Air Quality Forecasts Improved by Combining Data Assimilation and Machine Learning with Satellite AOD

Input data for random forest model. 1) UM_RDAPS.egg file: It provides analysis and forecast products four times a day (00, 06, 12, 18 UTC) in 12 km x 12 km spatial resolution. In this study, analysis products were only considered as the input variables (i.e., 2m temperature and dew-point temperature, relative humidity (RH), maximum wind speed, visibility at height above the ground, planetary boundary layer height (PBLH), and surface pressure). The accumulated maximum wind speed during 1, 3, 5, 7 days were also used in this study. 2) data_1.zip file: GOCI Aerosol product, MODIS Land cover, MODIS NDVI, Population density, Road density, SRTM_DEM. The detailed information of input variables is written in the supporting information of the paper.