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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,对全球降雨估计的表现进行评估

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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. 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. The analysis is carried out during the period 2007-2012 using daily rainfall accumulation products obtained at 1 ? ×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. The methodolo
机译:基于卫星的降雨估计在土地上具有很大的潜力,可实现各种应用,但由于地球许多地区的降雨观察稀缺,他们的验证是挑战。最近的研究表明,使用三重搭配(TC)来表征通过使用三个并置降雨产品的降雨估计相关的不确定性。然而,TC要求三种产品的同时可用性具有相互不相关的误差,这是难以满足当前全局降水数据集的要求。在这项研究中,对土壤水分观察的最近开发的降雨方法SM2Rain进行了说明,以便于准确地应用TC在包含两个最先进的卫星降雨估计和再分析产品的三胞胎中。不同TC假设的有效性是通过在连续的美国(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来源,这些信息唯一满足TC底层的假设。在此基础上,TC在全球范围内以最佳配置在全球范围内应用,以便在不使用地面基准数据集的情况下计算上述产品的第一次可靠的全局相关(与未知真实性)。该分析在2007 - 2012年期间进行,使用1次获得的每日降雨积累产物进行×1?空间分辨率。结果传达了东北和南美洲,南部非洲,南部和东亚,东澳大利亚和南欧的卫星降雨估计的相对高性能,以及重新分析产品和SM2RAIN之间的互补性表演,第一次表现合理井在北半球,第二个在南半球提供了非常好的表现。方法

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