Rain
; Satellites
; Soil moisture
; Temperature measurement
; Uncertainty analysis
; Global precipitation
; Ground-based observations
; Independent sources
; Northern Hemispheres
; Optimal integration
; Rainfall estimations
; Satellite rainfalls
; Southern Hemisphere
; Precipitation (meteorology)
; assessment method
; ground-based measurement
; hydrological modeling
; Northern Hemisphere
; rainfall
; soil moisture
; Southern Hemisphere
; spatial resolution
; Africa
; Asia
; Australia
; Europe
; North America
; South America
; United States
英文摘要:
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 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.
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy; United States Department of Agriculture -Hydrology and Remote Sensing Laboratory, BeltsvilleMD, United States
Recommended Citation:
Massari C,, Crow W,, Brocca L. An assessment of the performance of global rainfall estimates without ground-based observations[J]. Hydrology and Earth System Sciences,2017-01-01,21(9)