Application of the improved dynamical–Statistical–Analog ensemble forecast model for landfalling typhoon precipitation in Fujian province

Abstract

The forecasting performance of the Dynamical–Statistical–Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon [or tropical cyclone (TC)] Precipitation (DSAEF_LTP), with new values of two parameters (i.e., similarity region and ensemble method) for landfalling TC precipitation over Fujian Province, is tested in four experiments. Forty-two TCs with precipitation over 100 mm in Fujian Province during 2004–2020 are chosen as experimental samples. Thirty of them are training samples and twelve are independent samples. First, simulation experiments for the training samples are used to determine the best scheme of the DSAEF_LTP model. Then, the forecasting performance of this best scheme is evaluated through forecast experiments. In the forecast experiments, the TSsum (the sum of threat scores for predicting TC accumulated rainfall of ≥250 mm and ≥100 mm) of experiments DSAEF_A, B, C, D is 0.0974, 0.2615, 0.2496, and 0.4153, respectively. The results show that the DSAEF_LTP model performs best when both adding new values of the similarity region and ensemble method (DSAEF_D). At the same time, the TSsum of the best performer of numerical weather prediction (NWP) models is only 0.2403. The improved DSAEF_LTP model shows advantages compared to the NWP models. It is an important method to improve the predictability of the DSAEF_LTP model by adopting different schemes in different regions.