Articles | Volume 12, issue 9
https://doi.org/10.5194/gmd-12-4165-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4165-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Sep 2019
Model description paper |
| 25 Sep 2019
| 25 Sep 2019
eSCAPE: Regional to Global Scale Landscape Evolution Model v2.0
Tristan Salles
CORRESPONDING AUTHOR
School of Geosciences, University of Sydney, Sydney, NSW, 2006, Australia
Related authors
Beatriz Hadler Boggiani, Tristan Salles, Claire Mallard, and Nicholas Atwood
Earth Surf. Dynam., 13, 683–704, https://doi.org/10.5194/esurf-13-683-2025, https://doi.org/10.5194/esurf-13-683-2025, 2025
Short summary
Short summary
We studied how erosion and tectonic forces can affect the exposure and preservation of copper deposits formed in subduction zones in the past 65 Myr. We used a global model that simulates landscape changes over time based on climate and elevation changes. Our findings show that climate is more important in preserving or exposing copper deposits than previously described. We help improve methods for locating copper deposits, offering new insights for mineral exploration.
Yinbing Zhu, Patrice Rey, and Tristan Salles
EGUsphere, https://doi.org/10.5194/egusphere-2025-1585, https://doi.org/10.5194/egusphere-2025-1585, 2025
Short summary
Short summary
We use computer models to study how landscapes respond to changes in rainfall and tectonic uplift. We find that rainfall rate changes produce unique slope change reversals near the headwaters, which differ from the simpler responses caused by uplift rate changes. These reversals are more pronounced when hillslope diffusion is dominant. These findings help us understand how climate and tectonic forcing shape the landscape differently and may allow scientists to tell their effects apart in nature.
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
Earth Surf. Dynam., 12, 301–320, https://doi.org/10.5194/esurf-12-301-2024, https://doi.org/10.5194/esurf-12-301-2024, 2024
Short summary
Short summary
Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport, and sea level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
Carole Petit, Tristan Salles, Vincent Godard, Yann Rolland, and Laurence Audin
Earth Surf. Dynam., 11, 183–201, https://doi.org/10.5194/esurf-11-183-2023, https://doi.org/10.5194/esurf-11-183-2023, 2023
Short summary
Short summary
We present new tools in the landscape evolution model Badlands to simulate 10Be production, erosion and transport. These tools are applied to a source-to-sink system in the SW French Alps, where the model is calibrated. We propose a model that fits river incision rates and 10Be concentrations in sediments, and we show that 10Be in deep marine sediments is a signal with multiple contributions that cannot be easily interpreted in terms of climate forcing.
Claire A. Mallard and Tristan Salles
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-89, https://doi.org/10.5194/esurf-2021-89, 2021
Preprint withdrawn
Short summary
Short summary
Using landscape evolution models integrating mantle dynamics, climate, eustatism and surface processes, we break down a previous idea that considers mantle flow as the main driver of the pulse of sedimentation in the Orange Basin, SA, over the last 30 Ma. Instead, climate impact seems to be a predominant mechanism. We also show that sediment flux and landscape evolution in the region is the product of interlinked processes accounting for both lithology variations, mantle dynamics and climate.
Gilles Brocard, Jane Kathrin Willenbring, Tristan Salles, Michael Cosca, Axel Guttiérez-Orrego, Noé Cacao Chiquín, Sergio Morán-Ical, and Christian Teyssier
Earth Surf. Dynam., 9, 795–822, https://doi.org/10.5194/esurf-9-795-2021, https://doi.org/10.5194/esurf-9-795-2021, 2021
Short summary
Short summary
The rise of a mountain affects the circulation of water, both in the atmosphere and over the land surface, thereby affecting the erosion of the land surface. We document how the rise of a mountain in central Guatemala has affected the erosion of an older range nearby. The new range intercepts precipitation formerly delivered to the older range. River response to the uplift of the new range has decreased incision across the older one. Both have reduced hillslope erosion over the old range.
Tristan Salles, Patrice Rey, and Enrico Bertuzzo
Earth Surf. Dynam., 7, 895–910, https://doi.org/10.5194/esurf-7-895-2019, https://doi.org/10.5194/esurf-7-895-2019, 2019
Short summary
Short summary
Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Xuesong Ding, Tristan Salles, Nicolas Flament, and Patrice Rey
Geosci. Model Dev., 12, 2571–2585, https://doi.org/10.5194/gmd-12-2571-2019, https://doi.org/10.5194/gmd-12-2571-2019, 2019
Short summary
Short summary
This work introduced a quantitative stratigraphic framework within a source-to-sink numerical code, pyBadlands, and evaluated two stratigraphic interpretation techniques. This quantitative framework allowed us to quickly construct the strata formations and automatically produce strata interpretations. We further showed that the accommodation succession method, compared with the trajectory analysis method, provided more reliable interpretations as it is independent of time-dependent processes.
Tristan Salles, Jodie Pall, Jody M. Webster, and Belinda Dechnik
Geosci. Model Dev., 11, 2093–2110, https://doi.org/10.5194/gmd-11-2093-2018, https://doi.org/10.5194/gmd-11-2093-2018, 2018
Short summary
Short summary
We present a 1-D model of coral reefs' evolution over centennial to millennial timescales. The model enables us to estimate the effects of environmental conditions (such as oceanic variability, sedimentation rate, sea-level fluctuations or tectonics) and ecological coral competition on reef vertical accretion and stratigraphic succession. The tool can quantitatively test carbonate platform development and efficiently interpret vertical growth under various forcing scenarios.
Beatriz Hadler Boggiani, Tristan Salles, Claire Mallard, and Nicholas Atwood
Earth Surf. Dynam., 13, 683–704, https://doi.org/10.5194/esurf-13-683-2025, https://doi.org/10.5194/esurf-13-683-2025, 2025
Short summary
Short summary
We studied how erosion and tectonic forces can affect the exposure and preservation of copper deposits formed in subduction zones in the past 65 Myr. We used a global model that simulates landscape changes over time based on climate and elevation changes. Our findings show that climate is more important in preserving or exposing copper deposits than previously described. We help improve methods for locating copper deposits, offering new insights for mineral exploration.
Yinbing Zhu, Patrice Rey, and Tristan Salles
EGUsphere, https://doi.org/10.5194/egusphere-2025-1585, https://doi.org/10.5194/egusphere-2025-1585, 2025
Short summary
Short summary
We use computer models to study how landscapes respond to changes in rainfall and tectonic uplift. We find that rainfall rate changes produce unique slope change reversals near the headwaters, which differ from the simpler responses caused by uplift rate changes. These reversals are more pronounced when hillslope diffusion is dominant. These findings help us understand how climate and tectonic forcing shape the landscape differently and may allow scientists to tell their effects apart in nature.
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
Earth Surf. Dynam., 12, 301–320, https://doi.org/10.5194/esurf-12-301-2024, https://doi.org/10.5194/esurf-12-301-2024, 2024
Short summary
Short summary
Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport, and sea level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
Carole Petit, Tristan Salles, Vincent Godard, Yann Rolland, and Laurence Audin
Earth Surf. Dynam., 11, 183–201, https://doi.org/10.5194/esurf-11-183-2023, https://doi.org/10.5194/esurf-11-183-2023, 2023
Short summary
Short summary
We present new tools in the landscape evolution model Badlands to simulate 10Be production, erosion and transport. These tools are applied to a source-to-sink system in the SW French Alps, where the model is calibrated. We propose a model that fits river incision rates and 10Be concentrations in sediments, and we show that 10Be in deep marine sediments is a signal with multiple contributions that cannot be easily interpreted in terms of climate forcing.
Claire A. Mallard and Tristan Salles
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-89, https://doi.org/10.5194/esurf-2021-89, 2021
Preprint withdrawn
Short summary
Short summary
Using landscape evolution models integrating mantle dynamics, climate, eustatism and surface processes, we break down a previous idea that considers mantle flow as the main driver of the pulse of sedimentation in the Orange Basin, SA, over the last 30 Ma. Instead, climate impact seems to be a predominant mechanism. We also show that sediment flux and landscape evolution in the region is the product of interlinked processes accounting for both lithology variations, mantle dynamics and climate.
Gilles Brocard, Jane Kathrin Willenbring, Tristan Salles, Michael Cosca, Axel Guttiérez-Orrego, Noé Cacao Chiquín, Sergio Morán-Ical, and Christian Teyssier
Earth Surf. Dynam., 9, 795–822, https://doi.org/10.5194/esurf-9-795-2021, https://doi.org/10.5194/esurf-9-795-2021, 2021
Short summary
Short summary
The rise of a mountain affects the circulation of water, both in the atmosphere and over the land surface, thereby affecting the erosion of the land surface. We document how the rise of a mountain in central Guatemala has affected the erosion of an older range nearby. The new range intercepts precipitation formerly delivered to the older range. River response to the uplift of the new range has decreased incision across the older one. Both have reduced hillslope erosion over the old range.
Tristan Salles, Patrice Rey, and Enrico Bertuzzo
Earth Surf. Dynam., 7, 895–910, https://doi.org/10.5194/esurf-7-895-2019, https://doi.org/10.5194/esurf-7-895-2019, 2019
Short summary
Short summary
Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Xuesong Ding, Tristan Salles, Nicolas Flament, and Patrice Rey
Geosci. Model Dev., 12, 2571–2585, https://doi.org/10.5194/gmd-12-2571-2019, https://doi.org/10.5194/gmd-12-2571-2019, 2019
Short summary
Short summary
This work introduced a quantitative stratigraphic framework within a source-to-sink numerical code, pyBadlands, and evaluated two stratigraphic interpretation techniques. This quantitative framework allowed us to quickly construct the strata formations and automatically produce strata interpretations. We further showed that the accommodation succession method, compared with the trajectory analysis method, provided more reliable interpretations as it is independent of time-dependent processes.
Tristan Salles, Jodie Pall, Jody M. Webster, and Belinda Dechnik
Geosci. Model Dev., 11, 2093–2110, https://doi.org/10.5194/gmd-11-2093-2018, https://doi.org/10.5194/gmd-11-2093-2018, 2018
Short summary
Short summary
We present a 1-D model of coral reefs' evolution over centennial to millennial timescales. The model enables us to estimate the effects of environmental conditions (such as oceanic variability, sedimentation rate, sea-level fluctuations or tectonics) and ecological coral competition on reef vertical accretion and stratigraphic succession. The tool can quantitatively test carbonate platform development and efficiently interpret vertical growth under various forcing scenarios.
Related subject area
Climate and Earth system modeling
COSP-RTTOV-1.0: flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design
Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)
Correction of sea surface biases in the NEMO ocean general circulation model using neural networks
Representing lateral groundwater flow from land to river in Earth system models
FINAM is not a model (v1.0): a new Python-based model coupling framework
The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7
Enhancing winter climate simulations of the Great Lakes: insights from a new coupled lake–ice–atmosphere (CLIAv1) system on the importance of integrating 3D hydrodynamics with a regional climate model
Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol–climate model ECHAM6.3–HAM2.3
Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM
Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing
ICON-HAM-lite 1.0: simulating the Earth system with interactive aerosols at kilometer scales
Process-based modeling framework for sustainable irrigation management at the regional scale: integrating rice production, water use, and greenhouse gas emissions
Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration
Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models
FLAME 1.0: a novel approach for modelling burned area in the Brazilian biomes using the maximum entropy concept
SURFER v3.0: a fast model with ice sheet tipping points and carbon cycle feedbacks for short- and long-term climate scenarios
NMH-CS 3.0: a C# programming language and Windows-system-based ecohydrological model derived from Noah-MP
A method for quantifying uncertainty in spatially interpolated meteorological data with application to daily maximum air temperature
Baseline Climate Variables for Earth System Modelling
PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
ZEMBA v1.0: an energy and moisture balance climate model to investigate Quaternary climate
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions
The ensemble consistency test: from CESM to MPAS and beyond
Linear Meta-Model optimization for regional climate models (LiMMo version 1.0)
An example of how data quality hinders progress: translating the latest findings on the regulation of leaf senescence timing in trees into the DP3 model (v1.0)
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
OpenBench: a land models evaluation system
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
ROCKE-3D 2.0: An updated general circulation model for simulating the climates of rocky planets
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The sensitivity of EC-Earth3 decadal predictions to the choice of volcanic forcing dataset: Insights for the next major eruption
A first calibration of the JULES-crop version 7.4 for rice using the novel O3-FACE experiment in China
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
Geosci. Model Dev., 18, 4935–4950, https://doi.org/10.5194/gmd-18-4935-2025, https://doi.org/10.5194/gmd-18-4935-2025, 2025
Short summary
Short summary
Satellites have observed Earth's emissions of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about Earth and the atmosphere. We present a tool that runs within Earth system models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon
Geosci. Model Dev., 18, 4899–4913, https://doi.org/10.5194/gmd-18-4899-2025, https://doi.org/10.5194/gmd-18-4899-2025, 2025
Short summary
Short summary
The most popular algorithm for calculating cloud droplet number concentrations in climate models is sensitive to parameters that control simulated aerosol particle number concentrations at different sizes. We recommend small modifications to functions in the algorithm to improve its performance. Implementing the changes in the UK Met Office climate model reduced average bias in simulated global droplet number concentrations, leading to more reflected solar radiation and a net cooling effect.
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev., 18, 4789–4804, https://doi.org/10.5194/gmd-18-4789-2025, https://doi.org/10.5194/gmd-18-4789-2025, 2025
Short summary
Short summary
Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
Chang Liao, L. Ruby Leung, Yilin Fang, Teklu Tesfa, and Robinson Negron-Juarez
Geosci. Model Dev., 18, 4601–4624, https://doi.org/10.5194/gmd-18-4601-2025, https://doi.org/10.5194/gmd-18-4601-2025, 2025
Short summary
Short summary
Understanding horizontal groundwater flow is important for understanding how water moves through the ground. Current climate models often simplify this process because they do not have information about the land surface that is detailed enough. Our study developed a new model that divides the land surface into hillslopes to better represent how groundwater flows. This model can help improve predictions of water availability and how it affects ecosystems.
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev., 18, 4483–4498, https://doi.org/10.5194/gmd-18-4483-2025, https://doi.org/10.5194/gmd-18-4483-2025, 2025
Short summary
Short summary
This study presents FINAM (
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
Geosci. Model Dev., 18, 4399–4416, https://doi.org/10.5194/gmd-18-4399-2025, https://doi.org/10.5194/gmd-18-4399-2025, 2025
Short summary
Short summary
Climate model simulations of the response to human and natural influences together, natural climate influences alone and greenhouse gases alone are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies and to underpin the next IPCC report.
Pengfei Xue, Chenfu Huang, Yafang Zhong, Michael Notaro, Miraj B. Kayastha, Xing Zhou, Chuyan Zhao, Christa Peters-Lidard, Carlos Cruz, and Eric Kemp
Geosci. Model Dev., 18, 4293–4316, https://doi.org/10.5194/gmd-18-4293-2025, https://doi.org/10.5194/gmd-18-4293-2025, 2025
Short summary
Short summary
This study introduces a new 3D lake–ice–atmosphere coupled model that significantly improves winter climate simulations for the Great Lakes compared to traditional 1D lake model coupling. The key contribution is the identification of critical hydrodynamic processes – ice transport, heat advection, and shear-driven turbulence production – that influence lake thermal structure and ice cover and explain the superior performance of 3D lake models to their 1D counterparts.
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, https://doi.org/10.5194/gmd-18-4183-2025, https://doi.org/10.5194/gmd-18-4183-2025, 2025
Short summary
Short summary
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.
Ziming Ke, Qi Tang, Jean-Christophe Golaz, Xiaohong Liu, and Hailong Wang
Geosci. Model Dev., 18, 4137–4153, https://doi.org/10.5194/gmd-18-4137-2025, https://doi.org/10.5194/gmd-18-4137-2025, 2025
Short summary
Short summary
This study assesses volcanic aerosol representation in E3SM (Energy Exascale Earth System Model), showing that an emission-based approach moderately improves temperature variability and cloud responses compared to a prescribed forcing approach, yet significant bias persists.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev., 18, 4009–4021, https://doi.org/10.5194/gmd-18-4009-2025, https://doi.org/10.5194/gmd-18-4009-2025, 2025
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025, https://doi.org/10.5194/gmd-18-3877-2025, 2025
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.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev., 18, 3799–3817, https://doi.org/10.5194/gmd-18-3799-2025, https://doi.org/10.5194/gmd-18-3799-2025, 2025
Short summary
Short summary
This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with vital physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for multi-objective optimization of rice irrigation schemes at a large scale.
Carolina A. Bieri, Francina Dominguez, Gonzalo Miguez-Macho, and Ying Fan
Geosci. Model Dev., 18, 3755–3779, https://doi.org/10.5194/gmd-18-3755-2025, https://doi.org/10.5194/gmd-18-3755-2025, 2025
Short summary
Short summary
Access to deep moisture below the Earth's surface is important for vegetation in areas of the Amazon where there is little precipitation for part of the year. Most existing numerical models of the Earth system do not adequately capture where and when deep root water uptake occurs. We address this by adding deep soil layers and a root water uptake feature to an existing model. Out modifications lead to increased dry-month transpiration and improved simulation of the annual transpiration cycle.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev., 18, 3661–3679, https://doi.org/10.5194/gmd-18-3661-2025, https://doi.org/10.5194/gmd-18-3661-2025, 2025
Short summary
Short summary
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.
Maria Lucia Ferreira Barbosa, Douglas I. Kelley, Chantelle A. Burton, Igor J. M. Ferreira, Renata Moura da Veiga, Anna Bradley, Paulo Guilherme Molin, and Liana O. Anderson
Geosci. Model Dev., 18, 3533–3557, https://doi.org/10.5194/gmd-18-3533-2025, https://doi.org/10.5194/gmd-18-3533-2025, 2025
Short summary
Short summary
As fire seasons in Brazil become increasingly severe, confidently understanding the factors driving fires is more critical than ever. To address this challenge, we developed FLAME (Fire Landscape Analysis using Maximum Entropy), a new model designed to predict fires and to analyse the spatial influence of both environmental and human factors while accounting for uncertainties. By adapting the model to different regions, we can enhance fire management strategies, making FLAME a powerful tool for protecting landscapes in Brazil and beyond.
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
Geosci. Model Dev., 18, 3081–3129, https://doi.org/10.5194/gmd-18-3081-2025, https://doi.org/10.5194/gmd-18-3081-2025, 2025
Short summary
Short summary
We present SURFER v3.0, a simple climate model designed to estimate the impact of CO2 and CH4 emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over timescales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.
Yong-He Liu and Zong-Liang Yang
Geosci. Model Dev., 18, 3157–3174, https://doi.org/10.5194/gmd-18-3157-2025, https://doi.org/10.5194/gmd-18-3157-2025, 2025
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.
Conor T. Doherty, Weile Wang, Hirofumi Hashimoto, and Ian G. Brosnan
Geosci. Model Dev., 18, 3003–3016, https://doi.org/10.5194/gmd-18-3003-2025, https://doi.org/10.5194/gmd-18-3003-2025, 2025
Short summary
Short summary
We present, analyze, and validate a methodology for quantifying uncertainty in gridded meteorological data products produced by spatial interpolation. In a validation case study using daily maximum near-surface air temperature (Tmax), the method works well and produces predictive distributions with closely matching theoretical versus actual coverage levels. Application of the method reveals that the magnitude of uncertainty in interpolated Tmax varies significantly in both space and time.
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, https://doi.org/10.5194/gmd-18-2639-2025, https://doi.org/10.5194/gmd-18-2639-2025, 2025
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.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, https://doi.org/10.5194/gmd-18-2609-2025, 2025
Short summary
Short summary
PaleoSTeHM v1.0 is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo-records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
Short summary
Short summary
Tropical ocean basins influence each other through multiple pathways and mechanisms, referred to here as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models but have obtained conflicting results. This may be partly due to differences in experiment protocols and partly due to systematic model errors. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
Short summary
Short summary
This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth's orbit. We demonstrate that ZEMBA reproduces many features of the Earth's climate for both the pre-industrial period and the Earth's most recent cold extreme – the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
Short summary
Short summary
Improving climate predictions has significant socio-economic impacts. In this study, we develop and apply a new weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. This system is meant to advance our understanding of the ocean's role in climate predictability.
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
Short summary
Short summary
Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
Short summary
Short summary
The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
Sergei Petrov, Andreas Will, and Beate Geyer
EGUsphere, https://doi.org/10.5194/egusphere-2025-710, https://doi.org/10.5194/egusphere-2025-710, 2025
Short summary
Short summary
This study introduces a new method that helps improve the accuracy of climate models by automatically selecting the best parameters to match real-world observations. Instead of manually adjusting many parameters, the method uses a mathematical tool to find the most appropriate settings for the model. It can be especially helpful for researchers who introduce new physical parameters into climate models to assess their impact on model results and optimize them along with the old ones.
Michael Meier, Christof Bigler, and Isabelle Chuine
EGUsphere, https://doi.org/10.5194/egusphere-2025-460, https://doi.org/10.5194/egusphere-2025-460, 2025
Short summary
Short summary
Formulated according to the leaf development process, the DP3 model of leaf coloring considerably contrasts previous models and allows to set up new hypotheses, e.g. on aging versus stress caused color changes. The DP3 model was as accurate as previous models and a comparison to the constant simulation of the mean date of leaf coloring indicated that noisy leaf coloring data forced the models to resort to this mean, which hinders model evaluation.
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
Short summary
Short summary
We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary
Short summary
We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
Short summary
Short summary
Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Zhongwang Wei, Qingchen Xu, Fan Bai, Xionghui Xu, Zixin Wei, Wenzong Dong, Hongbin Liang, Nan Wei, Xingjie Lu, Lu Li, Shupeng Zhang, Hua Yuan, Laibo Liu, and Yongjiu Dai
EGUsphere, https://doi.org/10.5194/egusphere-2025-1380, https://doi.org/10.5194/egusphere-2025-1380, 2025
Short summary
Short summary
Land surface models are used for simulating earth's surface interacts with the atmosphere. As models grow more complex and detailed, researchers need better tools to evaluate their performance. OpenBench, a new software system that makes evaluation process more comprehensive and efficient. It stands out by incorporating various factors and working with data at any scale which enabling scientists to incorporate new types of models and measurements as our understanding of Earth’s systems evolves.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
Short summary
Short summary
Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
Short summary
Short summary
Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Kostas Tsigaridis, Andrew S. Ackerman, Igor Aleinov, Mark A. Chandler, Thomas L. Clune, Christopher M. Colose, Anthony D. Del Genio, Maxwell Kelley, Nancy Y. Kiang, Anthony Leboissetier, Jan P. Perlwitz, Reto A. Ruedy, Gary L. Russell, Linda E. Sohl, Michael J. Way, and Eric T. Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2025-925, https://doi.org/10.5194/egusphere-2025-925, 2025
Short summary
Short summary
We present the second generation of ROCKE-3D, a generalized 3-dimensional model for use in Solar System and exoplanetary simulations of rocky planet climates. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Roberto Bilbao, Thomas J. Aubry, Matthew Toohey, and Pablo Ortega
EGUsphere, https://doi.org/10.5194/egusphere-2025-609, https://doi.org/10.5194/egusphere-2025-609, 2025
Short summary
Short summary
Large volcanic eruptions are unpredictable and can have significant climatic impacts. If one occurs, operational decadal forecasts will become invalid and must be rerun including the volcanic forcing. By analyzing the climate response in EC-Earth3 retrospective predictions, we show that idealised forcings produced with two simple models could be used in operational decadal forecasts to account for the radiative impacts of the next major volcanic eruption.
Beiyao Xu, Steven Dobbie, Huiyi Yang, Lianxin Yang, Yu Jiang, Andrew Challinor, Karina Williams, Yunxia Wang, and Tijian Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-4077, https://doi.org/10.5194/egusphere-2024-4077, 2025
Short summary
Short summary
Ozone (O3) pollution harms rice production and threatens food security. To understand these impacts, we calibrated a crop model using unique data from experiments where rice was grown in open fields under controlled O3 exposure (free air). This is the first time such data has been used to improve a model’s ability to predict how rice responds to O3 pollution. Our work provides a more accurate tool to study O3’s effects and guide strategies to protect agriculture.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
Short summary
Short summary
Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
Short summary
Short summary
We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
Short summary
Short summary
Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
Short summary
Short summary
The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
Short summary
Short summary
HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
Short summary
Short summary
We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
Short summary
Short summary
This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
Short summary
Short summary
Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
Short summary
Short summary
The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
Short summary
Short summary
CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
Short summary
Short summary
The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
Short summary
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Cited articles
Ahrens, J., Jourdain, S., O'Leary, P., Patchett, J., Rogers, D. H., and
Petersen, M.: An image-based approach to extreme scale in situ visualization
and analysis, Proceedings of the International Conference for High
Performance Computing, https://doi.org/10.1109/SC.2014.40, 2014. a
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis., NOAA Technical Memorandum NESDIS
NGDC-24, 19 pp., available at: http://www.ngdc.noaa.gov/mgg/global/global.html (last access: 23 September 2019), 2009. a
Armitage, J. J.: Short communication: flow as distributed lines within the landscape, Earth Surf. Dynam., 7, 67–75, https://doi.org/10.5194/esurf-7-67-2019, 2019. a, b, c, d
Barnes, R.: Parallel non-divergent flow accumulation for trillion cell
digital elevation models on desktops or clusters, Environ. Model.
Softw., 92, 202–212, https://doi.org/10.1016/j.envsoft.2017.02.022, 2017. a, b
Barnes, R.: Accelerating a fluvial incision and landscape evolution model
with parallelism, Geomorphology, 330, 28–39,
https://doi.org/10.1016/j.geomorph.2019.01.002, 2019. a, b, c
Beaumont, C., Fullsack, P., and Hamilton, J.: Erosional control of active
compressional orogens, in: Thrust Tectonics, edited by: McClay, K. R.,
Chapman Hall, New York, 1–18, https://doi.org/10.1007/978-94-011-3066-0_1, 1992. a, b
Bellugi, D., Dietrich, W. E., Stock, J., McKean, J., Kazian, B., and Hargrove,
P.: Spatially explicit shallow landslide susceptibility mapping over large
areas, in: Fifth International Conference on Debris-flow Hazards Mitigation,
Mechanics, Prediction and Assessment, edited by: Genevois, R., Hamilton, D. L., and Prestininzi, A., Casa Editrice Universita La Sapienza, Rome, pp. 309–407, https://doi.org/10.4408/IJEGE.2011-03.B-045, 2011. a
Beucher, R., Moresi, L., Giordani, J., Mansour, J., Sandiford, D., Farrington,
R., Mondy, L., Mallard, C., Rey, P., Duclaux, G., Kaluza, O., Laik, A., and
Moroon, S.: UWGeodynamics: A teaching and research tool for numerical
geodynamic modelling, J. Open Source Softw., 4, 1136,
https://doi.org/10.21105/joss.01136, 2019. a
Bianchi, V., Salles, T., Ghinassi, M., Billi, P., Dallanave, E., and Duclaux,
G.: Numerical modeling of tectonically driven river dynamics and deposition
in an upland incised valley, Geomorphology, 241, 353–370,
https://doi.org/10.1016/j.geomorph.2015.04.007, 2015. a
Bovy, B., Braun, J., and Demoulin, A.: Soil production and hillslope transport
in mid-latitudes during the last glacial-interglacial cycle: a combined data
and modelling approach in northern Ardennes, Earth Surf. Proc. Land., 41, 1758–1775, https://doi.org/10.1002/esp.3993, 2016. a, b
Carretier, S., Martinod, P., Reich, M., and Godderis, Y.: Modelling sediment clasts transport during landscape evolution, Earth Surf. Dynam., 4, 237–251, https://doi.org/10.5194/esurf-4-237-2016, 2016. a
Chen, A., Darbon, J., and Morel, J.-M.: Landscape evolution models: a review
of their fundamental equations, Geomorphology, 219, 68–86, 2014. a
Cordonnier, G., Bovy, B., and Braun, J.: A versatile, linear complexity algorithm for flow routing in topographies with depressions, Earth Surf. Dynam., 7, 549–562, https://doi.org/10.5194/esurf-7-549-2019, 2019. a, b
Coulthard, T. J., Macklin, M. G., and Kirkby, M. J.: A cellular model of
Holocene upland river basin and alluvial fan evolution, Earth Surf. Proc.
Land., 27, 269–288, https://doi.org/10.1002/esp.318, 2002. a, b
Davy, P. and Lague, D.: Fluvial erosion/transport equation of landscape
evolution models revisited., J. Geophys. Res.-Earth, 114, F03007,
https://doi.org/10.1029/2008JF001146, 2009. a, b
DiBiase, R. A., Whipple, K. X., Heimsath, A. M., and Ouimet, W. B.: Landscape
form and millennial erosion rates in the San Gabriel Mountains, CA,
Earth Planet. Sc. Lett., 289, 134–144, 2010. a
Dietrich, W. E., Bellugi, D., Sklar, L. S., Stock, J., Heimsath, A. M., and
Roering, J. J.: Geomorphic transport laws for predicting landscape form and
dynamics, in: Prediction in
Geomorphology, edited by: Wilcock, P. R. and Iverson, R. M., 135, 103–132, Blackwell Publishing Ltd, 2003. a
Eddins, S.: Upslope area – Forming and solving the flow matrix, MathWorks, available at:
http://blogs.mathworks.com/steve/2007/08/07/upslope-area-flow-matrix (last access: 23 September 2019), 2007. a
Falgout, R., Kolev, T., Schroder, J., Vassilevski, P., and Yang, U. M.:
Lawrence Livermore National Laboratory, HYPRE Package, available at:
https://computation.llnl.gov/casc/hypre/software.html (last access: 23 September 2019), 2012. a
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1-km spatial resolution
climate surfaces for global land areas, Int. J. Climatol.,
37, 4302–4315, https://doi.org/10.1002/joc.5086, 2017. a
Foufoula-Georgiou, E., Ganti, V., and Dietrich, W. E.: A nonlocal theory of
sediment transport on hillslopes, J. Geophys. Res.-Earth, 115, F00A16, https://doi.org/10.1029/2009JF001280, 2010. a
Grieve, S., Mudd, S., and Hurst, M.: How long is a hillslope?, Earth Surf.
Process. Landforms, 41, 1039–1054, https://doi.org/10.1002/esp.3884,
2016a. a
Grieve, S. W. D., Mudd, S. M., Hurst, M. D., and Milodowski, D. T.: A nondimensional framework for exploring the relief structure of landscapes, Earth Surf. Dynam., 4, 309–325, https://doi.org/10.5194/esurf-4-309-2016, 2016b. a
Hobley, D. E. J., Sinclar, H. D., Mudd, S. M., and Cowie, P. A.: Field
calibration of sediment flux dependent river incision, J. Geophys. Res.-Earth, 116, F04017, https://doi.org/10.1029/2010JF001935, 2011. a
Hobley, D. E. J., Adams, J. M., Nudurupati, S. S., Hutton, E. W. H., Gasparini, N. M., Istanbulluoglu, E., and Tucker, G. E.: Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics, Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, 2017. a, b, c
Hodge, R. A. and Hoey, T. B.: Upscaling from grain-scale processes to
alluviation in bedrock channels using a cellular automaton model, J. Geophys.
Res., 117, F01017, https://doi.org/10.1029/2011JF002145, 2012. a
Jenson, S. and Domingue, J.: Extracting topographic structure from digital
elevation data for geographic information system analysis, Photogramm. Eng.
Remote Sens., 54, 1593–1600, 1988. a
Lague, D.: Reduction of long-term bedrock incision efficiency by short-term
alluvial cover intermittency, J. Geophys. Res., 115, F02011,
https://doi.org/10.1029/2008JF001210, 2010. a
Larsen, I. J. and Montgomery, D. R.: Landslide erosion coupled to tectonics and river incision, Nat. Geosci., 5, 468–473, 2012. a
Li, F., Griffiths, C. M., Dyt, C. P., Weill, P., Feng, M., Salles, T., and
Jenkins, C.: Multigrain seabed sediment transport modelling for the
south-west Australian Shelf, Mar. Freshwater Res. 60, 774–785,
https://doi.org/10.1071/MF08049, 2009. a
Mark, D. M.: Network models in geomorphology, Modelling Geomorphological
Systems, edited by: Anderson, M. G., Wiley, NY, 73–97, 1988. a
Milliman, J. and Syvitski, J.: Geomorphic/tectonic control of sediment
discharge to the ocean: the importance of small mountainous rivers,
J. Geol., 100, 525–544, 1992. a
Murphy, B. P., Johnson, J. P. L., Gasparini, N. M., and Sklar, L. S.: Chemical weathering as a mechanism for the climatic control of bedrock river incision, Nature, 532, 223–227, 2016. a
O'Callaghan, J. F. and Mark, D. M.: The extraction of drainage networks from
digital elevation data, Comput. Vision Graph., 28,
323–344, 1984. a
Pelletier, J. D.: Persistent drainage migration in a numerical landscape
evolution model, Geophys. Res. Lett., 31, L20501, https://doi.org/10.1029/2004GL020802, 2004. a
Perron, J. T. and Hamon, J. L.: Equilibrium form of horizontally retreating,
soil-mantled hillslopes: Model development and application to a groundwater
sapping landscape, J. Geophys. Res., 117, F01027, https://doi.org/10.1029/2011JF002139, 2012. a, b
Planchon, O. and Darboux, F.: A fast, simple and versatile algorithm to fill
the depressions of digital elevation models, Catena, 46, 159–176,
https://doi.org/10.1016/S0341-8162(01)00164-3, 2002. a
Quinn, P., Beven, K., Chevallier, P., and Planchon, O.: The prediction of
hillslope flow paths for distributed hydrological modelling using digital
terrain models, Hydrol. Process., 5, 59–79, https://doi.org/10.1002/hyp.3360050106,
1991. a
Saad, Y.: Iterative Methods for Sparse Linear Systems, Society for Industrial and Applied Mathematics, Philadelphia, PA, 2003. a
Salles, T.: Badlands: A parallel basin and landscape dynamics model, SoftwareX, 5, 195–202, 2016. a
Salles, T.: eSCAPE: parallel global-scale landscape evolution model, J. Open Source Softw., 3, 964, https://doi.org/10.21105/joss.00964, 2018. a, b
Salles, T.: Geodels/eSCAPE: eSCAPE: Regional to Global Scale Landscape
Evolution Model v2.0 (Version v2.0), Zenodo, https://doi.org/10.5281/zenodo.3239569 , 2019. a
Salles, T. and Duclaux, G.: Combined hillslope diffusion and sediment
transport simulation applied to landscape dynamics modelling., Earth Surf.
Process Landf., 40, 823–839, 2015. a
Salles, T., Griffiths, C., Dyt, C., and Li, F.: Australian shelf sediment
transport responses to climate change-driven ocean perturbations, Mar.
Geol., 282, 268–274, 2011. a
Salles, T., Ding, X., and Brocard, G.: pyBadlands: A framework to simulate
sediment transport, landscape dynamics and basin stratigraphic evolution
through space and time, PLOS ONE, 13, 1–24,
https://doi.org/10.1371/journal.pone.0195557, 2018. a, b
Schoorl, J. M., Sonneveld, M. P. W., and Veldkamp, A.: Three-dimensional
landscape process modelling: the effect of DEM resolution, Earth Surf. Proc.
Land., 25, 1025–1034, 2000. a
Schwanghart, W. and Kuhn, N. J.: Topotoolbox: A set of Matlab functions for
topographic analysis, Environ. Modell. Softw., 25, 770–781,
https://doi.org/10.1016/j.envsoft.2009.12.002, 2010. a
Shobe, C. M., Tucker, G. E., and Barnhart, K. R.: The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution, Geosci. Model Dev., 10, 4577–4604, https://doi.org/10.5194/gmd-10-4577-2017, 2017. a, b, c
Simoes, M., Braun, J., and Bonnet, S.: Continental-scale erosion and transport laws: A new approach to quantitatively investigate macroscale landscapes and associated sediment fluxes over the geological past, Geochem. Geophy. Geosy., 11, Q09001, https://doi.org/10.1029/2010GC003121, 2010. a
Simpson, G. and Schlunegger, F.: Topographic evolution and morphology of
surfaces evolving in response to coupled fluvial and hillslope sediment
transport, J. Geophys. Res., 108, 2300, https://doi.org/10.1029/2002JB002162, 2003. a
Snyder, N. P., Whipple, K. X., Tucker, G. E., and Merritts, D. J.: Importance
of a stochastic distribution of floods and erosion thresholds in the bedrock
river incision problem, Water Resour. Res., 108, 2117,
https://doi.org/10.1029/2001JB001655, 2003. a
Syvitski, J., Peckham, S., Hilberman, R., and T., M.: Predicting the
terrestrial flux of sediment to the global ocean: a planetary perspective,
Sediment. Geol., 162, 5–24, https://doi.org/10.1016/S0037-0738(03)00232-X, 2003. a
Tarboton, D. G.: A new method for the determination of flow directions and
upslope areas in grid digital elevation models, Water Resour. Res., 33,
309–319, https://doi.org/10.1029/96WR03137, 1997. a
Tarboton, D. G.: Utah State University, TauDEM Web page, available at:
http://hydrology.usu.edu/taudem/taudem5 (last access: 23 September 2019), 2013. a
Tesfa, T., Tarboton, D., Watson, D., Schreuders, K., Baker, M., and Wallace,
R.: Extraction of hydrological proximity measures from DEMs using parallel
processing, Environ. Model. Softw., 26, 1696–1709, 2011. a
Thieulot, C., Steer, P., and Huismans, R. S.: Three-dimensional numerical
simulations of crustal systems undergoing orogeny and subjected to surface
processes, Geochem. Geophy. Geosy., 15, 4936–4957, 2014. a
Tomkin, J. H., Brandon, M. T., Pazzaglia, F. J., Barbour, J. R., and Willett,
S. D.: Quantitative testing of bedrock incision models for the Clearwater
River, NW Washington State, J. Geophys. Res., 108, 2308,
https://doi.org/10.1029/2001JB000862, 2003. a
Tucker, G. E. and Bradley, D. N.: Trouble with diffusion: Reassessing hillslope erosion laws with a particle-based model, J. Geophys. Res.-Earth, 115, F00A10, https://doi.org/10.1029/2009JF001264, 2010. a
Tucker, G. E. and Bras, R. L.: Hillslope processes, drainage density, and
landscape morphology, Water Resour. Res., 34, 2751–2764, 1998. a
Tucker, G. E. and Slingerland, R. L.: Erosional dynamics, flexural isostasy,
and long-lived escarpments: A numerical modeling study, J. Geophys. Res., 99,
12229–12243, https://doi.org/10.1029/94JB00320, 2017. a
Tucker, G. E., Lancaster, S. T., Gasparini, N. M., Bras, R. L., and Rybarczyk, S. M.: An object-oriented framework for distributed hydrologic and geomorphic
modeling using triangulated irregular networks, Comput. Geosci., 27,
959–973, 2001. a
Turowski, J. M. and Hodge, R.: A probabilistic framework for the cover effect in bedrock erosion, Earth Surf. Dynam., 5, 311–330, https://doi.org/10.5194/esurf-5-311-2017, 2017. a
Valla, P. G., van der Beek, P. A., and Lague, D.: Fluvial incision into
bedrock: insights from morphometric analysis and numerical modeling of gorges
incising glacial hanging valleys (Western Alps, France), J. Geophys. Res.-Earth, 115, F02010, https://doi.org/10.1029/2008JF001079, 2010. a
van der Beek, P. and Bishop, P.: Cenozoic river profile development in the
Upper Lachlan catchment (SE Australia) as a test of quantitative fluvial
incision models, J. Geophys. Res., 108, 2309, https://doi.org/10.1029/2002JB002125, 2003. a
Wallace, R. M., Tarboton, D. G., Watson, D. W., Schreuders, K. A. T., and
Tesfa, T. K.: Parallel algorithms for processing hydrologic properties from
digital terrain, in: Sixth International Conference on Geographic
Information Science, edited by: Purves, R. and Weibel, R., Zurich,
Switzerland, 2010. a
Wallis, C., Wallace, R. M., Tarboton, D. G., Watson, D. W., Schreuders, K.
A. T., and Tesfa, T. K.: Hydrologic terrain processing using parallel
computing, in: 18th World IMACS Congress and MODSIM09 International Congress
on Modelling and Simulation, edited by: Anderssen, R. S., Braddock, R. D., and Newham, L. T. H., 2540–2545, 2009. a, b
Wang, L. and Liu, H.: An efficient method for identifying and filling surface
depressions in digital elevation models for hydrologic analysis and
modelling, Int. J. Geogr. Inf. Sci., 20,
193–213, https://doi.org/10.1080/13658810500433453, 2006. a
Wei, H., Zhou, G., and Fu, S.: Efficient Priority-Flood depression filling in
raster digital elevation models, Int. J. Digit Earth, 12, 415–427, https://doi.org/10.1080/17538947.2018.1429503, 2018. a
Willgoose, G. R., Bras, R. L., and Rodriguez-Iturbe, I.: A physically based
coupled network growth and hillslope evolution model: 1 – Theory, Water
Resour. Res., 27, 1671–1684, https://doi.org/10.1029/91WR00935, 1991.
a, b
Yang, R., Willett, S. D., and Goren, L.: In situ low-relief landscape formation
as a result of river network disruption, Nature, 526–529,
https://doi.org/10.1038/nature14354, 2015. a
Yıldırım, A., Watson, D., Tarboton, D., and Wallace, R.: A virtual tile
approach to raster-based calculations of large digital elevation models in a
shared-memory system, Comput. Geosci., 82, 78–88, 2015. a
Zhou, G., Sun, Z., and Fu, S.: An efficient variant of the priority-flood
algorithm for filling depressions in raster digital elevation models,
Comput. Geosci., 90, 87–96, https://doi.org/10.1016/j.cageo.2016.02.021, 2016. a
Zhou, G., Liu, X., Fu, S., and Sun, Z.: Parallel Identification and Filling of
Depressions in Raster Digital Elevation Models, Int. J. Geogr. Inf. Sci., 31, 1061–1078, https://doi.org/10.1080/13658816.2016.1262954, 2017. a, b
Short summary
This paper presents a new numerical model able to simulate for the first time the evolution of Earth's surface at a global scale under different precipitation, sea level, and tectonic conditions. This is significant as it can help to bridge the gap between local- and global-scale predictions of Earth's past and future variations.
This paper presents a new numerical model able to simulate for the first time the evolution of...
