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Adverse weather such as hurricanes can have significant impact on power system reliability. One of the challenges of incorporating weather effects in power system reliability evaluation is to assess how adverse weather affects the reliability parameters of system components. In this paper, a fuzzy inference system (FIS) built by using fuzzy clustering method is combined with the regional weather model to solve the preceding problem. The composite power system is assumed to be partitioned into different regions and the FIS maps the nonlinear functional relationship between hurricane parameters and the increment multipliers of the failure rates (IMFR) of the transmission lines in different regions. The possible case that transmission lines traverse bordering regions is investigated by using the weighted average method. Since hurricanes last only a limited time period, the short-term reliability indices over the duration of hurricane instead of the steady-state ones are calculated by using the minimal cut-set method (MCSM). The proposed method is applied to the modified IEEE Reliability Test System (RTS). The implementation demonstrates that the proposed method is effective and efficient and is flexible in applications.