Application of FY-2C Cloud Drift Winds in a Mesoscale Numerical Model

Statistical tests and error analysis of cloud drift winds (CDWs) from the FY-2C satellite were made by using radiosonde observations. According to the error characteristics of the CDW, a bias correction using the thermal wind theory was applied in the data quality control. The CDW data were then assimilated into the GRAPES-meso model via the GRAPES-3DVar. A torrential rain event that occurred in northwestern China during 1-2 July 2005 was simulated. The results indicate that the CDW data were mainly distributed above 500 hPa and the largest amount of data were at 250 hPa. The CDW data below 500 hPa had errors in both the wind direction and wind speed, and the distribution of the errors was irregular, so these data were discarded. The CDW data above 500 hPa had smaller errors, which presented a Gaussian distribution, so these data were adopted. With the assimilation of the CDW data, the southwest airflow near the torrential rain area became stronger in the initial wind field, which intensified the moisture transport and water vapor flux convergence, and finally improved the accuracy of the 24-h forecast of the torrential rain in both rain intensity and rain areal coverage.