Articles | Volume 10, issue 11
https://doi.org/10.5194/gmd-10-4207-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-10-4207-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
20 Nov 2017
Model description paper |
| 20 Nov 2017
SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Bertrand Decharme
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Joris Pianezze
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Laboratoire de l'Atmosphère et des Cyclones, LACy, CNRS
UMR8105/Université de la Réunion/Météo-France, Saint Denis
de la Réunion, France
Cindy Lebeaupin Brossier
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Florence Sevault
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Léo Seyfried
Laboratoire d'Aérologie, LA, CNRS UMR5560/Université
de Toulouse, Toulouse, France
Valérie Garnier
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Soline Bielli
Laboratoire de l'Atmosphère et des Cyclones, LACy, CNRS
UMR8105/Université de la Réunion/Météo-France, Saint Denis
de la Réunion, France
Sophie Valcke
CECI, Université de Toulouse, CNRS UMR5318, CERFACS,
Toulouse, France
Antoinette Alias
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Mickael Accensi
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Fabrice Ardhuin
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Marie-Noëlle Bouin
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Véronique Ducrocq
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Stéphanie Faroux
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Hervé Giordani
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Fabien Léger
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Patrick Marsaleix
Laboratoire d'Aérologie, LA, CNRS UMR5560/Université
de Toulouse, Toulouse, France
Romain Rainaud
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
Jean-Luc Redelsperger
Laboratoire d'Océanographie Physique et Spatiale, LOPS, CNRS
UMR6523/Ifremer/IRD/UBO, Brest, France
Evelyne Richard
Laboratoire d'Aérologie, LA, CNRS UMR5560/Université
de Toulouse, Toulouse, France
Sébastien Riette
Centre National de Recherches Météorologiques, CNRM,
Météo-France/CNRS UMR3589, Toulouse, France
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The GRACE (Gravity Recovery And Climate Experiment) satellite mission enabled the quantification of water mass redistributions from 2002 to 2017. The analysis of GRACE satellite data shows here that slow changes in terrestrial water storage occurring over a few years to a decade are severely underestimated by global hydrological models. Several sources of errors may explain such biases, likely including the inaccurate representation of groundwater storage changes.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Alisée A. Chaigneau, Stéphane Law-Chune, Angélique Melet, Aurore Voldoire, Guillaume Reffray, and Lotfi Aouf
Ocean Sci., 19, 1123–1143, https://doi.org/10.5194/os-19-1123-2023, https://doi.org/10.5194/os-19-1123-2023, 2023
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Wind waves and swells are major drivers of coastal environment changes and can drive coastal marine hazards such as coastal flooding. In this paper, by using numerical modeling along the European Atlantic coastline, we assess how present and future wave characteristics are impacted by sea level changes. For example, at the end of the century under the SSP5-8.5 climate change scenario, extreme significant wave heights are higher by up to +40 % due to the effect of tides and mean sea level rise.
Antoine Sobaga, Bertrand Decharme, Florence Habets, Christine Delire, Noële Enjelvin, Paul-Olivier Redon, Pierre Faure-Catteloin, and Patrick Le Moigne
Hydrol. Earth Syst. Sci., 27, 2437–2461, https://doi.org/10.5194/hess-27-2437-2023, https://doi.org/10.5194/hess-27-2437-2023, 2023
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Seven instrumented lysimeters are used to assess the simulation of the soil water dynamic in one land surface model. Four water potential and hydraulic conductivity closed-form equations, including one mixed form, are evaluated. One form is more relevant for simulating drainage, especially during intense drainage events. The soil profile heterogeneity of one parameter of the closed-form equations is shown to be important.
Thibault Guinaldo, Aurore Voldoire, Robin Waldman, Stéphane Saux Picart, and Hervé Roquet
Ocean Sci., 19, 629–647, https://doi.org/10.5194/os-19-629-2023, https://doi.org/10.5194/os-19-629-2023, 2023
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In the summer of 2022, France experienced a series of unprecedented heatwaves. This study is the first to examine the response of sea surface temperatures to these events, using spatial operational data and attributing the observed abnormally warm SSTs to atmospheric forcings. The findings of this study underscore the critical need for an efficient and sustainable operational system to monitor alterations that threaten the oceans in the context of climate change.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
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The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Matias Alday, Fabrice Ardhuin, Guillaume Dodet, and Mickael Accensi
Ocean Sci., 18, 1665–1689, https://doi.org/10.5194/os-18-1665-2022, https://doi.org/10.5194/os-18-1665-2022, 2022
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Obtaining accurate results from wave models in coastal regions is typically more difficult. This is due to the complex interactions between waves and the local environment characteristics like complex shorelines, sea bottom topography, the presence of strong currents, and other processes that include wave growth and decay. In the present study we analyze which elements can be adjusted and/or included in order to reduce errors in the modeled output.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Antoine Sobaga, Bertrand Decharme, Florence Habets, Christine Delire, Noële Enjelvin, Paul-Olivier Redon, Pierre Faure-Catteloin, and Patrick Le Moigne
EGUsphere, https://doi.org/10.5194/egusphere-2022-274, https://doi.org/10.5194/egusphere-2022-274, 2022
Preprint archived
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Seven instrumented lysimeters are used to assess the simulation of the soil water dynamic in one land surface model. Three water potential and hydraulic conductivity closed-form equations including one mixed form are evaluated. The mixed form is more relevant to simulate drainage especially during intense drainage events. Soil profile heterogeneity of one parameter of the closed-form equations is shown to be important.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258, https://doi.org/10.5194/essd-14-2239-2022, https://doi.org/10.5194/essd-14-2239-2022, 2022
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This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Joris Pianezze, Jonathan Beuvier, Cindy Lebeaupin Brossier, Guillaume Samson, Ghislain Faure, and Gilles Garric
Nat. Hazards Earth Syst. Sci., 22, 1301–1324, https://doi.org/10.5194/nhess-22-1301-2022, https://doi.org/10.5194/nhess-22-1301-2022, 2022
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Most numerical weather and oceanic prediction systems do not consider ocean–atmosphere feedback during forecast, and this can lead to significant forecast errors, notably in cases of severe situations. A new high-resolution coupled ocean–atmosphere system is presented in this paper. This forecast-oriented system, based on current regional operational systems and evaluated using satellite and in situ observations, shows that the coupling improves both atmospheric and oceanic forecasts.
Alisée A. Chaigneau, Guillaume Reffray, Aurore Voldoire, and Angélique Melet
Geosci. Model Dev., 15, 2035–2062, https://doi.org/10.5194/gmd-15-2035-2022, https://doi.org/10.5194/gmd-15-2035-2022, 2022
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Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
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Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
César Sauvage, Cindy Lebeaupin Brossier, and Marie-Noëlle Bouin
Atmos. Chem. Phys., 21, 11857–11887, https://doi.org/10.5194/acp-21-11857-2021, https://doi.org/10.5194/acp-21-11857-2021, 2021
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Air–sea processes are key elements during Mediterranean heavy precipitation events. We aim to progress in their representation in high-resolution weather forecast. Using coupled ocean–air–wave simulations, we investigated air–sea mechanisms modulated by ocean and waves during a case that occurred in southern France. Results showed significant impact of the forecast on low-level dynamics and air–sea fluxes and illustrated potential benefits of coupled numerical weather prediction systems.
Julien Beaumet, Michel Déqué, Gerhard Krinner, Cécile Agosta, Antoinette Alias, and Vincent Favier
The Cryosphere, 15, 3615–3635, https://doi.org/10.5194/tc-15-3615-2021, https://doi.org/10.5194/tc-15-3615-2021, 2021
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We use empirical run-time bias correction (also called flux correction) to correct the systematic errors of the ARPEGE atmospheric climate model. When applying the method to future climate projections, we found a lesser poleward shift and an intensification of the maximum of westerly winds present in the southern high latitudes. This yields a significant additional warming of +0.6 to +0.9 K of the Antarctic Ice Sheet with respect to non-corrected control projections using the RCP8.5 scenario.
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.
Olivier Caumont, Marc Mandement, François Bouttier, Judith Eeckman, Cindy Lebeaupin Brossier, Alexane Lovat, Olivier Nuissier, and Olivier Laurantin
Nat. Hazards Earth Syst. Sci., 21, 1135–1157, https://doi.org/10.5194/nhess-21-1135-2021, https://doi.org/10.5194/nhess-21-1135-2021, 2021
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This study focuses on the heavy precipitation event of 14 and 15 October 2018, which caused deadly flash floods in the Aude basin in south-western France.
The case is studied from a meteorological point of view using various operational numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. The peculiarities of this case compared to other cases of Mediterranean heavy precipitation events are presented.
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021, https://doi.org/10.5194/gmd-14-1309-2021, 2021
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Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services such as freshwater supply. Despite the impact of lakes on the water cycle, they are generally not considered in global hydrological studies. Based on a model called MLake, we assessed both the importance of lakes in simulating river flows at global scale and the value of their level variations for water resource management.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
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.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Olivier Nuissier, Fanny Duffourg, Maxime Martinet, Véronique Ducrocq, and Christine Lac
Atmos. Chem. Phys., 20, 14649–14667, https://doi.org/10.5194/acp-20-14649-2020, https://doi.org/10.5194/acp-20-14649-2020, 2020
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This present article demonstrates how numerical simulations with very high horizontal resolution (150 m) can contribute to better understanding the key physical processes (turbulence and microphysics) that lead to Mediterranean heavy precipitation.
Louis Marié, Fabrice Collard, Frédéric Nouguier, Lucia Pineau-Guillou, Danièle Hauser, François Boy, Stéphane Méric, Peter Sutherland, Charles Peureux, Goulven Monnier, Bertrand Chapron, Adrien Martin, Pierre Dubois, Craig Donlon, Tania Casal, and Fabrice Ardhuin
Ocean Sci., 16, 1399–1429, https://doi.org/10.5194/os-16-1399-2020, https://doi.org/10.5194/os-16-1399-2020, 2020
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With present-day techniques, ocean surface currents are poorly known near the Equator and globally for spatial scales under 200 km and timescales under 30 d. Wide-swath radar Doppler measurements are an alternative technique. Such direct surface current measurements are, however, affected by platform motions and waves. These contributions are analyzed in data collected during the DRIFT4SKIM airborne and in situ experiment, demonstrating the possibility of measuring currents from space globally.
Damien Héron, Stephanie Evan, Joris Pianezze, Thibaut Dauhut, Jerome Brioude, Karen Rosenlof, Vincent Noel, Soline Bielli, Christelle Barthe, and Jean-Pierre Cammas
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-870, https://doi.org/10.5194/acp-2020-870, 2020
Publication in ACP not foreseen
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Upward transport within tropical cyclones of water vapor from the low troposphere into the colder upper troposphere/lower stratosphere can result in the moistening of this region. Balloon observations and model simulations of tropical cyclone Enawo in the less-observed Southwest Indian Ocean (the third most tropical cyclone active region on Earth) are used to show how convective overshoots within Enawo penetrate the tropopause directly, injecting water/ice into the stratosphere.
Marie-Noëlle Bouin and Cindy Lebeaupin Brossier
Ocean Sci., 16, 1125–1142, https://doi.org/10.5194/os-16-1125-2020, https://doi.org/10.5194/os-16-1125-2020, 2020
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A kilometre-scale coupled ocean–atmosphere simulation is used to study the impact of a medicane on the oceanic upper layer. The processes responsible for the surface cooling are comparable to those of weak tropical cyclones. The oceanic response is influenced by the dynamics of the central Mediterranean. In particular, a cyclonic eddy leads to weaker cooling. Heavy rain occuring early in the event creates a salinity barrier layer, reinforcing the effects of the surface fluxes on the cooling.
Guillaume Dodet, Jean-François Piolle, Yves Quilfen, Saleh Abdalla, Mickaël Accensi, Fabrice Ardhuin, Ellis Ash, Jean-Raymond Bidlot, Christine Gommenginger, Gwendal Marechal, Marcello Passaro, Graham Quartly, Justin Stopa, Ben Timmermans, Ian Young, Paolo Cipollini, and Craig Donlon
Earth Syst. Sci. Data, 12, 1929–1951, https://doi.org/10.5194/essd-12-1929-2020, https://doi.org/10.5194/essd-12-1929-2020, 2020
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Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent. The CCI is a program of the European Space Agency, whose objective is to realize the full potential of global Earth Observation archives in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset.
Patrick Le Moigne, François Besson, Eric Martin, Julien Boé, Aaron Boone, Bertrand Decharme, Pierre Etchevers, Stéphanie Faroux, Florence Habets, Matthieu Lafaysse, Delphine Leroux, and Fabienne Rousset-Regimbeau
Geosci. Model Dev., 13, 3925–3946, https://doi.org/10.5194/gmd-13-3925-2020, https://doi.org/10.5194/gmd-13-3925-2020, 2020
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The study describes how a hydrometeorological model, operational at Météo-France, has been improved. Particular emphasis is placed on the impact of climatic data, surface, and soil parametrizations on the model results. Model simulations and evaluations carried out on a variety of measurements of river flows and snow depths are presented. All improvements in climate, surface data, and model physics have a positive impact on system performance.
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
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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.
Pierre Nabat, Samuel Somot, Christophe Cassou, Marc Mallet, Martine Michou, Dominique Bouniol, Bertrand Decharme, Thomas Drugé, Romain Roehrig, and David Saint-Martin
Atmos. Chem. Phys., 20, 8315–8349, https://doi.org/10.5194/acp-20-8315-2020, https://doi.org/10.5194/acp-20-8315-2020, 2020
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The present work aims at better understanding regional climate–aerosol interactions over the Euro-Mediterranean region by studying the relationships between aerosols and atmospheric circulation. Based on 40-year regional climate simulations (1979–2018), our results show the role of the North Atlantic Oscillation in driving the interannual aerosol variability, and that of weather regimes for the daily variability, with ensuing effects on shortwave surface radiation and surface temperature.
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.
Marie-Noëlle Bouin and Cindy Lebeaupin Brossier
Atmos. Chem. Phys., 20, 6861–6881, https://doi.org/10.5194/acp-20-6861-2020, https://doi.org/10.5194/acp-20-6861-2020, 2020
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A coupled, kilometre-scale simulation of a medicane is used to assess the impact of the ocean feedback and role of surface fluxes. Sea surface temperature (SST) drop is much weaker than for tropical cyclones, resulting in no impact on the cyclone. Surface fluxes depend mainly on wind and SST for evaporation and on air temperature for sensible heat. Processes in the Mediterranean, like advection of continental air, rain evaporation and dry air intrusion, play a role in cyclone development.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
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The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Guillaume Boutin, Camille Lique, Fabrice Ardhuin, Clément Rousset, Claude Talandier, Mickael Accensi, and Fanny Girard-Ardhuin
The Cryosphere, 14, 709–735, https://doi.org/10.5194/tc-14-709-2020, https://doi.org/10.5194/tc-14-709-2020, 2020
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We investigate the interactions of surface ocean waves with sea ice taking place at the interface between the compact sea ice cover and the open ocean. We use a newly developed coupling framework between a wave and an ocean–sea ice numerical model. Our results show how the push on sea ice exerted by waves changes the amount and the location of sea ice melting, with a strong impact on the ocean surface properties close to the ice edge.
Pierre Garreau, Franck Dumas, Stéphanie Louazel, Stéphanie Correard, Solenn Fercocq, Marc Le Menn, Alain Serpette, Valérie Garnier, Alexandre Stegner, Briac Le Vu, Andrea Doglioli, and Gerald Gregori
Earth Syst. Sci. Data, 12, 441–456, https://doi.org/10.5194/essd-12-441-2020, https://doi.org/10.5194/essd-12-441-2020, 2020
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The oceanic circulation is composed of the main currents, of large eddies and meanders, and of fine motions at a scale of about a few hundreds of metres, rarely observed in situ. PROTEVS-MED experiments were devoted to very high resolution observations of water properties (temperature and salinity) and currents, thanks to an undulating trawled vehicle revealing a patchy, stirred and energetic ocean in the first 400 m depth. These fine-scale dynamics drive the plankton and air–sea exchanges.
César Sauvage, Cindy Lebeaupin Brossier, Marie-Noëlle Bouin, and Véronique Ducrocq
Atmos. Chem. Phys., 20, 1675–1699, https://doi.org/10.5194/acp-20-1675-2020, https://doi.org/10.5194/acp-20-1675-2020, 2020
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Air–sea exchanges during Mediterranean heavy precipitation events are key and their representation must be improved for high-resolution weather forecasts. This study investigates the mechanisms acting at the air–sea interface during a case that occurred in southern France. To focus on the impact of sea state, we developed and used an original coupled air–wave model. Results show modifications of the forecast for the air–sea fluxes, the near-surface wind and the location of precipitation.
Sébastien Riette
Geosci. Model Dev., 13, 443–460, https://doi.org/10.5194/gmd-13-443-2020, https://doi.org/10.5194/gmd-13-443-2020, 2020
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Numerical weather or climate models use several interacting parametrizations to represent different physical processes. PPPY 1.1 is a Python package for running and comparing individual parametrizations in offline mode, independently of other parametrizations and of the host model. In this paper, the tool is described and used to assess and reduce the time-step dependency present in a microphysical parametrization.
Thomas Holding, Ian G. Ashton, Jamie D. Shutler, Peter E. Land, Philip D. Nightingale, Andrew P. Rees, Ian Brown, Jean-Francois Piolle, Annette Kock, Hermann W. Bange, David K. Woolf, Lonneke Goddijn-Murphy, Ryan Pereira, Frederic Paul, Fanny Girard-Ardhuin, Bertrand Chapron, Gregor Rehder, Fabrice Ardhuin, and Craig J. Donlon
Ocean Sci., 15, 1707–1728, https://doi.org/10.5194/os-15-1707-2019, https://doi.org/10.5194/os-15-1707-2019, 2019
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FluxEngine is an open-source software toolbox designed to allow for the easy and accurate calculation of air–sea gas fluxes. This article describes new functionality and capabilities, which include the ability to calculate fluxes for nitrous oxide and methane, optimisation for running FluxEngine on a stand-alone desktop computer, and extensive new features to support the in situ measurement community. Four research case studies are used to demonstrate these new features.
Julien Beaumet, Michel Déqué, Gerhard Krinner, Cécile Agosta, and Antoinette Alias
The Cryosphere, 13, 3023–3043, https://doi.org/10.5194/tc-13-3023-2019, https://doi.org/10.5194/tc-13-3023-2019, 2019
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The atmospheric model ARPEGE is used with a stretched grid in order to reach an average horizontal resolution of 35 km over Antarctica. Over 1981–2010, we forced the model with observed and modelled sea surface conditions (SSCs). For the late 21st century, we use original and bias-corrected sea surface conditions from RCP8.5 climate projections. We assess the impact of using direct or bias-corrected SSCs for the evolution of Antarctic climate and surface mass balance.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd
Geosci. Model Dev., 12, 2657–2678, https://doi.org/10.5194/gmd-12-2657-2019, https://doi.org/10.5194/gmd-12-2657-2019, 2019
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The AROME-WMED (western Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model that ran in real time during the first special observation period of HyMeX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX reanalyses. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, Nadia Fourrié, and Pascal Marquet
Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, https://doi.org/10.5194/nhess-19-907-2019, 2019
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The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, and Nadia Fourrié
Nat. Hazards Earth Syst. Sci., 19, 821–835, https://doi.org/10.5194/nhess-19-821-2019, https://doi.org/10.5194/nhess-19-821-2019, 2019
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The study reports on the impact of the assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP model on predicting heavy precipitation events in the Mediterranean area. The positive impact of the assimilation of such data is particularly evidenced for a heavy precipitation event and results are slightly encouraging over a 45-day period. In addition, the impact of the length of the assimilation window in a 3h-3DVar assimilation system is investigated.
Jordi Etchanchu, Vincent Rivalland, Stéphanie Faroux, Aurore Brut, and Gilles Boulet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-126, https://doi.org/10.5194/hess-2019-126, 2019
Revised manuscript not accepted
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This study presents an innovative method to assess irrigation volumes in the ISBA land surface model with high resolution optical remote sensing. We developed a new automated irrigation scheme which can adapt to a wide variety of crops and irrigation practices. Remotely sensed vegetation dynamics was used to drive its parameters. The simulation performed on several maize plots in south-western France shows an improvement on the simulated irrigation volumes and timing.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 23, 1801–1818, https://doi.org/10.5194/hess-23-1801-2019, https://doi.org/10.5194/hess-23-1801-2019, 2019
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This work aims to estimate the extent to which the terrain descriptors and the spatial resolution of the hydrological model influence flash-flood modelling at the local and basin scale. The skill of the hydrological simulations is evaluated with conventional data (such as discharge measurements) and impact data (post-event surveys and high-water marks). The results reveal that the spatial resolution has the largest impact on the hydrological simulations, larger than soil texture and land cover.
Léo Seyfried, Claude Estournel, Patrick Marsaleix, and Evelyne Richard
Ocean Sci., 15, 179–198, https://doi.org/10.5194/os-15-179-2019, https://doi.org/10.5194/os-15-179-2019, 2019
Shunya Koseki, Hervé Giordani, and Katerina Goubanova
Ocean Sci., 15, 83–96, https://doi.org/10.5194/os-15-83-2019, https://doi.org/10.5194/os-15-83-2019, 2019
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With an ocean frontogenetic function, the frontogenesis of the Angola–Benguela Frontal Zone (ABFZ) is investigated. On an annual-mean timescale, the meridional confluence of Angola and Benguela currents and tilting effect due to the upwelling are the main sources to generate the ABFZ. The annual cycle of the ABFZ is also mainly driven by these two effects.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
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The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Keun-Ok Lee, Cyrille Flamant, Fanny Duffourg, Véronique Ducrocq, and Jean-Pierre Chaboureau
Atmos. Chem. Phys., 18, 16845–16862, https://doi.org/10.5194/acp-18-16845-2018, https://doi.org/10.5194/acp-18-16845-2018, 2018
Pedro Veras Guimarães, Fabrice Ardhuin, Peter Sutherland, Mickael Accensi, Michel Hamon, Yves Pérignon, Jim Thomson, Alvise Benetazzo, and Pierre Ferrant
Ocean Sci., 14, 1449–1460, https://doi.org/10.5194/os-14-1449-2018, https://doi.org/10.5194/os-14-1449-2018, 2018
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This paper introduces a new design of drifting buoy. The "surface kinematics buoy'' (SKIB) is particularly optimized for measuring wave–current interactions, including relatively short wave components, from 0.09 to 1 Hz, that are important for air–sea interactions and remote-sensing applications. The capability of this instrument is compared to other sensors, and the ability to measure current-induced wave variations is illustrated with data acquired in a macro-tidal coastal environment.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354, https://doi.org/10.5194/os-14-337-2018, https://doi.org/10.5194/os-14-337-2018, 2018
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The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
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
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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.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
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We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Roland Séférian, Sunghye Baek, Olivier Boucher, Jean-Louis Dufresne, Bertrand Decharme, David Saint-Martin, and Romain Roehrig
Geosci. Model Dev., 11, 321–338, https://doi.org/10.5194/gmd-11-321-2018, https://doi.org/10.5194/gmd-11-321-2018, 2018
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This paper presents a new interactive scheme for ocean surface albedo suited for the current generation of Earth system models. This scheme computes the ocean surface albedo accounting for the spectral dependence (across a range of wavelengths between 200 and 4000 nm), the characteristics of incident solar radiation (direct of diffuse), the effects of surface winds, chlorophyll content and whitecaps in addition to the canonical solar zenith angle dependence.
Charles Peureux, Alvise Benetazzo, and Fabrice Ardhuin
Ocean Sci., 14, 41–52, https://doi.org/10.5194/os-14-41-2018, https://doi.org/10.5194/os-14-41-2018, 2018
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Little is known on the short ocean wave (1 to 20 m wave length typically) directional distribution. It has been measured from a platform in the Adriatic Sea using a three-dimensional reconstruction technique, used for the first time for this purpose. In this record, while longer waves propagate along the wind direction, shorter waves have been found to propagate mainly along two oblique directions, more and more separated towards smaller scales.
Léo Seyfried, Patrick Marsaleix, Evelyne Richard, and Claude Estournel
Ocean Sci., 13, 1093–1112, https://doi.org/10.5194/os-13-1093-2017, https://doi.org/10.5194/os-13-1093-2017, 2017
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Mathieu Barrere, Florent Domine, Bertrand Decharme, Samuel Morin, Vincent Vionnet, and Matthieu Lafaysse
Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, https://doi.org/10.5194/gmd-10-3461-2017, 2017
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Global warming projections still suffer from a limited representation of the permafrost–carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Anthony Craig, Sophie Valcke, and Laure Coquart
Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, https://doi.org/10.5194/gmd-10-3297-2017, 2017
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The OASIS software package provides capabilities that allow different models to be coupled together to carry out new scientific investigation. This is particularly useful in climate model simulations where atmosphere, ocean, sea ice, hydrology, land, ocean wave, chemistry, and other types of Earth system models are often coupled together. The OASIS software package is used by several groups around the world, and this paper describes features of the latest implementation.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Pierre Tulet, Andréa Di Muro, Aurélie Colomb, Cyrielle Denjean, Valentin Duflot, Santiago Arellano, Brice Foucart, Jérome Brioude, Karine Sellegri, Aline Peltier, Alessandro Aiuppa, Christelle Barthe, Chatrapatty Bhugwant, Soline Bielli, Patrice Boissier, Guillaume Boudoire, Thierry Bourrianne, Christophe Brunet, Fréderic Burnet, Jean-Pierre Cammas, Franck Gabarrot, Bo Galle, Gaetano Giudice, Christian Guadagno, Fréderic Jeamblu, Philippe Kowalski, Jimmy Leclair de Bellevue, Nicolas Marquestaut, Dominique Mékies, Jean-Marc Metzger, Joris Pianezze, Thierry Portafaix, Jean Sciare, Arnaud Tournigand, and Nicolas Villeneuve
Atmos. Chem. Phys., 17, 5355–5378, https://doi.org/10.5194/acp-17-5355-2017, https://doi.org/10.5194/acp-17-5355-2017, 2017
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The STRAP campaign was conducted in 2015 to investigate the volcanic plumes of Piton de La Fournaise (La Réunion, France). For the first time, measurements were conducted at the local (near the vent) and regional scales around the island. The STRAP 2015 campaign gave a unique set of multi-disciplinary data that can now be used by modellers to improve the numerical parameterisations of the physical and chemical evolution of the volcanic plumes.
Adrien Napoly, Aaron Boone, Patrick Samuelsson, Stefan Gollvik, Eric Martin, Roland Seferian, Dominique Carrer, Bertrand Decharme, and Lionel Jarlan
Geosci. Model Dev., 10, 1621–1644, https://doi.org/10.5194/gmd-10-1621-2017, https://doi.org/10.5194/gmd-10-1621-2017, 2017
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This paper is the second part of a new parameterization for canopy representation that has been developed in the Interactions between the Surface Biosphere Atmosphere model (ISBA). A module for the explicit representation of the litter bellow forest canopies has been added. Then, the first evaluation of these new developments is performed at local scale among three well-instrumented sites and then at the global scale using the FLUXNET network.
Aaron Boone, Patrick Samuelsson, Stefan Gollvik, Adrien Napoly, Lionel Jarlan, Eric Brun, and Bertrand Decharme
Geosci. Model Dev., 10, 843–872, https://doi.org/10.5194/gmd-10-843-2017, https://doi.org/10.5194/gmd-10-843-2017, 2017
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Land surface models describe the different exchanges of mass, heat, and momentum with the atmosphere. They are pushing towards improved realism owing to an increasing number of in situ observations, improving satellite data-sets and increasing computing resources. As a part of the trend, a new parameterization has been developed called the Interactions between the Surface Biosphere Atmosphere-Multi-Energy Budget model. This technical paper describes model equations and theoretical background.
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Justin E. Stopa, Fabrice Ardhuin, and Fanny Girard-Ardhuin
The Cryosphere, 10, 1605–1629, https://doi.org/10.5194/tc-10-1605-2016, https://doi.org/10.5194/tc-10-1605-2016, 2016
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Satellite observations show the Arctic sea ice has decreased the last 30 years. From our wave model hindcast and satellite altimeter datasets we observe profound increasing wave heights, which are caused by the loss of sea ice and not the driving winds. If ice-free conditions persist later into fall, then regions like the Beaufort–Chukchi Sea will be prone to developing larger waves since the driving winds are strong this time of year.
Mathieu Hamon, Jonathan Beuvier, Samuel Somot, Jean-Michel Lellouche, Eric Greiner, Gabriel Jordà, Marie-Noëlle Bouin, Thomas Arsouze, Karine Béranger, Florence Sevault, Clotilde Dubois, Marie Drevillon, and Yann Drillet
Ocean Sci., 12, 577–599, https://doi.org/10.5194/os-12-577-2016, https://doi.org/10.5194/os-12-577-2016, 2016
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The paper describes MEDRYS, a MEDiterranean sea ReanalYsiS at high resolution for the period 1992–2013. The NEMOMED12 ocean model is forced at the surface by a new high resolution atmospheric forcing dataset (ALDERA). Altimeter data, satellite SST and temperature and salinity vertical profiles are jointly assimilated. The ability of the reanalysis to represent the sea surface high-frequency variability, water mass characteristics and transports through the Strait of Gibraltar is shown.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
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This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
Bertrand Decharme, Eric Brun, Aaron Boone, Christine Delire, Patrick Le Moigne, and Samuel Morin
The Cryosphere, 10, 853–877, https://doi.org/10.5194/tc-10-853-2016, https://doi.org/10.5194/tc-10-853-2016, 2016
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We analyze how snowpack processes and soil properties impact the soil temperature profiles over northern Eurasian regions using a land surface model. A correct representation of snow compaction is critical in winter while snow albedo is dominant in spring. In summer, soil temperature is more affected by soil organic carbon content, which strongly influences the maximum thaw depth in permafrost regions. This work was done to improve the representation of boreal region processes in climate models.
W. Wang, A. Rinke, J. C. Moore, X. Cui, D. Ji, Q. Li, N. Zhang, C. Wang, S. Zhang, D. M. Lawrence, A. D. McGuire, W. Zhang, C. Delire, C. Koven, K. Saito, A. MacDougall, E. Burke, and B. Decharme
The Cryosphere, 10, 287–306, https://doi.org/10.5194/tc-10-287-2016, https://doi.org/10.5194/tc-10-287-2016, 2016
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We use a model-ensemble approach for simulating permafrost on the Tibetan Plateau. We identify the uncertainties across models (state-of-the-art land surface models) and across methods (most commonly used methods to define permafrost).
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
S. Garrigues, A. Olioso, D. Carrer, B. Decharme, J.-C. Calvet, E. Martin, S. Moulin, and O. Marloie
Geosci. Model Dev., 8, 3033–3053, https://doi.org/10.5194/gmd-8-3033-2015, https://doi.org/10.5194/gmd-8-3033-2015, 2015
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This paper investigates the impacts of uncertainties in the climate, the vegetation dynamic, the soil properties and the cropland management on the simulation of evapotranspiration from the ISBA-A-gs land surface model over a 12-year Mediterranean crop succession. It mainly shows that errors in the soil parameters and the lack of irrigation in the simulation have the largest influence on evapotranspiration compared to the uncertainties in the climate and the vegetation dynamic.
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
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We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, D. Carrer, H. Verbeeck, M. De Weirdt, and D. Bonal
Geosci. Model Dev., 8, 1709–1727, https://doi.org/10.5194/gmd-8-1709-2015, https://doi.org/10.5194/gmd-8-1709-2015, 2015
P. Nabat, S. Somot, M. Mallet, M. Michou, F. Sevault, F. Driouech, D. Meloni, A. di Sarra, C. Di Biagio, P. Formenti, M. Sicard, J.-F. Léon, and M.-N. Bouin
Atmos. Chem. Phys., 15, 3303–3326, https://doi.org/10.5194/acp-15-3303-2015, https://doi.org/10.5194/acp-15-3303-2015, 2015
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This paper uses an original approach based on a coupled regional aerosol--atmosphere--ocean model to study the dust radiative effects over the Mediterranean in summer 2012. After an evaluation of the prognostic aerosol scheme, the dust aerosol daily variability is shown to improve the simulated surface radiation and temperature at the daily scale. It has also a significant impact on the summer average, thus highlighting the importance of a relevant representation of aerosols in climate models.
A. Hally, O. Caumont, L. Garrote, E. Richard, A. Weerts, F. Delogu, E. Fiori, N. Rebora, A. Parodi, A. Mihalović, M. Ivković, L. Dekić, W. van Verseveld, O. Nuissier, V. Ducrocq, D. D'Agostino, A. Galizia, E. Danovaro, and A. Clematis
Nat. Hazards Earth Syst. Sci., 15, 537–555, https://doi.org/10.5194/nhess-15-537-2015, https://doi.org/10.5194/nhess-15-537-2015, 2015
E. Defer, J.-P. Pinty, S. Coquillat, J.-M. Martin, S. Prieur, S. Soula, E. Richard, W. Rison, P. Krehbiel, R. Thomas, D. Rodeheffer, C. Vergeiner, F. Malaterre, S. Pedeboy, W. Schulz, T. Farges, L.-J. Gallin, P. Ortéga, J.-F. Ribaud, G. Anderson, H.-D. Betz, B. Meneux, V. Kotroni, K. Lagouvardos, S. Roos, V. Ducrocq, O. Roussot, L. Labatut, and G. Molinié
Atmos. Meas. Tech., 8, 649–669, https://doi.org/10.5194/amt-8-649-2015, https://doi.org/10.5194/amt-8-649-2015, 2015
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The paper summarizes the scientific objectives and the observational/modeling strategy of the atmospheric electricity PEACH project of the HyMeX program focusing on the lightning activity and the electrical state of Mediterranean thunderstorms. Examples of concurrent observations from radio frequency to acoustic for regular and atypical lightning flashes and for storms are discussed, showing the unique and comprehensive description of lightning flashes recorded during a dedicated field campaign.
N. Canal, J.-C. Calvet, B. Decharme, D. Carrer, S. Lafont, and G. Pigeon
Hydrol. Earth Syst. Sci., 18, 4979–4999, https://doi.org/10.5194/hess-18-4979-2014, https://doi.org/10.5194/hess-18-4979-2014, 2014
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Regional French agricultural yield statistics are used to benchmark root water uptake representations in the ISBA-A-gs model. Key model parameters governing the inter-annual variability of the simulated biomass are retrieved. A complex multi-layer soil hydrology model does not outperform a simple bulk root-zone reservoir approach. This could be explained by missing processes/information in the model such as hydraulic redistribution and detailed soil properties.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir
Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, https://doi.org/10.5194/gmd-7-2933-2014, 2014
A. Jansa, P. Alpert, P. Arbogast, A. Buzzi, B. Ivancan-Picek, V. Kotroni, M. C. Llasat, C. Ramis, E. Richard, R. Romero, and A. Speranza
Nat. Hazards Earth Syst. Sci., 14, 1965–1984, https://doi.org/10.5194/nhess-14-1965-2014, https://doi.org/10.5194/nhess-14-1965-2014, 2014
A. Hally, E. Richard, and V. Ducrocq
Nat. Hazards Earth Syst. Sci., 14, 1071–1084, https://doi.org/10.5194/nhess-14-1071-2014, https://doi.org/10.5194/nhess-14-1071-2014, 2014
M.-P. Moine, S. Valcke, B. N. Lawrence, C. Pascoe, R. W. Ford, A. Alias, V. Balaji, P. Bentley, G. Devine, S. A. Callaghan, and E. Guilyardi
Geosci. Model Dev., 7, 479–493, https://doi.org/10.5194/gmd-7-479-2014, https://doi.org/10.5194/gmd-7-479-2014, 2014
H. Brenot, A. Walpersdorf, M. Reverdy, J. van Baelen, V. Ducrocq, C. Champollion, F. Masson, E. Doerflinger, P. Collard, and P. Giroux
Atmos. Meas. Tech., 7, 553–578, https://doi.org/10.5194/amt-7-553-2014, https://doi.org/10.5194/amt-7-553-2014, 2014
E. Joetzjer, H. Douville, C. Delire, P. Ciais, B. Decharme, and S. Tyteca
Hydrol. Earth Syst. Sci., 17, 4885–4895, https://doi.org/10.5194/hess-17-4885-2013, https://doi.org/10.5194/hess-17-4885-2013, 2013
P. Huszar, H. Teyssèdre, M. Michou, A. Voldoire, D. J. L. Olivié, D. Saint-Martin, D. Cariolle, S. Senesi, D. Salas Y Melia, A. Alias, F. Karcher, P. Ricaud, and T. Halenka
Atmos. Chem. Phys., 13, 10027–10048, https://doi.org/10.5194/acp-13-10027-2013, https://doi.org/10.5194/acp-13-10027-2013, 2013
R. Alkama, L. Marchand, A. Ribes, and B. Decharme
Hydrol. Earth Syst. Sci., 17, 2967–2979, https://doi.org/10.5194/hess-17-2967-2013, https://doi.org/10.5194/hess-17-2967-2013, 2013
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
S. Valcke
Geosci. Model Dev., 6, 373–388, https://doi.org/10.5194/gmd-6-373-2013, https://doi.org/10.5194/gmd-6-373-2013, 2013
S. Valcke, V. Balaji, A. Craig, C. DeLuca, R. Dunlap, R. W. Ford, R. Jacob, J. Larson, R. O'Kuinghttons, G. D. Riley, and M. Vertenstein
Geosci. Model Dev., 5, 1589–1596, https://doi.org/10.5194/gmd-5-1589-2012, https://doi.org/10.5194/gmd-5-1589-2012, 2012
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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.
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
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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
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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.
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
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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.
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
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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
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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.
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.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Cited articles
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Short summary
This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications. The objective of this development is to build and share a common structure for the atmosphere–surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models.
This study presents the principles of the new coupling interface based on the SURFEX...
Special issue