GMD - Model description paper

GMD - Model description paper
Model description paper
23 Apr 2026
MeteoSaver v1.0: a machine-learning based software for the transcription of historical weather data
Derrick Muheki, Bas Vercruysse, Krishna Kumar Thirukokaranam Chandrasekar, Christophe Verbruggen, Julie M. Birkholz, Koen Hufkens, Hans Verbeeck, Pascal Boeckx, Seppe Lampe, Ed Hawkins, Peter Thorne, Dominique Kankonde Ntumba, Olivier Kapalay Moulasa, and Wim Thiery
Geosci. Model Dev., 19, 3213–3255,
2026
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Archives worldwide host vast records of observed weather data crucial for understanding climate variability. However, most of these records are still in paper form, limiting their use. To address this, we developed MeteoSaver, an open-source tool, to transcribe these records to machine-readable format. Applied to ten handwritten temperature sheets, it achieved a median accuracy of 74 %. This tool offers a promising solution to preserve records from archives and unlock historical weather insights.
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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)
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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.
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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)
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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.
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21 Apr 2026
Landslide-Tsurrogate v1.0: a computationally efficient framework for probabilistic tsunami hazard assessment applied to Mayotte (France)
Cléa Denamiel, Alexis Marboeuf, Anne Mangeney, Anne Le Friant, Marc Peruzzetto, Antoine Lucas, Manuel J. Castro Díaz, and Enrique Fernández-Nieto
Geosci. Model Dev., 19, 3075–3107,
2026
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Landslide-Tsurrogate v1.0 is an open-source Python/MATLAB tool that create surrogate models that replace costly numerical simulations. These models estimate tsunami hazards from submarine landslides in a few seconds. Based on polynomial chaos expansions, they also enable sensitivity analyses, fast probabilistic results, and user-friendly visualization. Tested in Mayotte, Landslide-Tsurrogate v1.0 can be applied to any coastal region.
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20 Apr 2026
The Community Fire Behavior model for coupled fire–atmosphere modeling: implementation in the Unified Forecast System
Pedro A. Jiménez y Muñoz, Maria Frediani, Masih Eghdami, Daniel Rosen, Michael Kavulich, and Timothy W. Juliano
Geosci. Model Dev., 19, 3035–3052,
2026
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We present the Community Fire Behavior model (CFBM) a fire behavior model designed to facilitate coupling to atmospheric models. We describe its implementation in the Unified Forecast System (UFS). Simulations of the Cameron Peak fire allowed us to verify our implementation. Our vision is to foster collaborative development in fire behavior modeling with the ultimate goal of increasing our fundamental understanding of fire science and minimizing the adverse impacts of wildland fires.
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17 Apr 2026
The coupled Southern Ocean–Sea ice–Ice shelf Model (SOSIM v1.0): configuration and evaluation
Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew McC. Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay I. Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
Geosci. Model Dev., 19, 2985–3033,
2026
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We developed a high-resolution computer model to simulate how the ocean, sea ice, and ice shelves interact around Antarctica. This helps us understand their critical role in global climate and sea-level rise. Our model successfully captures essential features like major currents and seasonal ice changes. Despite some remaining biases, it provides a useful tool for predicting future changes in this vital and rapidly evolving region.
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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)
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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.
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16 Apr 2026
MinSIA v1: a lightweight and efficient implementation of the shallow ice approximation
Stefan Hergarten
Geosci. Model Dev., 19, 2903–2917,
2026
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Numerical glacier and ice-sheet models have been widely used in the context of climate change and landform evolution. While simulations of ice flow were numerically expensive for a long time, their performance has recently been boosted to an unprecedented level by machine learning techniques. This paper aims at keeping classical numerics competitive by introducing a novel numerical scheme, which allows for simulations at spatial resolutions of 25 m or even finer on standard desktop PCs.
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16 Apr 2026
RTSEvo v1.0: a retrogressive thaw slump evolution model
Jiwei Xu, Shuping Zhao, Zhuotong Nan, Fujun Niu, and Yaonan Zhang
Geosci. Model Dev., 19, 2919–2943,
2026
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Permafrost is warming, causing more ground collapses known as retrogressive thaw slumps that damage ecosystems and infrastructure. We created a new computer model to predict how these slumps grow and spread over time. By combining satellite data, statistics, and rules that mimic natural erosion, the model can reproduce changes with high accuracy. This helps scientists and planners better forecast future permafrost hazards.
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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)
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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.
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13 Apr 2026
“Norkyst” version 3: the coastal ocean forecasting system for Norway
Kai Håkon Christensen, Jon Albretsen, Lars Asplin, Håvard Guldbrandsen Frøysa, Yvonne Gusdal, Silje Christine Iversen, Mari Fjalstad Jensen, Ingrid Askeland Johnsen, Nils Melsom Kristensen, Pål Næverlid Sævik, Anne Dagrun Sandvik, Magne Simonsen, Jofrid Skarðhamar, Ann Kristin Sperrevik, and Marta Trodahl
Geosci. Model Dev., 19, 2785–2798,
2026
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This paper describes
Norkyst
, the operational coastal ocean forecasting system for mainland Norway, which is now in version 3. The system produces five day forecasts of ocean currents, temperature, salinity, and sea surface height every day, and we also maintain an archive of historical data going back to 2012. We show that the outputs of Norkyst have sufficient quality so that it's intended use as a free public service supporting scientists, ocean managers, and industry is justified.
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13 Apr 2026
High-performance coupled surface-subsurface flow simulation with SERGHEI-SWE-RE
Na Zheng, Zhi Li, Gregor Rickert, Mario Morales-Hernández, Ilhan Özgen-Xian, and Daniel Caviedes-Voullième
Geosci. Model Dev., 19, 2799–2819,
2026
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This study introduces a computer model that simulates water flow both on the land surface and underground, and their interaction. The model can run efficiently on many kinds of computers, and its design lets each part update at its own pace to save time. In the tests performed, the model's results matched those from well-known tools in the field. Overall, the model offers a fast, flexible, and scalable way to study combined surface and groundwater behavior.
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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)
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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.
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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)
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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.
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07 Apr 2026
DEEP-SEAM: an explainable semi-supervised deep learning framework for mineral prospectivity mapping
Zijing Luo, Ehsan Farahbakhsh, Stephen Hore, and R. Dietmar Müller
Geosci. Model Dev., 19, 2593–2625,
2026
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By combining multi-source data with advanced processing techniques, our deep learning model effectively identifies mineralisation patterns despite extremely limited deposit samples, analyses data and validates the geological relevance of its decisions through explainability analysis, providing a universally reliable solution for artificial intelligence-assisted mineral prospectivity mapping.
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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)
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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.
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31 Mar 2026
Advancing crop modeling and data assimilation using AquaCrop v7.2 in NASA's Land Information System Framework v7.5
Gabriëlle J. M. De Lannoy, Louise Busschaert, Michel Bechtold, Niccolò Lanfranco, Shannon de Roos, Zdenko Heyvaert, Martynas Bielinis, Jonas Mortelmans, Samuel A. Scherrer, Maxime Van den Bossche, Sujay Kumar, David M. Mocko, Eric Kemp, Lee Heng, Pasquale Steduto, and Dirk Raes
Geosci. Model Dev., 19, 2551–2575,
2026
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The AquaCrop model has been incorporated into the NASA Land Information System, to advance regional crop growth simulations at any spatial resolution, with a range of different input sources for meteorology, soil and crop parameters. This system also facilitates the assimilation of satellite data to update the crop and water conditions during model simulations. We present three exploratory applications to highlight pathways for future research on regional-scale crop estimation.
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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)
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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.
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26 Mar 2026
Deep learning representation of the aerosol size distribution
Donifan Barahona, Katherine H. Breen, Karoline Block, and Anton Darmenov
Geosci. Model Dev., 19, 2437–2459,
2026
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Particulate matter impacts Earth's radiation, clouds, and human health, but modeling their size is challenging due to computational and observational limits. We developed a machine learning model to predict aerosol size distributions, which accurately replicates advanced models and field measurements.
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26 Mar 2026
The microbial community model MCoM 1.0: a scalable framework for modelling phototroph–heterotrophic interactions in diverse microbial communities
Leonhard Lücken, Michael J. Follows, Jason G. Bragg, and Sinikka T. Lennartz
Geosci. Model Dev., 19, 2461–2477,
2026
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The Microbial Community Model (MCoM) is a flexible biogeochemical modeling framework which resolves a rich set of interactions between photosynthetic and heterotrophic microbes, including cross-feeding, metabolite exchange, and nutrient recycling. As such, it allows to assess community-level effects on elemental turnover emerging from microbial interactions. Its scalability allows to represent both simple pairwise interactions and large, diverse communities.
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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)
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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.
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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)
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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.
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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)
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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.
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20 Mar 2026
sedExnerFoam 2412: a 3D Exner-based sediment transport and morphodynamics model
Matthias Renaud, Cyrille Bonamy, Olivier Bertrand, and Julien Chauchat
Geosci. Model Dev., 19, 2299–2331,
2026
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Sediment transport refers to the displacement of granular materials, such as sand and gravel, under the combined action of gravity and fluid flow. This study presents an open-source numerical model developed to investigate this process, with particular emphasis on the migration of an isolated dune. Beyond this specific application, the model has broad potential, including the analysis of erosion around engineered structures, ripple formation, and the morphological evolution of river systems.
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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)
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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.
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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)
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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.
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16 Mar 2026
Development of the global chemistry-climate coupled model BCC-GEOS-Chem v2.0: improved atmospheric chemistry performance and new capability of chemistry-climate interactions
Ruize Sun, Xiao Lu, Haipeng Lin, Tongwen Wu, Xingpei Ye, Lu Shen, Xuan Wang, Haolin Wang, Jingyu Li, Ni Lu, Jiayin Su, Jie Zhang, Fang Zhang, Xiaoge Xin, Xiong Liu, Xiao Yang, and Lin Zhang
Geosci. Model Dev., 19, 2111–2136,
2026
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We present the development of a global chemistry-climate coupled model BCC-GEOS-Chem v2.0, with improved representation of comprehensive troposphere-stratosphere chemistry and new capability to account for radiative-cloud feedbacks from short-lived climate forcers. The development of the BCC-GEOS-Chem v2.0 provides a useful framework for investigating climate–chemistry interactions and for future projections of global atmospheric chemistry
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16 Mar 2026
The BiogeochemicAl Model for Hypoxic and Benthic Influenced areas: BAMHBI v1.0
Marilaure Grégoire, Luc Vandenbulcke, Séverine Chevalier, Mathurin Choblet, Ilya Drozd, Jean-François Grailet, Evgeny Ivanov, Loïc Macé, Polina Verezemskaya, Haolin Yu, Lauranne Alaerts, Ny Riana Randresihaja, Victor Mangeleer, Guillaume Maertens de Noordhout, Arthur Capet, Catherine Meulders, Anne Mouchet, Guy Munhoven, and Karline Soetaert
Geosci. Model Dev., 19, 2137–2175,
2026
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This paper describes the ocean BiogeochemicAl Model for Hypoxic and Benthic Influenced areas (BAMHBI). BAMHBI is a moderate complexity marine biogeochemical model that describes the cycling of carbon, nitrogen, phosphorus, silicon and oxygen through the marine foodweb. BAMHBI is a stand-alone biogeochemical model that can be coupled to any hydrodynamical model and is particularly appropriate for modelling low oxygen environments and the generation of sulfidic waters.
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11 Mar 2026
CHANS-SD-YRB V1.0: a system dynamics model of the coupled human-natural systems for the Yellow River Basin
Shan Sang, Yan Li, Shuang Zong, Lu Yu, Shuai Wang, Yanxu Liu, Xutong Wu, Shuang Song, Wenwu Zhao, Xuhui Wang, and Bojie Fu
Geosci. Model Dev., 19, 2039–2058,
2026
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Regional coupled human–natural systems models are essential for regional sustainability. We developed a new model, CHANS-SD-YRB, using System Dynamics for the Yellow River Basin in China, which faces severe human-water conflicts. The model links 10 components, including Population, Economy, Energy, Food, Water, Sediment, Land, Carbon, and Climate to simulate basin's key human-natural interactions. The model is applicable for sustainable development through scenario analyses and predictions.
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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)
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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.
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10 Mar 2026
Accumulation-based Runoff and Pluvial Flood Estimation Tool (AccRo v.1.0)
Hannes Leistert, Andreas Hänsler, Max Schmit, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 19, 2023–2037,
2026
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The newly developed model AccRo (Accumulation-based Runoff and Pluvial Flood Estimation Tool) is a computationally efficient method to derive key parameters for estimating pluvial flood hazards. Here, we compare results of AccRo with the data of two hydrodynamic models for different cases. We find that AccRo is able to represent the simulations of the hydrodynamic models in high quality, but with much lower computational effort, making it a valuable tool for assessing pluvial flood hazards.
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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)
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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.
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09 Mar 2026
Implementation of a dry surface layer soil resistance in two contrasting semi-arid sites with SURFEX-ISBA V9.0
Belén Martí, Jannis Groh, Guylaine Canut, and Aaron Boone
Geosci. Model Dev., 19, 1991–2021,
2026
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The characterization of vegetation at two sites proved insufficient to adequately simulate the evapotranspiration. A dry surface layer was implemented in the land surface model SURFEX-ISBA (Externalized Surface-Interactions Soil-Biosphere-Atmosphere) v9.0. It is compared to simulations without a soil resistance. The application to an alfalfa site and a natural grass site in semiarid conditions results in an improvement in the estimation of the latent heat flux. The surface energy budget and the soil and vegetation characteristics are explored in detail.
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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)
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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.
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06 Mar 2026
Assessing seasonal climate predictability using a deep learning application: NN4CAST
Víctor Galván Fraile, Belén Rodríguez-Fonseca, Irene Polo, Marta Martín-Rey, and María N. Moreno-García
Geosci. Model Dev., 19, 1917–1935,
2026
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We present a new deep learning framework designed to assess seasonal climate predictability by identifying the key predictors that influence climate variability across different regions. This tool enhances understanding of how remote areas are connected through climate interactions and providing accurate and explainable seasonal predictions. Our results demonstrate its potential to support more reliable and informed climate services at both regional and global scales.
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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)
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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.
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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)
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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.
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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)
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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.
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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)
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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.
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02 Mar 2026
Improved bathymetry estimates beneath Amundsen Sea ice shelves using a Markov Chain Monte Carlo gravity inversion (GravMCMC, version 1)
Michael J. Field, Emma J. MacKie, Lijing Wang, Atsuhiro Muto, and Niya Shao
Geosci. Model Dev., 19, 1749–1768,
2026
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Short summary
Ice shelves are thinning and losing mass in West Antarctica because of interaction with warm water. The topography of the bedrock beneath the ice shelves is difficult to measure but important for understanding how quickly the ice shelves will melt. This study uses gravity data to infer the bedrock topography beneath the ice shelves. We use statistical methods to create an ensemble of bathymetry models that sample the uncertainty of the assumptions in the problem.
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27 Feb 2026
A Transformer-based agent model of GEOS-Chem v14.2.2 for informative prediction of PM
2.5
and O
levels to future emission scenarios: TGEOS v1.0
Dehao Li, Jianbing Jin, Guoqiang Wang, Mijie Pang, Weihong Zhang, and Hong Liao
Geosci. Model Dev., 19, 1703–1725,
2026
Short summary
Short summary
To support air quality decision-making in future emission scenarios, this study presents an agent model for a classic chemical transport model based on a transformer deep-learning framework. Addressing the long runtimes and input/output limitations of previous approaches, our agent model accurately reproduces simulations of fine particulate matter and ozone, enabling rapid air quality assessment.
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27 Feb 2026
The atmospheric composition component of the ICON modeling framework: ICON-ART version 2025.10
Gholam Ali Hoshyaripour, Andreas Baer, Sascha Bierbauer, Julia Bruckert, Dominik Brunner, Jochen Förstner, Arash Hamzehloo, Valentin Hanft, Corina Keller, Martina Klose, Pankaj Kumar, Patrick Ludwig, Enrico Metzner, Lisa Muth, Andreas Pauling, Nikolas Porz, Maryam Ramezani Ziarani, Thomas Reddmann, Luca Reißig, Roland Ruhnke, Khompat Satitkovitchai, Axel Seifert, Miriam Sinnhuber, Michael Steiner, Stefan Versick, Heike Vogel, Michael Weimer, Sven Werchner, and Corinna Hoose
Geosci. Model Dev., 19, 1645–1681,
2026
Short summary
Short summary
This paper presents recent advances in ICON-ART, a modeling system that simulates atmospheric composition – such as gases and particles – and their interactions with weather and climate. By integrating updated chemistry, emissions, and aerosol processes, ICON-ART enables detailed, scale-spanning simulations. It supports both scientific research and operational forecasts, contributing to improved air quality, weather and climate predictions.
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27 Feb 2026
Advancing ecohydrological modelling: coupling LPJ-GUESS with ParFlow for integrated vegetation and surface-subsurface hydrology simulations
Zitong Jia, Shouzhi Chen, Yongshuo H. Fu, David Martín Belda, David Wårlind, Stefan Olin, Chongyu Xu, and Jing Tang
Geosci. Model Dev., 19, 1727–1747,
2026
Short summary
Short summary
Groundwater sustains vegetation and regulates land-atmosphere exchanges, yet most Earth system models oversimplify its dynamics. Our study develops an integrated framework coupling a dynamic vegetation model with the three-dimensional hydrological model ParFlow to explicitly represent groundwater-vegetation interactions. The results provide evidence that groundwater flow strongly regulates water exchanges and provides a powerful tool to improve simulations of water cycles in Earth system models.
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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.
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26 Feb 2026
Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets
Yijia Sun, Ann M. Fridlind, Israel Silber, Nicole Riemer, and Daniel A. Knopf
Geosci. Model Dev., 19, 1581–1617,
2026
Short summary
Short summary
The role of Arctic clouds in the regional climate remains uncertain due to insufficient understanding of the amount of liquid droplets and ice crystals present in these clouds. An aerosol-cloud model is employed to examine the role of different aerosol types and freezing parameterizations on the number of ice crystals. The choice of freezing parameterization significantly changes the number of ice crystals impacting the interpretation of the evolution and warming effect of Arctic clouds.
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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.
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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.
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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.
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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.
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20 Feb 2026
The Met Office Unified Model Global Atmosphere 8.0 and JULES Global Land 9.0 configurations
Martin Willett, Melissa Brooks, Andrew Bushell, Paul Earnshaw, Samantha Smith, Lorenzo Tomassini, Martin Best, Ian Boutle, Jennifer Brooke, John M. Edwards, Andrew D. Elvidge, Kalli Furtado, Catherine Hardacre, Andrew J. Hartley, Alan J. Hewitt, Ben Johnson, Adrian Lock, Andy Malcolm, Jane Mulcahy, Eike Müller, Ian A. Renfrew, Heather Rumbold, Gabriel G. Rooney, Alistair Sellar, Masashi Ujiie, Annelize van Niekerk, Andy Wiltshire, and Michael Whitall
Geosci. Model Dev., 19, 1473–1517,
2026
Short summary
Short summary
Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of Joint UK Land Environment Simulator (JULES) are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA8GL9, which includes improvements to the representation of convection and other physical processes. GA8GL9 is used for operational weather prediction in the UK and forms the basis for the next GA and GL configuration.
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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.
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17 Feb 2026
FRIDA-Clim v1.0.1: a simple climate model with process-based carbon cycle used in the integrated assessment model FRIDAv2.1
Christopher D. Wells, Lennart Ramme, Chris Smith, Jannes Breier, Adakudlu Muralidhar, Chao Li, Ada Gjermundsen, William Alexander Schoenberg, Benjamin Blanz, and Cecilie Mauritzen
Geosci. Model Dev., 19, 1429–1453,
2026
Short summary
Short summary
Understanding the change in climate that would occur under different future pathways of greenhouse gas emissions and changes in land use is crucial. Here, we develop a new simple climate model to help study this. We reduce the number of inputs so that our model can be connected to a model of the human causes of climate change. This way, we can study the interaction between climate change and society, including climate impacts. Our model broadly agrees with historical observations.
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13 Feb 2026
ConcentrationTracker: Landlab components for tracking material concentrations in sediment
Laurent O. Roberge, Nicole M. Gasparini, Benjamin Campforts, and Gregory E. Tucker
Geosci. Model Dev., 19, 1387–1404,
2026
Short summary
Short summary
Landscape evolution models compute the movement of sediment across landscapes. However, few account for the storage, fate, and transport of sediment properties, such as lithology or geochemistry. We present new Landlab model components that track such properties. Our unit-agnostic approach allows users to define the sediment properties for a wide range of applications (for example, mass of magnetite, volume of quartz, number of zircons, number of
10
Be atoms,
equivalent dose
of luminescence).
Hide
12 Feb 2026
AGILE v0.1: The Open Global Glacier Data Assimilation Framework
Patrick Schmitt, Fabien Maussion, Daniel N. Goldberg, and Philipp Gregor
Geosci. Model Dev., 19, 1301–1319,
2026
Short summary
Short summary
To improve large-scale understanding of glaciers, we developed a new data assimilation method that integrates available observations in a dynamically consistent way, while taking their timestamps into account. It is designed to flexibly include new glacier data as it becomes available. We tested the method with idealized experiments and found promising results in terms of accuracy and efficiency, showing strong potential for real-world applications.
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12 Feb 2026
| Highlight paper
NorESM2–DIAM: a coupled model for investigating global and regional climate-economy interactions
Jenny Bjordal, Anthony A. Smith Jr., Henri Cornec, and Trude Storelvmo
Geosci. Model Dev., 19, 1337–1365,
2026
Short summary
Editorial statement
Short summary
We introduce NorESM2-DIAM (Norwegian Earth System Model version 2-Disaggregated Integrated Assessment Model), a first-of-its-kind tool linking a climate model with a high-resolution economic model to study how climate change, internal variability, and economic activity interact across the world. The model reveals strong regional differences and large annual swings in economic impacts, offers insights for climate policy discussions, and provides a strong foundation for future model development.
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Editorial statement
Earth System Models are highly sophisticated computer models of the physical, chemical and biological processes that make up our planet. They are a key tool in predicting the climate change. Integrated Assessment Models tie physical changes in the climate to economic and social effects. Traditionally, Earth System Models (ESM) and Integrated Assessment Models (IAM) are loosely coupled through a static, unidirectional, asynchronous way. The work presented by this paper develops a novel framework that couples an ESM and a spatially disaggregated IAM in a dynamic, bidirectonal and synchronous way. This work represents a significant advance towards tight, bi-directional coupling between the Earth and Human systems. The tools developed here provide a blueprint for future studies seeking to identify precisely who is affected, where, and when by climate change—an essential step toward designing politically feasible and effective policies.
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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.
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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.
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11 Feb 2026
TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry
Oscar H. Díaz-Ibarra, Samuel G. Frederick, Jeffrey H. Curtis, Zachary D'Aquino, Peter A. Bosler, Lekha Patel, Cosmin Safta, Matthew West, and Nicole Riemer
Geosci. Model Dev., 19, 1281–1299,
2026
Short summary
Short summary
We developed TChem-atm, a new open-source tool for simulating atmospheric chemistry and aerosols. As models become more detailed, traditional methods are too slow. TChem-atm runs on both standard processors and graphics processors, making these simulations faster and more efficient. The tool provides a foundation for next-generation models that improve predictions of air quality and climate.
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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.
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10 Feb 2026
The representation of climate impacts in the FRIDAv2.1 Integrated Assessment Model
Christopher D. Wells, Benjamin Blanz, Lennart Ramme, Jannes Breier, Beniamino Callegari, Adakudlu Muralidhar, Jefferson K. Rajah, Andreas Nicolaidis Lindqvist, Axel E. Eriksson, William Alexander Schoenberg, Alexandre C. Köberle, Lan Wang-Erlandsson, Cecilie Mauritzen, Martin B. Grimeland, and Chris Smith
Geosci. Model Dev., 19, 1229–1260,
2026
Short summary
Short summary
Computer models built to study future developments of human activity and climate change often exclude the impacts of climate change. Here, we include these effects in a new model. We create functions connecting changes in global temperature, carbon dioxide, and sea level to energy supply and demand, food systems, mortality, economic damages, and other important quantities. Including these effects will allow us to explore their impact on future changes in the human and climate realms.
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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.
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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.
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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.
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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.
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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.
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04 Feb 2026
The Western United States Large Forest-Fire Stochastic Simulator (WULFFSS) 1.0: a monthly gridded forest-fire model using interpretable statistics
A. Park Williams, Winslow D. Hansen, Caroline S. Juang, John T. Abatzoglou, Volker C. Radeloff, Bowen Wang, Jazlynn Hall, Jatan Buch, and Gavin D. Madakumbura
Geosci. Model Dev., 19, 1157–1191,
2026
Short summary
Short summary
The new Western United States Large Forest Fire Stochastic Simulator (WULFFSS) is a monthly gridded model to simulate forest fires across the western United States in response to vegetation, topographic, anthropogenic, and climate factors. The model is highly skillful, accounting for over 80 % of the observed variability in annual forest-fire area and capturing observed spatial, intra-annual variations, and trends.
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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.
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03 Feb 2026
LEX v1.6.0: a new large-eddy simulation model in JAX with GPU acceleration and automatic differentiation
Xingyu Zhu, Yongquan Qu, and Xiaoming Shi
Geosci. Model Dev., 19, 1103–1120,
2026
Short summary
Short summary
By using the newly developed Python library JAX, we developed a fast and differentiable large-eddy simulation model, named LEX. Evaluated with a warm bubble case, LEX maintains high accuracy as the Cloud Model 1. With the hardware acceleration and better numerical stability, LEX can be quite faster. To report its differentiability, we further trained a deep learning-based parameterization scheme. The newly trained model can surpass the conventional scheme and get proper forecast results.
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03 Feb 2026
GeoDS (v.1.0): a simple Geographical DownScaling model for long-term precipitation data over complex terrains
Jean-Baptiste Brenner, Aurélien Quiquet, Didier M. Roche, Didier Paillard, and Pradeebane Vaittinada Ayar
Geosci. Model Dev., 19, 1075–1101,
2026
Short summary
Short summary
Due to the limited spatial and temporal coverage of observations, global models are essential tools to study climate. However, long-term climate data at fine spatial scale are difficult to obtain because of elevated computational costs such algorithms involve. This paper presents a simple model based on the description of climate/topography interactions to generate local precipitation fields at low cost. The objective is to provide a flexible and easy to use method for paleoclimate studies.
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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.
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30 Jan 2026
A probabilistic approach to wildfire spread prediction using a denoising diffusion surrogate model
Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn, Rossella Arcucci, Marc Bocquet, and Sibo Cheng
Geosci. Model Dev., 19, 1027–1054,
2026
Short summary
Short summary
We introduce the first denoising diffusion model for wildfire spread prediction, a new kind of generative AI model that learns to simulate fires not just as one fixed outcome, but as a range of possible scenarios. This allows us to capture the inherent uncertainty of wildfire dynamics. Our model produces ensembles of forecasts that reflect physically meaningful distributions of where fire might go next.
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30 Jan 2026
Coastal-Cosmo-Model (CCMv1): a cosmogenic nuclide model for rocky coastlines
Richard S. Jones
Geosci. Model Dev., 19, 989–1005,
2026
Short summary
Short summary
This paper presents a new modelling framework that reconstructs the history of rocky shores using cosmogenic nuclide data. The model can be applied to both eroding and stable coasts, and allows users to test how factors like cliff retreat, down-wearing and sea-level change have shaped coastal landscapes. It provides a flexible tool for exploring long-term coastal evolution across diverse environments.
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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.
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29 Jan 2026
BuRNN (v1.0): a data-driven fire model
Seppe Lampe, Lukas Gudmundsson, Basil Kraft, Stijn Hantson, Douglas Kelley, Vincent Humphrey, Bertrand Le Saux, Emilio Chuvieco, and Wim Thiery
Geosci. Model Dev., 19, 955–988,
2026
Short summary
Short summary
We introduce BuRNN (BUrned area modelling by Recurrent Neural Networks), a model which estimates monthly burned area based on satellite observations and climate, vegetation, and socio-economic data using machine learning. BuRNN outperforms existing process-based fire models, which improves our capabilities of modelling past and future burned areas.
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27 Jan 2026
Global atmospheric hydrogen chemistry and source-sink budget equilibrium simulation with the EMAC v2.55 model
Nic Surawski, Benedikt Steil, Christoph Brühl, Sergey Gromov, Klaus Klingmüller, Anna Martin, Andrea Pozzer, and Jos Lelieveld
Geosci. Model Dev., 19, 911–931,
2026
Short summary
Short summary
Hydrogen usage will likely increase to achieve net zero emission targets. We undertook calculations with an Earth system model using a high-performance computer to explore hydrogen atmospheric dynamics. Simulations with our model yielded highly accurate results at global scale. Correctly representing hydroxyl radicals in the model is a critical requirement for predicting hydrogen concentrations well. Our hydrogen budget is also in very good agreement with bottom-up literature estimates.
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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.
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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.
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26 Jan 2026
Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area
Jishi Zhang, Peter Bogenschutz, Mark Taylor, and Philip Cameron-Smith
Geosci. Model Dev., 19, 795–826,
2026
Short summary
Short summary
We pushed a global cloud-resolving model to a novel 100 m setup over the San Francisco Bay Area using a regionally refined mesh. The model captured fine-scale air motions over complex terrain and coastal regions at large-eddy scales with comprehensive global modeling configuration, enabled by scale-aware turbulence parameterization. Performance tests demonstrated that graphics processing unit (GPU) acceleration make such high-resolution simulations feasible within practical timeframes.
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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.
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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.
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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.
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22 Jan 2026
A modelling system for identification of maize ideotypes, optimal sowing dates and nitrogen fertilization under climate change – PREPCLIM-v1
Mihaela Caian, Catalin Lazar, Petru Neague, Antoanela Dobre, Vlad Amihaesei, Zenaida Chitu, Adrian Irasoc, Andreea Popescu, and George Cizmas
Geosci. Model Dev., 19, 627–645,
2026
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We present the implementation of a new climate-phenology integrated system for adaptation to climate change, using high-resolution scenarios and the Decision Support System for Agrotechnology Transfer crop model, with new modules developed for optimal agromanagement and genotypes identification using a hybrid deterministic/machine learning Genetic-Algorithms method. The system is user-interactive in real time. It has been implemented for South Romania and is applicable and extendable for Europe.
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22 Jan 2026
IPSL-Perm-LandN: improving the IPSL Earth System Model to represent permafrost carbon-nitrogen interactions
Rémi Gaillard, Patricia Cadule, Philippe Peylin, Nicolas Vuichard, and Bertrand Guenet
Geosci. Model Dev., 19, 661–711,
2026
Short summary
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The release of carbon from thawing permafrost soils could amplify future climate warming. However, this feedback is highly uncertain because most Earth system models (ESM) do not represent permafrost carbon. We have improved the Institut Pierre-Simon Laplace ESM by including permafrost physical, carbon and nitrogen processes to better represent Arctic ecosystems. The model more accurately represents past and present permafrost physics and biogeochemistry, paving the way for future projections.
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22 Jan 2026
Toward exascale climate modelling: a python DSL approach to ICON's (icosahedral non-hydrostatic) dynamical core (icon-exclaim v0.2.0)
Anurag Dipankar, Mauro Bianco, Mona Bukenberger, Till Ehrengruber, Nicoletta Farabullini, Oliver Fuhrer, Abishek Gopal, Daniel Hupp, Andreas Jocksch, Samuel Kellerhals, Clarissa A. Kroll, Xavier Lapillonne, Matthieu Leclair, Magdalena Luz, Christoph Müller, Chia Rui Ong, Carlos Osuna, Praveen Pothapakula, Andreas Prein, Matthias Röthlin, William Sawyer, Christoph Schär, Sebastian Schemm, Giacomo Serafini, Hannes Vogt, Ben Weber, Robert C. Jnglin Wills, Nicolas Gruber, and Thomas C. Schulthess
Geosci. Model Dev., 19, 713–729,
2026
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Climate models are becoming more detailed and accurate by simulating weather at scales of just a few kilometers. Simulating at km-scale is computationally demanding requiring powerful supercomputers and efficient code. This work presents a refactored dynamical core of a state-of-the-art climate model using a Python-based approach. The refactored code has passed through a sequence of verification and validation demonstrating its usability in performing km-scale global simulations.
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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
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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.
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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
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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.
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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
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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.
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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
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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.
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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
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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.
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15 Jan 2026
Retrieving atmospheric thermodynamic and hydrometeor profiles using a thermodynamic-constrained Kalman filter 1D-Var framework based on ground-based microwave radiometer
Qi Zhang, Tianmeng Chen, Jianping Guo, Yu Wu, Bin Deng, and Junjie Yan
Geosci. Model Dev., 19, 505–522,
2026
Short summary
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We propose TCKF1D-Var, a thermodynamic-constrained variational framework for ground-based microwave radiometer retrievals. Using virtual potential temperature, a ratio-based cost function, and a microphysics closure, it reduces biases relative to ERA5 and 1D-Var, improves cloud liquid water representation, and enhances heavy rainfall precursors, extending lead times. This approach strengthens continuous profiling and supports high-impact weather nowcasting.
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14 Jan 2026
Advanced modeling of gas chemistry and aerosol dynamics with SSH-aerosol v2.0
Karine Sartelet, Zhizhao Wang, Youngseob Kim, Victor Lannuque, and Florian Couvidat
Geosci. Model Dev., 19, 389–421,
2026
Short summary
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The model simulates the evolution of primary and secondary pollutants via gas-phase chemistry, aerosol dynamics (including ultrafine particles), and intra-particle reactions. It uses a sectional approach for size and composition, includes a wall-loss module, and links gas-phase mechanisms of different complexity to secondary organic aerosol formation. Representation of particle phase composition allows viscosity and non-ideality to be taken into account.
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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
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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.
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13 Jan 2026
This is FRIDA
Cecilie Mauritzen
EGUsphere,
2026
Revised manuscript under review for GMD
(discussion: final response, 4 comments)
Short summary
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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.
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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
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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.
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09 Jan 2026
Development of CAS-ESM_MMF: improving East Asian summer precipitation simulation with a Multiscale Modeling Framework
Guangxing Lin, Wei Liao, Zhaohui Lin, He Zhang, Wenbin Kou, Xiaojie Guo, Zhenghui Xie, Qiu Yang, Chenglai Wu, and Minghua Zhang
Geosci. Model Dev., 19, 327–343,
2026
Short summary
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Traditional climate models struggle to accurately represent storm clouds, leading to large rainfall biases over East Asia. To address this, we used a multiscale modeling framework that embeds a high-resolution cloud model into each grid cell of the Chinese Academy of Sciences Earth System Model. This approach greatly improves the simulation of East Asian precipitation.
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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.
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08 Jan 2026
Modeling supercritical CO
flow and mineralization in reactive host rocks with PFLOTRAN v7.0
Michael Nole, Katherine A. Muller, Glenn Hammond, Xiaoliang He, and Peter Lichtner
Geosci. Model Dev., 19, 289–325,
2026
Short summary
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Subsurface injection of carbon dioxide (CO
) can be used for a variety of purposes including geologic carbon storage and enhanced oil recovery. Recently, CO
injection into reactive host rocks has been explored as a way to transform CO
into dense solid minerals. We present a simulation framework for modeling flow of CO
due to injection and subsequent reactions that take place to mineralize CO
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08 Jan 2026
SWIIFT v0.10: a numerical model of wave-induced sea ice breakup with an energy criterion
Nicolas Guillaume Alexandre Mokus, Véronique Dansereau, Guillaume Boutin, Jean-Pierre Auclair, and Alexandre Tlili
Geosci. Model Dev., 19, 261–288,
2026
Short summary
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Arctic sea ice recedes, and is thus more exposed to waves, which can fracture continuous pack ice into smaller floes. These are more mobile and easier to melt. Ice fracture itself is not well understood, because of harsh field conditions. We propose a novel criterion parametrising this process, and incorporate it into a numerical model that simulates wave propagation. This criterion can be compared to existing ones. We relate our results to lab experiments, and find qualitative agreement.
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07 Jan 2026
Sentinel-1 SAR-based globally distributed co-seismic landslide detection by deep neural networks
Lorenzo Nava, Alessandro Mondini, Kushanav Bhuyan, Chengyong Fang, Oriol Monserrat, Alessandro Novellino, and Filippo Catani
Geosci. Model Dev., 19, 167–185,
2026
Short summary
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This paper presents a framework for landslide rapid detection using radar and deep learning, trained and tested on data from ≈73000 landslides across diverse regions in the world. The method showed high accuracy and rapid response potential regardless of weather and illumination conditions. By overcoming the limits of optical satellite imagery, it offers a powerful tool for timely landslide disaster response, benefiting disaster management and advancing methods for monitoring hazardous terrains.
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06 Jan 2026
Seasonal cycles of the carbon export flux in the ocean: insights from the SISSOMA mechanistic model
Athanasios Kandylas and Andre William Visser
Geosci. Model Dev., 19, 93–113,
2026
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The ocean plays an important role in regulating the Earth's climate by storing excess atmospheric carbon in its interior mainly through the sinking of small organic particles originating from planktonic organisms. Once produced these particles are constantly being transformed (sticking together, breaking into smaller pieces and being consumed by microbes). Here, we try to understand the dynamics of these processes by testing a variety of factors, such as stickiness and water column mixing.
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06 Jan 2026
NoahPy: a differentiable Noah land surface model for simulating permafrost thermo-hydrology
Wenbiao Tian, Hu Yu, Shuping Zhao, Yuhe Cao, Wenjun Yi, Jiwei Xu, and Zhuotong Nan
Geosci. Model Dev., 19, 57–72,
2026
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Accurately predicting how permafrost will thaw with land surface models is a grand challenge in Earth science. We created a new computer model by rebuilding a traditional physics model to work with artificial intelligence. Our results show this new approach is much faster and more reliable for tuning model parameters with data. This provides a better tool to build the next generation of climate models and improve predictions of permafrost's future.
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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
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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.
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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
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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.
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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
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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.
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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
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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.
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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
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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.
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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
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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.
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18 Dec 2025
MITgcm-RN v1.0: modeling the transport and fate of radionuclides released from nuclear power plants wastewater in the global ocean using MITgcm_c65i with the radionuclide module
Mao Mao, Yujuan Wang, Peipei Wu, Shaojian Huang, Zhengcheng Song, and Yanxu Zhang
Geosci. Model Dev., 18, 10169–10183,
2025
Short summary
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This study examines how radionuclides released from nuclear power plants are transported and transformed in the global ocean over time. Using an advanced ocean simulation model, it focuses on radionuclides released during the Fukushima accident and from planned wastewater discharges. The findings show that some radionuclides can travel across the Pacific within a few years and gradually spread to other ocean basins by mid-century, emphasizing potential long-term environmental impacts.
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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.
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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
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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.
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15 Dec 2025
| Highlight paper
Feedback-based sea level rise impact modelling for integrated assessment models with FRISIAv1.0
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
Geosci. Model Dev., 18, 10017–10052,
2025
Short summary
Editorial statement
Short summary
We present FRISIA version 1.0, a model for emulating sea level rise (SLR) and representing SLR impacts and adaptation in integrated assessment models (IAMs). FRISIA includes previously uncaptured coastal socio-economic feedback and a diverse set of impact strains, thereby improving the represenation of SLR impacts in IAMs. Here we describe the baseline behaviour of FRISIA, explore the effects of the additional feedback and showcase the coupling of FRISIA to an IAM.
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Editorial statement
Sea-level rise is a crucial concern, and a central channel through which climate change impacts human and natural systems. The FRISIA model introduced in this paper allows calculating sea-level rise and associated macro-economic damages as a function of climate forcers and socio-economic developments. It is designed to be coupled with other models, such as process-detailed Integrated Assessment Models, and therefore expcted to be of substantial value to the broader scientific community.
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15 Dec 2025
WIce-FOAM 1.0: coupled dynamic and thermodynamic modelling of heterogeneous sea ice and waves using OpenFOAM-v2306
Rutger Marquart, Alberto Alberello, Alfred Bogaers, Francesca De Santi, and Marcello Vichi
Geosci. Model Dev., 18, 10053–10076,
2025
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This study developed a kilometre-scale sea-ice model in OpenFOAM that couples dynamic and thermodynamic processes for two types of ice, solid-like ice floes and fluid-like grease ice, under wave forcing. This model can help to improve data input for large-scale sea-ice models. Results show a linear relationship between the proportion of ice floes in the field and the overall viscosity. Additionally, we found that viscosity responds nonlinearly to the inclusion of thermodynamic sea-ice growth.
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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
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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.
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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.
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11 Dec 2025
DRIVE v1.0: a data-driven framework to estimate road transport emissions and temporal profiles
Daniel Kühbacher, Jia Chen, Patrick Aigner, Mario Ilic, Ingrid Super, and Hugo Denier van der Gon
Geosci. Model Dev., 18, 9967–9990,
2025
Short summary
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We present DRIVE v1.0, a data-driven framework to estimate road transport emissions, their temporal profiles, and the associated uncertainties. The method was applied to the city of Munich, where we present bottom-up emission estimates for the years 2019 to 2022. The estimates are compared against official municipal reports as well as national and European downscaled inventories.
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10 Dec 2025
r.avaflow v4, a multi-purpose landslide simulation framework
Martin Mergili, Hanna Pfeffer, Andreas Kellerer-Pirklbauer, Christian Zangerl, and Shiva P. Pudasaini
Geosci. Model Dev., 18, 9879–9896,
2025
Short summary
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We present a new version of the landslide model r.avaflow. It includes a model where different materials move on top of each other instead of mixing; a model supporting the entire range from block sliding to flowing; a model for slow-moving processes; and an interface for virtual reality visualization. Based on the results for four case studies we conclude that, at the moment, our enhancements are very useful for visualization of landslides for awareness building and environmental education.
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09 Dec 2025
QuadTune version 1: a regional tuner for global atmospheric models
Vincent E. Larson, Zhun Guo, Benjamin A. Stephens, Colin Zarzycki, Gerhard Dikta, Yun Qian, and Shaocheng Xie
Geosci. Model Dev., 18, 9767–9790,
2025
Short summary
Short summary
Global models of the atmosphere contain errors that lead to inaccurate simulations. A software tool ("QuadTune") is presented that attempts to mitigate errors related to suboptimal parameter values. It also displays diagnostic plots that provide hints about where structural errors might lie in the model.
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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.
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05 Dec 2025
UpsFrac v1.0: an open-source software for integrating modelling and upscaling permeability for fractured porous rocks
Tao Chen, Honghao Sheng, Yu Zhang, and Fengxin Kang
Geosci. Model Dev., 18, 9687–9708,
2025
Short summary
Short summary
Understanding fluid flow through fractured porous rocks is crucial for groundwater and geothermal energy management. Existing tools lack integrated workflows. We developed UpsFrac, an open-source software that integrates fracture modeling and permeability upscaling. It handles complex fracture patterns and rock properties. The software enables uncertainty quantification, helping scientists make accurate and efficient predictions for groundwater protection and renewable energy development.
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04 Dec 2025
The glacial systems model (GSM) Version 25G
Lev Tarasov, Benoit S. Lecavalier, Kevin Hank, and David Pollard
Geosci. Model Dev., 18, 9565–9603,
2025
Short summary
Short summary
We document the glacial system model (GSM), a 3D glaciological ice sheet systems model specifically designed for large ensemble modelling in glacial cycle contexts. The model is distinguished by the breadth of relevant processes represented for this context. This ranges from meltwater surface drainage with proglacial lake formation to state-of-the-art subglacial sediment production/transport/deposition. The other key distinguishing design feature is attention to addressing process uncertainties.
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04 Dec 2025
PortUrb: a performance portable, high-order, moist atmospheric large eddy simulation model with variable-friction immersed boundaries
Matthew Norman, Muralikrishnan Gopalakrishnan Meena, Kalyan Gottiparthi, Nicholson Koukpaizan, and Stephen Nichols
Geosci. Model Dev., 18, 9605–9631,
2025
Short summary
Short summary
A new code, portUrb, is described and validated. portUrb is an atmospheric simulation code for turbulent boundary layers including flow through urban areas. The model is coded with an emphasis on robustness, simplicity, readability, portable performance on Graphics Processing Units (GPUs), and rapid prototyping of surrogate models through an ensemble capability where many different configurations can be run simultaneously to explore parameter choices.
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03 Dec 2025
SnapWave: fast, implicit wave transformation from offshore to nearshore
Dano Roelvink, Maarten van Ormondt, Johan Reyns, and Marlies van der Lugt
Geosci. Model Dev., 18, 9469–9495,
2025
Short summary
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Existing wave models are often quite heavy for coastal applications. The SnapWave model simulates wave refraction (turning towards the coast), shoaling (steepening up) and dissipation (loss of energy by friction and wave breaking), and it uses an efficient computational mesh that you can refine where you need it. In the paper we show that the model can reproduce time series of waves anywhere in the world, using a depth map and wave data from a global model (ERA5) or a local wave buoy.
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02 Dec 2025
Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0
Ian R. B. Reeves, Andrew D. Ashton, Erika E. Lentz, Christopher R. Sherwood, Davina L. Passeri, and Sara L. Zeigler
Geosci. Model Dev., 18, 9319–9348,
2025
Short summary
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We describe a new model of coastal barrier ecogeomorphic change that operates over spatiotemporal scales congruous with effective management practices, incorporates key ecogeomorphic feedbacks, and provides probabilistic projections. The model skillfully captures important barrier dynamics through robust data integration and calibration of relatively simple model parameterizations, and can be used to understand and predict when, where, and how barriers evolve to inform decision-making processes.
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01 Dec 2025
Hybrid Lake Model (HyLake) v1.0: unifying deep learning and physical principles for simulating lake-atmosphere interactions
Yuan He and Xiaofan Yang
Geosci. Model Dev., 18, 9257–9277,
2025
Short summary
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This study introduces HyLake, a hybrid lake model that embeds a deep-learning surrogate for the water temperature module within a process-based backbone. HyLake simulates lake surface temperature and the latent and sensible heat fluxes in Lake Taihu more accurately than traditional process-based models and other hybrid experiments across different forcing datasets. The proposed coupling strategy provides a reliable tool for quantifying the impacts of climate change on aquatic ecosystems.
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28 Nov 2025
VaPOrS v1.0.1: an automated model for functional group detection and property prediction of organic compounds via SMILES notation
Mojtaba Bezaatpour, Miikka Dal Maso, and Matti Rissanen
Geosci. Model Dev., 18, 9189–9217,
2025
Short summary
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We developed a computer program that can read chemical formulas and identify key features in thousands of organic compounds. This helps scientists estimate how easily these compounds evaporate, which is important for understanding air pollution and climate. We tested the program using real-world data and found it to be highly accurate. Our work makes it faster and easier to study the behavior of many complex chemicals in the atmosphere.
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27 Nov 2025
Matter (v1): an open-source MPM solver for granular matter
Lars Blatny and Johan Gaume
Geosci. Model Dev., 18, 9149–9166,
2025
Short summary
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Matter is a new computer model that simulates granular media like sand, snow, and soil. These materials can behave like both solids and fluids, making their modeling difficult. Matter addresses this with a unified framework, using a numerical solver called MPM. Able to capture cohesion, density variations and complex terrains, it's particularly relevant for snow avalanches or landslides. Matter runs efficiently on standard computers, making advanced simulations more accessible.
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27 Nov 2025
Enhancing simulations of snowpack properties in land surface models with the Soil, Vegetation and Snow scheme v2.0 (SVS2)
Vincent Vionnet, Nicolas R. Leroux, Vincent Fortin, Maria Abrahamowicz, Georgina Woolley, Giulia Mazzotti, Manon Gaillard, Matthieu Lafaysse, Alain Royer, Florent Domine, Nathalie Gauthier, Nick Rutter, Chris Derksen, and Stéphane Bélair
Geosci. Model Dev., 18, 9119–9147,
2025
Short summary
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Snow microstructure controls snowpack properties, but most land surface models overlook this factor. To support future satellite missions, we created a new land surface model based on the Crocus scheme that simulates snow microstructure. Key improvements include better snow albedo representation, enhanced Arctic snow modeling, and improved forest module to capture Canada's diverse snow conditions. Results demonstrate improved simulations of snow density and melt across large regions of Canada.
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26 Nov 2025
The Chemical Mechanism Integrator
Cminor
v1.0: a stand-alone Fortran environment for the particle-based simulation of chemical multiphase mechanisms
Levin Rug, Willi Schimmel, Fabian Hoffmann, and Oswald Knoth
Geosci. Model Dev., 18, 9039–9059,
2025
Short summary
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We present the Chemical Mechanism Integrator (
Cminor
) v1.0, a tool to predict concentrations of chemical compounds undergoing arbitrary reactions.
Cminor
is an advanced, open-source solver to model either combustion chemistry, or atmospheric chemistry and its direct influence on condensation of cloud droplets and the subsequent processing of aerosol. It uses the superdroplet idea, making it particularly feasible for coupling with such models, which is part of future work.
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25 Nov 2025
ClimLoco1.0: CLimate variable confidence Interval of Multivariate Linear Observational COnstraint
Valentin Portmann, Marie Chavent, and Didier Swingedouw
Geosci. Model Dev., 18, 9015–9038,
2025
Short summary
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The future climate is very uncertain due to the large dispersion in projections from numerical models. Observational constraints (OCs) decrease this uncertainty using real-world observations. The article proposes a new rigorous statistical OC
model that provides updated estimates of confidence intervals as used in Intergovernmental Panel on Climate Change (IPCC) reports. It allows the use of multiple observations simultaneously and proposes an innovative and proper illustration of this OC approach.
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24 Nov 2025
The Lagrangian moisture source and transport diagnostic WaterSip V3.2
Harald Sodemann
Geosci. Model Dev., 18, 8887–8926,
2025
Short summary
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The WaterSip software locates regions where precipitation comes from. WaterSip evaluates of the water budget of the air masses, providing information on the conditions during evaporation, transport, and arrival at the target area. WaterSip can be easily configured and writes gridded output files. Guidance is given on where uncertainties arise using a case study, and best practices are recommended. This manuscript supports the comparison of different methods to find precipitation sources.
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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
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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.
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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.
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17 Nov 2025
JuWavelet – continuous wavelet transform and
transform for wave analysis
Jörn Ungermann and Robert Reichert
Geosci. Model Dev., 18, 8613–8626,
2025
Short summary
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This paper describes the software package JuWavelet, which implements the continuous wavelet transform, which is a popular tool in the geosciences to analyse wave-like phenomena. The code implements the transform in 1-D, 2-D, and 3-D for both analysis and synthesis, which closes a gap in available open-source software. The mathematics behind the transformation are given, and several examples showcase the capabilities of the software.
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17 Nov 2025
Data-driven estimation of the hydrologic response using generalized additive models
Quentin Duchemin, Maria Grazia Zanoni, Marius G. Floriancic, Hansjörg Seybold, Guillaume Obozinski, James W. Kirchner, and Paolo Benettin
Geosci. Model Dev., 18, 8663–8678,
2025
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We introduce GAMCR (Generalized Additive Models for Catchment Responses), a data-driven model that estimates how catchments respond to individual precipitation events. We validate GAMCR on synthetic data and demonstrate its ability to investigate the characteristic runoff responses from real-world hydrologic series. GAMCR provides new data-driven opportunities to understand and compare hydrological behavior across different catchments.
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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
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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.
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14 Nov 2025
CIBUSmod 25.09: a spatially disaggregated biophysical agri-food systems model for studying national-level demand- and production-side intervention scenarios
Johan O. Karlsson, Hanna Karlsson-Potter, Oscar Lagnelöv, Niclas Ericsson, Rasmus Einarsson, and Per-Anders Hansson
Geosci. Model Dev., 18, 8589–8611,
2025
Short summary
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CIBUSmod is a biophysical agri-food system model designed to evaluate resource use and environmental impacts on national and sub-national level under future scenarios involving changes in demand and agricultural production systems. It provides a flexible framework that can integrate regionalised data at the spatial resolution and aggregation level available. By enhancing transparency and usability in food systems modelling, CIBUSmod is a valuable tool for exploring agri-food systems transitions.
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13 Nov 2025
A double-box model for aircraft exhaust plumes based on the MADE3 aerosol microphysics (MADE3 v4.0)
Monica Sharma, Mattia Righi, Johannes Hendricks, Anja Schmidt, Daniel Sauer, and Volker Grewe
Geosci. Model Dev., 18, 8485–8510,
2025
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A plume model is developed to simulate aerosol microphysics in a dispersing aircraft plume, including interactions between ice crystals and aerosols in vortex regime. Compared to an instantaneous dispersion approach, the plume approach estimates 15 % lower aviation aerosol number concentrations, due to more efficient coagulation at plume scale. The model is sensitive to background conditions and initialization parameters, such as ice crystal number concentration and fuel sulfur content.
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13 Nov 2025
The SAPRC atmospheric chemical mechanism generation system (MechGen)
William P. L. Carter, Jia Jiang, Zhizhao Wang, and Kelley C. Barsanti
Geosci. Model Dev., 18, 8461–8483,
2025
Short summary
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The SAPRC Atmospheric Chemical Mechanism Generation System (MechGen) generates explicit chemical reaction mechanisms for organic compounds. MechGen has been used for decades in the development of the widely used SAPRC mechanisms. This paper, detailing the software system, and a companion paper, detailing the chemical basis, represent the first complete documentation of MechGen. This paper includes examples and instructions for generating explicit and reduced mechanisms.
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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
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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.
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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
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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.
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11 Nov 2025
BOSSE v1.0: the Biodiversity Observing System Simulation Experiment
Javier Pacheco-Labrador, Ulisse Gomarasca, Daniel E. Pabon-Moreno, Wantong Li, Mirco Migliavacca, Martin Jung, and Gregory Duveiller
Geosci. Model Dev., 18, 8401–8422,
2025
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Measuring biodiversity is necessary to assess its loss, evolution, and role in ecosystem functions. Satellites image the whole terrestrial surface and could cost-efficiently map plant diversity globally. However, developing the necessary methods lacks consistent and sufficient field measurements. Thus, we propose using a simulation tool that generates virtual ecosystems, with species properties and functions varying in response to meteorology and the respective remote sensing imagery.
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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.
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06 Nov 2025
METEORv1.0.1: a novel framework for emulating multi-timescale regional climate responses
Marit Sandstad, Norman Julius Steinert, Susanne Baur, and Benjamin Mark Sanderson
Geosci. Model Dev., 18, 8269–8312,
2025
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We present METEORv1.0.1, a climate model emulator, that can be trained on full spatially resolved and widely available climate model data to reproduce climate variables and make predictions from unseen emission trajectories. The methodology identifies patterns with timescales of impact for one or more forcers using idealised experiments and anomaly calculations. Results for precipitation and temperature show good model performance and can reproduce hysteresis for overshoot scenarios.
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05 Nov 2025
age_flow_line-1.0: a fast and accurate numerical age model for a pseudo-steady flow tube of an ice sheet
Frédéric Parrenin, Ailsa Chung, and Carlos Martín
Geosci. Model Dev., 18, 8203–8216,
2025
Short summary
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We developed a new numerical age solver for a pseudo-steady flow tube of an ice sheet. Thanks to a new coordinate system which tracks the trajectories and a change of the time variable, our scheme combines the advantages of Eulerian and Lagrangian schemes: no numerical diffusion and no dilution of tracers. Our model is so fast that it is easy to optimize its parameters. Our model is made available to the ice sheet community as an easy to use open-source software coded in python.
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05 Nov 2025
HOPE: an arbitrary-order non-oscillatory finite-volume shallow water dynamical core with automatic differentiation
Lilong Zhou, Wei Xue, and Xueshun Shen
Geosci. Model Dev., 18, 8175–8201,
2025
Short summary
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This study develops a novel physics-based weather prediction model using artificial intelligence development platform, achieving high accuracy while maintaining strict physical conservation laws. Our algorithms are optimized for modern super computers, enabling efficient large-scale weather simulations. A key innovation is the model's inherent differentiable nature, allowing seamless integration with AI systems to enhance predictive capabilities through machine learning techniques.
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04 Nov 2025
Fluid flow channeling and mass transport with discontinuous porosity distribution
Simon Boisserée, Evangelos Moulas, and Markus Bachmayr
Geosci. Model Dev., 18, 8143–8156,
2025
Short summary
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Understanding porous fluid flow is key for many geology applications. Traditional methods cannot resolve cases with sharp discontinuities in hydraulic/mechanical properties across those layers. Here we present a new space-time method that can handle such discontinuities. This approach is coupled with trace element transport. Our study reveals that the layering of rocks significantly influences the formation of fluid-rich channels and the material distribution adjacent to discontinuities.
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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
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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.
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30 Oct 2025
An overview of FRIDA v2.1: a feedback-based, fully coupled, global integrated assessment model of climate and humans
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
Geosci. Model Dev., 18, 8047–8069,
2025
Short summary
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The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA (Feedback-based knowledge Repository for IntegrateD Assessments) v2.1 integrates these systems and generate results that suggest standard scenarios the shared socioeconomic pathways baseline scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
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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.
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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.
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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.
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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.
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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.
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28 Oct 2025
REMO2020: a modernised modular regional climate model
Joni-Pekka Pietikäinen, Kevin Sieck, Lars Buntemeyer, Thomas Frisius, Christine Nam, Peter Hoffmann, Christina Pop, Diana Rechid, and Daniela Jacob
Geosci. Model Dev., 18, 7907–7949,
2025
Short summary
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This paper introduces REMO2020, a modernised version of the well-known and widely used REMO regional climate model. We demonstrate why REMO2020 will be our new model version for future dynamical downscaling activities. REMO2020 outperforms the previous REMO version in almost all areas used to evaluate the European climate.  It also supports climate service need-based developments through a new, more modular structure.
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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.
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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.
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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.
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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.
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