The importance of seasonal climate prediction lead time in agricultural decision making

Abstract Monthly and seasonal climate predictions are of potential value in agricultural decision making. Most studies evaluating the usefulness of climate predictions to various economic sectors have focused primarily on accuracy levels as the primary impediment to wider use of the predictions in decision making. It is argued here, however, that prediction lead time is also an important factor in the usefulness of the predictions. It is shown that lead time (or lack thereof) is the most important variable distinguishing between subscribers to a National Oceanic and Atmospheric Administration (NOAA) prediction who use the prediction in decision making from those who do not. Indeed, the lack of lead time is a major deterrent to the use of the prediction. Detailed decision analysis of east-central Illinois corn production reveals that a prediction of early summer conditions available in early spring has significantly more value than the same prediction available in late spring. The increased value of the early summer prediction that is available in early spring stems primarily from added flexibility in nitrogen application. Further, economic trade-offs are found between lead time and predictive accuracy. These findings are likely to have relevance beyond agriculture to other dynamic decision-making activities.