M. Houngnibo, B. Minoungou, S. Traoré, R. Maidment, A. Alhassane, Abdou Ali
{"title":"Validation of high-resolution satellite precipitation products over West Africa for rainfall monitoring and early warning","authors":"M. Houngnibo, B. Minoungou, S. Traoré, R. Maidment, A. Alhassane, Abdou Ali","doi":"10.3389/fclim.2023.1185754","DOIUrl":null,"url":null,"abstract":"Satellite rainfall estimation products (SRPs) can help overcome the absence of rain gauge data to monitor rainfall-related risks and provide early warning. However, SRPs can be subject to several sources of errors and need to be validated before specific uses. In this study, a comprehensive validation of nine high spatial resolution SRPs (less than 10 km) was performed on monthly and dekadal time scales for the period 2001–2015 in West Africa. Both SRPs and reference data were remapped to a spatial resolution of 0.1 ° and the validation process was carried out on a grid scale, with 1,202 grids having at least one rain gauge throughout West Africa. Unconditional statistical metrics, such as mean absolute error, Pearson correlation, Kling-Gupta efficiency and relative bias, as well as the reproducibility of rainfall seasonality, were used to describe the agreement between SRPs and reference data. The PROMETHEE II multi-criteria decision analysis (MCDA) method was employed to rank SRPs by considering criteria encompassing both their intrinsic characteristics and performance metrics. Overall, IMERGv6-Final, MSWEPv2.2, RFE2, ARC2, and TAMSATv3.1, performed reasonably well, regardless of West African climate zones and rainy season period. Given the performances displayed by each of these SRPs, RFE2, ARC2, and MSWEPv2.2 would be suitable for drought monitoring. TAMSATv3.1, IMERGv6-Final, RFE2, ARC2, and MSWEPv2.2 are recommended for comprehensive basin water resources assessments. TAMSATv3.1 and MSWEPv2.2 would be of interest for the characterization of variability and long-term changes in precipitation. Finally, TAMSATv3.1, ARC2, and MSWEPv2.2, could be good alternatives to observed data as predictants in West African Regional Climate Outlook Forum (RCOF) process.","PeriodicalId":33632,"journal":{"name":"Frontiers in Climate","volume":"1 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Climate","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fclim.2023.1185754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Satellite rainfall estimation products (SRPs) can help overcome the absence of rain gauge data to monitor rainfall-related risks and provide early warning. However, SRPs can be subject to several sources of errors and need to be validated before specific uses. In this study, a comprehensive validation of nine high spatial resolution SRPs (less than 10 km) was performed on monthly and dekadal time scales for the period 2001–2015 in West Africa. Both SRPs and reference data were remapped to a spatial resolution of 0.1 ° and the validation process was carried out on a grid scale, with 1,202 grids having at least one rain gauge throughout West Africa. Unconditional statistical metrics, such as mean absolute error, Pearson correlation, Kling-Gupta efficiency and relative bias, as well as the reproducibility of rainfall seasonality, were used to describe the agreement between SRPs and reference data. The PROMETHEE II multi-criteria decision analysis (MCDA) method was employed to rank SRPs by considering criteria encompassing both their intrinsic characteristics and performance metrics. Overall, IMERGv6-Final, MSWEPv2.2, RFE2, ARC2, and TAMSATv3.1, performed reasonably well, regardless of West African climate zones and rainy season period. Given the performances displayed by each of these SRPs, RFE2, ARC2, and MSWEPv2.2 would be suitable for drought monitoring. TAMSATv3.1, IMERGv6-Final, RFE2, ARC2, and MSWEPv2.2 are recommended for comprehensive basin water resources assessments. TAMSATv3.1 and MSWEPv2.2 would be of interest for the characterization of variability and long-term changes in precipitation. Finally, TAMSATv3.1, ARC2, and MSWEPv2.2, could be good alternatives to observed data as predictants in West African Regional Climate Outlook Forum (RCOF) process.