Extended‐range seasonal hurricane forecasts for the North Atlantic with a hybrid dynamical‐statistical model

Abstract

A hybrid forecast model for seasonal hurricane activity in the North Atlantic is developed using a combined numerical coupled ocean‐atmosphere climate and empirical prediction models. Based on a 29‐yr (1981‐2009) dataset, an empirical relationship developed between the number of seasonal hurricane and the large‐scale variables from ECMWF hindcasts. The increase of seasonal hurricane activity correlates negatively with the sea surface temperature (SST) anomaly over the tropical East Pacific, positively with the SST anomaly over the Main Development Region (MDR) and North Atlantic and the decrease of wind shear over the MDR. The North Atlantic SST and the MDR vertical wind shear are selected as predictors based on sensitivity tests. Forecasts of these predictors are made with the ECMWF climate model run in ensemble mode thus providing a probability distribution of hurricane number. The forecast skill of the hybrid model is better than or at least competitive with publicly‐available forecast models but made with a one month earlier lead‐time. The hybrid model initialized in June and July 2010 forecasts an active season with 9 hurricanes.