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Evaluation of rainfall products over the West African region will be an important
component of the Megha-Tropiques (MT) Ground Validation (GV) plan. In this paper, two
dense research gauge networks from Benin and Niger, integrated in the MT GV plan are
presented and are used to evaluate several currently available global or regional satellitebased
rainfall products. Eight products: Precipitation Estimation from Remotely Sensed
Information using Artificial Neural Networks PERSIANN, Climate Prediction Center
Morphing method (CMORPH), Tropical Rainfall Measuring Mission (TRMM) Multisatellite
Precipitation Analysis (TMPA) 3B42 real time and gauge adjusted version, Global
Satellite Mapping of Precipitation (GSMAP), Climate Prediction Center (CPC) African
Rainfall Estimate (RFE), Estimation des Precipitation par SATellite (EPSAT), and Global
Precipitation Climatology Project One Degree Daily estimate (GPCP-1DD) are compared
to the ground reference. The comparisons are carried out at daily time step and one-degree
resolution, over the rainy season (JJAS), between the years 2003 and 2010. The work
focuses on the ability of the various products to reproduce salient features of the rainfall
regime that impact the hydrological response. The products are analyzed on a multi-criteria
basis, focusing in particular on the way they distribute the rainfall within the season and by
rain rate class. Standard statistical diagnoses such as the correlation coefficient, the bias,
the root mean square error and the Nash skill score are computed and the inter-annual
variability is documented. Two simplified hydrological models are used to illustrate how
the nature and structure of the product error impact the model output in term of runoff
(calculated with the Soil Conservation Service method, SCS, in Niger) or outflow
(calculated with the 'modèle du Génie Rural à 4 paramètres Journalier', GR4J model, in
Benin). |
