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has been cited by the following article:

• TITLE: Short-Term Precipitation Forecasting Rolling Update Correction Technology Based on Optimal Fusion Correction

  AUTHORS: Meijin Huang, Qing Lin, Ning Pan, Nengzhu Fan, Tao Jiang, Qianshan He, Lingguang Huang

  KEYWORDS: Optimal Fusion Correction, Radar QPF, Numerical Model, Short-Term Precipitation Forecasting, Rolling Test

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.7 No.3, March 28, 2019

  ABSTRACT: In order to improve the availability of regional model precipitation forecast, this project intends to use the measured heavy rainfall data of dense automatic stations to carry out historical precipitation in the high resolution: the Severe Weather Automatic Nowcast System (SWAN) quantitative precipitation forecast and the High-Resolution Rapid Refresh (HRRR) regional numerical model precipitation forecast in short-term nowcasting aging. Based on the error analysis, the grid fusion technology is used to establish the measured rainfall, HRRR regional model precipitation forecast, and optical flow radar quantitative precipitation forecast (QPF) three-source fusion correction scheme, comprehensively integrate the revised forecasting effect, adjust the fusion correction parameters, establish an optimal correction plan, generate a frozen rolling update revised product based on measured dense data and short-term forecast, and put it into business operation, and perform real-time effect rolling test evaluation on the forecast product.