An assessment of the accuracy of global rainfall estimates without ground-based observations
Christian Massari1, Wade Crow2, and Luca Brocca11Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy 2United States Department of Agriculture - Hydrology and Remote Sensing Laboratory, Beltsville, Maryland, USA
Received: 21 Mar 2017 – Accepted for review: 07 Apr 2017 – Discussion started: 10 Apr 2017
Abstract. Satellite-based rainfall estimates have great potential value 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 products of this variable. However, TC requires the simultaneous availability of three products with mutually-uncorrelated errors, a requirement that is difficult to satisfy among current global precipitation datasets.
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 (versus an unknown truth) of the aforementioned products without using a ground benchmark dataset.
The analysis is carried out during the period 2012–2015 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high accuracy of the satellite rainfall estimates in Eastern North and South America, South Africa, Southern and Eastern Asia, Eastern Australia as well as Southern Europe and 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.
Massari, C., Crow, W., and Brocca, L.: An assessment of the accuracy of global rainfall estimates without ground-based observations, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-163, in review, 2017.