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.

中文翻译：

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以0.5°/日空间/时间分辨率评估PUSH框架对准全球红外降水的适用性

与卫星降水检索相关的误差估计对于推断此类产品在其运行应用中的可靠性至关重要。但是，由于降水固有的时间和空间变异性，测量误差和采样不确定性（尤其是在精细的时间和空间分辨率下），评估卫星降水误差特征具有挑战性。这项研究的目的是估计与陆地上基于卫星的红外（IR）降水量全球近似（60°N-60°S）相关的误差。这项研究采用的错误模型是卫星水文学中的概率不确定性（PUSH）框架，它针对不同的Koppen气候区，以日分辨率（3DPRD）基于卫星的Level-3双频降水雷达产品进行了校准和验证。尽管PUSH的性能取决于区域气候，但它可以有效地估计IR检索中的误差。具体而言，与其他地区相比，大陆性气候区在观测误差和估计误差之间显示出更好的一致性，这可以归因于该区域降水的总体空间均匀性以及IR和3DPRD估算之间的更好相关性。