Evaluation of Reanalysis Estimates of Precipitation, Radiation, and Temperature over Benin (West Africa)
Author:
Bodjrenou René123, Cohard Jean-Martial2, Hector Basile2, Lawin Emmanuel Agnidé1, Chagnaud Guillaume2, Danso Derrick Kwadwo4, N’tcha M’po Yekambessoun1, Badou Félicien5, Ahamide Bernard3
Affiliation:
1. a Laboratory of Applied Hydrology, National Water Institute, University of Abomey-Calavi, Abomey-Calavi, Benin 2. b Institute of Engineering and Management, University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France 3. e Faculty of Agricultural Sciences, University of Abomey-Calavi, Abomey-Calavi, Benin 4. c Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa 5. d National University of Agriculture, Ketou, Benin
Abstract
Abstract
In West Africa, climatic data issues, especially availability and quality, remain a significant constraint to the development and application of distributed hydrological modeling. As alternatives to ground-based observations, reanalysis products have received increasing attention in recent years. This study aims to evaluate three reanalysis products, namely, ERA5, Water and Global Change (WATCH) Forcing Data (WFD) ERA5 (WFDE5), and MERRA-2, from 1981 to 2019 to determine their ability to represent four hydrological climates variables over a range of space and time scales in Benin. The variables from the reanalysis products are compared with point station databased metrics Kling–Gupta efficiency (KGE), mean absolute error (MAE), correlation, and relative error in precipitation annual (REPA). The results show that ERA5 presents a better correlation for annual mean temperature (between 0.74 and 0.90) than do WFDE5 (0.63–0.78) and MERRA-2 (0.25–0.65). Both ERA5 and WFDE5 are able to reproduce the observed upward trend of temperature (0.2°C decade−1) in the region. We noted a systematic cold bias of ∼1.3°C in all reanalyses except WFDE5 (∼0.1°C). On the monthly time scale, the temperature of the region is better reproduced by ERA5 and WFDE5 (KGE ≥ 0.80) than by MERRA-2 (KGE < 0.5). At all time scales, WFDE5 produces the best MAE scores for longwave (LW) and shortwave (SW) radiation, followed by ERA5. WFDE5 also provides the best estimates for the annual precipitation (REPA ∈ ]−25, 25[ and KGE ≥ 50% at most stations). ERA5 produces similar results, but MERRA-2 performs poorly in all the metrics. In addition, ERA5 and WFDE5 reproduce the bimodal rainfall regime in southern Benin, unlike MERRA-2, but all products have too many small rainfall events.
Funder
Institut de Recherche pour le Développement Ambassade de la France au Bénin Projet Omidelta-INE
Publisher
American Meteorological Society
Subject
Atmospheric Science
Reference49 articles.
1. Amoussou, E., and Coauthors, 2016: Évolution climatique du Bénin de 1950 à 2010 et son influence sur les eaux de surface. Colloque de l’Association Internationale de Climatologie: Climat et Pollution de l’air, Besançon, France, Association Internationale de Climatologie, 231–236, https://hal.science/hal-01360108. 2. Changing rainfall and anthropogenic-induced flooding: Impacts and adaptation strategies in Benin City, Nigeria;Atedhor, G. O.,2011 3. Uncertainties in remotely sensed precipitation data over Africa;Awange, J. L.,2016 4. What controls the formation of nocturnal low-level stratus clouds over southern West Africa during the monsoon season?;Babić, K.,2019 5. Badameli, A., and V. Dubreuil, 2015: Diagnostic du changement climatique au Togo à travers l’évolution de la température entre 1961 et 2010. XXVIIIe Colloque de l’Association Internationale de Climatologie, Liège, Belgium, Association Internationale de Climatologie, 421–426, http://www.climato.be/aic/colloques/actes/ACTES_AIC2015/5%20Variabilites%20et%20aleas%20climatiques/067-BADAMELI-421-426.pdf.
|
|