A Heuristic Method for Time Disaggregation of Seasonal Climate Forecasts

Abstract

To be immediately useful in practical applications that employ daily weather generators, seasonal climate forecasts issued for overlapping 3-month periods need to be disaggregated into a sequence of 1-month forecasts. Direct linear algebraic approaches to disaggregation produce physically unrealistic sequences of monthly forecasts. As an alternative, a heuristic method has been developed to disaggregate the NOAA/Climate Prediction Center (CPC) probability of exceedance seasonal precipitation forecasts, and tested on observed precipitation data for 1971?2000 for the 102 forecast divisions covering the contiguous United States. This simple method produces monthly values that replicate the direction and amplitude of variations on the 3-month time scale, and approach the amplitude of variations on the 1-month scale, without any unrealistic behavior. Root-mean-square errors between the disaggregated values and the actual precipitation over the 30-yr test period and all forecast divisions averaged 0.94 in., which is 39% of the mean monthly precipitation, and 58% of the monthly standard deviation. This method performs equally well across widely different precipitation regimes and does a reasonable job reproducing the sudden onset of strong seasonal variations such as the southwest U.S. monsoon.