The AMMA Land Surface Model Intercomparison Project (ALMIP)

Aaron Boone
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Patricia de Rosnay
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Gianpaolo Balsamo
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Anton Beljaars
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Franck Chopin
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Bertrand Decharme
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Christine Delire
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Agnes Ducharne
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Simon Gascoin
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Manuela Grippa
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Françoise Guichard
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Yeugeniy Gusev
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Phil Harris
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Lionel Jarlan
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Laurent Kergoat
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Eric Mougin
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Olga Nasonova
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Anette Norgaard
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Tristan Orgeval
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Catherine Ottlé
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Isabelle Poccard-Leclercq
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Jan Polcher
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Inge Sandholt
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Stephane Saux-Picart
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Christopher Taylor
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Yongkang Xue
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The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.

GAME-Centre National de Recherche Météorologique, Toulouse, France

European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

IPSL, Laboratoire de Meteorologie Dynamique, Paris, France

ISE-Montpellier, Universite Montpellier 2, Montpellier, France

Sisyphe, Université Pierre et Marie Curie (UMPC/CNRS), Paris, France

Centres d'Etudes Spatiales de la Biosphère, Toulouse, France

Institute of Water Problems, Russian Academy of Sciences, Moscow, Russia

Centre for Ecology and Hydrology, Wallingford, United Kingdom

Institute of Geography, University of Copenhagen, Copenhagen, Denmark

IPSLLaboratoire des Sciences du Climat et de I'Environnement, Gif-sur-Yvette, France

LETG-Géolittomer, Université de Nantes, Nantes, France

IFREMER, Laboratoire d'Oceanographie Spatiale, Plouzané, France

University of California, Los Angeles, Los Angeles, California

CORRESPONDING AUTHOR: Aaron Boone, GAME-CNRM Meteo-France, 42 ave G. Coriolis, Toulouse, France 31057 E-mail: aaron.boone@meteo.fr

The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.

GAME-Centre National de Recherche Météorologique, Toulouse, France

European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

IPSL, Laboratoire de Meteorologie Dynamique, Paris, France

ISE-Montpellier, Universite Montpellier 2, Montpellier, France

Sisyphe, Université Pierre et Marie Curie (UMPC/CNRS), Paris, France

Centres d'Etudes Spatiales de la Biosphère, Toulouse, France

Institute of Water Problems, Russian Academy of Sciences, Moscow, Russia

Centre for Ecology and Hydrology, Wallingford, United Kingdom

Institute of Geography, University of Copenhagen, Copenhagen, Denmark

IPSLLaboratoire des Sciences du Climat et de I'Environnement, Gif-sur-Yvette, France

LETG-Géolittomer, Université de Nantes, Nantes, France

IFREMER, Laboratoire d'Oceanographie Spatiale, Plouzané, France

University of California, Los Angeles, Los Angeles, California

CORRESPONDING AUTHOR: Aaron Boone, GAME-CNRM Meteo-France, 42 ave G. Coriolis, Toulouse, France 31057 E-mail: aaron.boone@meteo.fr
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