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.