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contributor authorStanley, Thomas
contributor authorKirschbaum, Dalia B.
contributor authorHuffman, George J.
contributor authorAdler, Robert F.
date accessioned2017-06-09T16:47:16Z
date available2017-06-09T16:47:16Z
date copyright2017/04/01
date issued2017
identifier otherams-74071.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4216255
description abstractong-term precipitation records are vital to many applications, especially the study of extreme events. The Tropical Rainfall Measuring Mission (TRMM) has served this need, but TRMM?s successor mission, Global Precipitation Measurement (GPM), does not yet provide a long-term record. Quantile mapping, the conversion of values across paired empirical distributions, offers a simple, established means to approximate such long-term statistics but only within appropriately defined domains. This method was applied to a case study in Central America, demonstrating that quantile mapping between TRMM and GPM data maintains the performance of a real-time landslide model. Use of quantile mapping could bring the benefits of the latest satellite-based precipitation dataset to existing user communities, such as those for hazard assessment, crop forecasting, numerical weather prediction, and disease tracking.
publisherAmerican Meteorological Society
titleApproximating Long-Term Statistics Early in the Global Precipitation Measurement Era
typeJournal Paper
journal volume21
journal issue3
journal titleEarth Interactions
identifier doi10.1175/EI-D-16-0025.1
journal fristpage1
journal lastpage10
treeEarth Interactions:;2017:;volume( 021 ):;issue: 003
contenttypeFulltext


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