Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2155-2019
© 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-12-2155-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
03 Jun 2019
Model experiment description paper |
| 03 Jun 2019
| 03 Jun 2019
The Monash Simple Climate Model experiments (MSCM-DB v1.0): an interactive database of mean climate, climate change, and scenario simulations
Dietmar Dommenget
CORRESPONDING AUTHOR
Monash University, School of Earth, Atmosphere and Environment, Clayton, Victoria 3800, Australia
Kerry Nice
Monash University, School of Earth, Atmosphere and Environment, Clayton, Victoria 3800, Australia
Transport, Health, and Urban Design Hub, Faculty of Architecture, Building,
and Planning, University of Melbourne, Victoria 3010, Australia
Tobias Bayr
GEMOAR Helmholtz Centre for Ocean Research, Düsternbrooker Weg 20, 24105 Kiel, Germany
Dieter Kasang
DKRZ, Hamburg, Germany
Christian Stassen
Monash University, School of Earth, Atmosphere and Environment, Clayton, Victoria 3800, Australia
Michael Rezny
Monash University, School of Earth, Atmosphere and Environment, Clayton, Victoria 3800, Australia
Related authors
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblüh, Clarissa Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2473, https://doi.org/10.5194/egusphere-2025-2473, 2025
Short summary
Short summary
ICON XPP is a newly developed Earth System model configuration based on the ICON modeling framework. It merges accomplishments from the recent operational numerical weather prediction model with well-established climate components for the ocean, land and ocean-biogeochemistry. ICON XPP reaches typical targets of a coupled climate simulation, and is able to run long integrations and large-ensemble experiments, making it suitable for climate predictions and projections, and for climate research.
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.
Zhiang Xie and Dietmar Dommenget
EGUsphere, https://doi.org/10.5194/egusphere-2023-370, https://doi.org/10.5194/egusphere-2023-370, 2023
Preprint archived
Short summary
Short summary
Using numeric modelling, the global interaction between the climate system and ice sheets are examined in this study. The results show the existence of ice sheets slows the response of the climate system to external forcings and enhances the response in high latitude in Northern Hemisphere. Some interactions amplify the climate response, such as the ice-albedo, ice latent heat and topography feedbacks, while others damp or shift the climate response, such as snowfall and sea level feedbacks.
Zhiang Xie, Dietmar Dommenget, Felicity S. McCormack, and Andrew N. Mackintosh
Geosci. Model Dev., 15, 3691–3719, https://doi.org/10.5194/gmd-15-3691-2022, https://doi.org/10.5194/gmd-15-3691-2022, 2022
Short summary
Short summary
Paleoclimate research requires better numerical model tools to explore interactions among the cryosphere, atmosphere, ocean and land surface. To explore those interactions, this study offers a tool, the GREB-ISM, which can be run for 2 million model years within 1 month on a personal computer. A series of experiments show that the GREB-ISM is able to reproduce the modern ice sheet distribution as well as classic climate oscillation features under paleoclimate conditions.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Christian Stassen, Dietmar Dommenget, and Nicholas Loveday
Geosci. Model Dev., 12, 425–440, https://doi.org/10.5194/gmd-12-425-2019, https://doi.org/10.5194/gmd-12-425-2019, 2019
Short summary
Short summary
In this research article, we describe the development of a new model for the water cycle (evaporation, precipitation and transport) for a simple climate model called GREB. Before this work, the water cycle in GREB was merely a dummy. We compare our simple model against more complex models and find a similar skill. The results illustrate that the new GREB model's water cycle is a useful tool to study the changes of the water cycle to external forcings like El Niño or climate change.
Duncan Ackerley, Robin Chadwick, Dietmar Dommenget, and Paola Petrelli
Geosci. Model Dev., 11, 3865–3881, https://doi.org/10.5194/gmd-11-3865-2018, https://doi.org/10.5194/gmd-11-3865-2018, 2018
Short summary
Short summary
Climate models have been run using observed sea surface temperatures to identify biases in the atmospheric circulation. In this work, land surface temperatures are also constrained, which is not routinely done. Experiments include increasing sea surface temperatures, quadrupling atmospheric carbon dioxide and increasing solar radiation. The response of the land surface is then allowed or suppressed, and the global climate is evaluated. Information on how to obtain the model data is also given.
Duncan Ackerley and Dietmar Dommenget
Geosci. Model Dev., 9, 2077–2098, https://doi.org/10.5194/gmd-9-2077-2016, https://doi.org/10.5194/gmd-9-2077-2016, 2016
Short summary
Short summary
In order to evaluate climate models, scientists have historically run them using prescribed (for example observed) sea surface temperatures; however, no such restriction is typically applied to the land. This study presents a method of prescribing the land temperatures in a climate model and shows that the resultant climate simulation is consistent with the free running simulation. Such a model will be useful for perturbing and fixing surface temperatures globally, as demonstrated in this paper.
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblüh, Clarissa Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2473, https://doi.org/10.5194/egusphere-2025-2473, 2025
Short summary
Short summary
ICON XPP is a newly developed Earth System model configuration based on the ICON modeling framework. It merges accomplishments from the recent operational numerical weather prediction model with well-established climate components for the ocean, land and ocean-biogeochemistry. ICON XPP reaches typical targets of a coupled climate simulation, and is able to run long integrations and large-ensemble experiments, making it suitable for climate predictions and projections, and for climate research.
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.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
Short summary
Short summary
The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Jake W. Casselman, Joke F. Lübbecke, Tobias Bayr, Wenjuan Huo, Sebastian Wahl, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 471–487, https://doi.org/10.5194/wcd-4-471-2023, https://doi.org/10.5194/wcd-4-471-2023, 2023
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) has remote effects on the tropical North Atlantic (TNA), but the connections' nonlinearity (strength of response to an increasing ENSO signal) is not always well represented in models. Using the Community Earth System Model version 1 – Whole Atmosphere Community Climate Mode (CESM-WACCM) and the Flexible Ocean and Climate Infrastructure version 1, we find that the TNA responds linearly to extreme El Niño but nonlinearly to extreme La Niña for CESM-WACCM.
Zhiang Xie and Dietmar Dommenget
EGUsphere, https://doi.org/10.5194/egusphere-2023-370, https://doi.org/10.5194/egusphere-2023-370, 2023
Preprint archived
Short summary
Short summary
Using numeric modelling, the global interaction between the climate system and ice sheets are examined in this study. The results show the existence of ice sheets slows the response of the climate system to external forcings and enhances the response in high latitude in Northern Hemisphere. Some interactions amplify the climate response, such as the ice-albedo, ice latent heat and topography feedbacks, while others damp or shift the climate response, such as snowfall and sea level feedbacks.
Zhiang Xie, Dietmar Dommenget, Felicity S. McCormack, and Andrew N. Mackintosh
Geosci. Model Dev., 15, 3691–3719, https://doi.org/10.5194/gmd-15-3691-2022, https://doi.org/10.5194/gmd-15-3691-2022, 2022
Short summary
Short summary
Paleoclimate research requires better numerical model tools to explore interactions among the cryosphere, atmosphere, ocean and land surface. To explore those interactions, this study offers a tool, the GREB-ISM, which can be run for 2 million model years within 1 month on a personal computer. A series of experiments show that the GREB-ISM is able to reproduce the modern ice sheet distribution as well as classic climate oscillation features under paleoclimate conditions.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Katja Matthes, Arne Biastoch, Sebastian Wahl, Jan Harlaß, Torge Martin, Tim Brücher, Annika Drews, Dana Ehlert, Klaus Getzlaff, Fritz Krüger, Willi Rath, Markus Scheinert, Franziska U. Schwarzkopf, Tobias Bayr, Hauke Schmidt, and Wonsun Park
Geosci. Model Dev., 13, 2533–2568, https://doi.org/10.5194/gmd-13-2533-2020, https://doi.org/10.5194/gmd-13-2533-2020, 2020
Short summary
Short summary
A new Earth system model, the Flexible Ocean and Climate Infrastructure (FOCI), is introduced, consisting of a high-top atmosphere, an ocean model, sea-ice and land surface model components. A unique feature of FOCI is the ability to explicitly resolve small-scale oceanic features, for example, the Agulhas Current and the Gulf Stream. It allows to study the evolution of the climate system on regional and seasonal to (multi)decadal scales and bridges the gap to coarse-resolution climate models.
Naika Meili, Gabriele Manoli, Paolo Burlando, Elie Bou-Zeid, Winston T. L. Chow, Andrew M. Coutts, Edoardo Daly, Kerry A. Nice, Matthias Roth, Nigel J. Tapper, Erik Velasco, Enrique R. Vivoni, and Simone Fatichi
Geosci. Model Dev., 13, 335–362, https://doi.org/10.5194/gmd-13-335-2020, https://doi.org/10.5194/gmd-13-335-2020, 2020
Short summary
Short summary
We developed a novel urban ecohydrological model (UT&C v1.0) that is able to account for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements in three cities in different climates (Singapore, Melbourne, Phoenix) and can be used to assess urban climate mitigation strategies that aim at increasing or changing urban green cover.
Ashley M. Broadbent, Andrew M. Coutts, Kerry A. Nice, Matthias Demuzere, E. Scott Krayenhoff, Nigel J. Tapper, and Hendrik Wouters
Geosci. Model Dev., 12, 785–803, https://doi.org/10.5194/gmd-12-785-2019, https://doi.org/10.5194/gmd-12-785-2019, 2019
Short summary
Short summary
We present a simple model for assessing the cooling impacts of vegetation and water features (green and blue infrastructure) in urban environments. This model is designed to be computationally efficient so that those without technical knowledge or access to high-performance computers can use it. TARGET can be used to model average street-level air temperature at canyon to block scales (e.g. 100 m resolution). The model is carefully designed to provide reliable and accurate cooling estimates.
Christian Stassen, Dietmar Dommenget, and Nicholas Loveday
Geosci. Model Dev., 12, 425–440, https://doi.org/10.5194/gmd-12-425-2019, https://doi.org/10.5194/gmd-12-425-2019, 2019
Short summary
Short summary
In this research article, we describe the development of a new model for the water cycle (evaporation, precipitation and transport) for a simple climate model called GREB. Before this work, the water cycle in GREB was merely a dummy. We compare our simple model against more complex models and find a similar skill. The results illustrate that the new GREB model's water cycle is a useful tool to study the changes of the water cycle to external forcings like El Niño or climate change.
Jennifer Schröter, Daniel Rieger, Christian Stassen, Heike Vogel, Michael Weimer, Sven Werchner, Jochen Förstner, Florian Prill, Daniel Reinert, Günther Zängl, Marco Giorgetta, Roland Ruhnke, Bernhard Vogel, and Peter Braesicke
Geosci. Model Dev., 11, 4043–4068, https://doi.org/10.5194/gmd-11-4043-2018, https://doi.org/10.5194/gmd-11-4043-2018, 2018
Short summary
Short summary
In this paper, we introduce the most up-to-date version of the flexible tracer framework for the ICOsahedral Nonhydrostatic model with
Aerosols and Reactive Trace gases (ICON-ART).
We performed multiple simulations using different ICON physics configurations for weather and climate with ART.
The flexible tracer framework within ICON-ART 2.1 suits the demands of a large variety of different applications ranging from numerical weather prediction to climate integrations.
Duncan Ackerley, Robin Chadwick, Dietmar Dommenget, and Paola Petrelli
Geosci. Model Dev., 11, 3865–3881, https://doi.org/10.5194/gmd-11-3865-2018, https://doi.org/10.5194/gmd-11-3865-2018, 2018
Short summary
Short summary
Climate models have been run using observed sea surface temperatures to identify biases in the atmospheric circulation. In this work, land surface temperatures are also constrained, which is not routinely done. Experiments include increasing sea surface temperatures, quadrupling atmospheric carbon dioxide and increasing solar radiation. The response of the land surface is then allowed or suppressed, and the global climate is evaluated. Information on how to obtain the model data is also given.
Bryan N. Lawrence, Michael Rezny, Reinhard Budich, Peter Bauer, Jörg Behrens, Mick Carter, Willem Deconinck, Rupert Ford, Christopher Maynard, Steven Mullerworth, Carlos Osuna, Andrew Porter, Kim Serradell, Sophie Valcke, Nils Wedi, and Simon Wilson
Geosci. Model Dev., 11, 1799–1821, https://doi.org/10.5194/gmd-11-1799-2018, https://doi.org/10.5194/gmd-11-1799-2018, 2018
Short summary
Short summary
Weather and climate models consist of complex software evolving in response to both scientific requirements and changing computing hardware. After years of relatively stable hardware, more diversity is arriving. It is possible that this hardware diversity and the pace of change may lead to an inability for modelling groups to manage their software development. This
chasmbetween aspiration and reality may need to be bridged by large community efforts rather than traditional
in-houseefforts.
Duncan Ackerley and Dietmar Dommenget
Geosci. Model Dev., 9, 2077–2098, https://doi.org/10.5194/gmd-9-2077-2016, https://doi.org/10.5194/gmd-9-2077-2016, 2016
Short summary
Short summary
In order to evaluate climate models, scientists have historically run them using prescribed (for example observed) sea surface temperatures; however, no such restriction is typically applied to the land. This study presents a method of prescribing the land temperatures in a climate model and shows that the resultant climate simulation is consistent with the free running simulation. Such a model will be useful for perturbing and fixing surface temperatures globally, as demonstrated in this paper.
Related subject area
Climate and Earth system modeling
SASIEv.1: a framework for seasonal and multi-centennial Arctic sea ice emulation
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)
Sian Megan Chilcott, Malte Meinshausen, and Dirk Notz
Geosci. Model Dev., 18, 4965–4982, https://doi.org/10.5194/gmd-18-4965-2025, https://doi.org/10.5194/gmd-18-4965-2025, 2025
Short summary
Short summary
Climate models are expensive to run and often underestimate how sensitive Arctic sea ice is to climate change. To address this, we developed a simple model that emulates the response of sea ice to global warming. We find that the remaining carbon dioxide (CO2) emissions that will avoid a seasonally ice-free Arctic Ocean are lower than previous estimates of 821 Gt of CO2. Our model also provides insights into the future of winter sea ice, examining a larger ensemble than previously possible.
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.
Cited articles
Berger, A. and Loutre, M. F.: Insolation Values for the Climate of
the Last 10000000 Years, Quaternary Sci. Rev., 10, 297–317, 1991.
Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama,
M., Pincus, R., Shepherd, T. G., Sherwood, S. C., Siebesma, A. P.,
Sobel, A. H., Watanabe, M., and Webb, M. J.: How well do we understand and
evaluate climate change feedback processes?, J. Climate, 19, 3445–3482,
2006.
Bony, S., Stevens, B., Frierson, D. M. W., Jakob, C., Kageyama, M., Pincus,
R., Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H.,
Watanabe, M., and Webb, M. J.: Clouds, circulation and climate
sensitivity, Nat. Geosci., 8, 261–268, 2015.
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P.,
Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K.,
Sherwood, S., Stevens, B., and Zhang, X. Y: Clouds and Aerosols, in: Climate
Change 2013: The Physical Science Basis, Contribution of Working Group I to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J.,
Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., Peterchmitt,
J.-Y., Abe-Ouchi, A., Crucifix, M., Driesschaert, E., Fichefet, Th., Hewitt,
C. D., Kageyama, M., Kitoh, A., Laîné, A., Loutre, M.-F., Marti, O., Merkel,
U., Ramstein, G., Valdes, P., Weber, S. L., Yu, Y., and Zhao, Y.: Results of
PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum – Part
1: experiments and large-scale features, Clim. Past, 3, 261–277,
https://doi.org/10.5194/cp-3-261-2007, 2007.
Cess, R. D., Zhang, M.-H., Potter, G. L., Barker, H. W., Colman, R. A.,
Dazlich, D. A., Del Genio, A. D., Esch, M., Fraser, J. R., Galin, V., Gates,
W. L.,
Hack, J. J., Ingram, W. J., Kiehl, J. T., Lacis, A. A., Le Treut, H.,
Li, Z.-X.,
Liang, X.-Z., Mahfouf, J.-F., McAvaney, B. J., Meleshko, V. P., Morcrette,
J.-J.,
Randal, D. A., Roeckner, E., Royer, J.-F., Sokolov, A. P., Sporyshev, P. V.,
Taylor, K. E., Wang, W.-C., and Wetherald, R. T.: Uncertainties in Carbon-Dioxide
Radiative Forcing in Atmospheric General-Circulation Models, Science, 262,
1252–1255, 1993.
Cubasch, U., Voss, R., Hegerl, G. C., Waszkewitz, J., and Crowley, T. J.:
Simulation of the influence of solar radiation variations on the global
climate with an ocean-atmosphere general circulation model, Clim. Dynam., 13,
757–767, 1997.
Donohoe, A., Frierson, D. M. W., and Battisti, D. S.: The effect of
ocean mixed layer depth on climate in slab ocean aquaplanet experiments,
Clim. Dynam., 43, 1041–1055, https://doi.org/10.1007/s00382-013-1843-4, 2014.
Dommenget, D.: Analysis of the Model Climate Sensitivity Spread Forced
by Mean Sea Surface Temperature Biases, J. Climate, 25, 7147–7162, 2012.
Dommenget, D. and Floter, J.: Conceptual understanding of climate
change with a globally resolved energy balance model, Clim. Dynam., 37,
2143–2165, 2011.
Dommenget, D., Nice, K., Bayr, T., Kasang, D., Stassen, C., and Rezny, M.:
Monash Simple Climate Model (webpage interface),
https://doi.org/10.4225/03/5a8cadac8db60, 2018.
Forster, P. M., Andrews, T., Good, P., Gregory, J. M., Jackson, L. S., and
Zelinka, M.: Evaluating adjusted forcing and model spread for historical
and future scenarios in the CMIP5 generation of climate models, J. Geophys. Res.-Atmos.,
118, 1139–1150, 2013.
Goosse, H., Brovkin, V., Fichefet, T., Haarsma, R., Huybrechts, P., Jongma,
J., Mouchet, A., Selten, F., Barriat, P.-Y., Campin, J.-M., Deleersnijder,
E., Driesschaert, E., Goelzer, H., Janssens, I., Loutre, M.-F., Morales
Maqueda, M. A., Opsteegh, T., Mathieu, P.-P., Munhoven, G., Pettersson, E.
J., Renssen, H., Roche, D. M., Schaeffer, M., Tartinville, B., Timmermann,
A., and Weber, S. L.: Description of the Earth system model of intermediate
complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633,
https://doi.org/10.5194/gmd-3-603-2010, 2010.
Hansen, J., Sato, M., and Ruedy, R.: Radiative forcing and climate
response, J. Geophys. Res.-Atmos., 102, 6831–6864, 1997.
Held, I. M., Winton, M., Takahashi, K., Delworth, T., Zeng, F. R., and
Vallis, G. K.: Probing the Fast and Slow Components of Global Warming by
Returning Abruptly to Preindustrial Forcing, J. Climate, 23, 2418–2427, 2010.
Huybers, P.: Early Pleistocene glacial cycles and the integrated
summer insolation forcing, Science, 313, 508–511, 2006.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C.,
Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.:
The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77,
437–471, 1996.
Kang, S. M., Seager, R., Frierson, D. M. W., and Liu, X.: Croll
revisited: Why is the northern hemisphere warmer than the southern
hemisphere?, Clim. Dynam., 44, 1457–1472, https://doi.org/10.1007/s00382-014-2147-z, 2015.
Kasting, J. F., Whitmire, D. P., and Reynolds, R. T.: Habitable Zones
around Main-Sequence Stars, Icarus, 101, 108–128, 1993.
Kiehl, J. T. and Ramanathan, V.: Radiative Heating Due to Increased
CO2 – the Role of H2O Continuum Absorption in the 12–18 Mu-M Region, J.
Atmos. Sci., 39, 2923–2926, 1982.
Knutti, R., Meehl, G. A., Allen, M. R., and Stainforth, D. A.:
Constraining climate sensitivity from the seasonal cycle in surface
temperature, J. Climate, 19, 4224–4233, 2006.
Lorbacher, K., Dommenget, D., Niiler, P. P., and Kohl, A.: Ocean mixed
layer depth: A subsurface proxy of ocean-atmosphere variability, J. Geophys. Res.-Oceans,
111, C07010, https://doi.org/10.1029/2003JC002157, 2006.
Meehl, G. A., Arblaster, J. M., Matthes, K., Sassi, F., and van Loon, H.:
Amplifying the Pacific Climate System Response to a Small 11-Year Solar
Cycle Forcing, Science, 325, 1114–1118, 2009.
Myhre, G., Highwood, E. J., Shine, K. P., and Stordal, F.: New estimates
of radiative forcing due to well mixed greenhouse gases, Geophys. Res. Lett.,
25, 2715–2718, 1998.
Peixoto, J. P. and Oort, A. H.: Physics of Climate, Springer US, 1992.
Petoukhov, V., Ganopolski, A., Brovkin, V., Claussen, M., Eliseev, A.,
Kubatzki, C., and Rahmstorf, S.: CLIMBER-2: a climate system model of
intermediate complexity. Part I: model description and performance for
present climate, Clim. Dynam., 16, 1–17, 2000.
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R.,
Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L.,
Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U.,
and Tompkins, A.: The atmospheric general circulation model
ECHAM 5. Part I: Model description, Reports of the Max-Planck-Institute for
Meteorology, 349, 2003.
Rossow, W. B. and Schiffer, R. A.: Isccp Cloud Data Products,
B. Am. Meteorol. Soc., 72, 2–20, 1991.
Rossow, W. B. and Zhang, Y. C., 1995: Calculation of Surface and Top of
Atmosphere Radiative Fluxes from Physical Quantities Based on Isccp Data
Sets.2. Validation and First Results, J. Geophys. Res.-Atmos., 100, 1167–1197, 1995.
Smith, R. S., Gregory, J. M., and Osprey, A.: A description of the FAMOUS
(version XDBUA) climate model and control run, Geosci. Model Dev., 1, 53–68,
https://doi.org/10.5194/gmd-1-53-2008, 2008.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of Cmip5
and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, 2012.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K.,
Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V.,
Lamarque, J.-F., Masui, T., Meinshausen, M.,
Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
representative concentration pathways: an overview, Clim.
Change, 109, 5–31, 2011.
Weaver, A. J., Eby, M., Augustus, F. F., and Wiebe, E. C.: Simulated
influence of carbon dioxide, orbital forcing and ice sheets on the climate
of the Last Glacial Maximum, Nature, 394, 847–853, 1998.
Weaver, A. J., Eby, M., Wiebe, E. C., Bitz, C. M.,
Duffy, P. B., Ewen, T. L., Fanning, A. F., Holland, M. M., MacFadyen, A.,
Matthews, H. D., Meissner, K. J., Saenko, O., Schmittner, A.,
Wang, H., and Yoshimori, M.: The UVic Earth System Climate Model: Model
description, climatology, and applications to past, present and future
climates, Atmos.-Ocean, 39, 361–428, 2001.
Willson, R. C. and Hudson, H. S.: The Suns Luminosity over a Complete
Solar-Cycle, Nature, 351, 42–44, 1991.
Yang, H., Li, Q., Wang, K., Sun, Y., and Sun, D.: Decomposing the
meridional heat transport in the climate system, Clim. Dynam., 44,
2751–2768, https://doi.org/10.1007/s00382-014-2380-5, 2015.
Short summary
This study describes the scientific basis for a public web page that gives access to a large set of climate model simulations. This web page is called the Monash Simple Climate Model. It provides access to more than 1300 experiments and has an interactive interface for fast analysis of the experiments and open access to the data. The study gives a short overview of the simulation experiments and discusses some of the results.
This study describes the scientific basis for a public web page that gives access to a large set...
