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3. LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

Author

Van Den Hurk, Bart, Kim, Hyungjun, Krinner, Gerhard, Seneviratne, Sonia I, Derksen, Chris, Oki, Taikan, Douville, Herve, Colin, Jeanne, Ducharne, Agnes, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael J, Wada, Yoshide, Li, Weiping, Jia, Binghao, Alessandri, Andrea, Lawrence, Dave M, Weedon, Graham P, Ellis, Richard, and Hagemann, Stefan

Subjects
Meteorology And Climatology
Abstract

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems).The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (LMIP, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (LFMIP, building upon the GLACE-CMIP blueprint).

Published
2016
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4. The CNRM Global Atmosphere Model ARPEGE‐Climat 6.3: Description and Evaluation

Author

Roehrig, Romain, primary, Beau, Isabelle, additional, Saint‐Martin, David, additional, Alias, Antoinette, additional, Decharme, Bertrand, additional, Guérémy, Jean‐François, additional, Voldoire, Aurore, additional, Abdel‐Lathif, Ahmat Younous, additional, Bazile, Eric, additional, Belamari, Sophie, additional, Blein, Sebastien, additional, Bouniol, Dominique, additional, Bouteloup, Yves, additional, Cattiaux, Julien, additional, Chauvin, Fabrice, additional, Chevallier, Matthieu, additional, Colin, Jeanne, additional, Douville, Hervé, additional, Marquet, Pascal, additional, Michou, Martine, additional, Nabat, Pierre, additional, Oudar, Thomas, additional, Peyrillé, Philippe, additional, Piriou, Jean‐Marcel, additional, Salas y Mélia, David, additional, Séférian, Roland, additional, and Sénési, Stéphane, additional

Published
2020
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5. Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future Climate

Author

Séférian, Roland, primary, Nabat, Pierre, additional, Michou, Martine, additional, Saint‐Martin, David, additional, Voldoire, Aurore, additional, Colin, Jeanne, additional, Decharme, Bertrand, additional, Delire, Christine, additional, Berthet, Sarah, additional, Chevallier, Matthieu, additional, Sénési, Stephane, additional, Franchisteguy, Laurent, additional, Vial, Jessica, additional, Mallet, Marc, additional, Joetzjer, Emilie, additional, Geoffroy, Olivier, additional, Guérémy, Jean‐François, additional, Moine, Marie‐Pierre, additional, Msadek, Rym, additional, Ribes, Aurélien, additional, Rocher, Matthias, additional, Roehrig, Romain, additional, Salas‐y‐Mélia, David, additional, Sanchez, Emilia, additional, Terray, Laurent, additional, Valcke, Sophie, additional, Waldman, Robin, additional, Aumont, Olivier, additional, Bopp, Laurent, additional, Deshayes, Julie, additional, Éthé, Christian, additional, and Madec, Gurvan, additional

Published
2019
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6. Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate

Author

Seferian, Roland, Nabat, Pierre, Michou, Martine, Saint-martin, David, Voldoire, Aurore, Colin, Jeanne, Decharme, Bertrand, Delire, Christine, Berthet, Sarah, Chevallier, Matthieu, Senesi, Stephane, Franchisteguy, Laurent, Vial, Jessica, Mallet, Marc, Joetzjer, Emilie, Geoffroy, Olivier, Gueremy, Jean-francois, Moine, Marie-pierre, Msadek, Rym, Ribes, Aurelien, Rocher, Matthias, Roehrig, Romain, Salas-y-melia, David, Sanchez, Emilia, Terray, Laurent, Valcke, Sophie, Waldman, Robin, Aumont, Olivier, Bopp, Laurent, Deshayes, Julie, Ethe, Christian, Madec, Gurvan, Seferian, Roland, Nabat, Pierre, Michou, Martine, Saint-martin, David, Voldoire, Aurore, Colin, Jeanne, Decharme, Bertrand, Delire, Christine, Berthet, Sarah, Chevallier, Matthieu, Senesi, Stephane, Franchisteguy, Laurent, Vial, Jessica, Mallet, Marc, Joetzjer, Emilie, Geoffroy, Olivier, Gueremy, Jean-francois, Moine, Marie-pierre, Msadek, Rym, Ribes, Aurelien, Rocher, Matthias, Roehrig, Romain, Salas-y-melia, David, Sanchez, Emilia, Terray, Laurent, Valcke, Sophie, Waldman, Robin, Aumont, Olivier, Bopp, Laurent, Deshayes, Julie, Ethe, Christian, and Madec, Gurvan

Abstract

This study introduces CNRM-ESM2-1, the Earth system (ES) model of second generation developed by CNRM-CERFACS for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). CNRM-ESM2-1 offers a higher model complexity than the Atmosphere-Ocean General Circulation Model CNRM-CM6-1 by adding interactive ES components such as carbon cycle, aerosols, and atmospheric chemistry. As both models share the same code, physical parameterizations, and grid resolution, they offer a fully traceable framework to investigate how far the represented ES processes impact the model performance over present-day, response to external forcing and future climate projections. Using a large variety of CMIP6 experiments, we show that represented ES processes impact more prominently the model response to external forcing than the model performance over present-day. Both models display comparable performance at replicating modern observations although the mean climate of CNRM-ESM2-1 is slightly warmer than that of CNRM-CM6-1. This difference arises from land cover-aerosol interactions where the use of different soil vegetation distributions between both models impacts the rate of dust emissions. This interaction results in a smaller aerosol burden in CNRM-ESM2-1 than in CNRM-CM6-1, leading to a different surface radiative budget and climate. Greater differences are found when comparing the model response to external forcing and future climate projections. Represented ES processes damp future warming by up to 10% in CNRM-ESM2-1 with respect to CNRM-CM6-1. The representation of land vegetation and the CO2-water-stomatal feedback between both models explain about 60% of this difference. The remainder is driven by other ES feedbacks such as the natural aerosol feedback.

Published
2019
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7. Overview of the Meso-NH model version 5.4 and its applications

Author

Lac, Christine, Chaboureau, Jean-Pierre, Masson, Valéry, Pinty, Jean-Pierre, Tulet, Pierre, Escobar, Juan, Leriche, Maud, Barthe, Christelle, Aouizerats, Benjamin, Augros, Clotilde, Aumond, Pierre, Auguste, Franck, Bechtold, Peter, Berthet, Sarah, Bielli, Soline, Bosseur, Frédéric, Caumont, Olivier, Cohard, Jean-Martial, Colin, Jeanne, Couvreux, Fleur, Cuxart, Joan, Delautier, Gaëlle, Dauhut, Thibaut, Ducrocq, Véronique, Filippi, Jean-Baptiste, Gazen, Didier, Geoffroy, Olivier, Gheusi, François, Honnert, Rachel, Lafore, Jean-Philippe, Lebeaupin Brossier, Cindy, Libois, Quentin, Lunet, Thibaut, Mari, Céline, Maric, Tomislav, Mascart, Patrick, Mogé, Maxime, Molinié, Gilles, Nuissier, Olivier, Pantillon, Florian, Peyrillé, Philippe, Pergaud, Julien, Perraud, Emilie, Pianezze, Joris, Redelsperger, Jean-Luc, Ricard, Didier, Richard, Evelyne, Riette, Sébastien, Rodier, Quentin, Schoetter, Robert, Seyfried, Léo, Stein, Joël, Suhre, Karsten, Taufour, Marie, Thouron, Odile, Turner, Sandra, Verrelle, Antoine, Vié, Benoît, Visentin, Florian, Vionnet, Vincent, Wautelet, Philippe, Centre national de recherches météorologiques (CNRM), Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LAERO), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Laboratoire de l'Atmosphère et des Cyclones (LACy), Centre National de la Recherche Scientifique (CNRS)-Université de La Réunion (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France, Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), CERFACS, European Centre for Medium-Range Weather Forecasts (ECMWF), Sciences pour l'environnement (SPE), Centre National de la Recherche Scientifique (CNRS)-Université Pascal Paoli (UPP), Institut des Géosciences de l’Environnement (IGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), University of the Balearic Islands (UIB), CERFACS [Toulouse], Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Océanographie Physique et Spatiale (LOPS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Météo-France [Paris], Météo France, Institute of Bioinformatics and Systems Biology [München], Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Weill Cornell Medicine [Qatar], Revenue Canada Agency, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LA), Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP)-Université Toulouse III - Paul Sabatier (UPS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Météo France-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS), VU University Amsterdam, Météo France-Centre National de la Recherche Scientifique (CNRS), Département Infrastructures et Mobilité (IFSTTAR/IM), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-PRES Université Nantes Angers Le Mans (UNAM), Institut de mécanique des fluides de Toulouse (IMFT), Université Toulouse III - Paul Sabatier (UPS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Pascal Paoli (UPP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Feux de Forêt, Université Pascal Paoli (UPP)-Centre National de la Recherche Scientifique (CNRS)-Université Pascal Paoli (UPP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Génie Electrique de Grenoble (G2ELab), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire Associé de Météorologie Physique, Aubière, Compilation pour les Architectures MUlti-coeurS (CAMUS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Biogéosciences [Dijon] (BGS), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Information génomique et structurale (IGS), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques ( CNRM ), Météo France-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'aérologie - LA ( LA ), Université Paul Sabatier - Toulouse 3 ( UPS ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Observatoire Midi-Pyrénées ( OMP ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de l'Atmosphère et des Cyclones ( LACy ), Météo France-Université de la Réunion ( UR ) -Centre National de la Recherche Scientifique ( CNRS ), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique ( CERFACS ), European Centre for Medium-Range Weather Forecasts ( ECMWF ), Sciences pour l'environnement ( SPE ), Université Pascal Paoli ( UPP ) -Centre National de la Recherche Scientifique ( CNRS ), Institut des Géosciences de l’Environnement ( IGE ), Institut de Recherche pour le Développement ( IRD ) -Institut polytechnique de Grenoble - Grenoble Institute of Technology ( Grenoble INP ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ), University of the Balearic Islands ( UIB ), Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Océanographie Physique et Spatiale ( LOPS ), Institut de Recherche pour le Développement ( IRD ) -Institut Français de Recherche pour l'Exploitation de la Mer ( IFREMER ) -Université de Brest ( UBO ) -Centre National de la Recherche Scientifique ( CNRS ), Technische Universität München [München] ( TUM ), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS)-Météo-France, Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), and Météo-France

Subjects
[ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Physics::Atmospheric and Oceanic Physics, ComputingMilieux_MISCELLANEOUS
Abstract

This paper presents the Meso-NH model version 5.4. Meso-NH is an atmospheric non hydrostatic research model that is applied to a broad range of resolutions, from synoptic to turbulent scales, and is designed for studies of physics and chemistry. It is a limited-area model employing advanced numerical techniques, including monotonic advection schemes for scalar transport and fourth-order centered or odd-order WENO advection schemes for momentum. The model includes state-of-the-art physics parameterization schemes that are important to represent convective-scale phenomena and turbulent eddies, as well as flows at larger scales. In addition, Meso-NH 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. Here, we present the main innovations to the dynamics and physics of the code since the pioneer paper of Lafore et al. (1998) and provide an overview of recent applications and couplings.

Published
2018

8. ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks

Author

Krinner, Gerhard, Derksen, Chris, Essery, Richard, Flanner, Mark, Hagemann, Stefan, Clark, Martyn, Hall, Alex, Rott, Helmut, Brutel-Vuilmet, Claire, Kim, Hyungjun, Ménard, Cécile B., Mudryk, Lawrence, Thackeray, Chad, Wang, Libo, Arduini, Gabriele, Balsamo, Gianpaolo, Bartlett, Paul, Boike, Julia, Boone, Aaron, Chéruy, Frédérique, Colin, Jeanne, Cuntz, Matthias, Dai, Yongjiu, Decharme, Bertrand, Derry, Jeff, Ducharne, Agnès, Dutra, Emanuel, Fang, Xing, Fierz, Charles, Ghattas, Josephine, Gusev, Yeugeniy, Haverd, Vanessa, Kontu, Anna, Lafaysse, Matthieu, Law, Rachel, Lawrence, Dave, Li, Weiping, Marke, Thomas, Marks, Danny, Ménégoz, Martin, Nasonova, Olga, Nitta, Tomoko, Niwano, Masashi, Pomeroy, John, Raleigh, Mark S., Schaedler, Gerd, Semenov, Vladimir, Smirnova, Tanya G., Stacke, Tobias, Strasser, Ulrich, Svenson, Sean, Turkov, Dmitry, Wang, Tao, Wever, Nander, Yuan, Hua, Zhou, Wenyan, Zhu, Dan, SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, World Climate Research Programme's Climate and Cryosphere (CliC) core project NERC Natural Environment Research CouncilNE/P011926/1European Space Agency Russian Science Foundation (RSF)16-17-10039Russian Foundation for Basic Research (RFBR)18-05-60216APPLICATE project European Union (EU)727862Swiss National Science Foundation (SNSF)200021E-160667European Union (EU)641816Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Japan Society for the Promotion of Science16H06291National Science Foundation (NSF)1543268, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Climate Research Division [Toronto], Environment and Climate Change Canada, School of Geosciences Grant Institute, University of Edinburgh, Department of Climate and Space Sciences and Engineering (CLaSP), University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Research Applications Laboratory [Boulder] (RAL), National Center for Atmospheric Research [Boulder] (NCAR), Environmental Earth Observation IT GmbH (ENVEO), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institute of Industrial Science (IIS), The University of Tokyo, Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École pratique des hautes études (EPHE)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), The University of Tokyo (UTokyo), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), École pratique des hautes études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.EE]Life Sciences [q-bio]/Ecology, environment, thermal-conductivity, arctic amplification, latitude hydrological processes, torne-kalix basin, water equivalent, Modélisation et simulation, land-surface model, intercomparison project, Earth sciences, Modeling and Simulation, [SDE]Environmental Sciences, ddc:550, albedo feedback, pilps phase-2(e), [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, Milieux et Changements globaux, sensitivity-analysis
Abstract

Krinner, Gerhard Derksen, Chris Essery, Richard Flanner, Mark Hagemann, Stefan Clark, Martyn Hall, Alex Rott, Helmut Brutel-Vuilmet, Claire Kim, Hyungjun Menard, Cecile B. Mudryk, Lawrence Thackeray, Chad Wang, Libo Arduini, Gabriele Balsamo, Gianpaolo Bartlett, Paul Boike, Julia Boone, Aaron Cheruy, Frederique Colin, Jeanne Cuntz, Matthias Dai, Yongjiu Decharme, Bertrand Derry, Jeff Ducharne, Agnes Dutra, Emanuel Fang, Xing Fierz, Charles Ghattas, Josephine Gusev, Yeugeniy Haverd, Vanessa Kontu, Anna Lafaysse, Matthieu Law, Rachel Lawrence, Dave Li, Weiping Marke, Thomas Marks, Danny Menegoz, Martin Nasonova, Olga Nitta, Tomoko Niwano, Masashi Pomeroy, John Raleigh, Mark S. Schaedler, Gerd Semenov, Vladimir Smirnova, Tanya G. Stacke, Tobias Strasser, Ulrich Svenson, Sean Turkov, Dmitry Wang, Tao Wever, Nander Yuan, Hua Zhou, Wenyan Zhu, Dan Menard, Cecile/F-7860-2014; Raleigh, Mark S/M-7687-2015; Krinner, Gerhard/A-6450-2011; Balsamo, Gianpaolo/M-5734-2019; Flanner, Mark/C-6139-2011; Nasonova, Olga/B-6093-2014; KIM, HYUNGJUN/I-5099-2014; Dutra, Emanuel/A-3774-2010; Turkov, Dmitry/Y-3186-2018; gusev, yeugeniy/G-4711-2014; Kontu, Anna/O-8886-2014; Zhu, Dan/J-4450-2019; Balsamo, Gianpaolo/I-3362-2013; Niwano, Masashi/N-6723-2016 Menard, Cecile/0000-0003-2166-9523; Raleigh, Mark S/0000-0002-1303-3472; Krinner, Gerhard/0000-0002-2959-5920; Balsamo, Gianpaolo/0000-0002-1745-3634; Flanner, Mark/0000-0003-4012-174X; KIM, HYUNGJUN/0000-0003-1083-8416; Dutra, Emanuel/0000-0002-0643-2643; Turkov, Dmitry/0000-0002-1813-757X; gusev, yeugeniy/0000-0003-3886-2143; Kontu, Anna/0000-0001-6880-6260; Zhu, Dan/0000-0002-5857-1899; Balsamo, Gianpaolo/0000-0002-1745-3634; Fang, Xing/0000-0002-4333-4815; Decharme, Bertrand/0000-0002-8661-1464; Niwano, Masashi/0000-0003-3121-3802 1991-9603; International audience; This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local-and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercom-parison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).

Published
2018

9. Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications

Author

Decharme, Bertrand, primary, Delire, Christine, additional, Minvielle, Marie, additional, Colin, Jeanne, additional, Vergnes, Jean‐Pierre, additional, Alias, Antoinette, additional, Saint‐Martin, David, additional, Séférian, Roland, additional, Sénési, Stéphane, additional, and Voldoire, Aurore, additional

Published
2019
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12. Adaptation of the meteorological model Meso-NH to laboratory experiments: implementations and validation.

Author

Colin, Jeanne, Lac, Christine, Massion, Valéry, and Paci, Alexandre

Subjects
*ATMOSPHERIC chemistry, *HYDROSTATICS, *BOUNDARY layer equations
Abstract

A meteorological numerical model can be a powerful tool to complement laboratory experiments applied to atmospheric sciences, but it needs to be adapted in order to represent flows generated in laboratory. This paper presents such an adaptation of the atmospheric non-hydrostatic model Meso-NH. The usually neglected viscous diffusive fluxes have been added to the model's equations, along with the coding of an explicit bottom no-slip boundary condition was implemented. These implementations are validated against exact solutions of ideal flows. Meso-NH is then used in a configuration matching a laboratory experiment performed in the CNRM large stratified water flume meant to reproduce a neutral atmospheric boundary layer. The model is run for the first time in an explicit mode (Direct Numerical Simulation - DNS) at a very high resolution (1 mm) over a large grid. The comparison with the experimental data shows that the boundary layer height and vertical profiles of mean velocity are well captured by the model. This result further validates the implementations carried out in Meso-NH which can now be used in a DNS mode to simulate channel flows. The joint use of Meso-NH and laboratory experiments, along with the possibility to run DNS with Meso-NH, could lead to new findings or improvements in the field of atmospheric sciences. [ABSTRACT FROM AUTHOR]

Published
2017
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13. Etude des événements précipitants intenses en Méditerranée : approche par la modélisation climatique régionale

Author

Colin, Jeanne and Colin, Jeanne

Abstract

Une étude de la variabilité climatique des événements méditerranéens de précipitations intenses dans le Sud-Est de la France (HPE : High Precipitation Events) est proposée au travers de l'analyse des performances du modèle de climat à aire limitée ALADIN-Climat. La sensibilité des pluies extrêmes simulées à différents paramètres de configuration du modèle est évaluée dans un cadre d'étude idéalisé ou à travers des expériences pilotées par la ré-analyse ERA-40. Les tests de sensibilité portent sur le couplage dynamique de l'atmosphère avec le modèle de mer Méditerranée NEMO-MED8, l'application d'une technique de pilotage spectral, la taille du domaine d'intégration et la résolution horizontale (passage de 50 à 12.5 km). Seule l'augmentation de la résolution conduit à une modification des précipitations extrêmes. Une étude détaillée de la valeur ajoutée ainsi apportée est alors conduite. Les résultats obtenus avec ALADIN-Climat sont ensuite comparés à ceux issus de deux méthodes de descente d'échelle statistique : la méthode de désagrégation DSCLIM (Boé et al., 2006) et la méthode de détection développée par Nuissier et al. (2011). Il s'avère que les performances d'ALADIN-Climat à 12.5 km sont plus satisfaisantes que celles de la première méthode et au moins équivalentes à celles de la seconde, d'où l'on conclut que ce modèle constitue donc un outil adéquat à l'étude de la variabilité climatique des HPE. Un scénario de changement climatique A1B est alors réalisé avec ALADIN-Climat pour la fin du XXe siècle, et différentes méthodes sont proposées pour l'analyse des résultats. Elles suggèrent un accroissement de la fréquence d'occurrence et une intensification des HPE., The climatic variability of intense rainfall events in the Mediterranean is studied using the limited area climate model ALADIN-Climate, whose ability to simulate these events in South-East France is explored. Several sensitivity studies are conducted to assess the impact of various configuration parameters on the model's skill to downscale such extreme events : coupling with a Mediterranean sea model, use of the spectral nudging technique, size of the domain of integration and horizontal resolution. These studies are either performed within the so-called Big-Brother Experiment framework or through hindcast simulations driven by the ERA-40 reanalysis. The increase of resolution (from 50 to 12.5 km) is found to be the only parameter affecting the modeling of extreme precipitation. The added value of the higher resolution on the way ALADIN-Climate simulates High Precipitation Events (HPE) in South-East France is carefully studied. Comparisons of ALADIN-Climate's skills to those of two State-of-the-art statistical methods of downscaling and detection of these events -- DSCLIM (Boé et al., 2006) and "CYPRIM" (Nuissier et al., 2011) -- show that with a resolution of 12.5 km, the model offers better results than the first method and appears to be at least as good as the second one, therefore it constitutes an appropriate numerical tool to explore the climatic variability of the HPE. A climate change scenario (A1B) is then performed with this tool for the end of the XXe century and we assess the simulated changes affecting HPE in future climate. Several methods are proposed to analyse and display the results, suggesting an increase of both the frequency and intensity of the HPE.

Published
2011

14. Sea level variability in the Mediterranean Sea during the 1990s on the basis to two 2d and one 3d model

Author

Tsimplis, Michael, Marcos, Marta, Colin, Jeanne, Somot, Samuel, Pascual, Ananda, Shaw, A.G.P., Tsimplis, Michael, Marcos, Marta, Colin, Jeanne, Somot, Samuel, Pascual, Ananda, and Shaw, A.G.P.

Abstract

The sea level rise in the 1990s at the Mediterranean Sea as evidenced by satellite altimetry is studied with the aid of ocean models. Two barotropic two dimensional (2d) models and one three dimensional (3d) model are used. Both 2d models indicate that the contribution of direct atmospheric forcing causes localised trends of up to 2 mm/yr. The 3d model successfully describes the evolution in temperature of the upper and intermediate waters. However the salinity changes are not well described. The steric contribution of sea level rise during this period is in places in excess of 10 mm/yr. Notably oceanic circulation is also found to contribute to sea level trends by up to − 3 mm/yr. Thus the observed sea level changes in the 1990s are better understood. The exceptional nature of the sea level behaviour in 1990s, especially in the eastern basin, when compared with previous decades is confirmed on the basis of both the 2d and the 3d models.

Published
2009

15. The Land Surface, Snow and Soil moisture Model Intercomparison Program (LS3MIP): aims, set-up and expected outcome.

Author

van den Hurk, Bart, Hyungjun Kim, Krinner, Gerhard, Seneviratne, Sonia I., Derksen, Chris, Taikan Oki, Douville, Hervé, Colin, Jeanne, Ducharne, Agnès, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael, Yoshihide Wada, Weiping Li, Binghao Jia, Alessandri, Andrea, Lawrence, Dave, Weedon, Graham P., Ellis, Richard, and Hagemann, Stefan

Subjects
SOIL moisture, SNOW & the environment, CLIMATE change, MATHEMATICAL models
Abstract

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode ("LMIP", building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework ("LFMIP", building upon the GLACE-CMIP blueprint). [ABSTRACT FROM AUTHOR]

Published
2016
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18. ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks

Author

Krinner, Gerhard, Derksen, Chris, Essery, Richard, Flanner, Mark, Hagemann, Stefan, Clark, Martyn, Hall, Alex, Rott, Helmut, Brutel-Vuilmet, Claire, Kim, Hyungjun, Ménard, Cécile B., Mudryk, Lawrence, Thackeray, Chad, Wang, Libo, Arduini, Gabriele, Balsamo, Gianpaolo, Bartlett, Paul, Boike, Julia, Boone, Aaron, Chéruy, Frédérique, Colin, Jeanne, Cuntz, Matthias, Dai, Yongjiu, Decharme, Bertrand, Derry, Jeff, Ducharne, Agnès, Dutra, Emanuel, Fang, Xing, Fierz, Charles, Ghattas, Josephine, Gusev, Yeugeniy, Haverd, Vanessa, Kontu, Anna, Lafaysse, Matthieu, Law, Rachel, Lawrence, Dave, Li, Weiping, Marke, Thomas, Marks, Danny, Ménégoz, Martin, Nasonova, Olga, Nitta, Tomoko, Niwano, Masashi, Pomeroy, John, Raleigh, Mark S., Schaedler, Gerd, Semenov, Vladimir, Smirnova, Tanya G., Stacke, Tobias, Strasser, Ulrich, Svenson, Sean, Turkov, Dmitry, Wang, Tao, Wever, Nander, Yuan, Hua, Zhou, Wenyan, and Zhu, Dan

Subjects
13. Climate action

19. LS3MIP (v1.0) contribution to CMIP6: The Land Surface, Snow and Soil moisture Model Intercomparison Project - Aims, setup and expected outcome

Author

Van den Hurk, Bart, Kim, Hyungjun, Krinner, Gerhard, Seneviratne, Sonia I., Derksen, Chris, Oki, Taikan, Douville, Hervé, Colin, Jeanne, Ducharne, Agnès, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael J., Wada, Yoshihide, Li, Weiping, Jia, Binghao, Alessandri, Andrea, Lawrence, Dave M., Weedon, Graham P., Ellis, Richard, Hagemann, Stefan, Mao, Jiafu, Flanner, Mark G., Zampieri, Matteo, Materia, Stefano, Law, Rachel M., and Sheffield, Justin

Subjects
13. Climate action, 15. Life on land, 6. Clean water
Abstract

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint)., Geoscientific Model Development, 9 (8), ISSN:1991-9603, ISSN:1991-959X

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