纬度
降水
气候学
卫星
震级(天文学)
数据同化
环境科学
数据集
气象学
地质学
大气科学
统计
地理
物理
数学
大地测量学
天文
航空航天工程
工程类
作者
Qiaohong Sun,Chiyuan Miao,Qingyun Duan,Hamed Ashouri,Soroosh Sorooshian,Kuolin Hsu
摘要
Abstract In this paper, we present a comprehensive review of the data sources and estimation methods of 30 currently available global precipitation data sets, including gauge‐based, satellite‐related, and reanalysis data sets. We analyzed the discrepancies between the data sets from daily to annual timescales and found large differences in both the magnitude and the variability of precipitation estimates. The magnitude of annual precipitation estimates over global land deviated by as much as 300 mm/yr among the products. Reanalysis data sets had a larger degree of variability than the other types of data sets. The degree of variability in precipitation estimates also varied by region. Large differences in annual and seasonal estimates were found in tropical oceans, complex mountain areas, northern Africa, and some high‐latitude regions. Overall, the variability associated with extreme precipitation estimates was slightly greater at lower latitudes than at higher latitudes. The reliability of precipitation data sets is mainly limited by the number and spatial coverage of surface stations, the satellite algorithms, and the data assimilation models. The inconsistencies described limit the capability of the products for climate monitoring, attribution, and model validation.
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