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contributor authorBaxter, Martin A.
contributor authorLackmann, Gary M.
contributor authorMahoney, Kelly M.
contributor authorWorkoff, Thomas E.
contributor authorHamill, Thomas M.
date accessioned2017-06-09T17:36:41Z
date available2017-06-09T17:36:41Z
date copyright2014/10/01
date issued2014
identifier issn0882-8156
identifier otherams-88042.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231779
description abstractOAA?s second-generation reforecasts are approximately consistent with the operational version of the 2012 NOAA Global Ensemble Forecast System (GEFS). The reforecasts allow verification to be performed across a multidecadal time period using a static model, in contrast to verifications performed using an ever-evolving operational modeling system. This contribution examines three commonly used verification metrics for reforecasts of precipitation over the southeastern United States: equitable threat score, bias, and ranked probability skill score. Analysis of the verification metrics highlights the variation in the ability of the GEFS to predict precipitation across amount, season, forecast lead time, and location. Beyond day 5.5, there is little useful skill in quantitative precipitation forecasts (QPFs) or probabilistic QPFs. For lighter precipitation thresholds [e.g., 5 and 10 mm (24 h)?1], use of the ensemble mean adds about 10% to the forecast skill over the deterministic control. QPFs have increased in accuracy from 1985 to 2013, likely due to improvements in observations. Results of this investigation are a first step toward using the reforecast database to distinguish weather regimes that the GEFS typically predicts well from those regimes that the GEFS typically predicts poorly.
publisherAmerican Meteorological Society
titleVerification of Quantitative Precipitation Reforecasts over the Southeastern United States
typeJournal Paper
journal volume29
journal issue5
journal titleWeather and Forecasting
identifier doi10.1175/WAF-D-14-00055.1
journal fristpage1199
journal lastpage1207
treeWeather and Forecasting:;2014:;volume( 029 ):;issue: 005
contenttypeFulltext


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