Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6521-2022
© Author(s) 2022. 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-15-6521-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
31 Aug 2022
Development and technical paper |
| 31 Aug 2022
| 31 Aug 2022
wavetrisk-2.1: an adaptive dynamical core for ocean modelling
Nicholas K.-R. Kevlahan
CORRESPONDING AUTHOR
Department of Mathematics and Statistics, McMaster University, Hamilton, Canada
Florian Lemarié
Laboratoire Jean Kuntzmann, Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France
Related authors
Nicholas K.-R. Kevlahan and Thomas Dubos
Geosci. Model Dev., 12, 4901–4921, https://doi.org/10.5194/gmd-12-4901-2019, https://doi.org/10.5194/gmd-12-4901-2019, 2019
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WAVETRISK-1.0 is a new adaptive dynamical core for global climate modelling. It uses multiscale adaptive wavelet methods to adjust the grid resolution of the model at each time to guarantee error and make optimal use of computational resources. This technique has the potential to make climate simulations more accurate and allow much higher local resolutions. This "zoom" capability could also be used to focus on significant phenomena (such as hurricanes) or particular regions of the Earth.
N. K.-R. Kevlahan, T. Dubos, and M. Aechtner
Geosci. Model Dev., 8, 3891–3909, https://doi.org/10.5194/gmd-8-3891-2015, https://doi.org/10.5194/gmd-8-3891-2015, 2015
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In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method.
Valentina Schüller, Florian Lemarié, Philipp Birken, and Eric Blayo
EGUsphere, https://doi.org/10.5194/egusphere-2025-1342, https://doi.org/10.5194/egusphere-2025-1342, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Earth system models consist of many components, coupled in time and space. Standard coupling algorithms introduce a numerical error, which one can compute with iterative coupling methods. We use such a method for the EC-Earth AOSCM, which models a single vertical column of the atmosphere, ocean, and sea ice. We find that coupling errors in the atmosphere and at the ice surface can be substantial and that discontinuous physics parameterizations lead to convergence issues of the iteration.
Achim Wirth and Florian Lemarié
Earth Syst. Dynam., 12, 689–708, https://doi.org/10.5194/esd-12-689-2021, https://doi.org/10.5194/esd-12-689-2021, 2021
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We show that modern concepts of non-equilibrium statistical mechanics can be applied to large-scale environmental fluid dynamics, where fluctuations are not thermal but come from turbulence. The work theorems developed by Jarzynski and Crooks are applied to air–sea interaction. Rather than looking at the average values of thermodynamic variables, their probability density functions are considered, which allows us to replace the inequalities of equilibrium statistical mechanics with equalities.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev., 14, 2959–2975, https://doi.org/10.5194/gmd-14-2959-2021, https://doi.org/10.5194/gmd-14-2959-2021, 2021
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State-of-the-art Earth system models, like the ones used in CMIP6, suffer from temporal inconsistencies at the ocean–atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. Its tremendous computational cost makes it unusable for production runs, but it allows us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer timescales of days to decades is not evaluated.
Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Hervé Giordani, Théo Brivoal, and Gurvan Madec
Geosci. Model Dev., 14, 543–572, https://doi.org/10.5194/gmd-14-543-2021, https://doi.org/10.5194/gmd-14-543-2021, 2021
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A simplified model of the atmospheric boundary layer (ABL) of intermediate complexity between a bulk parameterization and a full three-dimensional atmospheric model has been developed and integrated to the NEMO ocean model.
An objective in the derivation of such a simplified model is to reach an apt representation of ocean-only numerical simulations of some of the key processes associated with air–sea interactions at the characteristic scales of the oceanic mesoscale.
Théo Brivoal, Guillaume Samson, Hervé Giordani, Romain Bourdallé-Badie, Florian Lemarié, and Gurvan Madec
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-78, https://doi.org/10.5194/os-2020-78, 2020
Preprint withdrawn
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We investigate the interactions between near-surface winds and oceanic surface currents on the north-east atlantic region using a simplified lower atmosphere model coupled with an ocean model. we show that the upper ocean kinetic energy is significantly reduced due to these interactions, but in a smaller amplitude than if the wind feedback is ignored. We also show that wind-current interactions affect the deeper ocean by modifying its vertical structure and consequently the pressure field.
Xavier Couvelard, Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Fabrice Ardhuin, Rachid Benshila, and Gurvan Madec
Geosci. Model Dev., 13, 3067–3090, https://doi.org/10.5194/gmd-13-3067-2020, https://doi.org/10.5194/gmd-13-3067-2020, 2020
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Within the framework of the Copernicus Marine Environment Monitoring Service (CMEMS), an objective is to demonstrate the contribution of coupling the high-resolution analysis and forecasting system with a wave model. This study describes the necessary steps and discusses the various choices made for coupling a wave model and an oceanic model for global-scale applications.
Nicholas K.-R. Kevlahan and Thomas Dubos
Geosci. Model Dev., 12, 4901–4921, https://doi.org/10.5194/gmd-12-4901-2019, https://doi.org/10.5194/gmd-12-4901-2019, 2019
Short summary
Short summary
WAVETRISK-1.0 is a new adaptive dynamical core for global climate modelling. It uses multiscale adaptive wavelet methods to adjust the grid resolution of the model at each time to guarantee error and make optimal use of computational resources. This technique has the potential to make climate simulations more accurate and allow much higher local resolutions. This "zoom" capability could also be used to focus on significant phenomena (such as hurricanes) or particular regions of the Earth.
Anton Beljaars, Emanuel Dutra, Gianpaolo Balsamo, and Florian Lemarié
Geosci. Model Dev., 10, 977–989, https://doi.org/10.5194/gmd-10-977-2017, https://doi.org/10.5194/gmd-10-977-2017, 2017
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Coupling an atmospheric model with snow and sea ice modules presents numerical stability challenges in integrations with long time steps as commonly used for weather prediction and climate simulations. Explicit flux coupling is often applied for simplicity. In this paper a simple method is presented to stabilize the coupling without having to introduce fully implicit coupling. A formal stability analysis confirms that the method is unconditionally stable.
N. K.-R. Kevlahan, T. Dubos, and M. Aechtner
Geosci. Model Dev., 8, 3891–3909, https://doi.org/10.5194/gmd-8-3891-2015, https://doi.org/10.5194/gmd-8-3891-2015, 2015
Short summary
Short summary
In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, 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.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
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. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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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.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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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 key 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 irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Elizabeth J. Drenkard, Charles A. Stock, Andrew C. Ross, Yi-Cheng Teng, Theresa Morrison, Wei Cheng, Alistair Adcroft, Enrique Curchitser, Raphael Dussin, Robert Hallberg, Claudine Hauri, Katherine Hedstrom, Albert Hermann, Michael G. Jacox, Kelly A. Kearney, Remi Pages, Darren J. Pilcher, Mercedes Pozo Buil, Vivek Seelanki, and Niki Zadeh
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-195, https://doi.org/10.5194/gmd-2024-195, 2024
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We made a new regional ocean model to assist fisheries and ecosystem managers make decisions in the Northeast Pacific Ocean (NEP). We found that the model did well simulating past ocean conditions like temperature, and nutrient and oxygen levels, and can even reproduce metrics used by and important to ecosystem managers.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Cited articles
Adcroft, A., Campin, J.-M., Doddridge, E., Dutkiewicz, S., Evangelinos, C.,
Ferreira, D., Follows, M., Forget, G., Fox-Kemper, B., Heimbach, P., Hill,
C., Hill, E., Hill, H., Jahn, O., Klymak, J., Losch, M., Marshall, J., Maze,
G., Mazloff, M., Menemenlis, D., Molod, A., and Scott, J.: MITgcm
Documentation,
https://mitgcm.readthedocs.io/_/downloads/en/latest/pdf/ (last access: 22 August 2022),
2021. a, b, c, d, e
Adsuara, J. E., Cordero-Carrion, I., Cerda-Duran, P., Mewes, V., and Aloy,
M. A.: On the equivalence between the Scheduled Relaxation Jacobi method and
Richardson's non-stationary method, J. Comput. Phys., 332, 446–460,
https://doi.org/10.1016/j.jcp.2016.12.020, 2017. a
Aechtner, M., Kevlahan, N.-R., and Dubos, T.: A conservative adaptive wavelet
method for the shallow water equations on the sphere, Q. J. Roy. Meteor. Soc.,
141, 1712–1726, https://doi.org/10.1002/qj.2473,
2015. a
Beron-Vera, F.: Multilayer shallow-water model with stratification and shear,
Rev. Mex. Fis., 67, 351–364, https://doi.org/10.31349/RevMexFis.67.351, 2021. a, b, c
Bleck, R. and Smith, L.: A wind-driven isopycnic coordinate model of the North
and Equatorial Atlantic Ocean. 1. Model development and supporting
experiments, J. Geophys. Res., 95, 3273–3285, 1990. a
Danilov, S., Sidorenko, D., Wang, Q., and Jung, T.: The Finite-volumE Sea ice–Ocean Model (FESOM2), Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, 2017. a
Debreu, L., Kevlahan, N. K.-R., and Marchesiello, P.: Brinkman volume
penalization for bathymetry in three-dimensional ocean models, Ocean
Model., 145, 101530, https://doi.org/10.1016/j.ocemod.2019.101530, 2020. a, b, c, d
Dubos, T. and Kevlahan, N. K.-R.: A conservative adaptive wavelet method for
the shallow water equations on staggered grids, Q. J. Roy. Meteor. Soc., 139,
1997–2020, https://doi.org/10.1002/qj.2097, 2013. a, b
Dubos, T., Dubey, S., Tort, M., Mittal, R., Meurdesoif, Y., and Hourdin, F.: DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility, Geosci. Model Dev., 8, 3131–3150, https://doi.org/10.5194/gmd-8-3131-2015, 2015. a, b, c, d
Engwirda, D. and Kelley, M.: A WENO-type slope-limiter for a
family of piecewise polynomial methods, arXiv [preprint], https://doi.org/10.48550/arXiv.1606.08188, 2016. a, b, c
Griffies, S., Adcroft, A., and Hallberg, R.: A Primer on the Vertical
Lagrangian-Remap Method in Ocean Models Based on Finite Volume Generalized
Vertical Coordinates, Journal of Advances in Modeling Earth Systems, 12, e2019MS001954, https://doi.org/10.1029/2019MS001954, 2020. a
Guinot, V. and Soares-Frazao, S.: Flux and source term discretization in
two-dimensional shallow water models with porosity on unstructured grids,
Int. J. Numer. Meth. Fl., 50, 309–345, https://doi.org/10.1002/fld.1059,
2006. a
Guinot, V., Delenne, C., Rousseau, A., and Boutron, O.: Flux closures and
source term models for shallow water models with depth-dependent integral
porosity, Adv. Water Resour., 122, 1–26, 2018. a
Hallberg, R. and Adcroft, A.: Reconciling estimates of the free surface height
in Lagrangian vertical coordinate ocean models with mode-split time stepping,
Ocean Model., 29, 15–26, 2009. a
Kang, H.-G., Evans, K. J., Petersen, M. R., Jones, P. W., and Bishnu, S.: A
Scalable Semi-Implicit Barotropic Mode Solver for the MPAS-Ocean, JAMES,
13, e2020MS002238, https://doi.org/10.1029/2020MS002238, 2021. a, b, c
Kato, H. and Phillips, O.: On the penetration of a turbulent layer into
stratified fluid, J. Fluid Mech., 37, 643–655, 1969. a
Kevlahan, N.: WAVETRISK-2.1 (2.1), Zenodo [code], https://doi.org/10.5281/zenodo.5608548, 2021. a
Kevlahan, N. K.-R.: Adaptive Wavelet Methods for Earth Systems Modelling,
Fluids, 6, 236, https://doi.org/10.3390/fluids6070236, 2021. a, b
Kevlahan, N. K.-R., Dubos, T., and Aechtner, M.: Adaptive wavelet simulation of global ocean dynamics using a new Brinkman volume penalization, Geosci. Model Dev., 8, 3891–3909, https://doi.org/10.5194/gmd-8-3891-2015, 2015. a, b, c, d
Kinnmark, I. and Gray, W.: One-step integration methods of 3rd-order-4th-order
accuracy with large hyperbolic stability limits, Math. Comput. Simulat., 26,
181–188, https://doi.org/10.1016/0378-4754(84)90056-9, 1984. a
Madec, G. and Team, N.: NEMO ocean engine, Zenodo, https://doi.org/10.5281/zenodo.1464816, 2015. a, b, c, d
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A
finite-volume, incompressible Navier Stokes model for studies of the ocean on
parallel computers, J. Geophys. Res., 102, 5753–5766, 1997. a
McCorquodale, P., Ullrich, P., Johansen, H., and Colella, P.: An adaptive
multiblock high-order finite-volume method for solving the shallow-water
equations on the sphere, Comm. App. Math. Com. Sc., 10, 121–162,
https://doi.org/10.2140/camcos.2015.10.121, 2015. a
Morvan, M., Carton, X., L'Hégaret, P., de Marez, C., Corréard, S., and
Louazel, S.: On the dynamics of an idealized bottom density current
overflowing in a semi-enclosed basin: mesoscale and submesoscale eddies
generation, Geophys. Astro. Fluid, 114, 607–630,
https://doi.org/10.1080/03091929.2020.1747058, 2020. a
Patankar, S.: Numerical heat transfer and fluid flow, Computational methods in
mechanical and thermal sciences, Hemisphere Pub. Corp., ISBN 0-07-048740-5, 1980. a
Popinet, S.: Quadtree-adaptive tsunami modelling, Ocean Dynam., 61,
1261–1285, https://doi.org/10.1007/s10236-011-0438-z, 2011. a
Popinet, S.: A vertically-Lagrangian, non-hydrostatic, multilayer model for
multiscale free-surface flows, J. Comput. Phys., 418, 109609,
https://doi.org/10.1016/j.jcp.2020.109609, 2021. a, b, c, d
Popinet, S. and Rickard, G.: A tree-based solver for adaptive ocean
modelling, Ocean Model., 16, 224–249, https://doi.org/10.1016/j.ocemod.2006.10.002,
2007. a
Rasmussen, J. T., Cottet, G.-H., and Walther, J.: A multiresolution remeshed
Vortex-In-Cell algorithm using patches, J. Comput. Phys., 230,
6742–6755, https://doi.org/10.1016/j.jcp.2011.05.006, 2011. a
Ringler, T. D., Thuburn, J., Klemp, J. B., and Skamarock, W. C.: A
unified approach to energy conservation and potential vorticity dynamics for
arbitrarily-structured C-grids, J. Comput. Phys., 229, 3065–3090,
https://doi.org/10.1016/j.jcp.2009.12.007, 2010. a, b, c
Shchepetkin, A. and McWilliams, J.: The regional oceanic modeling system
(ROMS): a split-explicit, free-surface, topography-following-coordinate
oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a, b
Vallis, G. K.: Atmospheric and oceanic fluid dynamics, Cambridge University
Press, ISBN 10 0521849691, 2006. a
Vasilyev, O. V. and Kevlahan, N. K.-R.: An adaptive multilevel wavelet
collocation method for elliptic problems, J. Comput. Phys., 206, 412–431,
2005. a
Walters, R. A., Lane, E. M., and Hanert, E.: Useful time-stepping methods for
the Coriolis term in a shallow water model, Ocean Model., 28, 66–74,
https://doi.org/10.1016/j.ocemod.2008.10.004, 2009. a
Wieczorek, M. and Meschede, M.: SHTools – Tools for working with spherical
harmonics, Geochem. Geophy. Geosy., 19, 2574–2592, 2018. a
Willis, G. and Deardorff, J.: A laboratory model of the unstable planetary
boundary layer, J. Atmos. Sci., 31, 1297–1307, 1974. a
Yang, X. I. A. and Mittal, R.: Acceleration of the Jacobi iterative method by
factors exceeding 100 using scheduled relaxation, J. Comput. Phys., 274,
695–708, https://doi.org/10.1016/j.jcp.2014.06.010, 2014. a
Short summary
WAVETRISK-2.1 is an innovative climate model for the world's oceans. It uses state-of-the-art techniques to change the model's resolution locally, from O(100 km) to O(5 km), as the ocean changes. This dynamic adaptivity makes optimal use of available supercomputer resources, and allows two-dimensional global scales and three-dimensional submesoscales to be captured in the same simulation. WAVETRISK-2.1 is designed to be coupled its companion global atmosphere model, WAVETRISK-1.x.
WAVETRISK-2.1 is an innovative climate model for the world's oceans. It uses state-of-the-art...
