Evaluation of Reanalysis Estimates of Precipitation, Radiation, and Temperature over Benin (West Africa)

René Bodjrenou aLaboratory of Applied Hydrology, National Water Institute, University of Abomey-Calavi, Abomey-Calavi, Benin
bInstitute of Engineering and Management, University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France
eFaculty of Agricultural Sciences, University of Abomey-Calavi, Abomey-Calavi, Benin

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Jean-Martial Cohard bInstitute of Engineering and Management, University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France

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Basile Hector bInstitute of Engineering and Management, University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France

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Emmanuel Agnidé Lawin aLaboratory of Applied Hydrology, National Water Institute, University of Abomey-Calavi, Abomey-Calavi, Benin

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Guillaume Chagnaud bInstitute of Engineering and Management, University of Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France

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Derrick Kwadwo Danso cDepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

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Yekambessoun N’tcha M’po aLaboratory of Applied Hydrology, National Water Institute, University of Abomey-Calavi, Abomey-Calavi, Benin

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Félicien Badou dNational University of Agriculture, Ketou, Benin

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Bernard Ahamide eFaculty of Agricultural Sciences, University of Abomey-Calavi, Abomey-Calavi, Benin

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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.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: René Bodjrenou, renebodjrenou@gmail.com

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.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: René Bodjrenou, renebodjrenou@gmail.com
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