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07 Apr 2026
| Highlight paper
The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7)
Detlef P. Van Vuuren, Brian C. O'Neill, Claudia Tebaldi, Benjamin M. Sanderson, Louise P. Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh M. N. Fall, Katja Frieler, Matthew J. Gidden, Laila K. Gohar, Annika Högner, Andrew D. Jones, Jarmo Kikstra, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camilla Mathison, Shahbaz Mehmood, Zebedee Nicholls, Luciana F. Prado, Qiang Zhang, Steven K. Rose, Alex C. Ruane, Marit Sandstad, Carl-Friedrich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna A. Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha S. Vishwanathan, Tokuta Yokohata, Marco Zecchetto, and Tilo Ziehn
Geosci. Model Dev., 19, 2627–2656,
2026
Final revised paper published in GMD
(31 comments)
Short summary
Editorial statement
Short summary
We propose a set of seven plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
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Editorial statement
This article describes the design of the next version of emission scenarios that will be used for the 7th phase of the Coupled Model Intercomparison Project, which in turn will be used for the 7th Assessment Report of the Intergovernmental Panel on Climate Change. It provides the story lines for the creation of the emission scenarios and therefore it envisions future trajectories of policies and energy use. Models in CMIP 7 will use these scenarios to run simulations of future climate change using the scenarios as the main forcing. The authors carefully considered all community comments and maintained an open approach to develop these scenarios.
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14 Jan 2026
Application of flux footprint equations from Kljun et al. (2015) to field eddy-covariance systems for footprint characteristics into flux network datasets
Xinhua Zhou, Zhi Chen, Ryan Campbell, Atefeh Hosseini, Tian Gao, Xiufen Li, Jianmin Chu, Sen Wu, Ning Zheng, and Jiaojun Zhu
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 25 comments)
Short summary
Short summary
To help environmental researchers better understand the sources of greenhouse gas measurements, we developed a practical method for field instruments to calculate the footprints. By using simplified math and efficient computing, our approach allows real-time analysis of measurement zones, which was previously too complex for on-site processing. This enables more accurate data collection worldwide, helping improve climate change monitoring and ecosystem studies.
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14 May 2025
Baseline Climate Variables for Earth System Modelling
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O'Rourke, and Beth Dingley
Geosci. Model Dev., 18, 2639–2663,
2025
Final revised paper published in GMD
(22 comments)
Short summary
Short summary
The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used variables from Earth system models based on an assessment of data publication and download records from the largest archive of global climate projects.
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29 Oct 2025
Intercomparison of bias correction methods for precipitation of multiple GCMs across six continents
Young Hoon Song and Eun-Sung Chung
Geosci. Model Dev., 18, 8017–8045,
2025
Final revised paper published in GMD
(20 comments)
Short summary
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This study assessed three methods for correcting daily precipitation data: Quantile Delta Mapping, Empirical Quantile Mapping (EQM), and Detrended Quantile Mapping (DQM) using 11 GCMs. EQM performed best overall, offering reliable corrections and lower uncertainty. The best bias correction method for each grid is selected differently depending on the weighting case. The best bias correction method can vary depending on factors such as climate and terrain.
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10 Oct 2025
Towards viscous debris flow simulation using DualSPHysics v5.2: internal behaviour of viscous flows and mixtures
Suzanne Lapillonne, Georgios Fourtakas, Vincent Richefeu, Guillaume Piton, and Guillaume Chambon
Geosci. Model Dev., 18, 7059–7075,
2025
Final revised paper published in GMD
(18 comments)
Short summary
Short summary
Debris flows are fast-flowing events that are saturated with granular material. They naturally occur in steep creeks and are a threat to local communities. Scientists have turned to numerical models to better understand how they behave. We investigate the accuracy of a numerical model that relies on modelling the debris flow as a mixture of a granular phase and a fluid phase. We focus on a demonstration of the capacity of the model to reliably represent the behaviour of the flow at different scales.
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21 Jan 2026
Threshold atmospheric electric fields for initiating relativistic runaway electron avalanches: theoretical estimates and CORSIKA simulations
Ashot Chilingarian, Liza Hovhannisyan, and Mary Zazyan
Geosci. Model Dev., 19, 621–626,
2026
Final revised paper published in GMD
(16 comments)
Short summary
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Thunderstorms can accelerate particles in the atmosphere, producing bursts of radiation at the ground. We investigated how strong the electric field inside a cloud must be to start such events. Using advanced computer simulations and comparing with measurements from mountain stations, we found that fields must be stronger than earlier theory suggested. Our results improve understanding of storm electricity and its role in natural radiation.
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12 Nov 2025
Simulated and Observed Transport Estimates Across the Overturning in the Subpolar North Atlantic Program (OSNAP) Section
Gokhan Danabasoglu, Frederic S. Castruccio, Burcu Boza, Alice M. Barthel, Arne Biastoch, Adam Blaker, Alexandra Bozec, Diego Bruciaferri, Frank O. Bryan, Eric P. Chassignet, Yao Fu, Ian Grooms, Catherine Guiavarc'h, Hakase Hayashida, Andrew McC. Hogg, Ryan M. Holmes, Doroteaciro Iovino, Andrew E. Kiss, M. Susan Lozier, Gustavo Marques, Alex Megann, Franziska U. Schwarzkopf, Dave Storkey, Luke van Roekel, Jon Wolfe, Xiaobiao Xu, and Rong Zhang
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 16 comments)
Short summary
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A comparison of simulated and observed overturning transports across the Overturning in the Subpolar North Atlantic Program sections for the 2014–2022 period is presented. Eighteen ocean simulations participate in the study. The simulated transports are in general agreement with observations. Analyzing overturning circulations in both depth and density space together provides a more complete picture of the overturning properties. The study serves as a benchmark for evaluation of ocean models.
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18 Nov 2025
A computationally efficient method to model similar and alternate stratospheric aerosol injection experiments using prescribed aerosols in a lower-complexity version of the same model: a case study using CESM(CAM) and CESM(WACCM)
Jasper de Jong, Daniel Pflüger, Simone Lingbeek, Claudia E. Wieners, Michiel L. J. Baatsen, and René R. Wijngaard
Geosci. Model Dev., 18, 8679–8702,
2025
Final revised paper published in GMD
(15 comments)
Short summary
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Injection of reflective sulfate aerosols high in the atmosphere is a proposed method to mitigate global warming. Climate simulations with injection are more expensive than standard future projections. We propose a method that dynamically scales the forcing fields based on pre-existing full-complexity data. This opens up possibilities for ensemble generation, new scenarios and higher resolution runs. We show that our method works for multiple model versions, injection scenarios and resolutions.
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22 Aug 2025
FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites
Jie Lai, Yuan Zhang, Anzhi Wang, Wenli Fei, Yiwei Diao, Rongping Li, and Jiabing Wu
Geosci. Model Dev., 18, 5115–5142,
2025
Final revised paper published in GMD
(15 comments)
Short summary
Short summary
In this study,
a new model called FLAML-LUE was created by combining the Fast Lightweight Automated Machine Learning (FLAML) model with light use efficiency (LUE) models; the latter provides the key variables of vegetation growth for modeling. Such knowledge- and data-driven models aim to reduce the large uncertainty in estimating gross primary productivity (GPP).
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15 Oct 2025
Ensemble data assimilation to diagnose AI-based weather prediction models: a case with ClimaX version 0.3.1
Shunji Kotsuki, Kenta Shiraishi, and Atsushi Okazaki
Geosci. Model Dev., 18, 7215–7225,
2025
Final revised paper published in GMD
(14 comments)
Short summary
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Artificial intelligence (AI) is playing a bigger role in weather forecasting, often competing with physical models. However, combining AI models with data assimilation, a process that improves weather forecasts by incorporating observation data, is still relatively unexplored. This study explored the coupling of ensemble data assimilation with an AI weather prediction model, ClimaX, which succeeded in employing weather forecasts stably by applying techniques conventionally used for physical models.
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25 Sep 2025
The updated Multi-Model Large Ensemble Archive and the Climate Variability Diagnostics Package: new tools for the study of climate variability and change
Nicola Maher, Adam S. Phillips, Clara Deser, Robert C. Jnglin Wills, Flavio Lehner, John Fasullo, Julie M. Caron, Lukas Brunner, Urs Beyerle, and Jemma Jeffree
Geosci. Model Dev., 18, 6341–6365,
2025
Final revised paper published in GMD
(14 comments)
Short summary
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We present the new Multi-Model Large Ensemble Archive (MMLEAv2) and introduce the newly updated Climate Variability Diagnostics Package version 6 (CVDPv6), which is designed specifically for use with large ensembles. For highly variable quantities, we demonstrate that a model might perform evaluation poorly or favourably compared to the single realisation of the world that the observations represent, highlighting the need for large ensembles for model evaluation.
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09 Feb 2026
Runoff evaluation in an Earth System Land Model for permafrost regions in Alaska
Xiang Huang, Yu Zhang, Bo Gao, Charles J. Abolt, Ryan L. Crumley, Cansu Demir, Richard P. Fiorella, Bob Busey, Bob Bolton, Scott L. Painter, and Katrina E. Bennett
Geosci. Model Dev., 19, 1193–1211,
2026
Final revised paper published in GMD
(13 comments)
Short summary
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Predicting hydrological runoff in Arctic permafrost regions is difficult due to limited observations and complex terrain. We used a detailed physics-based model simulations to improve runoff estimates in a Earth system land model. Our method improved runoff accuracy and worked well across two different Arctic regions. This helps make runoff parameterization schemes more reliable for understanding water flow in permafrost areas under a changing climate.
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06 Nov 2025
Stripe patterns in wind forecasts induced by physics-dynamics coupling on a staggered grid in CMA-GFS 3.0
Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen
Geosci. Model Dev., 18, 8253–8267,
2025
Final revised paper published in GMD
(13 comments)
Short summary
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Weather forecasts sometimes show high-frequency noise degrading predictions. Our study reveals stripe patterns arise from mismatches between dynamic and physical calculations in models. Simplified experiments demonstrate that adjusting their connection eliminates stripes. This advances numerical weather prediction understanding, aiding forecasters and the public. Our diagnostic methods provide a framework for solving this global meteorological modeling challenge.
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10 Oct 2025
A hybrid-grid global model for the estimation of atmospheric weighted mean temperature considering time-varying vertical adjustment rate in GNSS precipitable water vapour retrieval
Shaofeng Xie, Jihong Zhang, Liangke Huang, Fade Chen, Yongfeng Wu, Yijie Wang, and Lilong Liu
Geosci. Model Dev., 18, 6987–7002,
2025
Final revised paper published in GMD
(13 comments)
Short summary
Short summary
We developed a new global atmospheric weighted mean temperature (
) model considering time-varying vertical adjustment rate. Firstly, a global
vertical adjustment rate model (NGGTm-H) was developed using the sliding-window algorithm. Secondly, the daily variation characteristics of
and its relationships with geographical situations were investigated. Finally, a hybrid-grid global
model considering the time-varying vertical adjustment rate (NGGTm) was developed.
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10 Oct 2025
MLUCM BEP + BEM: an offline one-dimensional multi-layer urban canopy model based on the BEP + BEM scheme
Gianluca Pappaccogli, Andrea Zonato, Alberto Martilli, Riccardo Buccolieri, and Piero Lionello
Geosci. Model Dev., 18, 7129–7145,
2025
Final revised paper published in GMD
(13 comments)
Short summary
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We present a multilayer urban model, named MLUCM BEP+BEM, able to represent detailed urban geometry and vegetation, while simulating their interactions and feedback with the atmosphere. Its accuracy and low computational cost make it ideal for offline climate projections assessing urban impacts under various emission scenarios. Its features enable analysis of urban overheating, energy demand, thermal comfort, and evaluation of strategies like green/cool roofs and photovoltaic panels.
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23 Jun 2025
Wastewater matters: incorporating wastewater treatment and reuse into a process-based hydrological model (CWatM v1.08)
Dor Fridman, Mikhail Smilovic, Peter Burek, Sylvia Tramberend, and Taher Kahil
Geosci. Model Dev., 18, 3735–3754,
2025
Final revised paper published in GMD
(13 comments)
Short summary
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Global hydrological models are applied at high spatial resolutions to quantify water availability and evaluate water scarcity mitigation options. Yet, they mainly oversee critical local processes. This paper presents and demonstrates the inclusion of wastewater treatment and reuse into a global hydrological model. As a result, model performance improves, and models consider treated wastewater as an alternative water source.
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13 Jan 2026
Evaluating Modifications to Tiedtke Cumulus Parameterization for Improving Summer Precipitation Forecasts in the Nested Grid of Taiwan Global Forecast System (TGFS v1.1)
Chang-Hung Lin, Guo-Yuan Lien, and Ling-Feng Hsiao
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 12 comments)
Short summary
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This study presents a series of modifications to the Tiedtke convection scheme, aiming to improve summer rainfall predictions in the 4.8-km-resolution nested grid of the Taiwan Global Forecast System (TGFS). The modifications improve the spatial distribution of rainfall and reduce the heavy rainfall bias in five-day forecast, as demonstrated by case studies and evaluations over a two-month period.
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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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10 Dec 2025
rsofun v5.1: a model-data integration framework for simulating ecosystem processes
Josefa Arán Paredes, Fabian Bernhard, Koen Hufkens, Mayeul Marcadella, and Benjamin D. Stocker
Geosci. Model Dev., 18, 9855–9878,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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Mechanistic vegetation models serve to estimate terrestrial carbon fluxes and climate impacts on ecosystems across diverse conditions. Here, we demonstrate and evaluate the
rsofun
R package, which provides a computationally efficient implementation of the P-model for site-scale simulations of ecosystem photosynthesis. Bayesian model fitting to observed fluxes and traits and evaluation on an independent test data set indicated robust calibration and unbiased prediction capabilities.
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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
Final revised paper published in GMD
(12 comments)
Short summary
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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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25 Nov 2025
ISARD (v1.0) : A Reproducible Geostatistical Framework for Daily Precipitation Ensemble in Mountainous Terrain
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
EGUsphere,
2025
Preprint under review for GMD
(discussion: final response, 12 comments)
Short summary
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Traditional precipitation analysis often misrepresent seasonal totals and spatial variability of intense rainfall in mountains. This study introduces a reproducible workflow to generate a daily precipitation ensembles, conditioned on rain gauges. It outperforms standard products by better capturing seasonal totals. It also quantifies interpolation uncertainty, improving flood modeling. The open-source workflow is transferable to regions with sparse rain-gauge networks or limited radar coverage.
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06 Nov 2025
Bias correcting regional scale Earth system model projections: novel approach using empirical mode decomposition
Arkaprabha Ganguli, Jeremy Feinstein, Ibraheem Raji, Akintomide Akinsanola, Connor Aghili, Chunyong Jung, Jordan Branham, Tom Wall, Whitney Huang, and Rao Kotamarthi
Geosci. Model Dev., 18, 8313–8332,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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This study introduces a timescale-aware bias-correction framework to enhance Earth system model assessments, vital for the geoscience community. By decomposing model outputs into oscillatory components, we preserve critical information across various timescales, ensuring more reliable projections. This improved reliability supports strategic decisions in sectors such as agriculture, water resources, and disaster preparedness.
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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
Final revised paper published in GMD
(12 comments)
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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27 Oct 2025
Implementation of solar UV and energetic particle precipitation within the LINOZ scheme in ICON-ART
Maryam Ramezani Ziarani, Miriam Sinnhuber, Thomas Reddmann, Bernd Funke, Stefan Bender, and Michael Prather
Geosci. Model Dev., 18, 7891–7905,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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Our study aims to present a new method for incorporating top-down solar forcing into stratospheric ozone relying on linearized ozone scheme. The addition of geomagnetic forcing led to significant ozone losses in the polar upper stratosphere of both hemispheres due to the catalytic cycles involving NO
. In addition to the particle precipitation effect, accounting for solar UV variability in the ICON-ART model leads to the changes in ozone in the tropical stratosphere.
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27 Oct 2025
Multigrid beta filter for faster computation of ensemble covariance localization
Sho Yokota, Miodrag Rancic, Ting Lei, R. James Purser, and Manuel S. F. V. De Pondeca
Geosci. Model Dev., 18, 7815–7829,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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Covariance localization to mitigate sampling error of ensemble-based forecast error covariances is one of the main parts of the calculation in ensemble-variational data assimilation for the atmosphere. This study clarifies that the multigrid beta filter-based localization makes it several times faster than the conventional recursive filter-based one without significantly changing the analysis if a coarser filter grid is applied and filters except for the coarsest resolution are omitted.
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23 Oct 2025
Soil parameterization in land surface models drives large discrepancies in soil moisture predictions across hydrologically complex regions of the contiguous United States
Kachinga Silwimba, Alejandro N. Flores, Irene Cionni, Sharon A. Billings, Pamela L. Sullivan, Hoori Ajami, Daniel R. Hirmas, and Li Li
Geosci. Model Dev., 18, 7707–7734,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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Land models need reliable soil properties to simulate water, but these settings are uncertain. We analyzed Community Land Model version 5 simulations for the United States from 1980 to 2010 to see how different soil settings shape patterns of soil moisture. Compared with an independent global land dataset, patterns align in many regions but differ in water-limited areas such as the Great Plains. Our maps show where to improve settings and guide future tests with observations.
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10 Jul 2025
Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol–climate model ECHAM6.3–HAM2.3
Anisbel Leon-Marcos, Moritz Zeising, Manuela van Pinxteren, Sebastian Zeppenfeld, Astrid Bracher, Elena Barbaro, Anja Engel, Matteo Feltracco, Ina Tegen, and Bernd Heinold
Geosci. Model Dev., 18, 4183–4213,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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This study represents the primary marine organic aerosol (PMOA) emissions, focusing on their sea–atmosphere transfer. Using the FESOM2.1–REcoM3 model, concentrations of key organic biomolecules were estimated and integrated into the ECHAM6.3–HAM2.3 aerosol–climate model. Results highlight the influence of marine biological activity and surface winds on PMOA emissions, with reasonably good agreement with observations improving aerosol representation in the southern oceans.
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10 Jul 2025
Why does the signal-to-noise paradox exist in seasonal climate predictability?
Yashas Shivamurthy, Subodh Kumar Saha, Samir Pokhrel, Mahen Konwar, and Utkarsh Verma
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 12 comments)
Short summary
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This study highlights challenges in estimating seasonal climate predictability using the "perfect model" approach, which assumes only initial conditions cause error. We find that forecasts can exceed the predicted limit, known as the Potential Predictability Limit (PPL), due to model imperfections and short-term weather influences. A new method is proposed to estimate PPL more accurately and avoid such paradoxes.
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20 Jun 2025
Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev., 18, 3661–3679,
2025
Final revised paper published in GMD
(12 comments)
Short summary
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We present an automatic tool that optimizes resource distribution in coupled climate models, enhancing speed and reducing computational costs without requiring expert knowledge. Users can set energy/time criteria or limit resource usage. Tested on various European Community Earth System Model (EC-Earth) configurations and high-performance computing (HPC) platforms, it achieved up to 34 % faster simulations with fewer resources.
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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
Final revised paper published in GMD
(11 comments)
Short summary
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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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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
Final revised paper published in GMD
(11 comments)
Short summary
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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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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
Final revised paper published in GMD
(11 comments)
Short summary
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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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07 Jan 2026
Assessing vertical coordinate system performance in the Regional Modular Ocean Model 6 configuration for Northwest Pacific
Inseong Chang, Young Ho Kim, Young-Gyu Park, Hyunkeun Jin, Gyundo Pak, Andrew C. Ross, and Robert Hallberg
Geosci. Model Dev., 19, 187–216,
2026
Final revised paper published in GMD
(11 comments)
Short summary
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We conducted sensitivity experiments to examine how different vertical coordinates influence the representation of water masses and tides using a high-resolution regional ocean model for the Northwest Pacific. We found that the choice of vertical coordinate  strongly affects the degree of artificial mixing, which in turn changes how well the model reproduces key ocean features. This highlights the importance of selecting a vertical coordinate when developing regional ocean models.
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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
Final revised paper published in GMD
(11 comments)
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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22 Oct 2025
CLEO: The Fundamental Design for High Computational Performance of a New Superdroplet Model
Clara J. A. Bayley, Tobias Kölling, Ann Kristin Naumann, Raphaela Vogel, and Bjorn Stevens
EGUsphere,
2025
Revised manuscript accepted for GMD
(discussion: final response, 11 comments)
Short summary
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Cloud microphysics is a leading source of error in both regional and global climate models and this limits our ability to understand the Earth’s climate and how it is changing. However a fairly new type of model called a Superdroplet Model (SDM) may improve both regional and global models if it can be made cost-efficient enough. Hence we are introducing a novel version of SDM, called CLEO, and it's key features that make it efficient, especially on very high performance, “exascale”, computers.
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29 Aug 2025
ISWNM-NSCS v2.0: advancing the internal solitary wave numerical model with background currents and horizontally inhomogeneous stratifications
Yankun Gong, Xueen Chen, Jiexin Xu, Zhiwu Chen, Qingyou He, Ruixiang Zhao, Xiao-Hua Zhu, and Shuqun Cai
Geosci. Model Dev., 18, 5413–5433,
2025
Final revised paper published in GMD
(11 comments)
Short summary
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A new internal solitary wave (ISW) numerical model in the northern South China Sea (ISWNM-NSCS v2.0) improves ISW predictions by incorporating background currents and inhomogeneous stratifications. Additionally, viscosity and diffusivity coefficients are optimized to maintain stable stratifications, extending the forecasting period. Sensitivity experiments show that ISWNM-NSCS v2.0 significantly enhances predictions of various wave properties.
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25 Jul 2025
| Highlight paper
asQ: parallel-in-time finite element simulations using ParaDiag for geoscientific models and beyond
Joshua Hope-Collins, Abdalaziz Hamdan, Werner Bauer, Lawrence Mitchell, and Colin Cotter
Geosci. Model Dev., 18, 4535–4569,
2025
Final revised paper published in GMD
(11 comments)
Short summary
Editorial statement
Short summary
Effectively using modern supercomputers requires massively parallel algorithms. Time-parallel algorithms calculate the system state (e.g. the atmosphere) at multiple times simultaneously and have exciting potential but are tricky to implement and still require development. We have developed software to simplify implementing and testing the ParaDiag algorithm on supercomputers. We show that for some atmospheric problems it can enable faster or more accurate solutions than traditional techniques.
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Editorial statement
Parallelization is important for speeding up complex geoscientific
models. In addition to spatial parallelization, several parallel-in-time
(PinT) methods have been developed. This paper introduces the reader to
PinT methods for hyperbolic and geophysical models, and it presents the
asQ library which facilitates the implementation of
diagonalization-based (ParaDiag) methods.
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11 Jul 2025
EXSoDOS 1.0: downscaling of weather extremes shifts for ensemble climate projections using ground-based measurements, reanalysis and stochastic modelling
Hendrik Wouters, Jente Broeckx, Francisco Pereira, Boucary Dara, Afoussatou Diarra, Robin Houdmeyers, and Dirk Lauwaet
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 11 comments)
Short summary
Short summary
Predicting shifts in local extreme weather under global warming is key for climate adaptation, but climate projections lack detail. A new tool, EXSoDOS, combines ground measurements, reanalysis data, and climate models to improve estimates of extreme weather, aiding better risk planning. Tested in five regions, it accurately captures temperature, rainfall, and wind extremes including their past changes, outperforming raw model data. Results show worsening heat (stress) and precipitation by 2100.
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30 Jun 2025
ICON-HAM-lite 1.0: simulating the Earth system with interactive aerosols at kilometer scales
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894,
2025
Final revised paper published in GMD
(11 comments)
Short summary
Short summary
Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of lognormal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of 5 km. It captures key processes like the formation of dust storms in the Sahara.
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28 May 2025
NMH-CS 3.0: a C# programming language and Windows-system-based ecohydrological model derived from Noah-MP
Yong-He Liu and Zong-Liang Yang
Geosci. Model Dev., 18, 3157–3174,
2025
Final revised paper published in GMD
(11 comments)
Short summary
Short summary
NMH-CS 3.0 is a C#-based ecohydrological model reconstructed from the WRF-Hydro/Noah-MP model by translating the Fortran code of WRF-Hydro 3.0 and integrating a parallel river routing module. It enables efficient execution on multi-core personal computers. Simulations in the Yellow River basin demonstrate its consistency with WRF-Hydro outputs, providing a reliable alternative to the original Noah-MP model.
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16 May 2025
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860,
2025
Final revised paper published in GMD
(11 comments)
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury
and the
Convention on Long-Range Transboundary Air Pollution
The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
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24 Mar 2026
A Bayesian statistical method to estimate the climatology of extreme temperature under multiple scenarios: the ANKIALE package
Yoann Robin, Mathieu Vrac, Aurélien Ribes, Occitane Barbaux, and Philippe Naveau
Geosci. Model Dev., 19, 2349–2372,
2026
Final revised paper published in GMD
(10 comments)
Short summary
Short summary
We describe an improved method and the associated free licensed package ANKIALE (ANalysis of Klimate with bayesian Inference: AppLication to extreme Events) for estimating the statistics of temperature extremes. This method uses climate model simulations (including multiple scenarios simultaneously) to provide a prior of the real-world changes, constrained by the observations. The method and the tool are illustrated via an application to temperature over Europe until 2100, for four scenarios.
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30 Jan 2026
Evaluation of the LandscapeDNDC model for drained peatland forest managements, LDNDC v1.35.2 (revision 11434)
Ahmed Hasan Shahriyer, David Kraus, Tiina Markkanen, Mika Korkiakoski, Helena Rautakoski, Suvi Orttenvuori, Yao Gao, Henri Kajasilta, Rüdiger Grote, Annalea Lohila, and Tuula Aalto
EGUsphere,
2026
Preprint under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
We successfully represented hydrology and carbon cycle associated with different forestry managements (Rotational and continuous cover forestry) for a drained peatland ecosystem using the processed based model LDNDC. This provides a robust framework for investigating future management scenarios and develop forest management strategies that supports climate neutrality in peatland ecosystems.
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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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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
Final revised paper published in GMD
(10 comments)
Short summary
Short summary
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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19 Dec 2025
Interpretation and Representation in Geomodels: The POKIMON Ontology for Formalizing Geomodelling Knowledge
Imadeddine Laouici, Boyan Brodaric, Christelle Loiselet, and Gautier Laurent
EGUsphere,
2025
Revised manuscript under review for GMD
(discussion: final response, 10 comments)
Short summary
Short summary
3D geoscience models lack transparency about the interpretation process and the assumption to model and represent geological entities, limiting explainability, reproducibility, and automation. To address this, we present POKIMON, an ontology that formalizes the expert knowledge, interpretative aspects, and geological entities descriptions underlying 3D geomodelling, enhancing understanding, transparency, and knowledge-driven automation.
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05 Dec 2025
Evaluating the impact of task aggregation in workflows with shared resource environments: use case for the MONARCH application
Manuel G. Marciani, Miguel Castrillo, Gladys Utrera, Mario C. Acosta, Bruno P. Kinoshita, and Francisco Doblas-Reyes
Geosci. Model Dev., 18, 9709–9721,
2025
Final revised paper published in GMD
(10 comments)
Short summary
Short summary
Earth System Model simulations are typically run on large, highly congested flagship computers using workflows. These workflows can consist of thousands of tasks. If these tasks are queued individually, the wait time can add up, resulting in a long response time. In this paper, we explore a technique for aggregating tasks into a single submission. We found that this simple technique reduced the time spent in the queue by up to 7 %.
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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
Final revised paper published in GMD
(10 comments)
Short summary
Short summary
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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07 Nov 2025
Datasets and protocols for including anomalous freshwater from melting ice sheets in climate simulations
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Clara Burgard, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anna Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
Geosci. Model Dev., 18, 8333–8361,
2025
Final revised paper published in GMD
(10 comments)
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
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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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