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ANNUAL VARIATIONS OF TEMPERATURE ON FOUR URBAN UNDERLYING SURFACES AND FITTING ANALYSIS

机译:ANNUAL VARIATIONS OF TEMPERATURE ON FOUR URBAN UNDERLYING SURFACES AND FITTING ANALYSIS

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abstract_textpBased on the observed 2-year temperature data for four kinds of typical urban underlying surfaces, including asphalt, cement, bare land and grass land, the annual variations and influencing factors of land surface temperature are analyzed. Then fitting equations for surface temperature are established. It is shown that the annual variation of daily average, maximum and minimum temperature and daily temperature range on the four urban underlying surfaces is consistent with the change in air temperature. The difference of temperature on different underlying surfaces in the summer half year (May to October) is much more evident than that in the winter half year (December to the following April). The daily average and maximum temperatures of asphalt, cement, bare land and grass land are higher than air temperature due to the atmospheric heating in the daytime, with that of asphalt being the highest, followed in turn by cement, bare land and grass land. Moreover, the daily average, maximum and minimum temperature on the four urban underlying surfaces are strongly impacted by total cloud amount, daily average relative humidity and sunshine hours. The land surface can be cooled (warmed) by increased total cloud amount (relative humidity). The changes in temperature on bare land and grass land are influenced by both the total cloud amount and the daily average relative humidity. The temperature parameters of the four land surfaces are significantly correlated with daily average, maximum and minimum temperature, sunshine hours, daily average relative humidity and total cloud amount, respectively. The analysis also indicates that the range of fitting parameter of a linear regression equation between the surface temperature of the four kinds of typical land surface and the air temperature is from 0.809 to 0.971, passing the F-test with a confidence level of 0.99./p/abstract_text

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