A MEASURE OF THE USEFULNESS OF SEASONAL PRECIPITATION FORECASTS FOR AGRICULTURAL APPLICATIONS

Abstract

NOAA’s Climate Prediction Center produces experimental climate forecasts that predict total precipitation over three–month periods out to a year in advance. The utility of these seasonal forecasts for agricultural applications will depend on a number of forecast characteristics, including dependability, effectiveness, and usefulness. Usefulness is defined as the ability of the forecasts to predict conditions significantly different from climatological norms. This definition assumes that producers would be more likely to “use” a forecast if it predicts a large departure from normal conditions. A simple measure of usefulness is developed for the NOAA probability of exceedance seasonal precipitation forecasts. Based on the archived precipitation forecasts from 1997 through 2001, this measure is evaluated for 102 forecast divisions covering the continental U.S. Results vary significantly across the U.S., with some regions showing much larger and more frequent forecasts for departures from climatological precipitation than others. For example, at the shortest lead times, precipitation forecast departures larger than 10% of climatological means were issued in 45% of the forecasts for southeastern Arizona, but were issued only 7% of the time for southern Nebraska. Usefulness also varies with lead time, ENSO state and intensity, and season, with the largest forecast departures issued at shorter lead times, during strong ENSO events, and during the fall, winter, and spring seasons. Even if seasonal precipitation forecasts are shown to be dependable and effective, the usefulness of these forecasts for individual, local agricultural planners and managers will be limited in regions and at lead times where forecasts rarely depart from climatology. Agricultural enterprises that operate at regional scales, and can profitably use predictions of small shifts in probable outcome (e.g., crop insurance programs, fertilizer production and distribution, and grain storage and transportation) are best suited to benefit in a direct fashion from these forecasts.