Abstract:

Using a mesoscale numerical model ARPS (Advanced Regional Prediction System) data analysis system (ADAS), CINRAD/SA and SB Doppler radar reflectivity and Fengyun-2E satellite data were implemented in the model field. A heavy rainstorm process on July 21, 2012 in the north China was simulated using a high resolution mesoscale numerical model (WRF). The results show that the Doppler radar and satellite data are helpful for improving the accuracy of simulated heavy rainfall because of the corrections on the water vapor in lower atmospheric layers, especially for the position of falling area of precipitation and its maximum amount. At the same time, the slow development of prediction by WRF model is improved after adding the assimilated satellite and radar data. Comparison between radar and satellite assimilation suggests that the former can improve the prediction of precipitation within 6 hours, while the latter can improve precipitation forecast within 24 hours. Using the satellite and radar data, precipitation forecast is closer to the observation, especially for the beginning time, intensity and range of precipitation.

Key words: Rainstorm, Satellite data, Radar data, Comprehensive cloud analysis