热岛效应时空特征及影响因素对认识和改善城市热污染意义重大，但针对关中平原城市群热岛效应的相关研究尚需加强。本文将中尺度天气预报模式（WRF）与随机森林算法（RF）相结合，构建WRF-RF模型并模拟城市近地面气温，计算并分析关中平原城市群热岛效应时空特征，再基于地理加权回归模型，探究自然和人为因素对热岛效应的贡献量。主要结论为：

     （1）WRF-RF模型模拟关中平原城市群近地面气温和能量收支状况的精确度更高。与WRF模式、随机森林算法和监测站点内插法等相比较，WRF-RF模型更加高效、准确，模拟近地面（2米）气温的空间相关系数可以达到0.9以上，并能反应出地形等下垫面条件对气温影响的效果。

     （2）关中平原城市群热岛效应存在明显的空间异质性和季节性变化。其中西安市热岛效应最强、范围最大。春夏季强热岛范围在西安、咸阳等大城市中心地区明显增加，而秋冬季热岛效应逐渐减弱。

     （3）关中平原城市群热岛效应受自然和人为因素共同影响，而自然因素起主导作用。首先，地形是城市热岛效应变化的主控因子，海拔越低，城市热岛效应越明显，在地势平坦的区域热岛效应增强最为显著。在季度和月份变化上，主要是湿度和太阳辐射起着主导作用，且太阳辐射为增强作用，湿度为减缓作用，太阳辐射的贡献量高于湿度。

     （4）在新冠肺炎疫情期间关中平原城市群热岛效应有所减弱。2020年年初新冠肺炎疫情发生后，在人为活动大幅减弱后，关中平原城市群强热岛范围减小比例为31.5％，但强热岛区域依旧自西向东出现在“咸阳-西安-渭南-运城”城市带的主城区，热岛效应总体态势也未发生根本变化。

       The temporal and spatial characteristics and influencing factors of the heat island effect are of great significance to understand and improve urban heat pollution, but the relevant research on the heat island effect of the Guanzhong Plain Urban Agglomeration needs to be strengthened. In this paper， the mesoscale weather forecast model (WRF) is combined with the random forest algorithm (RF) to construct the WRF-RF model and simulate the urban near-surface temperature，with calculating and analyzing the spatial and temporal characteristics of the heat island effect of the Guanzhong Plain Urban Agglomeration, and then explore the contribution of natural and human factors to the heat island effect based on the geographically weighted regression model. The main conclusions are as follows:

       (1) WRF-RF model is more accurate in simulating the near-surface air temperature and energy budget of the Guanzhong Plain Urban Agglomeration. Compared with the WRF model, random forest algorithm, and monitoring station interpolation, the WRF-RF model is more efficient and accurate. The spatial correlation coefficient of simulated near-surface (2m) air temperature can reach more than 0.9, and can reflect the effect on air temperature of underlying surface conditions such as terrain.

       (2) The heat island effect of the Guanzhong Plain Urban Agglomeration has obvious spatial heterogeneity and seasonal variation. Xi'an has the strongest and the largest range of heat island effect. In spring and summer, the range of strong heat island increases obviously in the central areas of big cities such as Xi'an and Xianyang, while the heat island effect weakens gradually in autumn and winter.

       (3) The heat island effect of the Guanzhong Plain Urban Agglomeration is affected by both natural and human factors, and the natural factors play a leading role. Firstly, the terrain is the main controlling factor of the urban heat island effect. The lower the altitude is, the more obvious the urban heat island effect is. The enhancement of the heat island effect is most significant in the flat area. In terms of seasonal and monthly changes, humidity and solar radiation play a leading role, and the solar radiation is enhanced and humidity is slowed down. The contribution of solar radiation is higher than that of humidity.

       (4) The heat island effect of Guanzhong Plain Urban Agglomeration was weakened during the COVID-19 epidemic. After the outbreak of COVID-19 at the beginning of 2020, the range of strong heat island in the Guanzhong Plain Urban Agglomeration has been reduced by 31.5% after human activities have been greatly weakened. However, the strong heat island region still appears in the main urban area of the "Xianyang-Xi'an-Weinan-Yuncheng" urban belt from west to east, and the overall situation of the heat island effect has not changed fundamentally.

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