A daily 25km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products

被引：48

作者：

Massari, Christian ^{[1
]}

Brocca, Luca ^{[1
]}

Pellarin, Thierry ^{[2
,3
]}

Abramowitz, Gab ^{[4
]}

Filippucci, Paolo ^{[1
]}

Ciabatta, Luca ^{[1
]}

Maggioni, Viviana ^{[5
]}

Kerr, Yann ^{[6
]}

Prieto, Diego Fernandez ^{[7
]}

机构：

[1] Natl Res Council CNR, Res Inst Geohydrol Protect IRPI, Perugia, Italy

[2] CNRS, Grenoble INP, Inst Geosci Environm IGE, Res Unit,IRD, F-38000 Grenoble, France

[3] Univ Grenoble Alpes, F-38000 Grenoble, France

[4] Univ New South Wales UNSW, ARC Ctr Excellence Climate Extremes, Sydney, NSW, Australia

[5] George Mason Univ, Sid & Reva Dewberry Dept Civil Environm & Infrast, Fairfax, VA 22030 USA

[6] Univ Toulouse 3, Ctr Etud Spatiales BIOsphere CESBIO, CNES, CNRS,IRD, F-31401 Toulouse, France

[7] European Space Agcy ESA, Frascati, Italy

来源：

HYDROLOGY AND EARTH SYSTEM SCIENCES | 2020年 / 24卷 / 05期

关键词：

DATA ASSIMILATION; GRIDDED PRECIPITATION; PASSIVE MICROWAVE; DATA SET; LAND; PERFORMANCE; ERROR; SMOS; SPACE; MODEL;

D O I：

10.5194/hess-24-2687-2020

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km(2). The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agricultural and water resource management applications, as gauges are also subject to malfunctions and regulations imposed by national authorities. A potential alternative is satellite-based rainfall estimates, yet comparisons with in situ data suggest they are often not optimal. In this study, we developed a short-latency (i.e. 2-3 d) rainfall product derived from the combination of the Integrated Multi-Satellite Retrievals for GPM (Global Precipitation Measurement) Early Run (IMERG-ER) with multiplesatellite soil-moisture-based rainfall products derived from ASCAT (Advanced Scatterometer), SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active and Passive) L3 (Level 3) satellite soil moisture (SM) retrievals. We tested the performance of this product over four regions characterized by high-quality ground-based rainfall datasets (India, the conterminous United States, Australia and Europe) and over data-scarce regions in Africa and South America by using triple-collocation (TC) analysis. We found that the integration of satellite SM observations with in situ rainfall observations is very beneficial with improvements of IMERG-ER up to 20% and 40% in terms of correlation and error, respectively, and a generalized enhancement in terms of categorical scores with the integrated product often outperforming reanalysis and ground-based long-latency datasets. We also found a relevant overestimation of the rainfall variability of GPM-based products (up to twice the reference value), which was significantly reduced after the integration with satellite soil-moisture-based rainfall estimates. Given the importance of a reliable and readily available rainfall product for water resource management and agricultural applications over data-scarce regions, the developed product can provide a valuable and unique source of rainfall information for these regions.

引用

页码：2687 / 2710

页数：24