Automatic Identification of Storm Cells Using Doppler Radars

Three storm automatic identification algorithms for Doppler radar are discussed. The WSR-88D Build 7.0 (B7SI) tests the intensity and continuity of the objective echoes by multiple-prescribed thresholds to build 3D storms, and when storms are merging, splitting, or clustered closely, the detection errors become larger. The B9SI algorithm is part of the Build 9.0 Radar Products Generator of the WSR-88D system.It uses multiple thresholds of reflectivity, newly designs the techniques of cell nucleus extraction and closestorms processing, and therefore is capable of identifying embedded cells in multi-cellular storms. The strong area components at a long distance are saved as 2D storms. However, the B9SI cannot give information on the convection strength of storm, because texture and gradient of reflectivity are not calculated and radial velocity data are not used. To overcome this limitation, the CSI (Convective Storm Identi cation) algorithm is designed in this paper. By using the fuzzy logic technique, and under the condition that the levels of the seven reflectivity thresholds of B9SI are lowered, the CSI processes the radar base data and the output of B9SI to obtain the convection index of storm. Finally, the CSI is veri ed with the case of a supercell occurring in Guangzhou on 11 August 2004. The computational and analysis results show that the two rises of convection index matched well with a merging growth and strong convergent growth of the supercell, and the index was 0.744 when the supercell was the strongest, and then decreased. Correspondingly, the height of the maximum reflectivity, detected by the radar also reduced, and heavy rain also occurred in a large-scale area.