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Unraveling the global water cycle from space
Precipitation is one of the most important components of the hydrologic water cycle. Global changes in precipitation space-time variability impact water
and food security and socioeconomic sustainability. These days, accurate monitoring of global precipitation using satellite observations plays a critical role in hydrologic forecasts, water resources management, and national security. Development of modern methodologies is needed for detection and estimation of precipitation. One recent method, called Shrunken locally linear embedding Algorithm for Retrieval of Precipitation (ShARP), relies on recent theoretical developments in sparse approximation and manifold learning. Applying the algorithm to the data from NASA’s Tropical Rainfall Measuring Mission (TRMM) satellite promises major improvements in retrievals of precipitation types and extremes over radiometrically complex land surfaces, such as in the vicinity of coastal regions and snow-covered orographic features. [30,31]
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