Publications des scientifiques de l'IRD

Satgé Frédéric, Defrance Dimitri, Sultan Benjamin, Bonnet Marie-Paule, Seyler Frédérique, Rouché Nathalie, Pierron F., Paturel Jean-Emmanuel. (2020). Evaluation of 23 gridded precipitation datasets across West Africa. Journal of Hydrology, 581, 124412 [19 p.]. ISSN 0022-1694.

Titre du document
Evaluation of 23 gridded precipitation datasets across West Africa
Année de publication
2020
Type de document
Article référencé dans le Web of Science WOS:000514758300038
Auteurs
Satgé Frédéric, Defrance Dimitri, Sultan Benjamin, Bonnet Marie-Paule, Seyler Frédérique, Rouché Nathalie, Pierron F., Paturel Jean-Emmanuel
Source
Journal of Hydrology, 2020, 581, 124412 [19 p.] ISSN 0022-1694
This study aims reporting on 23 gridded precipitation datasets (P-datasets) reliability across West Africa through direct comparisons with rain gauges measurement at the daily and monthly time scales over a 4 years period (2000-2003). All P-datasets reliability vary in space and time. The most efficient P-dataset in term of Kling-Gupta Efficiency (KGE) changes at the local scale and the P-dataset performance is sensitive to seasonal effects. Satellite-based P-datasets performed better during the wet than the dry season whereas the opposite is observed for reanalysis P-datasets. The best overall performance was obtained for MSWEP v.2.2 and CHIRPS v.2 for daily and monthly time-step, respectively. Part of the differences in P-dataset performance at daily and monthly time step comes from the time step used to proceed the gauges adjustment (Le day or month) and from a mismatch between gauge and satellite reporting times. In comparison to the others P-datasets, TMPA-Adj v.7 reliability is stable and reach the second highest KGE value at both daily and monthly time step. Reanalysis P-datasets (WFDEI, MERRA-2, JRA-55, ERA-Interim) present among the lowest statistical scores at the daily time step, which drastically increased at the monthly time step for WFDEI and MERRA-2. The non-adjusted P-datasets were the less efficient, but, their near-real time availability should be helpful for risk forecast studies (i.e. GSMaP-RT v.6). The results of this study give important elements to select the most adapted P-dataset for specific application across West Africa.
Plan de classement
Hydrologie [062]
Description Géographique
AFRIQUE DE L'OUEST
Localisation
Fonds IRD [F B010077958]
Identifiant IRD
fdi:010077958
Contact