| Summary: | Mesoscale vortices (MVs) play an important role in balancing global atmospheric momentum, moisture, and energy, and can induce almost all types of disastrous weather. To enhance the understanding of MVs, there is a need to identify them from various types of grid data. Despite the higher detection accuracy, manual identification is gradually being replaced by numerical methods, because the former has enormous time and manpower requirements. However, after decades of research to accurately detect MVs using numerical algorithms the process remains challenging. This study proposed the use of restricted vorticity (RV) as a new metric for numerical MV identification, based on which a numerical algorithm was developed. Compared with ∼1800 manually identified MVs, the new algorithm had a hit rate of over 97%, and a Heidke skill score of above 0.9. This indicates that RV will be of great practical value, and is suitable for popularizing and applying immediately.
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