Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spatial and temporal resolution. To improve the forecast of a heavy frontal rainfall event that occurred in the Yangtze-Huaihe River Basin from 4 July to 5 July 2014 in China, operational radar observations are assimilated by the Local Analysis and Prediction System (LAPS). Radar reflectivity data are used primarily in the LAPS cloud analysis procedure, which retrieves the number of hydrometeors and adjusts the moisture and cloud fields. Radial velocity data are analyzed through the LAPS wind analysis-based successive correction method. A new correction method is developed to correct three-dimensional radar reflectivity data based on hourly surface rain gauge observations. The performance of the correction method is demonstrated by assimilating radar reflectivity observations into LAPS. Experiments with different radar data assimilation are examined. Results show that the assimilation of radar data can effectively correct the background errors and improve the heavy rainfall forecast. The simulated intensity, pattern, and temporal evolution of the heavy rainfall event are better improved with radar reflectivity assimilation, especially when the correction method is implemented to correct radar observations.

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mesoscale model simulations threedimensional radar reflectivity data temporal evolution local analysis and prediction system background errors spatial and temporal resolution laps cloud analysis forecast simulated intensity pattern heavy frontal rainfall correction method laps wind analysisbased successive correction moisture and cloud fields radial velocity data hourly surface rain gauge

Hongli Li,Xiangde Xu,Yang Hu,Yanjiao Xiao,Zhibin Wang,.Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event. 2018 (),.

Hongli Li,Xiangde Xu,Yang Hu,Yanjiao Xiao,Zhibin Wang,"Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event" 2018

Hongli Li,Xiangde Xu,Yang Hu,Yanjiao Xiao,Zhibin Wang,"Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event"