4.7 Article

Errors of five satellite precipitation products for different rainfall intensities

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ATMOSPHERIC RESEARCH
卷 285, 期 -, 页码 -

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2023.106622

关键词

Precipitation; Error analysis; Rainfall intensity; Topography; Mainland China

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Revealing the errors and impact of elevation on satellite precipitation products (SPPs) for different rainfall intensity groups is crucial for their applications in hydro-meteorological field, however their spatial distribution and impact are still unclear.
Revealing the errors of the satellite precipitation products (SPPs) for various rainfall intensity groups is crucial for their applications in the hydro-meteorological field. However, the spatial maps of errors of SPPs for different rainfall intensity groups and the impact of elevation on them are still unclear. In this study, the spatial maps of errors of the five satellite precipitation products (i.e., IMERG-Late, IMERG-Final, GSMaP-MVK, GSMaP-Gauge, and PERSIANN-CCS) for the four rainfall intensity groups (i.e., light precipitation, moderate precipitation, heavy precipitation, and storm) are depicted. A novel score, namely the relative rainfall occurrence bias (ROB), is proposed as a means to evaluate the reproducibility of the spatial patterns of SPPs for different surface rainfall intensity occurrences. All five SPPs cannot reproduce the spatial patterns of the four surface rainfall intensity occurrences. Despite that, all SPPs except for PERSIANN-CCS can capture almost all rainfall intensity groups (except light precipitation) because their probability of detection (POD) values exceeds 0.8. Moreover, we found that the detection capability of SPPs for light precipitation decreases with the increasing standard deviation of elevation (SDE) but is the opposite for bias, while the impacts of elevation on the errors of SPPs for other rainfall intensity groups are unapparent. The overestimations of the number of surface heavy precipitation and storm occurrences for IMERG-Late and GSMaP-MVK are mainly due to overestimating the rainfall amount of the lower rain-rate surface rainfall events, while their total biases for heavy precipitation and storms originate from hit bias. The potential limitations of the bias correction algorithms used in the IMERG and GSMaP retrieval systems in correcting different rainfall intensity groups are identified by comparing the performance between gauge-adjusted products and satellite-only products. Finally, the optimal SPP precipitation product for each rainfall intensity group is discussed. The findings reported in this study can provide valuable information for data users to select a product that best meets the requirements of the applications.

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