Abstract
Error estimates associated with satellite precipitation retrievals are crucial to allow inferences about the reliability of such products in their operational applications. However, evaluating satellite precipitation error characteristics is challenging because of the inherent temporal and spatial variability of precipitation, measurement errors, and sampling uncertainties, especially at fine temporal and spatial resolutions. The aim of this study is to estimate errors associated with satellite-based infra-red (IR) precipitation retrievals quasi-globally (60°N − 60°S) over land. The error model adopted for this study is the Probability Uncertainty in Satellite Hydrology (PUSH) framework, which is calibrated and validated against the satellite-based Level-3 Dual frequency precipitation radar product at daily resolution (3DPRD) for different Koppen climate zones. PUSH is shown to efficiently estimate errors in the IR retrievals, although its performance depends on the regional climatology. Specifically, the continental climate zone shows better agreement between observed and estimated errors as compared to other regions, which can be attributed to the general spatial homogeneity of precipitation across this zone and better correlation between IR and 3DPRD estimates.
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