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A typical meteorological day database of solar terms for simplified simulation of outdoor thermal environment on a long-term
Urban Climate ( IF 6.0 ) Pub Date : 2024-08-30 , DOI: 10.1016/j.uclim.2024.102117 Junfeng Li , Jin Zhao , Zhengyan Lu
Urban Climate ( IF 6.0 ) Pub Date : 2024-08-30 , DOI: 10.1016/j.uclim.2024.102117 Junfeng Li , Jin Zhao , Zhengyan Lu
The simulation of the outdoor thermal environment long-term, represented by the annual conditions, can describe outdoor thermal environment characteristics more completely. To simplify the simulation, Typical Meteorological Year (TMY) or Principal Component Analysis (PCA) methods are often used to generate a Typical Meteorological Day (TMD) as input conditions for a simplified simulation of the outdoor thermal environment in the long term. However, the results of these typical days are accidental, the time interval between the typical days is heterogeneous, and these typical days cannot be linked together to represent a data sequence used to describe meteorological features in the long term. By combining knowledge of Solar Terms in the traditional Chinese calendar with the CSWD (the Chinese standard year) method, a meteorological element data sequence of a typical weather day (Solar Terms Typical Meteorological Day, STTMD) can be generated. There are 24 typical days obtained by the STTMD method. In the traditional Chinese calendar, they have a definite time order, and the time interval between the typical days is about 15 days. Connecting these typical days can form a hypothetical meteorological year, which is used to simplify the description of the annual meteorological characteristics with the maximum probability of occurrence. Based on meteorological observation data from 1981 to 2010, the STTMD data series of 61 stations in China were generated. These data were used to form a simple national climate division, and then the meteorological representation of different divisions was analyzed. Meteorological representativeness analysis for these subtions indicated the good accuracy of STTMD data. The method can simplify the numerical simulation process for those studied on long-term and can be extended to applications such as outdoor comfort evaluation and urban building energy consumption.
更新日期：2024-08-30
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