The Prediction of the Performance of a Nested Barotropic Hurricane Track Forecast Model

Abstract

Linear multiple regression and discriminant analyses provide estimates of the errors of track forecasts from a nested barotropic hurricane track forecast model (VICBAR), which was run in the North Atlantic Basin during the 1989?94 hurricane seasons. Predictors are determined from the synoptic situation, the magnitude of atmospheric changes in the environment of the tropical cyclone, the consistency between current and past predictions, and the past performance of the model for each particular storm. This technique distinguishes cases in which VICBAR performs well from those for which it performs poorly and can provide skillful operational predictions of model performance to forecasters.