Estimating of sunshine percentage using the cloud classification data from FY-2C

The sunshine percentage is an important index in the radiation research and the solar energy assessment. Taking Jiangxi Province for example,we discussed the possibility to use the data from geostationary meteorological satellite to stimulate the s unshine hour distribution. First,we collected the cloud of FY-2C of 2007 and 87 meteorological stations sunshine hour data of Jiangxi Province. Second,we used multiple liner regression and weight coefficient methods to create two inversion models. Third,we a cquired 5 km × 5 km spatial resolution hourly percentage sunshine grid data of Jiangxi Province. By comparing the inversion results with observations data from 17 stations which were not involved in creating models,we found that the relative error and the Mean Absolute Error( MAE) of the two estimation models is smaller than Inverse Distance Weighted( IDW) and Kriging for more than 50%. The MAE and the relative error of multiple liners method were 3. 40% and 8. 62% smaller than weight coefficient method 3. 47% and 8. 75%. Both RMSE and error distributions were the same. The inversion data of both methods were bigger than the validation data except for the 17: 00 sunshine hour data. The MAE,RMSIE and relative error of 8: 00 and 17: 00 are much higher than the other hours. Results based on the comprehensive analysis show that geostationary meteorological satellite data based on the FY2C can be used in sunshine hour inversion,and the MAE of the two estimation models are much better than the traditional IDW and Kriging methods. According to data in 2007,the multiple liner model is better than weight coefficient model.