 May 2019
Spatio-temporal consistent bias pattern detection on MIROC5 andFGOALS-g2
Bo Cao, Ying Zhao, and Ziheng Zhou
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
We propose a method to detect spatio-temporal consistent bias patterns, which are present in contiguous space with significant and coherent biases in continuous time periods, from climate model outputs. These patterns are ideal for revealing regional and seasonal characteristics of biases and worth further investigation by modelers. Experiment results on both MIROC5 and FGOALS-g2 precipitation outputs show that the proposed approach can produce some important findings.
Hide
06 May 2019
Evaluation of Unified Model Rainfall Forecasts over the Western Ghats and North East states of India
Kuldeep Sharma, Sushant Kumar, Raghavendra Ashrit, Sean Milton, Ashis K. Mitra, and Ekkattil N. Rajagopal
Geosci. Model Dev. Discuss.,
2019
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
This study is based on the long record (2007–2018) of UM model's real time rainfall forecasts over India to highlight the improved skill of forecasts over orographic regions of India. Some of these improvements are attributed to the increased horizontal and vertical resolutions as well as improved physics parameterization schemes while major credit to the substantial improvements in weather forecasting goes to the sophisticated data assimilation systems which utilizes satellite data.
Hide
13 Mar 2019
A reduced-order Kalman smoother for (paleo-)ocean state estimation: assessment and application to the LGM
Charlotte Breitkreuz, André Paul, Stefan Mulitza, Javier García-Pintado, and Michael Schulz
Geosci. Model Dev. Discuss.,
2019
Publication in GMD not foreseen
(discussion: closed, 2 comments)
Short summary
Short summary
We present a technique for ocean state estimation based on the combination of a simple data assimilation method with a state reduction approach. The technique proves to be very efficient and successful in reducing the model-data misfit and reconstructing a target ocean circulation from synthetic observations. In an application to Last Glacial Maximum proxy data the model-data misfit is greatly reduced but some misfit remains. Two different ocean states are found with similar model-data misfit.
Hide
28 Feb 2019
Physical-biogeochemical regional ocean model uncertainties stemming from stochastic parameterizations and potential impact on data assimilation
Vassilios D. Vervatis, Pierre De Mey-Frémaux, Nadia Ayoub, Sarantis Sofianos, Charles-Emmanuel Testut, Marios Kailas, John Karagiorgos, and Malek Ghantous
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Our contributions were specifically targeted at the generation of ensembles, in particular (but not solely) for high-resolution ocean configurations including regional and coastal physics and biogeochemistry. The most important paradigm of this work was to adopt a balanced approach building ocean biogeochemical model ensembles and testing their relevance against observational networks monitoring upper-ocean properties, in the sense of nonzero joint probabilities.
Hide
04 Feb 2019
Semantic Description and Complete Computer Characterization of Structural Geological Models
Xianglin Zhan, Jiandong Liang, Cai Lu, and Guangmin Hu
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We proposed the semantic descriptions for structural geological models in order to facilitate computer based processing of geological semantics. The semantic description is a complete representation of the structural model. And we use the multi-level heterogeneous network to be the computer characterization of the semantic description. Semantic descriptions can also be used to constrain structure modeling which forms a top-down modeling process. We validated the effectiveness with actual data.
Hide
01 Feb 2019
Mass-conserving coupling of total column CO
(XCO
) from global to mesoscale models: Case study with CMS-Flux inversion system and WRF-Chem (v3.6.1)
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at
Hide
29 Jan 2019
On fluctuating air-sea-interaction in local models: linear theory
Achim Wirth
Geosci. Model Dev. Discuss.,
2019
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
The dynamics of three local linear models of air-sea-interaction commonly employed in climate or ocean simulations is compared. The models differ by whether or not the ocean velocity is included in the shear calculation applied to the ocean and the atmosphere. Analytic calculations for the models with deterministic and random forcing (white and colored) are presented.The fluctuation-dissipation-relation, the fluctuation-dissipation-theorem and the fluctuation-theorem is discussed.
Hide
09 Jan 2019
Assimilation of SCATSAR Soil Wetness Index in SURFEX 8.0 to
improve weather forecasts
Stefan Schneider and Bernhard Bauer-Marschallinger
Geosci. Model Dev. Discuss.,
2019
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
This paper investigates the question if satellite-measured soil moisture data are useful to improve weather forecasts. To answer this question, historical forecasts are re-computed with and without this additional data source and compared against measurements from weather stations. This test shows an positive impact of using soil moisture data which indicates that they should be used operationally in regional weather forecast models.
Hide
19 Dec 2018
Chemistry and deposition in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTE v1.0). Part B. Dry deposition
Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Steven Compernolle, and Jozef Peeters
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 2 comments)
Short summary
Short summary
A new dry deposition model for gaseous species is presented. It relies on the species reactivity and water-solubility, for which a new prediction method is also presented. The deposition model parameters are adjusted based on comparisons with field data for ozone and organic compounds at numerous sites. The importance of dry deposition as a sink of oxygenated organic compounds and nitrogen oxides is demonstrated by global model simulations with the new deposition scheme.
Hide
10 Dec 2018
Optimization of the WRFV3.7 adjoint model
Qiang Cheng, Juanjuan Liu, and Bin Wang
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
Adjoint models are usually used to improve the weather forecast, but It's very time consuming. What we would like to do is determining how to significantly reduce the running cost of the adjoint model.The manuscript presented several methods. With them, we reduced the adjoint cost of the Weather Research and Forecasting plus (WRFPLUSV3.7) by almost half. Apparently, these are also productive in other applications in terms of adjoint model such as parameter estimation, singular vector etc.
Hide
30 Nov 2018
SBDM v1.0: A scaling-based discretization method for the Geographical Detector Model
Xiaoyu Meng, Xin Gao, Shengyu Li, Wenjing Huang, and Jiaqiang Lei
Geosci. Model Dev. Discuss.,
2018
Preprint withdrawn
(discussion: closed, 0 comments)
30 Nov 2018
A Conceptual Framework for Integration Development of GSFLOW Model: Concerns and Issues Identified and Addressed for Model Development Efficiency
Chao Chen, Sajjad Ahmad, and Ajay Kalra
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
This study proposed a conceptual framework for development of integrated surface and groundwater flow model, GSFLOW. Study provides guidance on addressing common challenges in the model development, i.e., model conceptualization, data exchange, model calibration, and sensitivity analysis. An application of the framework demonstrated that both model development efficiency and hydrologic characterization improved. The proposed framework can be useful for other similar modeling efforts.
Hide
22 Nov 2018
HIRHAM–NAOSIM 2.0: The upgraded version of the coupled regional atmosphere-ocean-sea ice model for Arctic climate studies
Wolfgang Dorn, Annette Rinke, Cornelia Köberle, Klaus Dethloff, and Rüdiger Gerdes
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
A new version of the coupled Arctic climate model HIRHAM-NAOSIM has been designed to study interactions between atmosphere, sea ice, and ocean in the Arctic. This version utilizes upgraded, high-resolution model components and a revised coupling procedure. Simulations with the new version reveal that Arctic sea ice is thicker in all seasons and closer to observations than in the previous version. Wintertime biases in sea-ice extent and near-surface air temperatures are reduced as well.
Hide
22 Nov 2018
Use an idealized protocol to assess the nesting procedure in regional climate
modelling
Shan Li, Laurent Li, and Hervé Le Treut
Geosci. Model Dev. Discuss.,
2018
Preprint withdrawn
(discussion: closed, 7 comments)
Short summary
Short summary
Newtonian relaxation allowing RCM (regional climate model) to follow GCM (global climate model) is a widely-used technique for climate downscaling and regional weather forecasting. It is thoroughly assessed in an idealized framework for both synoptic variability and long-term mean climate. LMDz is a GCM, but it can be configured as a RCM. It thus acts as both GCM and RCM. The experimental set-up “Master versus Slave” considers GCM as the reference to assess behaviors of RCM.
Hide
02 Nov 2018
Model evaluation by a cloud classification based on multi-sensor
observations
Akio Hansen, Felix Ament, Verena Grützun, and Andrea Lammert
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 5 comments)
Short summary
Short summary
Clouds are responsible for large uncertainties in atmospheric models, whereby the evaluation is very challenging due to their complexity. The Cloudnet project uses multi-sensor observations to create a comprehensive Target Classification showing the cloud structure and phase, but there is no comparable model output available. The presented cloud classification algorithm generates a consistent product, which provides a comprehensive view on clouds and is used for further in-depth evaluation.
Hide
11 Oct 2018
Common metrics of calibration for continuous Gaussian data and
exceedance probabilities
Rita Glowienka-Hense, Andreas Hense, Thomas Spangehl, and Marc Schröder
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
Ensemble forecast verification treats the issues of forecast errors and uncertainty estimated from ensemble spread. We suggest measures based on relative entropy. For continuous variables correlation and the mean ratio of the ensemble spread to climate variance (analysis of variance (anova)) are related to these entropies. For categorical data corresponding scores are deduced that allow the comparison with continuous data.
Hide
05 Oct 2018
Observation-based implementation of ecophysiological processes for a rubber plant functional type in the community land model (CLM4.5-rubber_v1)
Ashehad A. Ali, Yuanchao Fan, Marife D. Corre, Martyna M. Kotowska, Evelyn Hassler, Fernando E. Moyano, Christian Stiegler, Alexander Röll, Ana Meijide, Andre Ringeler, Christoph Leuschner, Tania June, Suria Tarigan, Holger Kreft, Dirk Hölscher, Chonggang Xu, Charles D. Koven, Rosie Fisher, Edzo Veldkamp, and Alexander Knohl
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We used carbon-use and water-use related datasets of small-holder rubber plantations from Jambi province, Indonesia to develop and calibrate a rubber plant functional type for the Community Land Model (CLM-rubber). Increased sensitivity of stomata to soil water stress and enhanced respiration costs enabled the model to capture the magnitude of transpiration and leaf area index. Including temporal variations in leaf life span enabled the model to better capture the seasonality of leaf litterfall.
Hide
05 Sep 2018
Impact of model resolution on Holocene climate simulations of the
Northern Hemisphere
Axel Wagner, Gerrit Lohmann, and Matthias Prange
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 6 comments)
Short summary
Short summary
This study demonstrates the dependence of simulated surface air temperatures on variations in grid resolution and resolution-dependent orography in simulations of the Mid-Holocene. A set of Mid-Holocene sensitivity experiments is carried out. The simulated Mid-Holocene temperature differences (low versus high resolution) reveal a response that regionally exceeds the Mid-Holocene to preindustrial modelled temperature anomalies, and show partly reversed signs across the same geographical regions.
Hide
09 Jul 2018
Simulation Improvements of ECHAM5-NEMO3.6 and ECHAM6-NEMO3.6 Coupled Models Compared to MPI-ESM and the Corresponding Physical Mechanisms
Shu Gui, Ruowen Yang, and Jie Cao
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 21 comments)
Short summary
Short summary
In this paper, two new coupled models have been developed, both of which show substantial improvements in the model simulation compared with the MPI-ESM model that is widely used in weather forecast and atmospheric research. Inter-model comparison suggests that cumulus convection and latent heat of evaporation over the sea surface are the two major factors that shape the model error of sea surface temperature. It implies a new vision of bias origin for coupled model development practices.
Hide
02 Jul 2018
Coupling Library Jcup3: Its philosophy and application
Takashi Arakawa, Takahiro Inoue, Hisashi Yashiro, and Masaki Satoh
Geosci. Model Dev. Discuss.,
2018
Preprint withdrawn
(discussion: closed, 5 comments)
Short summary
Short summary
In this paper, we discussed the design concept and implementation of a coupling software Jcup. The design concept can be summarized as dividing the function of the software into changing and not changing the values of the data and enabling users to manage and implement the function of changing the value. Based upon this concept, Jcup is constructed so that 1) remapping table is utilized as input information and 2) interpolation calculation codes can be freely implemented by users.
Hide
25 Jun 2018
Bias correction of multi-ensemble simulations from the HAPPI model intercomparison project
Fahad Saeed, Ingo Bethke, Stefan Lange, Ludwig Lierhammer, Hideo Shiogama, Dáithí A. Stone, Tim Trautmann, and Carl-Friedrich Schleussner
Geosci. Model Dev. Discuss.,
2018
Revised manuscript has not been submitted
(discussion: closed, 4 comments)
21 Jun 2018
NHM-Chem, the Japan MeteorologicalAgency's regional meteorology – chemistry model (v1.0): model description and aerosol representations
Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 4 comments)
06 Jun 2018
A simple weather generator for applications with limited data availability: TEmpotRain 1.0 for temperatures, extraterrestrial radiation, and potential evapotranspiration
Gerrit Huibert de Rooij
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 6 comments)
Short summary
Short summary
Areas that have few or no weather stations or are subject to climate change still need weather data in order to model the demand for water, the risk of floods and droughts, etc. TEmpotRain generates rainfall, daily temperature extremes, and daily potential evaporation (from the soil) / transpiration (by plants). The physical meaning of the model parameters is clear. This allows realistic values for them to be estimated, even for hypothetical (future) climates for which data are not available.
Hide
06 Jun 2018
MOVEIM v1.0: Development of a bottom-up motor vehicular emission inventories for the urban area of Manaus in central Amazon rainforest
Paulo R. Teixeira, Saulo R. de Freitas, Francis W. Correia, and Antonio O. Manzi
Geosci. Model Dev. Discuss.,
2018
Publication in GMD not foreseen
(discussion: closed, 4 comments)
Short summary
Short summary
Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues, and weather modification. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions.
Hide
02 May 2018
Marine biogeochemical cycling and climate-carbon cycle feedback simulated by
the NUIST Earth System Model: NESM-2.0.1
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
NESM-2.0.1 is one of the few models from China that present the ocean carbon cycle simulations. Our results demonstrate that NESM-2.0.1 does a reasonable job in simulating current-day marine ecosystems and oceanic CO
uptake. The model also can be used as a useful tool in the investigation of feedback interactions between the ocean carbon cycle, atmospheric CO
, and climate change.
Hide
14 Mar 2018
A new tool for model assessment in the frequency domain – Spectral
Taylor Diagram : application to a global ocean general
circulation model with tides
Mabel Costa Calim, Paulo Nobre, Peter Oke, Andreas Schiller, Leo San Pedro Siqueira, and Guilherme Pimenta Castelão
Geosci. Model Dev. Discuss.,
2018
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
A new tool inspired on tides is introduced. The Spectral Taylor Diagram designed for evaluating and monitoring models performance in frequency domain calculates the degree of correspondence between simulated and observed fields for a given frequency (or a band of frequencies). It's a powerful tool to detect co-oscillating patterns in multi scale analysis, without using filtering techniques.
Hide
24 Jan 2018
Development of the city-scale chemistry transport model CityChem-EPISODE and its application to the city of Hamburg
Matthias Karl
Geosci. Model Dev. Discuss.,
2018
Preprint retracted
(discussion: closed, 3 comments)
Short summary
Short summary
Urban air pollution issues in Europe are mainly related to the human health impacts of particulate matter and ozone. A large part of the population living in cities is exposed to ozone above the European Union air quality target. The new model CityChem-EPISODE has been developed to perform chemistry/transport simulations of multiple reactive pollutants in urban areas. The application of the model in Hamburg (Germany) in 2012 shows good performance for ozone at air quality monitoring stations.
Hide
02 Jan 2018
The Climate Generator: Stochastic climate representation for
glacial cycle integration
Mohammad Hizbul Bahar Arif, Lev Tarasov, and Tristan Hauser
Geosci. Model Dev. Discuss.,
2018
Revised manuscript has not been submitted
(discussion: closed, 4 comments)
Short summary
Short summary
This study is a first step answer to the following question: Can you
use emulators (machine learning techniques) to make the output of fast
simple climate models (a 2-D energy balance model in this test case)
indistinguishable from that of a much more computationally expensive
General Circulation climate model (GCM) within the uncertainties of
GCMs? Our preliminary test of this concept for large spatio-temporal
contexts gives a positive answer.
Hide
15 Dec 2017
Performance evaluation of ROMS v3.6 on a commercial cloud system
Kwangwoog Jung, Yang-Ki Cho, and Yong-Jin Tak
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The performance of the ROMS was evaluated on Amazon Web Services for various configurations. Our study shows how numerical ocean models can be constructed and parallelised in a commercial cloud computing environment and outlines how performance similar to local high-performance computing can be achieved in commercial cloud computing environments by optimising the modelling environment. Cloud computing can be a useful tool for those who have no available computing resource.
Hide
05 Dec 2017
A 1-Dimensional Ice-Pelagic-Benthic transport model (IPBM) v0.1:
Coupled simulation of ice, water column, and sediment
biogeochemistry
Shamil Yakubov, Philip Wallhead, Elizaveta Protsenko, and Evgeniy Yakushev
Geosci. Model Dev. Discuss.,
2017
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
Aquatic biogeochemical processes can strongly interact, especially in polar regions, with processes occurring in adjacent ice and sediment layers, yet there are few modelling tools to simulate these systems in a fully coupled manner. We have developed a 1D transport model that allows simultaneous simulation of the biogeochemistry of 3 different media: ice, water, and sediments. Description of transportation processes in ice, water, and sediments for both solutes and solids was provided.
Hide
20 Nov 2017
Methods of investigating forecast error sensitivity to ensemble size in
a limited-area convection-permitting ensemble
Ross Noel Bannister, Stefano Migliorini, Alison Clare Rudd, and Laura Hart Baker
Geosci. Model Dev. Discuss.,
2017
Revised manuscript has not been submitted
(discussion: closed, 7 comments)
Short summary
Short summary
An ensemble of weather forecasts (i.e. multiple forecasts) contains useful information that a traditional single forecast does not have. Most existing forecast ensembles though have few members (ensemble too small), meaning that the information that they contain is noisy. This paper shows how more ensemble members can be generated from an existing (small) ensemble, and how the value added by the extra members can be assessed in a quantitative way.
Hide
13 Nov 2017
On Quadruplet Interactions for Ocean Surface Waves
Adhi Susilo, Will Perrie, and Bash Toulany
Geosci. Model Dev. Discuss.,
2017
Preprint retracted
(discussion: closed, 6 comments)
Short summary
Short summary
Solving nonlinear wave-wave interactions with Boltzmann integral requires solving the domain of the integration correctly. While we are working on finding the loci of integration, we have an idea to find the loci with different way, an explicit way. The new method shows better results than the previous one and the algorithm is easy to follow.
Hide
10 Nov 2017
Adaptation of the meteorological model Meso-NH to laboratory
experiments: implementations and validation
Jeanne Colin, Christine Lac, Valéry Massion, and Alexandre Paci
Geosci. Model Dev. Discuss.,
2017
Preprint withdrawn
(discussion: closed, 5 comments)
Short summary
Short summary
The meteorological model Meso-NH is adapted in order to be run in DNS mode (Direct Numerical Simulation) to represent atmospheric flows generated in laboratory. The implementations we performed are validated against exact solutions and experimental data. Thus, Meso-NH can now be used as a complement to laboratory experiments, to complete and/or extend the data. The ability to run it in DNS also brings new prospects as it offers a new framework to test parametrizations of fine-scale processes.
Hide
06 Nov 2017
Evaluating a fire smoke simulation algorithm in the National Air Quality
Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign
Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
In this study, a system accounting for fire emissions in a chemical transport model is described. The focus of this work is to qualitatively evaluate the system's capability to capture fire signals identified by multiple observation data sets. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods.
Hide
16 Oct 2017
Development and calibration of a global hydrological model for integrated assessment modeling
Tingju Zhu, Petra Döll, Hannes Müller Schmied, Claudia Ringler, and Mark W. Rosegrant
Geosci. Model Dev. Discuss.,
2017
Revised manuscript has not been submitted
(discussion: closed, 6 comments)
Short summary
Short summary
The global hydrological model IGHM was developed to simulate water availability over global land areas month by month. The simulated water availability is for analyzing irrigation water supply and crop production in a global water and food projections model, IMPACT. Water availability simulated by another global hydrological model, WGHM, was used to determine parameter values in IGHM. This paper describes the structure of IGHM, the method of its parameter determination, and its performance.
Hide
22 Sep 2017
The degree of freedom for signal assessment of measurement networks for joint chemical state and emission analysis
Xueran Wu, Hendrik Elbern, and Birgit Jacob
Geosci. Model Dev. Discuss.,
2017
Preprint withdrawn
(discussion: closed, 9 comments)
Short summary
Short summary
It is novel that the tangent linear form of the atmospheric transport model was extended by emissions under the assumption that emissions preserve the invariant diurnal profiles. Base on the Kalman smoother, the degree of freedom for signal and several metrics is derived as the criterion to evaluate the potential improvement of model states. Besides, sensitivities of observations was formulated by seeking the fastest directions of the perturbation ratio between initial states and observations.
Hide
04 Aug 2017
Importance of the advection scheme for the simulation of water isotopes over Antarctica by general circulation models: a case study with LMDZ-iso (LMDZ5a revision 1750)
Alexandre Cauquoin and Camille Risi
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
AGCMs are known to have a warm and isotopically enriched bias over Antarctica. We test here the hypothesis that these biases are consequences of a too diffusive advection. We show here that a good representation of the advection, especially on the horizontal, is very important to reduce the bias in the isotopic contents of precipitation above this area and to improve the modelled water isotopes – temperature relationship, essential when using GCMs for paleoclimate applications.
Hide
13 Jul 2017
A map of global peatland distribution created using machine
learning for use in terrestrial ecosystem and earth system models
Yuanqiao Wu, Ed Chan, Joe R. Melton, and Diana L. Verseghy
Geosci. Model Dev. Discuss.,
2017
Preprint withdrawn
(discussion: closed, 6 comments)
Short summary
Short summary
Peatlands are an important component of the carbon cycle that is expected to change under climate change, but accurate information on the global distribution of peatlands is presently unavailable. We use a machine-learning method to create a map of global peatland extent suitable for use in an Earth system model. For areas where data exists we find excellent agreement with observations and our method has greater skill than solely using soil datasets to estimate peatland coverage.
Hide
27 Jun 2017
ShellTrace v1.0 – A new approach for modelling growth and trace element uptake in marine bivalve shells: Model verification on pacific oyster shells (Crassostrea gigas)
Niels J. de Winter
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 3 comments)
Short summary
Short summary
Bivalves grow by expanding their shells incrementally and record environmental conditions in the chemistry of their carbonate. To reconstruct these conditions, it is important to constrain the growth and trace element uptake rates in these bivalve shells. The present study models the development and chemical composition of the shells of bivalves based on XRF mapping of shell cross sections and allows changes in trace element uptake rates to be interpreted to reconstruct palaeoenvironment.
Hide
23 May 2017
Correct boundary conditions for DNS models of
nonlinear acoustic-gravity waves forced by
atmospheric pressure variations
Yuliya Kurdyaeva, Sergey Kshevetskii, Nikolay Gavrilov, and Sergey Kulichkov
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Various meteorological phenomena generate acoustic-gravity waves in the atmosphere and cause wave variations of atmospheric pressure. There are networks of microbarographs, which record pressure variations on the Earth's surface. The hydrodynamic problem of propagation of waves in the atmosphere from pressure variations on the Earth's surface is formulated. The problem wellposedness is proved. A supercomputer program for simulation of waves from pressure variations is developed and applied.
Hide
17 May 2017
Studying the Impact of Radioactive Charging on the Microphysical Evolution and Transport of Radioactive Aerosols with the TOMAS-RC v1 framework
Petros Vasilakos, Yong-Ηa Kim, Jeffrey R. Pierce, Sotira Yiacoumi, Costas Tsouris, and Athanasios Nenes
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Radioactive charging can significantly impact the way radioactive aerosols behave, and as a result their lifetime, but such effects are neglected in predictive model studies of radioactive plumes. We extend a well-established model that simulates the evolution of atmospheric particulate matter to account for radioactive charging effects in an accurate and computationally efficient way. It is shown that radioactivity can strongly impact the deposition patterns of aerosol.
Hide
15 Mar 2017
Numerical simulations of glacier evolution performed using
flow-line models of varying complexity
Antonija Rimac, Sharon van Geffen, and Johannes Oerlemans
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
The main aim of this paper is to use explicit glacier flow-line models of a different complexity to analyse the glacier length and volume evolution, and to disentangle climatic signals from geometric effects. We compare length and volume evolution of a synthetically designed glaciers simulated using Full-Stokes model based on Elmer/Ice code with the results obtained using SIA model.
Hide
13 Mar 2017
Neodymium isotopes in the ocean model of the Community Earth System Model (CESM1.3)
Sifan Gu, Zhengyu Liu, Alexandra Jahn, Johannes Rempfer, Jiaxu Zhang, and Fortunat Joos
Geosci. Model Dev. Discuss.,
2017
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
This paper is the documentation of the implementation of neodymium (Nd) isotopes in the ocean model of CESM. Our model can simulate both Nd concentration and Nd isotope ratio in good agreement with observations. Our Nd-enabled ocean model makes it possible for direct model-data comparison in paleoceanographic studies, which can help to resolve some uncertainties and controversies in our understanding of past ocean evolution. Therefore, our model provides a useful tool for paleoclimate studies.
Hide
09 Mar 2017
An Operational Thermodynamic-Dynamic Model for the Coastal Labrador Sea Ice Melt Season
Ian D. Turnbull and Rocky S. Taylor
Geosci. Model Dev. Discuss.,
2017
Preprint withdrawn
(discussion: closed, 4 comments)
Short summary
Short summary
We developed a model to forecast the timing of the seasonal break-up of coastal Labrador land-fast ice in order to aid offshore operators in the region with their planning and decision-making process. The model additionally provides shorter-term (several days) ice drift forecasts for the operators. Our model can forecast the break-up of the land-fast ice at specific locations along the Labrador coast accurately to within hours to days when initialized up to a month in advance.
Hide
23 Nov 2016
The FuGas 2.1 framework for atmosphere-ocean coupling in
geoscientific models: improving estimates of the solubilities and
fluxes of greenhouse gases and aerosols
Vasco M. N. C. S. Vieira, Pavel Jurus, Emanuela Clementi, Heidi Pettersson, and Marcos Mateus
Geosci. Model Dev. Discuss.,
2016
Revised manuscript has not been submitted
(discussion: closed, 7 comments)
16 Nov 2016
A multi-level canopy radiative transfer scheme for ORCHIDEE
(SVN r2566), based on a domain-averaged structure factor
Matthew J. McGrath, James Ryder, Bernard Pinty, Juliane Otto, Kim Naudts, Aude Valade, Yiying Chen, James Weedon, and Sebastiaan Luyssaert
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
16 Nov 2016
An intercomparison of Large-Eddy Simulations of the Martian daytime convective boundary layer
Tanguy Bertrand, Aymeric Spiga, Scot Rafkin, Arnaud Colaitis, François Forget, and Ehouarn Millour
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We compare the results of two numerical models which simulate the Martian atmospheric turbulence in the first km above the surface, using for both similar forcings. This intercomparison is a fruitful way to evaluate the models' predictions and to indicate possible areas of improvement, thus preparing for future martian missions. Although the model predict similar evolution of the turbulence in the lower atmosphere, the intensity of the processes differ by a factor of 1.5–2.
Hide
08 Nov 2016
Description and evaluation of REFIST v1.0: a regional greenhouse gas flux inversion system in Canada
Elton Chan, Douglas Chan, Misa Ishizawa, Felix Vogel, Jerome Brioude, Andy Delcloo, Yuehua Wu, and Baisuo Jin
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
The main objective of this study is to examine the impacts of errors introduced by different components in our newly developed inversion system on flux estimates with a series of controlled experiments. It is very critical for any inversion system to be fully evaluated prior to applying to real observations. As demonstrated, the results can be very sensitive to the model setup and region. It is not reasonable to expect realistic results can always be obtained using the same approach.
Hide
20 Oct 2016
eWaterCycle: a hyper-resolution global hydrological model for river
discharge forecasts made from open source pre-existing components
Rolf Hut, Niels Drost, Maarten van Meersbergen, Edwin Sutanudjaja, Marc Bierkens, and Nick van de Giesen
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
A system that predicts the amount of water flowing in each river on earth, 9 days ahead, is build using existing parts of open source computer code build by different researchers in other projects.
The glue between all pre-existing parts are all open interfaces which means that the pieces system click together like a house of LEGOs. It is easy to remove a piece (a brick) and replace it with another, improved, piece.
The resulting predictions are available online at forecast.ewatercycle.org
Hide
29 Sep 2016
The downscaling and adjustment method ADAMONT
v1.0 for climate projections in mountainous regions
applicable to energy balance land surface models
Deborah Verfaillie, Michel Déqué, Samuel Morin, and Matthieu Lafaysse
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 7 comments)
21 Sep 2016
Technical Note: Improving the computational efficiency of sparse matrix multiplication in linear atmospheric inverse problems
Vineet Yadav and Anna M. Michalak
Geosci. Model Dev. Discuss.,
2016
Revised manuscript has not been submitted
(discussion: closed, 2 comments)
Short summary
Short summary
Multiplication of two matrices that consists of few non-zero entries is a fundamental operation in problems that involve estimation of greenhouse gas fluxes from atmospheric measurements. To increase computational efficiency of estimating these quantities, modification of the standard matrix multiplication algorithm for multiplying these matrices is proposed in this research.
Hide
19 Aug 2016
Development of CarbonTracker Europe-CH
– Part 1: system set-up and sensitivity analyses
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, and Wouter Peters
Geosci. Model Dev. Discuss.,
2016
Revised manuscript has not been submitted
(discussion: closed, 6 comments)
Short summary
Short summary
In this study, we found that methane emission estimates, driven by the CTE-CH
model, depend on model setups and inputs, especially for regional estimates. An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role. The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
Hide
19 Aug 2016
Joint CO
state and flux estimation with the 4D-Var system EURAD-IM
Johannes Klimpt, Elmar Friese, and Hendrik Elbern
Geosci. Model Dev. Discuss.,
2016
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Atmospheric inversions optimize surface-atmosphere CO
fluxes using CO
concentration observations and atmospheric transport models. This study optimizes additionally the atmospheric initial concentration of CO
jointly with the fluxes. Artificial generated observations are used to estimate limits and benefits of the used inversion method.
Uncertainty of analyzed CO
fluxes can be reduced with the joint optimization of fluxes and the atmospheric CO
concentration.
Hide
15 Aug 2016
Establishing relationship between measured and predicted soil water characteristics using SOILWAT model in three agro-ecological zones of Nigeria
OrevaOghene Aliku and Suarau O. Oshunsanya
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 7 comments)
29 Jul 2016
Exploring global surface temperature pattern scaling methodologies and assumptions from a CMIP5 model ensemble
Cary Lynch, Corinne Hartin, Ben Bond-Lamberty, and Ben Kravitz
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
Pattern scaling is used to explore uncertainty in future forcing scenarios and assess local climate sensitivity to global temperature change. This paper examines the two dominant pattern scaling methods using a multi-model ensemble with two future socio-economic storylines. We find that high latitudes show the strongest sensitivity to global temperature change and that the simple least squared regression approach to generation of patterns is a better fit to projected global temperature.
Hide
05 Jul 2016
Fundamentals of Data Assimilation
Peter Rayner, Anna M. Michalak, and Frédéric Chevallier
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly. We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs. We show here that the many methods for doing this are special cases of underlying statistics. This provides a unified way of comparing and contrasting such methods.
Hide
21 Jun 2016
Microphysics parameterization sensitivity of the WRF Model version 3.1.7 to extreme precipitation: evaluation of the 1997 New Year’s flood of California
Elcin Tan
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
California is vulnerable to extreme precipitation, which occurs due to atmospheric rivers. This study is an attempt to evaluate the performance of the WRF Model for the extreme precipitation event that caused the 1997 New Year’s flood in California. The results show that the accuracy of the WRF Model is much higher for the 72-hr total basin-averaged evaluations than for the hourly and point-wise comparisons. The Thompson Scheme indicates more trustworthy results than others, with a 3.1 % error.
Hide
01 Jun 2016
A robust gap-filling method for Net Ecosystem Exchange based on Cahn–Hilliard inpainting
Yufeng He and Mark Rayment
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 5 comments)
Short summary
Short summary
We introduce a new method based on image inpainting to gap-filling the signal of Net Ecosystem Exchange.It is more intuitive, compact and highly comparable with a commonly-used method. Results showed a similar level of gap-filling errors between the two methods across twelve datasets. The gap-filling performance was improved from both methods when the original datasets were de-noised, implying that the noise or random structures embedded in signal determines the uncertainty level of gap-filling.
Hide
17 May 2016
AMOC-emulator M-AMOC1.0 for uncertainty assessment of future projections
Pepijn Bakker and Andreas Schmittner
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 11 comments)
Short summary
Short summary
We present an AMOC-emulator framework consisting of a box model and a statistical tuning methodology that allows us to mimic the behaviour of the Atlantic Meridional Overturning Circulation (AMOC) in any complex global climate model. The simplicity of the AMOC-emulator allows us to run large numbers of simulations, test the importance of a range of uncertainties and thus provide probabilistic AMOC projections driven by future climate change including the partial melt of the Greenland Ice Sheet.
Hide
22 Mar 2016
Comparison of the glacial isostatic adjustment behaviour in glacially induced fault models
Rebekka Steffen, Holger Steffen, and Patrick Wu
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We evaluate two model approaches intended to model glacially induced fault movements. We focus entirely on the glacial isostatic adjustment behaviour of those approaches and compare them with respect to displacement and stress changes. The results show that only one approach is able to model the glacial isostatic adjustment process correctly.
Hide
04 Mar 2016
Empirical Bayes approach to climate model calibration
Charles S. Jackson and Gabriel Huerta
Geosci. Model Dev. Discuss.,
2016
Preprint withdrawn
(discussion: closed, 3 comments)
Short summary
Short summary
Climate data is highly correlated which can make it difficult from a statistical perspective to quantify the significance of differences that arise between a model and observations. Here we explore a common device in Bayesian inference for assessing the statistical significance of a fit between a model and data and suggest how this approach may be applied to the calibration of a climate model.
Hide
15 Feb 2016
A near-global eddy-resolving OGCM for climate studies
X. Zhang, P. R. Oke, M. Feng, M. A. Chamberlain, J. A. Church, D. Monselesan, C. Sun, R. J. Matear, A. Schiller, and R. Fiedler
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 9 comments)
Short summary
Short summary
Eddy-resolving global ocean models are highly desired, but expensive to run, and also subject to many problems including drift. Here we modified a near-global eddy-resolving OGCM for climate studies with some novel strategies. We demonstrated that the historical experiment driven by Japanese atmospheric reanalysis product, didn't have significant drifts, and also provided an eddy-resolving simulation of the global ocean over 1979–2014. Our experiences can be helpful to other modelling groups.
Hide
11 Feb 2016
ClimateLearn: A machine-learning approach for climate prediction using network measures
Qing Yi Feng, Ruggero Vasile, Marc Segond, Avi Gozolchiani, Yang Wang, Markus Abel, Shilomo Havlin, Armin Bunde, and Henk A. Dijkstra
Geosci. Model Dev. Discuss.,
2016
Revised manuscript not accepted
(discussion: closed, 4 comments)
Short summary
Short summary
We present the toolbox ClimateLearn to tackle problems in climate prediction using machine learning techniques and climate network analysis. Because spatial temporal information on climate variability can be efficiently represented by complex network measures, such data are considered here as input to the machine-learning algorithms. As an example, the toolbox is applied to the prediction of the occurrence and the development of El Niño in the equatorial Pacific.
Hide
15 Jan 2016
Spatio-temporal variability in N
O emissions from a tea-planted soil in subtropical central China
X. L. Liu, X. Q. Fu, Y. Li, J. L. Shen, Y. Wang, G. H. Zou, Y. Z. Wu, Q. M. Ma, D. Chen, C. Wang, R. L. Xiao, and J. S. Wu
Geosci. Model Dev. Discuss.,
2016
Preprint withdrawn
(discussion: closed, 7 comments)
Short summary
Short summary
We examined the spatio-temporal variability in N2O emissions from a tea-planted soil. It has two highlights: i) that the size of large static chambers used for long-term observations should be no less than 0.4m and the time interval for gas sampling should be constrained to approximately 5 days; ii) that the predictions of the spatio-temporal kriging interpolations for the total N2O were approximately 25% higher than the results in long-term observation.
Hide
10 Dec 2015
An integrated Dissolved Organic Carbon Dynamics Model (DOCDM 1.0): model development and a case study in the Alaskan Yukon River Basin
X. Lu and Q. Zhuang
Geosci. Model Dev. Discuss., 8, 10411–10454,
2015
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
13 Nov 2015
Impacts of air–sea interactions on regional air quality predictions using WRF/Chem v3.6.1 coupled with ROMS v3.7: southeastern US example
J. He, R. He, and Y. Zhang
Geosci. Model Dev. Discuss., 8, 9965–10009,
2015
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
WRF/Chem simulations are performed to understand the impacts of cumulus parameterizations and air-sea interactions on coastal air quality. The use of different cumulus parameterizations gives different vertical mixing and wet scavenging. The use of different air-sea interaction treatments also gives different predictions of O3 and PM2.5 by up to 17.3 ppb and 7.9 μg m-3, respectively. WRF/Chem-ROMS improves model predictions, illustrating the benefits and needs of using coupled atmospheric-ocean
Hide
29 Oct 2015
InMAP: a new model for air pollution interventions
C. W. Tessum, J. D. Hill, and J. D. Marshall
Geosci. Model Dev. Discuss., 8, 9281–9321,
2015
Revised manuscript not accepted
(discussion: closed, 9 comments)
Short summary
Short summary
We develop InMAP (Intervention Model for Air Pollution), an Eulerian model which estimates changes in primary and secondary fine particle (PM2.5) concentrations attributable to annual changes in precursor emissions. InMAP uses a variable resolution grid to focus on human exposures by employing higher spatial resolution in urban areas and lower spatial resolution in rural and remote locations and in the upper atmosphere; and by directly calculating steady-state, annual average concentrations.
Hide
08 Oct 2015
The infrastructure MESSy submodels GRID (v1.0) and IMPORT (v1.0)
A. Kerkweg and P. Jöckel
Geosci. Model Dev. Discuss., 8, 8607–8633,
2015
Revised manuscript not accepted
(discussion: closed, 7 comments)
28 Aug 2015
DasPy 1.0 – the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., 8, 7395–7444,
2015
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
Hide
13 Aug 2015
DebrisInterMixing-2.3: a Finite Volume solver for three dimensional debris flow simulations based on a single calibration parameter – Part 2: Model validation
A. von Boetticher, J. M. Turowski, B. W. McArdell, D. Rickenmann, M. Hürlimann, C. Scheidl, and J. W. Kirchner
Geosci. Model Dev. Discuss., 8, 6379–6415,
2015
Preprint withdrawn
(discussion: closed, 2 comments)
13 Aug 2015
WRF4G: WRF experiment management made simple
V. Fernández-Quiruelas, J. Fernández, A. S. Cofiño, C. Blanco, M. García-Díez, M. Magariño, L. Fita, and J. M. Gutiérrez
Geosci. Model Dev. Discuss., 8, 6551–6582,
2015
Revised manuscript has not been submitted
(discussion: closed, 9 comments)
21 Jul 2015
Experiments on sensitivity of meridional circulation and ozone flux to parameterizations of orographic gravity waves and QBO phases in a general circulation model of the middle atmosphere
A. V. Koval, N. M. Gavrilov, A. I. Pogoreltsev, and E. N. Savenkova
Geosci. Model Dev. Discuss., 8, 5643–5670,
2015
Revised manuscript not accepted
(discussion: closed, 6 comments)
Short summary
Short summary
We implemented improved parameterizations of orographic gravity wave dynamical and thermal effects and QBO flows into a general circulation model and study the sensitivity of meridional circulation and vertical velocity to the parameterizations at altitudes up to 100km. Stationary OGW effects gives changes up to 40% in the meridional velocity and associated ozone fluxes in the stratosphere. Transitions from the easterly to westerly QBO phase may alter meridional and vertical velocities by 60%.
Hide
02 Jul 2015
A simplified gross primary production and evapotranspiration model for boreal coniferous forests – is a generic calibration sufficient?
F. Minunno, M. Peltoniemi, S. Launiainen, M. Aurela, A. Lindroth, A. Lohila, I. Mammarella, K. Minkkinen, and A. Mäkelä
Geosci. Model Dev. Discuss., 8, 5089–5137,
2015
Revised manuscript not accepted
(discussion: closed, 9 comments)
22 Jun 2015
Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO
fertilisation and of water stress in continental interiors
S. O. Los
Geosci. Model Dev. Discuss., 8, 4781–4821,
2015
Revised manuscript not accepted
(discussion: closed, 7 comments)
Short summary
Short summary
A model was developed to simulate spatio-temporal variations in vegetation in response to temperature, precipitation and atmospheric CO2 levels. The model reproduced variations in vegetation well; it showed a greater response to drought stress in N Hemisphere continents than previous implementations and showed a decline in vegetation during the US dust bowl (1930s and 1950s) and the drought of the century in the Sahel (1984). Vegetation greenness increased in response to atmospheric CO2 levels.
Hide
12 Jun 2015
Importance of bitwise identical reproducibility in earth system modeling and status report
L. Liu, S. Peng, C. Zhang, R. Li, B. Wang, C. Sun, Q. Liu, L. Dong, L. Li, Y. Shi, Y. He, W. Zhao, and G. Yang
Geosci. Model Dev. Discuss., 8, 4375–4400,
2015
Revised manuscript has not been submitted
(discussion: closed, 5 comments)
09 Mar 2015
Matching soil grid unit resolutions with polygon unit scales for DNDC modelling of regional SOC pool
H. D. Zhang, D. S. Yu, Y. L. Ni, L. M. Zhang, and X. Z. Shi
Geosci. Model Dev. Discuss., 8, 2653–2689,
2015
Revised manuscript not accepted
(discussion: closed, 7 comments)
Short summary
Short summary
Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation by DeNitrification–DeComposition (DNDC) process-based model as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units. Both format soil units were used for regional SOC pool simulation with DNDC model, to determine an optimal raster resolution of grid simulation units.
Hide
04 Mar 2015
Enhancement for bitwise identical reproducibility of Earth system modeling on the C-Coupler platform
L. Liu, R. Li, C. Zhang, G. Yang, B. Wang, and L. Dong
Geosci. Model Dev. Discuss., 8, 2403–2435,
2015
Revised manuscript not accepted
(discussion: closed, 5 comments)
18 Dec 2014
On the wind stress formulation over shallow waters in atmospheric models
P. A. Jiménez and J. Dudhia
Geosci. Model Dev. Discuss., 7, 9063–9077,
2014
Revised manuscript not accepted
(discussion: closed, 18 comments)
Short summary
Short summary
In spite of the substantial observational evidence supporting a higher drag over shallow waters than over the open ocean, regional and global models widely use a single formulation valid for the open ocean. Results of this work indicate that adding the extra drag is necessary to reconcile model results with long term observations of the wind profile within the first 100 m of the atmosphere, being the first modeling evidence supporting the reported added drag over shallow waters.
Hide
12 Dec 2014
Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme
J. Mielikainen, B. Huang, and A. H.-L. Huang
Geosci. Model Dev. Discuss., 7, 8941–8973,
2014
Revised manuscript has not been submitted
(discussion: closed, 1 comment)
22 Oct 2014
A user-friendly forest model with a multiplicative mathematical structure: a Bayesian approach to calibration
M. Bagnara, M. Van Oijen, D. Cameron, D. Gianelle, F. Magnani, and M. Sottocornola
Geosci. Model Dev. Discuss., 7, 6997–7031,
2014
Revised manuscript not accepted
(discussion: closed, 5 comments)
17 Sep 2014
Sensitivity analysis of PBL schemes by comparing WRF model and experimental data
A. Balzarini, F. Angelini, L. Ferrero, M. Moscatelli, M. G. Perrone, G. Pirovano, G. M. Riva, G. Sangiorgi, A. M. Toppetti, G. P. Gobbi, and E. Bolzacchini
Geosci. Model Dev. Discuss., 7, 6133–6171,
2014
Revised manuscript has not been submitted
(discussion: closed, 4 comments)
11 Sep 2014
Integration of Geographic Information System frameworks into domain discretisation and meshing processes for geophysical models
A. S. Candy, A. Avdis, J. Hill, G. J. Gorman, and M. D. Piggott
Geosci. Model Dev. Discuss., 7, 5993–6060,
2014
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
17 Jul 2014
Enhancing reproducibility of numerical simulation result on the C-Coupler platform
L. Liu, R. Li, C. Zhang, G. Yang, and B. Wang
Geosci. Model Dev. Discuss., 7, 4429–4461,
2014
Revised manuscript not accepted
(discussion: closed, 7 comments)
26 Jun 2014
Development and evaluation of a hydrostatic dynamical core using the spectral element/discontinuous Galerkin methods
S.-J. Choi and F. X. Giraldo
Geosci. Model Dev. Discuss., 7, 4119–4151,
2014
Preprint withdrawn
(discussion: closed, 4 comments)
11 Jun 2014
Parameters sensitivity analysis for a~crop growth model applied to winter wheat in the Huanghuaihai Plain in China
M. Liu, B. He, A. Lü, L. Zhou, and J. Wu
Geosci. Model Dev. Discuss., 7, 3867–3888,
2014
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
19 May 2014
Homogeneized modeling of mineral dust emissions over Europe and Africa using the CHIMERE model
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., 7, 3441–3480,
2014
Revised manuscript not accepted
(discussion: closed, 3 comments)
28 Apr 2014
Towards a representation of halogen chemistry within volcanic plumes in a chemistry transport model
L. Grellier, V. Marécal, B. Josse, P. D. Hamer, T. J. Roberts, A. Aiuppa, and M. Pirre
Geosci. Model Dev. Discuss., 7, 2581–2650,
2014
Revised manuscript not accepted
(discussion: closed, 4 comments)
11 Apr 2014
An improved coupling model for water flow, sediment transport and bed evolution (CASFE v.1)
S. He, W. Liu, X. Li, and C. Ouyang
Geosci. Model Dev. Discuss., 7, 2429–2454,
2014
Revised manuscript not accepted
(discussion: closed, 6 comments)
18 Mar 2014
A linear algorithm for solving non-linear isothermal ice-shelf equations
A. Sargent and J. L. Fastook
Geosci. Model Dev. Discuss., 7, 1829–1864,
2014
Revised manuscript has not been submitted
(discussion: closed, 5 comments)
14 Mar 2014
Explicit planktic calcifiers in the University of Victoria Earth System Climate Model
K. F. Kvale, K. J. Meissner, D. P. Keller, M. Eby, and A. Schmittner
Geosci. Model Dev. Discuss., 7, 1709–1758,
2014
Revised manuscript not accepted
(discussion: closed, 3 comments)
24 Feb 2014
A cusp catastrophe model for alluvial channel regime and classification of channel patterns
Y. Xiao, X. J. Shao, and Y. Yang
Geosci. Model Dev. Discuss., 7, 1477–1497,
2014
Revised manuscript not accepted
(discussion: closed, 5 comments)
17 Jan 2014
Three-dimensional phase-field study of crack-seal microstructures – insights from innovative post-processing techniques
K. Ankit, M. Selzer, and B. Nestler
Geosci. Model Dev. Discuss., 7, 631–658,
2014
Revised manuscript not accepted
(discussion: closed, 4 comments)
16 Jan 2014
Simulation of trace gases and aerosols over the Indian domain: evaluation of the WRF-Chem model
M. Michael, A. Yadav, S. N. Tripathi, V. P. Kanawade, A. Gaur, P. Sadavarte, and C. Venkataraman
Geosci. Model Dev. Discuss., 7, 431–482,
2014
Revised manuscript not accepted
(discussion: closed, 4 comments)
19 Dec 2013
Modelling economic and biophysical drivers of agricultural land-use change. Calibration and evaluation of the Nexus Land-Use model over 1961–2006
F. Souty, B. Dorin, T. Brunelle, P. Dumas, and P. Ciais
Geosci. Model Dev. Discuss., 6, 6975–7046,
2013
Revised manuscript has not been submitted
(discussion: closed, 2 comments)
17 Dec 2013
Influences of calibration data length and data period on model parameterization and quantification of terrestrial ecosystem carbon dynamics
Q. Zhu and Q. Zhuang
Geosci. Model Dev. Discuss., 6, 6835–6865,
2013
Revised manuscript not accepted
(discussion: closed, 8 comments)
04 Nov 2013
Are vegetation-specific model parameters required for estimating gross primary production?
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., 6, 5475–5488,
2013
Revised manuscript not accepted
(discussion: closed, 6 comments)
09 Oct 2013
ADISM v.1.0: an adjoint of a thermomechanical ice-sheet model obtained using an algorithmic differentiation tool
J. McGovern, I. Rutt, J. Utke, and T. Murray
Geosci. Model Dev. Discuss., 6, 5251–5288,
2013
Revised manuscript has not been submitted
(discussion: closed, 5 comments)
13 Jul 2013
CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs
C. E. Castro, J. Behrens, and C. Pelties
Geosci. Model Dev. Discuss., 6, 3743–3786,
2013
Revised manuscript not accepted
(discussion: closed, 5 comments)
28 Jun 2013
A coupled two-dimensional hydrodynamic and terrestrial input model to simulate CO
diffusive emissions from lake systems
H. Wu, C. Peng, M. Lucotte, N. Soumis, Y. Gélinas, É. Duchemin, J.-B. Plouhinec, A. Ouellet, and Z. Guo
Geosci. Model Dev. Discuss., 6, 3509–3556,
2013
Revised manuscript not accepted
(discussion: closed, 4 comments)
28 May 2013
Test of validity of a dynamic soil carbon model using data from leaf litter decomposition in a West African tropical forest
G. H. S. Guendehou, J. Liski, M. Tuomi, M. Moudachirou, B. Sinsin, and R. Mäkipää
Geosci. Model Dev. Discuss., 6, 3003–3032,
2013
Revised manuscript has not been submitted
(discussion: closed, 7 comments)
04 Apr 2013
The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model: a pollen production model for regional emission and transport modeling
T. R. Duhl, R. Zhang, A. Guenther, S. H. Chung, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, B. K. Lamb, T. M. VanReken, Y. Zhang, and E. Salathé
Geosci. Model Dev. Discuss., 6, 2325–2368,
2013
Revised manuscript not accepted
(discussion: closed, 7 comments)
06 Feb 2013
One-dimensional simulation of fire injection heights in contrasted meteorological scenarios with PRM and Meso-NH models
S. Strada, S. R. Freitas, C. Mari, K. M. Longo, and R. Paugam
Geosci. Model Dev. Discuss., 6, 721–790,
2013
Preprint withdrawn
(discussion: closed, 3 comments)
22 Jan 2013
Calibration of the Crop model in the Community Land Model
X. Zeng, B. A. Drewniak, and E. M. Constantinescu
Geosci. Model Dev. Discuss., 6, 379–398,
2013
Revised manuscript not accepted
(discussion: closed, 5 comments)
14 Nov 2012
The hybrid Eulerian Lagrangian numerical scheme tested with Chemistry
A. B. Hansen, B. Sørensen, P. Tarning-Andersen, J. H. Christensen, J. Brandt, and E. Kaas
Geosci. Model Dev. Discuss., 5, 3695–3732,
2012
Revised manuscript not accepted
(discussion: closed, 4 comments)
17 Oct 2012
COSTRICE – three model online coupling using OASIS: problems and solutions
H. T. M. Ho, B. Rockel, H. Kapitza, B. Geyer, and E. Meyer
Geosci. Model Dev. Discuss., 5, 3261–3310,
2012
Revised manuscript not accepted
(discussion: closed, 4 comments)
12 Sep 2012
A methodology for estimating seasonal cycles of atmospheric CO
resulting from terrestrial net ecosystem exchange (NEE) fluxes using the Transcom T3L2 pulse-response functions
C. D. Nevison, D. F. Baker, and K. R. Gurney
Geosci. Model Dev. Discuss., 5, 2789–2809,
2012
Revised manuscript not accepted
(discussion: closed, 4 comments)
23 Jul 2012
A simulation study of the ensemble-based data assimilation of satellite-borne lidar aerosol observations
T. T. Sekiyama, T. Y. Tanaka, and T. Miyoshi
Geosci. Model Dev. Discuss., 5, 1877–1947,
2012
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
16 Jul 2012
Activation of the operational ecohydrodynamic model (3-D CEMBS) – the hydrodynamic part
L. Dzierzbicka-Głowacka, J. Jakacki, M. Janecki, and A. Nowicki
Geosci. Model Dev. Discuss., 5, 1851–1875,
2012
Revised manuscript not accepted
(discussion: closed, 6 comments)
24 Oct 2011
Description of EQSAM4: gas-liquid-solid partitioning model for global simulations
S. Metzger, B. Steil, L. Xu, J. E. Penner, and J. Lelieveld
Geosci. Model Dev. Discuss., 4, 2791–2847,
2011
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
28 Sep 2011
Modelling oxygen isotopes in the University of Victoria Earth System Climate Model
C. E. Brennan, A. J. Weaver, M. Eby, and K. J. Meissner
Geosci. Model Dev. Discuss., 4, 2545–2576,
2011
Preprint withdrawn
(discussion: closed, 3 comments)
01 Aug 2011
Application of CMAQ at a hemispheric scale for atmospheric mercury simulations
P. Pongprueksa, C. J. Lin, P. Singhasuk, L. Pan, T. C. Ho, and H. W. Chu
Geosci. Model Dev. Discuss., 4, 1723–1754,
2011
Revised manuscript not accepted
(discussion: closed, 4 comments)
14 Jun 2011
Carbon monoxide as a tracer for tropical troposphere to stratosphere transport in the Chemical Lagrangian Model of the Stratosphere (CLaMS)
R. Pommrich, R. Müller, J.-U. Grooß, P. Konopka, G. Günther, H.-C. Pumphrey, S. Viciani, F. D'Amato, and M. Riese
Geosci. Model Dev. Discuss., 4, 1185–1211,
2011
Revised manuscript not accepted
(discussion: closed, 4 comments)
15 Feb 2011
Ground-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties
V. Sicardi, J. Ortiz, A. Rincón, O. Jorba, M. T. Pay, S. Gassó, and J. M. Baldasano
Geosci. Model Dev. Discuss., 4, 343–384,
2011
Revised manuscript not accepted
(discussion: closed, 5 comments)
15 Feb 2011
An aerosol dynamics model for simulating particle formation and growth in a mixed flow chamber
M. Vesterinen, H. Korhonen, J. Joutsensaari, P. Yli-Pirilä, A. Laaksonen, and K. E. J. Lehtinen
Geosci. Model Dev. Discuss., 4, 385–417,
2011
Revised manuscript has not been submitted
(discussion: closed, 2 comments)
14 Jan 2011
A two-layer flow model to represent ice-ocean interactions beneath Antarctic ice shelves
V. Lee, A. J. Payne, and J. M. Gregory
Geosci. Model Dev. Discuss., 4, 65–136,
2011
Revised manuscript not accepted
(discussion: closed, 4 comments)
13 Sep 2010
Linkage between an advanced air quality model and a mechanistic watershed model
K. Vijayaraghavan, J. Herr, S.-Y. Chen, and E. Knipping
Geosci. Model Dev. Discuss., 3, 1503–1548,
2010
Revised manuscript has not been submitted
(discussion: closed, 3 comments)
01 Jul 2009
Implementation of a new aerosol HAM model within the Weather Research and Forecasting (WRF) modeling system
R. Mashayekhi, P. Irannejad, J. Feichter, and A. A. Bidokhti
Geosci. Model Dev. Discuss., 2, 681–707,
2009
Revised manuscript has not been submitted
(discussion: closed, 4 comments)
17 Mar 2009
Next generation framework for aquatic modeling of the Earth System
B. M. Fekete, W. M. Wollheim, D. Wisser, and C. J. Vörösmarty
Geosci. Model Dev. Discuss., 2, 279–307,
2009
Revised manuscript has not been submitted
(discussion: closed, 4 comments)
11 Mar 2009
Evaluation of the parametrized transport of lead-210 in high-altitude European sites
I. Dombrowski-Etchevers, V.-H. Peuch, B. Josse, and M. Legrand
Geosci. Model Dev. Discuss., 2, 247–278,
2009
Revised manuscript has not been submitted
(discussion: closed, 2 comments)
06 Feb 2009
Derivation of a numerical solution of the 3D coupled velocity field for an ice sheet – ice shelf system, incorporating both full and approximate stress solutions
T. J. Reerink, R. S. W. van de Wal, and P.-P. Borsboom
Geosci. Model Dev. Discuss., 2, 81–158,
2009
Revised manuscript has not been submitted
(discussion: closed, 5 comments)
15 Sep 2008
Historical reconstruction of the Aral Sea shrinking by a full 3-D wetting and drying model ECOSMO
I. Alekseeva and C. Schrum
Geosci. Model Dev. Discuss., 1, 243–283,
2008
Revised manuscript has not been submitted
(discussion: closed, 5 comments)
CC BY 4.0