The Impact of the Dropwindsonde Data from DOTSTAR on the Prediction of Typhoon Conson (2004)

Since 2003, Dropsonde Observations for Typhoon Surveillance near the TAiwan Regions (DOTSTAR; Wu et al. 2005) has conducted 19 typhoon surveillance missions with the Astra aircraft in North-western Pacific. In this paper, the impact of dropwindsonde data on mesoscale weather prediction is investigated. The case study focuses on Typhoon Conson with various track forecasts occurred in 2004. The dropwindsonde data from DOTSTAR are assimilated into the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) using its three-dimensional variational data assimilation (3DVAR) system (Barker et al. 2003; 2004). With the assimilation into the numerical model of all the observations gathered during the surveillance mission of Typhoon Conson, the maximum difference of the deep-layer-mean winds (925-200 hPa) in the model initial condition between the cases with and without dropwindsondes is up to 7 ms-1, and the 6 to 48-h mean track forecasts show significant improvement of 56%. To evaluate how the dropwindsonde data influence model track predictions, PV inversion (Wu et al. 2003; 2004) is adapted in this study. Further experiments are made to test the impact of the subset of the dropwindsonde data, Taiwan terrain, vortex bogusing, and the data assimilation schemes. The main results are as following: First, in the test of the horizontal distribution of the dropwindsonde data, the results suggest that the northern 6 drops and the southern 6 drops are both crucial to the typhoon's movement. Second, in the test of the vertical distribution of the dropwindsionde data, the middle- and lower-tropospheric dropwindsonde data produce more significant reduction in track forecast error than the upper-tropospheric data. Third, the comparison between the experiments with and without dropwindsonde data shows that the impact of Taiwan terrain is much less important than the steering flow modified by the dropwindsonde data. Last, the test of different data assimilation schemes shows that in order to improve the typhoon track forecasts not only the dropwindsonde data but also the data assimilation scheme employed plays a very important role.