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Title: SEASONAL CLIMATE PREDICTIONS AND THEIR IMPLICATION FOR AGRICULTURAL MANAGEMENT IN THE CENTRAL GREAT PLAINS

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Submitted to: Proceedings of the Water and the Future of Kansas Conference
Publication Type: Abstract Only
Publication Acceptance Date: March 11, 2003
Publication Date: March 11, 2003
Citation: SCHNEIDER, J.M., GARBRECHT, J.D. SEASONAL CLIMATE PREDICTIONS AND THEIR IMPLICATION FOR AGRICULTURAL MANAGEMENT IN THE CENTRAL GREAT PLAINS. Proceedings of the Water and the Future of Kansas Conference. 2003. p. 14.

Technical Abstract: Experimental climate forecasts for 3-month total precipitation are issued monthly by the NOAA Climate Prediction Center (CPC) for lead times from 0.5 to 12.5 months. Among these predictions, the CPC probability of exceedance forecasts for 102 divisions covering the contiguous United States present information on expected shifts in the probability distribution of precipitation amounts, relative to climatological distributions. The statistical character of these forecasts could support a wide range of applications in agricultural management. However, assessments of forecast performance at regional scales are not offered with the forecasts. We have examined forecast utility over the years 1997-2001, for all lead times and all forecast divisions. Potential utility is assessed using three simple measures: usefulness (degree and frequency of forecast departures from climatological distributions), dependability (correspondence between direction and magnitude of forecast departures and actual occurrences), and effectiveness (the frequency of dependable forecasts with useful departures). Using these measures, forecasts during the study period are shown to have widely varying degrees of utility across the United States, depending on location, season, and ENSO state. Utility for the Central Great Plains has been modest at best, and limited to El Niño-related forecasts for wetter conditions during the late fall, winter, and early spring. Forecasts for drier conditions during the same seasons related to La Niña episodes have not been dependable in this region.

   
 
 
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