The Application Of Doppler Radar Data 3D-Var Assimilation In The Landfalling Typhoon Simulation

The mesoscale model ARPS (the Advanced Regional Prediction System) developed by CAPS (the Center for Analysis and Prediction of Storms) of Oklahoma University are put into an extensive application in the study of rainstorm, while the research of ARPS-3DVAR data assimilation system in China is needed. Using ARPS and its 3DVAR assimilation system,the Weather Doppler radar (CINRAD-SA) reflectivity and radial velocity are assimilated. The study is carried out on super typhoon SAOMAI (0608) which made landfall at East China and resulted in a large damage. In order to test the effect of Doppler radar data on the initial field and on the forecast of typhoon track,intensity and precipitation,the typhoon SAOMAI is simulated with Weather Doppler radar data only. Before assimilated by the ARPS-3DVAR system , Doppler radar raw data is preprocessed by the quality control module --88D2ARPS at first, including velocity dealiasing,removing background clutter,reconstructing missing data, and so on. The main results are as follows:1) ARPS-3DVAR can assimilate the Weather Doppler radar (CINRAD-SA) data reasonably and effectively. Comparison between with and without radar data assimilation shows that Doppler radar assimilation can adjust the dynamic and thermodynamic structure of the background field and obtain more realistic wind and precipitation structures within 6 hours initial time windows.2) The radar assimilation test successfully stimulates the precipitation areas which exist in the control test, and increase the amount of rainfall in these area . Furthermore, the radar assimilation test stimulates the mesoscale rain cell on the spiral rain belts and eyewall which not exist in the control test. The result shows that the radar assimilation by ARPS-3DVAR has the ability to improve the forecast on the mesoscale rain cell position and intensity.3) The improvement on typhoon track forecast is due to the effective adjustment of the typhoon vortex,radius of strong winds area and eye structure by radar data assimilation. The improvement on typhoon precipitation forecast is due to many changes of the physical quantities nearby the center of the typhoon, including the couple of vorticity and divergence in vertical direction,the stronger vertical motion in the typhoon eye and eyewall,the increased cloud liquid water content in middle troposphere and the thermodynamic moisture convection instability of potential equivalent temperature vertical structure. In a word, the physical quantities in assimilation test display typical characteristics of mesoscale system. The result of precipitation forecast is improved significantly, mainly because of the much more mesoscale observation information included in the initial field of radar assimilation test than that of control test .4) However, there are some insufficient in the stimulation of typhoon intensity. The intensity stimulated whether by assimilation test or by control test is weaker than observation. This deficiency might attribute mainly to the difficulties in characterizing super typhoon. By assimilating radar data with conventional observation data, a better result of intensity forecast is expected to be obtained. In addition, apply Bogus technology into simulation is expected to be a helpful way to improve the result of radar assimilation test on typhoon intensity.