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Tropical cyclone, a high energy destructive meteorological system with heavy rainfall and gale triggered massive landslides and windstorms, poses a significant threat to coastal areas. In this paper we have developed a Tropical Cyclone Potential Impact Index (TCPI) based on the air mass trajectories, disaster information, intensity, duration, and frequency of tropical cyclones. We analyzed the spatial pattern and interannual variation of the TCPI over the period 1949-2009, and taking the Super Typhoon Saomai as an example have examined the relationship between the TCPI and direct economic losses, total rainfall, and maximum wind speed. The results reveal that China's TCPI appears to be a weak decreasing trend over the period, which is not significant overall, but significant in some periods. Over the past 20 years, the TCPI decreased in the southern China coastal provinces of Hainan, Guangdong and Guangxi, while it increased in the southeastern coastal provinces of Zhejiang, Fujian and Taiwan. The highest values of TCPI are mainly observed in Taiwan, Hainan, the coastal areas of Guangdong and Fujian and Zhejiang's southern coast. The TCPI has a good correlation (P=0.01) with direct economic loss, rainfall, and maximum wind speed.

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A method is developed in this study to monitor and detect extreme precipitation events. For a rainfall event to be severe, it should last for a long period and affect a wide region while maintaining a strong intensity. However, if the duration is inappropriately taken as too long and the region is inappropriately taken as too wide, then the averaged intensity might be too weak. There should be a balance among the three quantities. Based upon understanding of the issue, the authors proposed a simple mathematical model, which contains two reasonable constraints. The relation of the “extreme” intensity with both duration and region (EIDR) is derived. With the prescribed baseline extreme intensities, the authors calculate the relative intensities with the data. Through comparison among different time periods and spatial sizes, one can identify the event that is most extreme, with its starting time, duration, and geographic region being determined. Procedures for monitoring the extreme event are provided. As an example, the extreme event contained in the 1991 persistent heavy rainfall over east China is detected.