Based on several kinds of numerical prediction products and RJTD products, the members of the European Central typhoon ensemble forecast are sorted by the optimal forecast track method, and the first best T prediction members are formed as a factor matrix X. Furthermore, under the same independent sample with the same years, the cross modeling prediction has been conducted for the factor matrix X using the intelligent computing methods of generalized regression neural network, the regression random forest algorithm and the partial least squares algorithm. In this way, three sequences Y={y1,y2,y3} with the same samples as the factor matrix X are obtained. Finally, the objective and quantitative forecast of the Northwest Pacific typhoon track has been developed using the multiple regression model for quadratic modeling and based on the matrix composed of Y, X and RJTD products as model input.

Comparison of Track Errors of ITFS-ICA, CMA Subjective and 

ECMWF EPS Mean Forecast in 2020 and 2021 Operation