Research on Typhoon Precipitation Prediction over Hainan Island Based on Dynamical–Statistical–Analog Technology

• Published in: Atmosphere Vol. 14; no. 8; p. 1210
• Main Authors: Jiang, Xianling, Ma, Yunqi, Ren, Fumin, Ding, Chenchen, Han, Jing, Shi, Juan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023
• Subjects: accumulated precipitation; Analysis; DSAEF_LTP_HN; Ensemble forecasting; Experiments; Forecasting; forecasting performance; Forecasting techniques; Hainan Island; Heavy precipitation; Hurricanes; Mathematical models; Modelling; Numerical models; Precipitation; Precipitation (Meteorology); Precipitation forecasting; Rain; Statistical analysis; Statistical prediction; Tropical cyclones; Typhoon research; Typhoons; Weather forecasting; China; Hainan Island
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos14081210

Based on the Dynamical–Statistical–Analog Ensemble Forecast model for Landfalling Typhoon Precipitation (DSAEF_LTP model), the optimal forecast scheme for the tropical cyclone (TC) accumulated precipitation over Hainan Island, China (DSAEF_LTP_HN) is established. To test the forecasting performance of DSAEF_LTP_HN, its forecasting results are compared with other numerical models. The average threat score (TS) of accumulated precipitation forecast by DSAEF_LTP_HN is compared with other numerical models over independent samples. The results show that for accumulated precipitation ≥ 100 mm, the TS produced by DSAEF_LTP_HN reaches 0.39, ranking first, followed by ECMWF (0.36). For accumulated precipitation ≥ 250 mm, the TS of DSAEF_LTP_HN (0.04) is second only to ECMWF (0.19). Further analysis reveals that the forecasting performance of DSAEF_LTP_HN for TC precipitation is closely related to the TC characteristics. The longer the TC impacts Hainan Island and the heavier the precipitation delivered to Hainan Island, the better the forecasting performance of DSAEF_LTP_HN is. DSAEF_LTP_HN can successfully capture the center of heavy precipitation. However, there is still a phenomenon of false forecasts for some TC heavy precipitation, which requires further improvement of the model in the future.