||Rapid urbanization have increased the sensitivity of urban environment to extreme weather. To improve the deteriorating urban environment, the current situation of urban climate should be evaluated systematically and applied to the planning process. This study reports on the temporal and spatial variability of urban climate and introduces a method for constructing an urban climate map based on spatial statistical analysis of field measurement data. Taking Xi’an, a metropolis in northern China, as the case study, we first conducted a 3-year meteorological investigation, including air temperature, relative humidity, and wind speed in both summer and winter. Meanwhile, five indicators with potential impacts on urban climate were selected to describe the urban characteristics. Then, the geographic information system was applied to integrate the meteorological data and urban characteristic data in order to assign more meteorological data. Next, three types of meteorological single-factor and thermal comfort spatial distribution maps were derived. The k-means clustering analysis method was then employed to classify three types of meteorological factors into seven zones in horizontal spatial dimension. Finally, urban climate maps were generated. This study can help planners quickly distinguish urban climate-sensitive and valuable zones in order to make better strategies for future development.