Development of a Multi-Model Ensemble Scheme for the Tropical Cyclone Forecast

Abstract:

A Multi-Model Ensemble (MME) prediction scheme using selected and weighted method was developed and evaluated for tropical cyclone forecast. The analyzed tropical cyclone track and intensity data set provided by Korea Meteorological Administration and 11 numerical model outputs - GDAPS, GEPS, GFS (data resolution; 50 and 100 km), GFES, HWRF, IFS(data resolution; 50 and 100 km), IFS EPS, JGSM, and TEPS - during 2011-2014 were used for this study. The procedure suggested in this study was divided into two stages: selecting and weighting process. First several numerical models were chosen based on the past model’s performances in the selecting stage. Next, weights, referred to as regression coefficients, for each model forecasts were calculated by applying the linear and nonlinear regression technique to past model forecast data in the weighting stage. Finally, tropical cyclone forecasts were determined by using both selected and weighted multi-model values at that forecast time. The preliminary result showed that selected MME’s improvement rate (%) was more than 5% comparing with non-selected MME at 72 h track forecast.