A Comparison of Dynamical and Statistical Predictions of Weekly Tropical Cyclone Activity in the Southern Hemisphere

Abstract

The skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast system to predict the occurrence of tropical cyclones (TCs) over the Southern Hemisphere during weekly periods has been evaluated and compared to the skill of a state-of-the-art statistical model. Probabilistic skill scores have been applied to a common series of hindcasts produced with the dynamical and statistical models. The ECMWF hindcasts have higher relative operating characteristic (ROC) scores than the statistical model for the first three weeks of integrations. The dynamical model also has skill over the Indian Ocean in week 4. The ECMWF hindcasts have lower Brier skill scores than the statistical model after week 2, which is likely because this version of the ECMWF model creates about 30% more TCs than observations and therefore generates a large number of false alarms. A simple calibration has been applied to the ECMWF probabilistic forecasts that significantly improves their reliability, but at the expense of the sharpness. The calibrated dynamical model has higher Brier skill scores than the statistical model during the first three weeks, although the statistical model remains more reliable. The multimodel combination of the calibrated dynamical forecasts with the statistical forecasts helps to improve the reliability of the ECMWF forecasts. The Brier skill score of the multimodel exceeds the Brier skill scores of the individual models, but with less sharpness than the calibrated dynamical model. This result suggests that the statistical model can be useful as a benchmark for dynamical models and as a component of a multimodel combination to improve the skill of the dynamical model. Potential economic value diagrams confirm that the multimodel forecasts are useful up to week 3 over the Southern Hemisphere.