Advancing the remote sensing of precipitation

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

42 Scopus citations


Satellite-based global precipitation data has addressed the limitations of rain gauges and weather radar systems in forecasting applications and for weather and climate studies. Inspite of this ability, a number of issues that require the development of advanced concepts to address key challenges in satellite-based observations of precipitation were identified during the Advanced Concepts Workshop on Remote Sensing of Precipitation at Multiple Scales at the University of California. These include quantification of uncertainties of individual sensors and their propagation into multisensor products warrants a great deal of research. The development of metrics for validation and uncertainty analysis are of great importance. Bias removal, particularly probability distribution function (PDF)-based adjustment, deserves more in-depth research. Development of a near-real-time probabilistic uncertainty model for satellitebased precipitation estimates is highly desirable.

Original languageEnglish (US)
Pages (from-to)1271-1272
Number of pages2
JournalBulletin of the American Meteorological Society
Issue number10
StatePublished - Oct 2011


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