气候变化领域集成服务门户(CCPortal): A daily 25 km 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

CCPortal

DOI	10.5194/hess-24-2687-2020
	A daily 25 km 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
	Massari C.; Brocca L.; Pellarin T.; Abramowitz G.; Filippucci P.; Ciabatta L.; Maggioni V.; Kerr Y.; Fernandez Prieto D.
发表日期	2020
ISSN	1027-5606
起始页码	2687
结束页码	2710
卷号	24 期号:5
英文摘要	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 km2. 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 multiple-satellite 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. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
语种	英语
scopus关键词	Agricultural robots; Agriculture; Data integration; Developing countries; Information management; Integration; Meteorological instruments; Rain; Rain gages; Resource allocation; Satellites; Soil moisture; Water management; Global precipitation measurement missions; Global precipitation measurements; Integrated products; Multiple satellites; Rainfall variability; Satellite soil moisture; Soil Moisture and Ocean Salinity (SMOS); Waterresource management; Soil surveys; ASCAT; correlation; integrated approach; measurement method; rainfall; raingauge; real time; resource management; satellite data; SMOS; soil moisture; water resource; Africa; Australia; Europe; India; South America; United States
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159396
作者单位	Massari, C., Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Perugia, Italy; Brocca, L., Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Perugia, Italy; Pellarin, T., Institut des Géosciences de l'Environnement (IGE), Research Unit of CNRS, Grenoble INP, IRD, Université Grenoble Alpes, Grenoble, 38000, France; Abramowitz, G., ARC Centre of Excellence for Climate Extremes, University of New South Wales (UNSW), Sydney, Australia; Filippucci, P., Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Perugia, Italy; Ciabatta, L., Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Perugia, Italy; Maggioni, V., Sid and Reva Dewberry Department of Civil Environmental, and Infrastructure Engineering, George Mason University, Fairfax, VA, United States; Kerr, Y., Centre d'Etudes Spatiales de la BIOsphère (CESBIO), Université Toulouse 3, CNES, CNRS, I...
推荐引用方式 GB/T 7714	Massari C.,Brocca L.,Pellarin T.,et al. A daily 25 km 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[J],2020,24(5).
APA	Massari C..,Brocca L..,Pellarin T..,Abramowitz G..,Filippucci P..,...&Fernandez Prieto D..(2020).A daily 25 km 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.Hydrology and Earth System Sciences,24(5).
MLA	Massari C.,et al."A daily 25 km 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".Hydrology and Earth System Sciences 24.5(2020).