Abstract
Satellite precipitation estimates are used as an alternative or as a supplement to the records of the in situ stations. Although some satellite precipitation products have reasonably consistent time series, they are often limited to specific geographic areas. The main objective of this study was to evaluate CHIRPS version 2, MSWEP version 2, and PERSIANN-CDR, compared to gridBR, as daily mean and extreme inputs represented on a monthly scale and their respective seasonal trends of rainfall in the Mearim River Drainage Basin (MDB), Maranhão state, Brazil. Estimates of errors were calculated (relative error, pbias; root mean square error, RMSE, and Willmott concordance index, d), and the chances of precipitation were estimated by remote sensing (RES). In addition, trends in precipitation were estimated by the two-sample Mann–Kendall test. Given the overall performance, the best products for estimating monthly mean daily rainfall in the MDB are CHIRPS and PERSIANN-CDR, especially for rainy months (December to May). For daily extremes on the monthly scale, the best RES is PERSIANN-CDR. There is no general agreement between gridBR and RES methods for the trend signal, even a nonsignificant one, much less a significant one. The use of MSWEP for the MDB region is discouraged by this study because it overestimates monthly averages and extremes. Finally, studies of this kind in drainage basins are essential to improve the information generated for managing territories and developing regionalized climate and hydrological models.
Highlights
Precipitation plays a key role in the hydrological cycle, especially in tropical regions, due to its abundance [1]
The following results and their respective discussions are divided between precipitation data from 1983 to 2013, data extracted for the comparison between Gridded Meteorological Variables in Brazil (gridBR) and remote sensing (RES), and data on the climatological mean, monthly means, and extremes on the monthly scale
The objective of this study was to provide a synthesis of the differences between observation data from previously interpolated in situ stations and satellite-derived products (RES): CHIRPS, Multi-Source Weighted-Ensemble Precipitation (MSWEP), and PERSIANN-CDR
Summary
Precipitation plays a key role in the hydrological cycle, especially in tropical regions, due to its abundance [1] It is considered the main input into the water balance of drainage basins, so it is used as a primordial input in hydrological and climatological modeling [2,3,4,5]. In the context of a drainage basin, analyzing satellite products is important for planning territorial development, flood and drought management, risk contingency plans, and adaptation to and mitigation of extreme events. It is a challenge, there are different methods to estimate precipitation (especially the liquid phase) [2]. There are between 150,000 and 250,000 such stations in the world [11], the spatial representation of these observations is scarce in some regions due to their variable spatial density, which compromises the dimensioning of the variability, intensity, and type of precipitation
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