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contributor authorGianotti, Dan
contributor authorAnderson, Bruce T.
contributor authorSalvucci, Guido D.
date accessioned2017-06-09T17:07:46Z
date available2017-06-09T17:07:46Z
date copyright2013/08/01
date issued2013
identifier issn0894-8755
identifier otherams-79822.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4222645
description abstractgeneralizable method is presented for establishing the potential predictability for seasonal precipitation occurrence using rain gauge data. This method provides an observationally based upper limit for potential predictability for 774 weather stations in the contiguous United States. It is found that the potentially predictable fraction varies seasonally and spatially, and that on average 30% of year-to-year seasonal variability is potentially explained by predictable climate processes. Potential predictability is generally highest in winter, appears to be enhanced by orography and land surface coupling, and is lowest (stochastic variance is highest) along the Pacific coast. These results depict ?hot? spots of climate variability, for use in guiding regional climate forecasting and in uncovering processes driving climate. Identified ?cold? spots are equally useful in guiding future studies as predictable climate signals in these areas will likely be undetectable.
publisherAmerican Meteorological Society
titleWhat Do Rain Gauges Tell Us about the Limits of Precipitation Predictability?
typeJournal Paper
journal volume26
journal issue15
journal titleJournal of Climate
identifier doi10.1175/JCLI-D-12-00718.1
journal fristpage5682
journal lastpage5688
treeJournal of Climate:;2013:;volume( 026 ):;issue: 015
contenttypeFulltext


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