An Efficient Data Analysis Method for Typical Meteorological Year Development Considering Climate Change During the Past Decades

In order to explore the impact of abrupt climate jump phenomenon on typical meteorological year (TMY) data used to simulate building energy consumption, this work was carried out. Firstly, the moving t-test method was applied to analyze abrupt climate jump phenomenon using the hourly weather database from 1960 to 2019 provided by the China Meteorological Data Center. All meteorological parameters involved in the TMY were analyzed by moving t-test method. Secondly, according to the time scale requirements of the original data for TMY's construction, it generally required original data 10 to 30 years ago. Therefore, the climate jump point that meets the above time scale requirements is considered as the climate jump point in this region. The year of the climate jump point is set to the beginning and ending of the time scale of the original data used to construct TMY. Thirdly, based on the above method, this study takes Beijing and Zhengzhou in China as examples. The calculation results show that there are two climate jump points in Beijing, and their years are 1988 and 2014 respectively; and Zhengzhou has one climate jump point, and the year is 1988. Therefore, the TMY's time scales of Beijing and Zhengzhou considering the abrupt climate jump phenomenon are 1988-2014 (total 27 years) and 1998-2019 (total 22 years). Finally, this paper compared the differences between old TMY and new TMY considering abrupt climate jump phenomenon.