|dc.description.abstract||Compared to conventional data, radar observations have an advantage of high spatial and temporal resolutions, and Doppler radars are capable of capturing detailed fow characteristics of rainfall systems. In addition, the high resolution radar observations can be used to retrieve three-dimensional mesoscale structures of dynamic and thermodynamic fields. In this study, the possible improvement of different kinds of weather systems predictions near Taiwan, particularly with regard to related rainfall forecasts, using Doppler radial wind observations is explored. Three cases of different precipitation systems was chosen for study, and a series of experiments and sensitivity tests were carried out using the Penn State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model Version 5 (MM5) with its three-dimensional variational (3D-VAR) data assimilation system.
In order to evaluate the impacts of Doppler radial velocity data assimilation, three different precipitation systems were chosed, include Hail strom, Mei-yu front and typhoon. These 3 weather systems have different dynamic and precipitation structures. Hail storm is small scale convection; Mei-yu front was observed a horizontal wind shear; Typhoon case had a large cyclonic circulation accompany heavy rainfall. The analyses of radar wind data assimilations were shown that the influences are slignt for pressure, vertical velocity and temperature. The major reponses of data assimilation are in the horizontal wind fields. Although the results are shown the Doppler wind data assimilation is worthless in the hail storm simulation, it is effective in other 2 convertive systems that are drived by dymanic structure. In the simulation results of Mei-yu and typhoon case, the horizontal wind structure and precipitation pattern were revised by date assimilation. The typhoon intensity also was increased and revised about 25 % errors from non-assimilation simulation.
Some sensitivity tests were demonstrated for the assimilation influences of rain water content and different observational data. The observational operator of Doppler radial velocity is related in terms of 3 dimensional wind and raindrop terminal velocity. The rain water content of background fields lead the deviation of horizontal wind in the data assimilation and the most deviations exceeded 1 ms-1. The dual-radar retrieval wind was also assimilated in one of the sensitivity experiments and was compared with Doppler radial wind for the verification of data assimilation impacts. The effects of dual-radar retrieval wind leads the best low level wind speed of typhoon over the land by the analysis of data assilation. The radar radial wind has the more symmetrical adjustment of dymanic structures than the dual-radar wind.