Statistical Deterministic and Ensemble Seasonal Prediction of Tropical Cyclones in the Northwest Australian Region

Abstract

Abstract Statistical seasonal prediction of tropical cyclones (TCs) has been ongoing for quite some time in many different ocean basins across the world. While a few basins (e.g., North Atlantic and western North Pacific) have been extensively studied and forecasted for many years, Southern Hemispheric TCs have been less frequently studied and generally grouped as a whole or into two primary basins: southern Indian Ocean and Australian. This paper investigates the predictability of TCs in the northwest Australian (NWAUS) basin of the southeast Indian Ocean (105°–135°E) and describes two statistical approaches to the seasonal prediction of TC frequency, TC days, and accumulated cyclone energy (ACE). The first approach is a traditional deterministic seasonal prediction using predictors identified from NCEP–NCAR reanalysis fields using multiple linear regression. The second is a 100-member statistical ensemble approach with the same predictors as the deterministic model but with a resampling of the dataset with replacement and smearing input values to generate slightly different coefficients in the multiple linear regression prediction equations. Both the deterministic and ensemble schemes provide valuable forecasts that are better than climatological forecasts. The ensemble approach outperforms the deterministic model as well as adding quantitative uncertainty that reflects the predictability of a given TC season.