本研究报告总结了博士后在站期间开展的城市热量环境观测与模型研究工作。通过2007年12月3-4日，和2008年3月19-20日开展的两次不同季节的观测试验，获得以下认识：冬季建筑物表面由于太阳光照、遮荫所引起的温差能够高达15℃以上，春季有轻霾的天气条件下，温差也能达到5℃以上；楼顶防渗层和窗玻璃热量储存小，释放快，温度日变化剧烈，瓷砖和水泥面热量储存大，释放慢，温度变化缓慢；人工地表与自然地表的温差下午较上午明显，能高出自然地表3-7℃，是城市热岛的主要贡献者；太阳光照、阴影对人工地表的影响远大于自然地表，是城市建筑区热量分布非均一性的主导因子。构建了能够显式计算建筑物阴影和光照区域，并求算各部分温度变化的单体建筑物热量平衡模型和单个街谷热量平衡模型。以实验观测的地物多角度光谱观测结果求算了实际的地表反射率参数，并用观测资料作为初值，进行了建筑物不同部位的温度模拟计算，结果表明，单体建筑物模型能够较好地再现不同部位温度随太阳光照、阴影而变化的日变化型态，模拟的温度峰值与观测值接近，但位相较观测滞后；单个街谷模型能够模拟出街谷内地面和墙面受建筑物遮荫影响而产生的温度变化，模拟的街谷尺度的反照率日变化型态较为符合规律。模拟结果说明本研究的建模思路是可行的，所建模型对城市局地热量环境具有一定的模拟预测能力，今后可沿此思路继续进行模型完善和优化工作。

his report introduces the preliminary study about urban thermal environment during my postdoctoral period at Beijing Normal University. In the first chapter, the review of the literatures focusing on the relative area is given. In the second chapter, I present the results of two micro thermal environment measurements，which were conducted on 3rd-4th December 2007 and 19th-20th March 2008, respectively. Main conclusion includes: (1) the difference of surface temperature between sunlit and shadowed area can be as high as 15℃ under fine weather conditions in winter, and be 5℃ under damp haze conditions in spring. (2) The diurnal variation of temperature of roof and windows is more distinct than that of wall and floor, which means that the heat capacity of the materials made of roof and windows is much lower than that of wall and floor. (3) The temperature of artificial surface is generally higher than the natural surface by 3-7℃ in the afternoon. (4) Sunlit and shadow have more significant effect on the temperature of artificial surface than that of natural surface. The distribution of sunlit and shadow is a main source to the thermal heterogeneous over building area. In the third chapter, a simple thermal equilibrium model is developed for single building and single canyon. The model is able to calculate the areas of sunlit and shadow accurately, and predict the diurnal variation temperature of each facet of building. To validate the model, we verify the albedo parameters of each facet with the high-spectrum measurement data, and initialize the model with the data collected from our experiments and other observations. The results of the modeling indicate: (1) The single building model can represent the variation of temperature of each facet with the sunlit and shadow very well. The peak value of temperature during the day is close to the value of measurement in spite of the phase falling behind to the measurement. (2) The canyon model can simulate the effects of buildings on canyon temperature. The values and the variation pattern of simulated canyon albedo are reasonable. It is evident that our models have the ability of predicting local thermal environment. We need develop, improve and optimize the framework in the further study.