Extraction Of Storm Information On Radial Velocity Map Of Doppler Radar

With the development of the science and technology, especially with the progress of radar detecting technology, the weather forecasting has stronger timeliness and the higher accuracy, however, it now cannot predict summer rainstorm especially short-time rainstorm in time and its accuracy remains to improve.With the popularity of a generation of new weather radar, the researchers both at home and abroad find that strong convective storm happens together with mesocyclones that are closely related to Spouts, heavy rain, strong winds and hail and other severe weather. Recognition of mesocyclones is important to the timeliness and accuracy of predicting tornado, rainstorm, and hail. In addition, recognition of adverse winds plays a significant role in forecasting the rainstorm and severe wind, especially short-time rainstorms.In this paper, we have done the research with digital image processing, Doppler radar and the knowledge relevant to the weather characteristics combined with meteorological expertise and apply MATLAB as software to process the information of convective rainstorms. The study includes as following aspects:1. In statistical characteristics analysis of mesocyclones, we obtain various shear information of speed pairs with the relation among the speed pairs existed in the mesocyclones. We also try to get the relation between the shear value of characteristic quantity in mesocyclones and all convective rainstorms with the method of characteristics analysis. Moreover, by analyzing the shear value to the time, the prediction of convective rainstorms is realized.2. In recognition on mesocyclone, we advance the algorithm of district inclusion with the knowledge related to the digital image processing and graphic feature of adverse-wind region and distinguish the adverse winds from radial velocity map of Doppler radar successfully.All above-mentioned algorithms have been carried out by programming. We program with MATLAB, which reduces the code line and improves work efficiency. By analyzing algorithm used in this paper is effective for adverse-wind recognition based on Doppler radar, and can be applied to the practical situations.