The default land use data used in the Weather Research and Forecasting Model (WRF) differ significantly from the actual land use situation, which affects the simulation results. For this reason, many researchers have proposed schemes for updating land use data prior to running the model. The simplest method involved correcting the size of the urban area. Due to the heterogeneity of the urban surface, it has been suggested that the urban landscape be subdivided into refined classification areas. However, in the literature on the impact of land use data on the WRF model, most studies have only compared the simulation results before and after data updating, and have not distinguished the two factors of changes in the urban areas and urban heterogeneity. In this paper, the authors consider the use of urban area correction and refined classification synthetically. In the area correction scheme and the two refined classification schemes, three kinds of optimized land use data are generated. Combined with default land use data, the authors established four cases to simulate two high temperature weather processes that occurred in August 2018 and August 2019 in Shanghai. The results of these two simulations are: 1) The simulation results for temperature, relative humidity, and wind speed were improved after the land use data in the WRF model had been updated. 2) The size of an urban area is the most critical factor affecting the temperature. The area correction reduces reduced the average root mean square error (RMSE) by 0.86℃, but the refined classification reduced the average RMSE by just 0.04℃ at most. 3) The refined classification method primarily affected the wind speed and relative humidity. Although area correction reduced the average RMSE of wind speed by just 0.04 m/s, the refined classification method further reduced the RMSE by up to 0.19 m/s. The mean RMSE of relative humidity was reduced by just 0.23% by area correction, while the maximum RMSE was reduced by 2.25% by refined classification. 4) Generally speaking, to some extent, the heterogeneity of a city is considered in refined classification schemes, so the simulation results for temperature, relative humidity, and wind speed are improved to a greater extent, and the more detailed is the classification, the better is the effect.