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An assessment of the performance of global rainfall estimates without ground-based observations

机译：在没有地面观测的情况下对全球降雨量估算的绩效进行评估

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pstrongAbstract./strong Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC) to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. brbr In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS), showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth) of the aforementioned products without using a ground benchmark data set. brbr The analysis is carried out during the period 2007a??2012 using daily rainfall accumulation products obtained at 1?°a????a??1?° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern Hemisphere. brbr The methodology presented in this study can be used to identify the best rainfall product for hydrologic models with sparsely gauged areas and provide the basis for an optimal integration among different rainfall products./p.
机译：> >摘要。陆地上基于卫星的降雨估计具有广泛的应用潜力，但由于缺乏在许多地区的地面降雨观测资料，因此其验证具有挑战性。行星。最近的研究建议使用三重搭配（TC）通过使用三种并置的降雨产品来表征与降雨估计有关的不确定性。但是，TC需要同时提供具有互不相关的误差的三种产品，这是当前全球降水数据集难以满足的要求。 在这项研究中，通过土壤水分观测的最近估算的降雨方法SM2RAIN被证明可促进TC在三胞胎中的准确应用，该方法包含两个最新的卫星降雨估算并进行了重新分析产品。不同的TC假设的有效性通过连续的美国（CONUS）上的高质量地面降雨产品间接测试，表明SM2RAIN可以提供真正独立的降雨累积信息源，可以唯一满足TC的假设。在此基础上，将TC与SM2RAIN以最佳配置在全球范围内应用，以首次计算上述产品的可靠全局相关性（相对于未知真相），而无需使用基本基准数据集。 分析是在2007a至2012年期间进行的，使用的每日降水累积量的空间分辨率为1？a ??????? a？1？1？°。结果表明，在北美和南美东部，南部非洲，南部和东部亚洲，澳大利亚东部和南部欧洲的卫星降雨量估算中，相对较高的性能，以及再分析产品和SM2RAIN之间的互补性能，其中第一项性能合理在北半球表现出色，第二个在南半球表现出色。 本研究提出的方法可用于为面积稀疏的水文模型确定最佳降雨产品，并为不同降雨产品之间的最佳整合提供基础。

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