Advanced concepts on remote sensing of precipitation at multiple scales

Soroosh Sorooshian, Amir Aghakouchak, Phillip Arkin, John Eylander, Efi Foufoula-Georgiou, Russell Harmon, Jan M.H. Hendrickx, Bisher Imam, Robert Kuligowski, Brian Skahill, Gail Skofronick-Jackson

Research output: Contribution to journalArticlepeer-review

123 Scopus citations

Abstract

Precipitation is the primary driver of the hydrologic cycle and the main input of hydrometeorological models and climate studies. The accuracy of hydrometeorological predictions significantly relies on the quality of observed precipitation intensity, pattern, duration, and aerial extent. Geostationary Operational Environmental Satellite-R (GOES-R) series will provide the spectral information required to produce precipitation data with 2-km/15-min resolution. An important step toward studying and assessing uncertainties in precipitation products is to define a set of metrics to quantify them. These metrics can serve as objective measures of how well satellite-derived precipitation estimates compare to ground reference observations. Each measure may emphasize a different aspect of performance and the users must decide which are more important to their purposes/applications. Development of uncertainty models for satellitebased precipitation estimates is highly desirable.

Original languageEnglish (US)
Pages (from-to)1353-1357
Number of pages5
JournalBulletin of the American Meteorological Society
Volume92
Issue number10
DOIs
StatePublished - Oct 1 2011

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