Data quality is a basic assurance for meteorological researches and data applications.In this paper, considering local climate in Shanghai, a localized quality control flow is formulated from 59 AWSs(Automatic Weather Stations) hourly temperature data during the period of 2006—2013.It includes station format parameter check, climate extreme value check, time consistency check and space consistency check, especially by using the methods of dynamic threshold in climate extreme value check and different distance standards for different areas in spatial consistency check.After quality control, the annual mean data missing rates of this data set are all below 10%, which means the AWS data in Shanghai bears good integrality and confidence.Thus a set of high-quality and high-resolution temperature data set is obtained.Compared with the manual observation data, it is found that the average annual and seasonal mean temperatures in Shanghai are almost the same, which proves that the quality of this data set is reliable.But the spatial difference is more obvious, which just indicates that the high resolution temperature data is more representative and effective in the researches about fine spatial distribution features in urban thermal environment.Based on standardized temperature, the spatial distribution of urban heat island in Shanghai is analyzed with this data set.The results indicate that the AWS data can reflect many fine features of the distribution of urban heat island.The urban heat island center has expanded from the city center to periphery and the southwest area, especially presents a multi-centered feature.In addition to the main center of heat island at the city center, there are two sub-centers in the north of Minhang district and the south of Songjiang district respectively, which are associated with rapid urbanization.Two regional construction projects, namely, "Songjiang New Town" in 2009 and "Big Hongqiao Section" in 2010, have greatly accelerated the process of urbanization.They have not only changed the underlying surface status, but also made a large amount of anthropogenic heat caused by lots of people moving into the sub-centers of the city.Also the heat islands are located in the southeast area in autumn and winter and in the northwest area in spring and summer, which is affected by local sea-land wind and seasonal transition of atmospheric circulation.The above detailed characteristics are not obvious or can not be reflected from manual data.Therefore, the AWS data with quality control is better applicable than manual data in the research of fine structures of urban heat island.