Expected and Actual Errors of Linear Inverse Model Forecasts

Abstract

The authors discuss forecast uncertainty, which should be employed for the purpose of judging prediction model performance, and actual forecast errors, which can be employed by users to judge the reliability of the forecasts. Realistic a priori estimates of forecast uncertainty for linear inverse modeling sea surface temperature predictions are presented and compared with the actual forecast errors occurring during the course of real-time predictions. The a priori estimates are of size similar to the actual errors except during the warmest phase of observed El Niño events.