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Manuela Grippa, Laurent Kergoat, Aaron Boone, Christophe Peugeot, Jérôme Demarty, Bernard Cappelaere, Laetitia Gal, Pierre Hiernaux, Eric Mougin, Agnès Ducharne, Emanuel Dutra, Martha Anderson, Christopher Hain, and ALMIP2 Working Group

Abstract

Land surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally overestimated, but the ALMIP2 multimodel mean reproduces in situ measurements of ET and water stress events rather well. However, ALMIP2 models are generally unable to distinguish among the two contrasted hydrological systems typical of the study area. Employing as input a soil map that explicitly represents shallow soils improves the representation of water fluxes for the models that can account for their representation. Shallow soils are shown to be also quite challenging for remote-sensing-based ET products, even if their effect on evaporative loss was captured by the diagnostic thermal-based ALEXI. A better representation of these soils, in soil databases, model parameterizations, and remote sensing algorithms, is fundamental to improve the estimation of water fluxes in this part of the Sahel.

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Aaron Boone, Patricia de Rosnay, Gianpaolo Balsamo, Anton Beljaars, Franck Chopin, Bertrand Decharme, Christine Delire, Agnes Ducharne, Simon Gascoin, Manuela Grippa, Françoise Guichard, Yeugeniy Gusev, Phil Harris, Lionel Jarlan, Laurent Kergoat, Eric Mougin, Olga Nasonova, Anette Norgaard, Tristan Orgeval, Catherine Ottlé, Isabelle Poccard-Leclercq, Jan Polcher, Inge Sandholt, Stephane Saux-Picart, Christopher Taylor, and Yongkang Xue

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.

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