A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China

A statistical dynamic model for forecasting Chinese landfall of tropical cyclones (CLTCs) was developed based on the empirical relationship between the observed CLTC variability and the hindcast atmospheric circulations from the Pusan National University coupled general circulation model (PNU-CGCM). In the last 31 years, CLTCs have shown strong year-to-year variability, with a maximum frequency in 1994 and a minimum frequency in 1987. Such features were well forecasted by the model. A cross-validation test showed that the correlation between the observed index and the forecasted CLTC index was high, with a coefficient of 0.71. The relative error percentage (16.3%) and root-mean-square error (1.07) were low. Therefore the coupled model performs well in terms of forecasting CLTCs; the model has potential for dynamic forecasting of landfall of tropical cyclones.