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Abstract: Weather data can vary significantly from year to year. There is a need to derive typical meteorological year (TMY) data to represent the long-term typical weather condition over a year, which is one of the crucial factors for successful building energy simulation. In this paper, various types of typical weather data sets including the TMY, TMY2, WYEC, WYEC2, WYEC2W, WYEC2T and IWEC were reviewed. The Finkelstein–Schafer statistical method was applied to analyze the hourly measured weather data of a 25-year period (1979–2003) in Hong Kong and select representative typical meteorological months (TMMs). The cumulative distribution function (CDF) for each year was compared with the CDF for the long-term composite of all the years in the period for four major weather indices including dry bulb temperature, dew point temperature, wind speed and solar radiation. Typical months for each of the 12 calendar months from the period of years were selected by choosing the one with the smallest deviation from the long-term CDF. The 12 TMMs selected from the different years were used for formulation of a TMY for Hong Kong. [Copyright &y& Elsevier]