Analysis of summer high temperature observations based on different sub surfaces

This paper selects three typical observation sites in Hengshui city, Hengshui Lake wetland, and youth woodland along the river, and uses non-contact infrared temperature measurement equipment to carry out high-temperature continuous observation of four kinds of underlay surfaces, namely, asphalt, grassland, woodland, and wetland, to compare the temporal characteristics of the surface temperature of each kind of underlay surface and its relationship with meteorological factors, and to establish the multivariate linear regression equations for the four kinds of maximum surface temperatures of underlay surfaces based on a variety of meteorological factors. Regression equations were established, and the main results were as follows: ①The daily maximum temperature, daily average temperature, and daily minimum temperature change curves of asphalt underlay were significantly higher than those of other underlay, and the change trends of grassland, woodland, and wetland were the same, and the curves were close to each other. ②The maximum and minimum temperatures of the four types of underlayment were ranked as asphalt > wetland > forestland > grassland. ③The maximum surface temperatures of the four types of underlayment were positively correlated with the daily maximum air temperature and solar radiation, with correlation coefficients around 0.9, and negatively correlated with the daily total cloudiness and the daily maximum relative humidity, with correlation coefficients above 0.5. ④The four types of sub surface maximum temperature forecasts are well fitted to the observed values, with correlation coefficients of 0.70 or more, and the error results are within the acceptable range, which can meet the needs of high-temperature forecasting, among which the grassy subsurface has the best fit, with a correlation coefficient of 0.90.The results have certain reference significance for knowing thermal environment of different urban underlying surfaces, while. providing scientific evidence for the development of refined urban meteorological forecasting services.