天津地区度日（时）数时空变化特征*
Spatio-temporal variation characteristics of degree days (hours) in Tianjin area
摘要：
以天津为例，基于国家级气象台站及自动站气象数据，研究了供暖/供冷度日数时空变化特征。结果表明：受气候变暖影响，1961—2017年天津地区平均供暖度日数显著减小，降幅为9.5 ℃·d/a，供冷度日数显著增大，增幅为1.1 ℃·d/a；其中，1991—2017年较1961—1990年供暖度日数减小9.7%，供冷度日数增加72.3%。天津地区度日数空间分布存在明显差异，且随着气候变暖，空间差异增大，近30年供暖度日数空间最大差值为18.7%，供冷度日数为134.9%。基于自动站数据计算得到的度时数也存在明显的空间差异，供暖度时数差异最大达37.8%，供冷度时数达80.0%。研究证实，天津地区供暖/供冷度日（时）数存在明显的时空分异，基于度日（时）数进行建筑节能设计时，要充分考虑气候变暖影响，及时更新度日（时）数。此外，基于一个台站数据计算得到的建筑节能设计参数（如度日数）难以满足整个城市建筑节能设计需求，需考虑建筑设计参数的空间差异，可应用全市气象自动站数据，为精准建筑节能设计提供依据。
Abstract：
Taking Tianjin as an example, based on the meteorological data of national meteorological stations and automatic stations, studies the spatio-temporal variation characteristics of heating/cooling degree days. The results show that, affected by climate warming, from 1961 to 2017, the mean heating degree days in Tianjin area significantly decreased by 9.5 ℃·d/a, but the cooling degree days significantly increased by 1.1 ℃·d/a. From 1991 to 2017, the heating degree days decreased by 9.7% and the cooling degree days increased by 72.3% compared with 1961-1990. There are obvious spatial distribution differences of the degree days in Tianjin area, and the spatial difference increases with the climate warming, with 18.7% and 134.9% of the maximum difference of the heating degree days and cooling degree days in recent 30 years, respectively. There are also obvious spatial differences in the degree hours based on automatic station data, with 37.8% and 80.0% of the maximum difference of the heating degree hours and the cooling degree huors, respectively. The effect of climate warming on degree days (hours) should be fully considered and the degree days (hours) should be updated in time for building energy saving design. In addition, the energy saving design parameters (such as degree days) calculated from the data of a meteorological station are difficult to meet the energy saving design requirements of whole city. The spatial differences of the design parameters should be taken into account. The data of automatic meteorological stations of a whole city can be used as the basis for accurate energy saving design of buildings.
Keywords:degreedays,degreehours,climatewarming,buildingenergyconservation,meteorologicalparameter,spatio-temporalvariation