Evaluation of CMIP6 DECK Experiments With CNRM-CM6-1
Aurore Voldoire,David Saint-Martin,Stephane Sénési,Bertrand Decharme,Antoinette Alias,Matthieu Chevallier,Jeanne Colin,Jean-François Guérémy,Martine Michou,M. P. Moine,Pierre Nabat,Romain Roehrig,D. Salas y Melia,Roland Séférian,Sophie Valcke,I. Beau,Sophie Belamari,Sarah Berthet,Christophe Cassou,Julien Cattiaux,Julie Deshayes,Hervé Douville,Christian Ethé,Laurent Franchistéguy,Olivier Geoffroy,C. Lévy,Gurvan Madec,Gurvan Madec,Yann Meurdesoif,Rym Msadek,Aurélien Ribes,Emilia Sanchez-Gomez,Laurent Terray,Robin Waldman +33 more
TLDR
In this paper, the authors describe the main characteristics of CNRM-CM6-1, the fully coupled atmosphere-ocean general circulation model of sixth generation jointly developed by Centre National de Recherches Meteorologiques (CNRM) and Cerfacs for the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6).Abstract:
This paper describes the main characteristics of CNRM-CM6-1, the fully coupled atmosphere-ocean general circulation model of sixth generation jointly developed by Centre National de Recherches Meteorologiques (CNRM) and Cerfacs for the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6). The paper provides a description of each component of CNRM-CM6-1, including the coupling method and the new online output software. We emphasize where model's components have been updated with respect to the former model version, CNRM-CM5.1. In particular, we highlight major improvements in the representation of atmospheric and land processes. A particular attention has also been devoted to mass and energy conservation in the simulated climate system to limit long-term drifts. The climate simulated by CNRM-CM6-1 is then evaluated using CMIP6 historical and Diagnostic, Evaluation and Characterization of Klima (DECK) experiments in comparison with CMIP5 CNRM-CM5.1 equivalent experiments. Overall, the mean surface biases are of similar magnitude but with different spatial patterns. Deep ocean biases are generally reduced, whereas sea ice is too thin in the Arctic. Although the simulated climate variability remains roughly consistent with CNRM-CM5.1, its sensitivity to rising CO 2 has increased: the equilibrium climate sensitivity is 4.9 K, which is now close to the upper bound of the range estimated from CMIP5 models.read more
Citations
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Journal ArticleDOI
Causes of Higher Climate Sensitivity in CMIP6 Models
Mark D. Zelinka,Timothy A. Myers,Daniel T. McCoy,Stephen Po-Chedley,Peter M. Caldwell,Paulo Ceppi,Stephen A. Klein,Karl E. Taylor +7 more
TL;DR: In this article, the authors show that the global surface temperature response to CO2 doubling has increased substantially in the Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8-5.6k across 27 GCMs and exceeding 4.5K in 10 of them.
Journal ArticleDOI
Presentation and evaluation of the IPSL‐CM6A‐LR climate model
Olivier Boucher,Jérôme Servonnat,Anna Lea Albright,Olivier Aumont,Yves Balkanski,Vladislav Bastrikov,Slimane Bekki,Rémy Bonnet,Sandrine Bony,Laurent Bopp,Pascale Braconnot,Patrick Brockmann,Patricia Cadule,Arnaud Caubel,Frédérique Cheruy,Francis Codron,Anne Cozic,David Cugnet,Fabio D'Andrea,Paolo Davini,Casimir de Lavergne,Sébastien Denvil,Julie Deshayes,Marion Devilliers,Agnès Ducharne,Jean-Louis Dufresne,Eliott Dupont,Christian Ethé,Laurent Fairhead,Lola Falletti,Simona Flavoni,Marie Alice Foujols,Sébastien Gardoll,Guillaume Gastineau,Josefine Ghattas,Jean Yves Grandpeix,Bertrand Guenet,E. Guez Lionel,Eric Guilyardi,Matthieu Guimberteau,Didier Hauglustaine,Frédéric Hourdin,Abderrahmane Idelkadi,Sylvie Joussaume,Masa Kageyama,Myriam Khodri,Gerhard Krinner,Nicolas Lebas,Guillaume Levavasseur,Claire Lévy,Laurent Li,François Lott,Thibaut Lurton,Sebastiaan Luyssaert,Gurvan Madec,Jean Baptiste Madeleine,Fabienne Maignan,Marion Marchand,Olivier Marti,Lidia Mellul,Yann Meurdesoif,Juliette Mignot,Ionela Musat,Catherine Ottlé,Philippe Peylin,Yann Planton,Jan Polcher,Catherine Rio,Nicolas Rochetin,Clément Rousset,Pierre Sepulchre,Adriana Sima,Didier Swingedouw,Rémi Thiéblemont,Abdoul Khadre Traore,Martin Vancoppenolle,Jessica Vial,Jérôme Vialard,Nicolas Viovy,Nicolas Vuichard +79 more
TL;DR: The authors presented the global climate model IPSL-CM6A-LR developed at the Institut Pierre-Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6).
Journal ArticleDOI
Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future Climate
Roland Séférian,Pierre Nabat,Martine Michou,David Saint-Martin,Aurore Voldoire,Jeanne Colin,Bertrand Decharme,Christine Delire,Sarah Berthet,Matthieu Chevallier,Stephane Sénési,Laurent Franchistéguy,Jessica Vial,Marc Mallet,Emilie Joetzjer,Olivier Geoffroy,Jean-François Guérémy,Marie-Pierre Moine,Rym Msadek,Aurélien Ribes,Matthias Rocher,Romain Roehrig,David Salas-y-Mélia,Emilia Sanchez,Laurent Terray,Sophie Valcke,Robin Waldman,Olivier Aumont,Laurent Bopp,Julie Deshayes,Christian Ethé,Gurvan Madec,Gurvan Madec +32 more
TL;DR: In this article, the Earth system (ES) model of second generation developed by CNRM-CERFACS for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) was compared to the Atmosphere Ocean General Circulation Model (AOCM) by adding interactive ES components such as carbon cycle, aerosols, and atmospheric chemistry.
Journal ArticleDOI
Projections of Precipitation and Temperature over the South Asian Countries in CMIP6
TL;DR: In this article, the authors analyzed the projected changes in temperature and precipitation over six South Asian countries during the twenty-first century, and showed that the CMIP6 models display higher sensitivity to greenhouse gas emissions over South Asia compared with the CMIA5 models.
Journal ArticleDOI
Added value of CMIP6 over CMIP5 models in simulating Indian summer monsoon rainfall
TL;DR: In this article, the authors compared the performance of models available in CMIP5 and CMIP6 consortium and their multi-model average (MMA) and found a significant improvement in model performance in capturing the spatiotemporal pattern of monsoon over Indian landmass, especially in the Western Ghats and North-east foothills of Himalayas.
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