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1. Process‐Based Climate Model Development Harnessing Machine Learning: I. A Calibration Tool for Parameterization Improvement

Author

Fleur Couvreux, Frédéric Hourdin, Daniel Williamson, Romain Roehrig, Victoria Volodina, Najda Villefranque, Catherine Rio, Olivier Audouin, James Salter, Eric Bazile, Florent Brient, Florence Favot, Rachel Honnert, Marie‐Pierre Lefebvre, Jean‐Baptiste Madeleine, Quentin Rodier, and Wenzhe Xu

Subjects
calibration, large‐eddy simulations, physical parameterizations, process‐oriented model tuning, single‐column models, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract

Abstract The development of parameterizations is a major task in the development of weather and climate models. Model improvement has been slow in the past decades, due to the difficulty of encompassing key physical processes into parameterizations, but also of calibrating or “tuning” the many free parameters involved in their formulation. Machine learning techniques have been recently used for speeding up the development process. While some studies propose to replace parameterizations by data‐driven neural networks, we rather advocate that keeping physical parameterizations is key for the reliability of climate projections. In this paper we propose to harness machine learning to improve physical parameterizations. In particular, we use Gaussian process‐based methods from uncertainty quantification to calibrate the model free parameters at a process level. To achieve this, we focus on the comparison of single‐column simulations and reference large‐eddy simulations over multiple boundary‐layer cases. Our method returns all values of the free parameters consistent with the references and any structural uncertainties, allowing a reduced domain of acceptable values to be considered when tuning the three‐dimensional (3D) global model. This tool allows to disentangle deficiencies due to poor parameter calibration from intrinsic limits rooted in the parameterization formulations. This paper describes the tool and the philosophy of tuning in single‐column mode. Part 2 shows how the results from our process‐based tuning can help in the 3D global model tuning.

Published
2021
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2. Process Oriented evaluation of the oversea AROME configuration: focus on the representation of cloud organisation

Author

Florent Beucher, Fleur Couvreux, Dominique Bouniol, Ghislain Faure, Florence Favot, Thibaut Dauhut, Alex Ayet, Centre national de recherches météorologiques (CNRM), 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), GIPSA - Signal Images Physique (GIPSA-SIGMAPHY), GIPSA Pôle Sciences des Données (GIPSA-PSD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Climat, Environnement, Couplages et Incertitudes [Toulouse] (CECI), and Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, evaluation, Clouds < 3. Physical phenomenon Boundary layer < 4. Geophysical sphere Tropics < 5. Geographic/climatic zone Dynamic/Processes < 1, [SDU]Sciences of the Universe [physics], Tropics < 5. Geographic/climatic zone, cloud resolving model, shallow convection, North Atlantic Trades, Boundary layer < 4. Geophysical sphere, cloud -organisation, Clouds < 3. Physical phenomenon, Dynamic/Processes < 1
Abstract

International audience; This study evaluates the ability of the French convection-permitting model AROME-OM to represent shallow cumulus and their main organisations forboreal winter conditions in the North Atlantic trades. It uses a set of three winter seasons (January–February, 2018–2020) of high-resolution (1.3 and 2.5 km) simulations over the Caribbean domain (9.7–22.9◦ N, 75.3–51.7◦ W). The model is assessed against soundings at Grantley Adams Airport and remote-sensing observations at a site located on the east coast of Barbados which is representative of downwind trade regimes. The thermodynamic environment of the model fits the observations overall but the boundary layer is slightly too deep, resulting in a weak cold and dry bias. Both model and observations clearly exhibit (a) a double peak of cloud fraction, a first peak near the cloud base and a second one near the cloud top and (b) a larger variance in cloudiness near the top of the deepest cumuli, at around 2 km, with a higher sensitivity to the environment. We then take advantage of the EUREC4 A field campaign which took place in January–February 2020 to assess the ability of the model to reproduce the four main mesoscale patterns and to characterize the air masses in which they develop. All the observations confirm the capacity of the model to predict the different mesoscale organizations and their associated environment.

Published
2022
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3. Process-based climate model development harnessing machine learning: I. a calibration tool for parameterization improvement

Author

James M. Salter, Wenzhe Xu, Daniel Williamson, Fleur Couvreux, Catherine Rio, Florent Brient, Florence Favot, Quentin Rodier, Marie-Pierre Lefebvre, Rachel Honnert, Najda Villefranque, Eric Bazile, Olivier Audouin, Victoria Volodina, Frédéric Hourdin, Romain Roehrig, Jean-Baptiste Madeleine, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), University of Exeter, The Alan Turing Institute, LAboratoire PLasma et Conversion d'Energie (LAPLACE), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), 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), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), and Université de Toulouse (UT)

Subjects
010504 meteorology & atmospheric sciences, Calibration (statistics), Computer science, Process (engineering), 0207 environmental engineering, Weather and climate, 02 engineering and technology, 01 natural sciences, process‐oriented model tuning, Task (project management), 010104 statistics & probability, lcsh:Oceanography, Development (topology), Environmental Chemistry, physical parameterizations, lcsh:GC1-1581, 0101 mathematics, 020701 environmental engineering, lcsh:Physical geography, 0105 earth and related environmental sciences, Global and Planetary Change, calibration, single‐column models, Industrial engineering, [SDU]Sciences of the Universe [physics], large‐eddy simulations, Key (cryptography), General Earth and Planetary Sciences, Climate model, lcsh:GB3-5030
Abstract

International audience; • We apply uncertainty quantification to single-column model/large-eddy simulation comparison to calibrate free parameters • We revisit model development strategy with an emphasiThe development of parameterizations is a major task in the development of weather and climate models. Model improvement has been slow in the past decades, due to the difficulty of encompassing key physical processes into parameterizations, but also of calibrating or “tuning” the many free parameters involved in their formulation. Machine learning techniques have been recently used for speeding up the development process. While some studies propose to replace parameterizations by data‐driven neural networks, we rather advocate that keeping physical parameterizations is key for the reliability of climate projections. In this paper we propose to harness machine learning to improve physical parameterizations. In particular, we use Gaussian process‐based methods from uncertainty quantification to calibrate the model free parameters at a process level. To achieve this, we focus on the comparison of single‐column simulations and reference large‐eddy simulations over multiple boundary‐layer cases. Our method returns all values of the free parameters consistent with the references and any structural uncertainties, allowing a reduced domain of acceptable values to be considered when tuning the three‐dimensional (3D) global model. This tool allows to disentangle deficiencies due to poor parameter calibration from intrinsic limits rooted in the parameterization formulations. This paper describes the tool and the philosophy of tuning in single‐column mode. Part 2 shows how the results from our process‐based tuning can help in the 3D global model tuning.s on processes for model calibration • The proposed tuning tool allows to formalize the complementary use of multicases with various metrics

Published
2020
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4. Representation of daytime moist convection over the semi‐arid Tropics by parametrizations used in climate and meteorological models

Author

T. Komori, Fleur Couvreux, Mihaela Caian, Catherine Rio, Peter Bechtold, M. P. Lefebvre, Fabio D'Andrea, Françoise Guichard, Florence Favot, S. H. Derbyshire, Pierre Gentine, and Romain Roehrig

Subjects
Convection, Atmospheric Science, Coupled model intercomparison project, Daytime, Mesoscale meteorology, Atmospheric sciences, Monsoon, Physics::Fluid Dynamics, Troposphere, Boundary layer, Diurnal cycle, Climatology, Environmental science, Physics::Atmospheric and Oceanic Physics
Abstract

A case of daytime development of deep convection over tropical semi-arid land is used to evaluate the representation of convection in global and regional models. The case is based on observations collected during the African Monsoon Multidisciplinary Analysis (AMMA) field campaign and includes two distinct transition phases, from clear sky to shallow cumulus and from cumulus to deep convection. Different types of models, run with identical initial and boundary conditions, are intercompared: a reference large-eddy simulation (LES), single-column model (SCM) version of four different Earth system models that participated in the Coupled Model Intercomparison Project 5 exercise, the SCM version of the European Centre for Medium-range Weather Forecasts operational forecast model, the SCM version of a mesoscale model and a bulk model. Surface fluxes and radiative heating are prescribed preventing any atmosphere–surface and cloud–radiation coupling in order to simplify the analyses so that it focuses only on convective processes. New physics packages are also evaluated within this framework. As the LES correctly reproduces the observed growth of the boundary layer, the gradual development of shallow clouds, the initiation of deep convection and the development of cold pools, it provides a basis to evaluate in detail the representation of the diurnal cycle of convection by the other models and to test the hypotheses underlying convective parametrizations. Most SCMs have difficulty in representing the timing of convective initiation and rain intensity, although substantial modifications to boundary-layer and deep-convection parametrizations lead to improvements. The SCMs also fail to represent the mid-level troposphere moistening during the shallow convection phase, which we analyse further. Nevertheless, beyond differences in timing of deep convection, the SCM models reproduce the sensitivity to initial and boundary conditions simulated in the LES regarding boundary-layer characteristics, and often the timing of convection triggering.

Published
2015
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5. Diurnal and Seasonal Cycles of Cloud Occurrences, Types, and Radiative Impact over West Africa

Author

Fleur Couvreux, Dominique Bouniol, Madeleine Leplay, Françoise Guichard, Florence Favot, Ewan O'Connor, and Pierre-Honoré Kamsu-Tamo

Subjects
Saharan Air Layer, Atmospheric Science, Lidar, Diurnal cycle, Cloud cover, International Satellite Cloud Climatology Project, Longwave, Environmental science, Radiative forcing, Monsoon, Atmospheric sciences
Abstract

This study focuses on the occurrence and type of clouds observed in West Africa, a subject that has been neither much documented nor quantified. It takes advantage of data collected above Niamey, Niger, in 2006 with the Atmospheric Radiation Measurement (ARM) Mobile Facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds, and midlevel clouds. A frequent occurrence of the latter clouds located at the top of the Saharan air layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution are investigated. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that midlevel clouds are present over the Sahara during most of the monsoon season. Moreover, using complementary datasets, the radiative impact of each type of clouds at the surface level has been quantified in the short- and longwave domains. Midlevel clouds and anvil clouds have the largest impact, respectively, in longwave (about 15 W m−2) and shortwave (about 150 W m−2) radiation. Furthermore, midlevel clouds exert a strong radiative forcing during the spring at a time when the other cloud types are less numerous.

Published
2012
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6. AMMA information system: an efficient cross-disciplinary tool and a legacy for forthcoming projects

Author

Laurence Fleury, Jean-Luc Redelsperger, Nicole Asencio, Jean-Luc Boichard, Guillaume Brissebrat, Jean Coppeaux, Oumarou Moulaye, Marie-Pierre Devic, Florence Favot, Laurence Eymard, Laurence Mastrorillo, Odile Roussot, Jean-Philippe Lafore, Karine Ginoux, Karim Ramage, Michel Tytéca, Sophie Cloché, Jan Polcher, Centre national de recherches météorologiques (CNRM), 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), Services communs OMP (UMS 831), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-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 Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre Régional AGRHYMET (CRA), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), African Monsoon Multidisciplinary Analyses (AMMA) programme, 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), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS Paris), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)

Subjects
campaign website, Atmospheric Science, 010504 meteorology & atmospheric sciences, Computer science, Data management, computer.software_genre, 01 natural sciences, Distribution system, 03 medical and health sciences, interdisciplinarity, Multidisciplinary approach, bibliography database, Information system, Information exchange, 030304 developmental biology, 0105 earth and related environmental sciences, 0303 health sciences, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Distributed database, Cross disciplinary, business.industry, Data science, distributed database, Data mining, business, computer
Abstract

International audience; In the framework of the African Monsoon Multidisciplinary Analyses (AMMA) programme, several tools have been developed in order to facilitate and speed up data and information exchange between researchers from different disciplines. The AMMA information system includes a multidisciplinary user-friendly distributed data management and distribution system, a reports and quick looks archive associated with a display website and scientific papers exchange systems. All the applications have been developed by several French institutions and fully duplicated in Niamey, Niger.

Published
2011
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7. The West African climate system: a review of the AMMA model inter-comparison initiatives

Author

Marta Domínguez, Teresa Losada, Filippo Giorgi, Françoise Guichard, Florence Favot, Markku Rummukainen, Jean-Philippe Lafore, P. F. J. van Velthoven, Ionela Musat, Béatrice Josse, J. E. Williams, Miguel Ángel Gaertner, Frédéric Hourdin, Céline Mari, Kathy S. Law, Xin Yang, A. K. Traore, Brice Barret, Jan Polcher, Idir Bouarar, M. B. Rodriguez de Fonseca, Paolo Ruti, Aaron Boone, Yongkang Xue, Energy Environment Modeling Unit-Climate and Impact Modeling Laboratory (UTMEA-CLIM), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile = Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Royal Netherlands Meteorological Institute (KNMI), Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Centre national de recherches météorologiques (CNRM), 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), Swedish Meteorological and Hydrological Institute (SMHI), Instituto de Ciencias Ambientales [Toledo] (ICAM), Universidad de Castilla-La Mancha = University of Castilla-La Mancha (UCLM), Departamento de Geofisica y Meteorologia [Madrid], Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Abdus Salam International Centre for Theoretical Physics [Trieste] (ICTP), Department of Geography [Los Angeles], University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'aérologie (LAERO), 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), Centre for Atmospheric Science [Cambridge, UK], University of Cambridge [UK] (CAM), Laboratoire de Physique de l'Atmosphère et de l'Océan Siméon Fongang (LPAO-SF), École Supérieure Polytechnique de Dakar (ESP), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), École normale supérieure - Paris (ENS Paris), Département des Géosciences - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), 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), Universidad de Castilla-La Mancha (UCLM), University of California-University of California, Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées

Subjects
2. Zero hunger, Systematic error, Atmospheric Science, 010504 meteorology & atmospheric sciences, Multidisciplinary analysis, [SDE.MCG]Environmental Sciences/Global Changes, Climate system, 0207 environmental engineering, 02 engineering and technology, 15. Life on land, Monsoon, Systematic errors, 01 natural sciences, West africa, West african, Geography, African monsoon, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, 020701 environmental engineering, Regional and global model uncertainties, 0105 earth and related environmental sciences
Abstract

International audience; We review the African Monsoon Multidisciplinary Analysis (AMMA) model inter-comparison activities for West Africa. The Model Inter-comparison Project is an evaluation exercise of how global and regional atmospheric models represent seasonal and intra-seasonal variations of the climate and rainfall over the Sahel. The Land surface Model Inter-comparison Project in turn focuses on modelling critical land surface processes over West Africa and on their link with the atmosphere. The CHEmistry Model Inter-comparison Project (CHEMIP) is a comparison of the tropospheric composition as simulated by a number of Chemical Transport Models (CTM) and Chemistry-Climate Models. We highlight the main model limitations and provide recommendations for future development.

Published
2011
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