Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA 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
Anno di pubblicazione2020
Formato-
Autore/iMassari, Christian; Brocca, Luca; Pellarin, Thierry; Abramowitz, Gab; Filippucci, Paolo; Ciabatta, Luca; Maggioni, Viviana; Kerr, Yann; Prieto, Diego Fernandez
Affiliazioni autoriNatl Res Council CNR; CNRS; Univ Grenoble Alpes; Univ New South Wales UNSW; George Mason Univ; Univ Toulouse 3; European Space Agcy ESA
Autori CNR e affiliazioni
  • PAOLO FILIPPUCCI
  • LUCA BROCCA
  • CHRISTIAN MASSARI
  • LUCA CIABATTA
Lingua/e
  • inglese
AbstractRain 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.
Lingua abstractinglese
Altro abstractIn 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.
Lingua altro abstract-
Pagine da2687
Pagine a2710
Pagine totali24
RivistaHydrology and earth system sciences
Attiva dal 1997
Editore: Copernicus Publ. - Göttingen
Paese di pubblicazione: Germania
Lingua: inglese
ISSN: 1027-5606
Titolo chiave: Hydrology and earth system sciences
Titolo proprio: Hydrology and earth system sciences.
Titolo abbreviato: Hydrol. earth syst. sci.
Titoli alternativi:
  • HESS (Göttingen. Print)
  • Hydrology and earth system sciences (Print)
Numero volume della rivista24
Fascicolo della rivista5
DOI10.5194/hess-24-2687-2020
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000537581300002)
Parole chiavesoil moisture, rainfall, remote sensing, SM2RAIN
Link (URL, URI)https://www.hydrol-earth-syst-sci.net/24/2687/2020/
Titolo parallelo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IRPI — Istituto di ricerca per la protezione idrogeologica
Moduli/Attività/Sottoprogetti CNR
  • DTA.AD003.026.001 : SMOS+RAINFALL
Progetti Europei-
Allegati