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Performance Comparison of an Improved Mesocyclone Detection Algorithm with the NEXRAD Mesocyclone Algorithm

机译：一种改进的mesocyclone检测算法与NEXRaD mesocyclone算法的性能比较

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An important impetus for NEXRAD was the capability to detect mesocyclones. Identification of mesocyclones can be invaluable to a forecaster because roughly half of all storms that contain them produce tornadoes and only weak tornadoes are known to form in their absence. In addition, nearly all storms that contain mesocyclones produce some form of severe weather. Mesocyclone identification is simple and straightforward by visual inspection of radar displays. It can be time consuming and mentally taxing, however, especially during severe storm outbreaks, because it requires a three-dimensional integration of the Doppler velocity field. In order to assist the forecaster NEXRAD will provide an automatic mesocyclone algorithm to sort through the myriad of data for mesocyclone. A new algorithm for automatic mesocyclone detection was developed because of perceived problems of sensitivity and discrimination with the existing NEXRAD algorithm. This new algorithm alleviates these problems with its analysis procedure that more closely replicates the thought process a human being follows to identify mesocyclones. The algorithm has the capability to detect both cyclonically and anticyclonically rotating features as well as Tornadic Vortex Signatures (TVS), qualities not shared by the NEXRAD algorithm. Testing of the new algorithm has yielded very satisfying results. In the cases examined all known mesocyclones and TVSs were detected by the algorithm. Reprints. (JHD)

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