Bias Correction and Statistical Downscaling Meteorological Parameters Forecast Technique Based on Large Scale Numerical Model Products Bias Correction and Statistical Downscaling Meteorological Parameters Forecast Technique Based on Large Scale Numerical Model Products
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Abstract:
Using self adaption Kalman filter method, bias correction of surface parameter products of large scale numerical prediction system are done. Through studying the appreciated method of obtaining bias correction coefficient, the filter method is improved and the forecasts of large scale model parameters such as 2 m temperature and 10 m wind are improved accordingly. Based on corrected large scale model forecast field and high resolution observatory field, downscaling vector function is obtained, and refined statistical downscaling meteorological parameter forecasts are created and it is an effective way to do high resolution meteorological parameter forecasts.