Corrected And Original Weather Radar Reflectivity Data Assimilation Comparison By Using Numerical Model ARPS

The purpose of the paper is to utilize the mesoscale model ARPS as a tool and rain gauge as the standard to verify the improvement of ground radar data correction effect on simulated precipitation forecast result. Firstly,the TRMM/PR reflectivity data is taken as the standard reference, and the correcting the ground radar reflectivity factor data with bias correction. Then using the mesoscale model ARPS and ADAS(ARPS Data Analysis System)assimilating the corrected and original radar reflectivity data, studying radar data assimilation scheme and application of mesoscale rainstorm weather forecast.By single layer grid mode, assimilating radar reflectivity factor data and simulating three rainstorm process in Jiangsu area in the year of June 25,2013 and the year of August 24 and July 12,2010. The results show that, in the case of only using NCEP Reanalysis data, the radar reflectivity factor assimilation can adjust meteorological element field and precipitation forecast field, especially, it improving the initial humidity field and precipitation forecast field obviously.The correction of reflectivity factor can further improve the effect of simulated precipitation by reflectivity factor assimilation.By double nested grid mode, assimilating radar reflectivity factor data and simulating two rainstorm process in Jiangsu area in the year of August 24 and July 12, 2010. Taking nested grid cuan improve the effect of precipitation prediction which only with NCEP reanalysis data assimilation, reflectivity factor can significantly improve the prediction effect of precipitation,and the correted radar reflectivity can improve the reflectivity assimilation results of simulating rainfall.