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Solar diffuse radiation (DIFRA) is an important component of solar radiation, but current research into the estimation of DIFRA is relatively limited. This study, based on remote sensing data, topographic data, meteorological reanalysis materials, and measured data from radiation observation stations in Chongqing, combined key factors such as the solar elevation angle, water vapor, aerosols, and cloud cover. A high-precision DIFRA estimation model was developed using the random forest algorithm, and a distributed simulation of DIFRA in Chongqing was achieved. The model was validated using 8179 measured data points, demonstrating good predictive capability with a correlation coefficient (R2) of 0.72, a mean absolute error (MAE) of 35.99 W/m2, and a root mean square error (RMSE) of 50.46 W/m2. Further validation was conducted based on 14 radiation observation stations, with the model demonstrating high stability and applicability across different stations and weather conditions. In particular, the fit was optimal for the model under overcast conditions, with R2 = 0.70, MAE = 32.20 W/m2, and RMSE = 47.51 W/m2. The results indicate that the model can be effectively adapted to all weather calculations, providing a scientific basis for assessing and exploiting solar energy resources in complex terrains. [ABSTRACT FROM AUTHOR]

With the continuous improvement of urbanization levels in the Lhasa area, the urban heat island effect (UHI) has seriously affected the ecological environment of the region. However, the satellite-based thermal infrared land surface temperature (LST), commonly used for UHI research, is affected by cloudy weather, resulting in a lack of continuous spatial and temporal information. In this study, focusing on the Lhasa region, we combine simulated LST data obtained by the Weather Research and Forecasting (WRF) model with remote sensing-based LST data to reconstruct the all-weather LST for March, June, September, and December of 2020 at a resolution of 0.01° while using the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST as a reference (in terms of accuracy). Subsequently, based on the reconstructed LST, an analysis of the UHI was conducted to obtain the spatiotemporal distribution of UHI in the Lhasa region under all-weather LST conditions. The results demonstrate that the reconstructed LST effectively captures the expected spatial distribution characteristics with high accuracy, with an average root mean square error of 2.20 K, an average mean absolute error of 1.51 K, and a correlation coefficient consistently higher than 0.9. Additionally, the heat island effect in the Lhasa region is primarily observed during the spring and winter seasons, with the heat island intensity remaining relatively stable in winter. The results of this study provide a new reference method for the reconstruction of all-weather LST, thereby improving the research accuracy of urban thermal environment from the perspective of foundational data. Additionally, it offers a theoretical basis for the governance of UHI in the Lhasa region. [ABSTRACT FROM AUTHOR]