Weather-sensitive decision-making may be improved by utilizing seasonal climate outlooks issued by the Climate Prediction Center (CPC). These seasonal climate outlooks, however, should carry assessments of their validity on both temporal and spatial scales. The objective of this study is to evaluate the spatial and temporal accuracy of CPC's seasonal climate outlooks for temperature and precipitation across the contiguous United States.

Observed temperature and precipitation data; tercile thresholds for differentiating above-normal, near-normal, and below-normal temperature and precipitation; and all seasonal climate outlooks for temperature and precipitation were provided by CPC. A logistic regression analysis was used to evaluate CPC's seasonal climate outlooks from JFM (January, February, March) 1995 through OND (October, November, December) 2000. Logistic regression determines the probability of correct outlooks for temperature and precipitation and the outlooks' dependence on season, outlook division, probability anomaly, prediction (above/below normal), year, and lead time. Logistic regression analysis in the U.S. High Plains (for the period 1995-1999) found that outlooks for temperature and precipitation had a 49% and 31% average probability of being correct, respectively. For the Southeast U.S. the average probability of a correct outlook for temperature was 47% and 44% for precipitation.