Identifying Three Shapes of Potential Vorticity Streamers Using Mask R-CNN

Potential vorticity (PV) streamers are elongated filaments of high PV intrusions that generally exhibit three distinct shapes: ordinarily southwestward, hook, and treble-clef, each with significant influences on weather. These PV streamers are most frequent over arid and semi-arid Central Asia in the mid-high latitudes. This study applied the Mask Region-based Convolutional Neural Network algorithm (Mask R-CNN) to PV streamers on the dynamical tropopause during the warm season (May to September) over the years 2000–04 to train a weighted variational model capable of identifying these different shapes. The trained model demonstrated a strong ability to distinguish between the three shapes. A climatological analysis of PV streamers over Central Asia spanning 2000 to 2021 revealed an increasingly deep and pronounced reversal of circulation from ordinary to treble-clef shapes. The treble-clef shape featured a PV tower and distinct cut-off low in the troposphere, but the associated upward motions and precipitation were confined within approximately 1200 km to the east of the PV tower. Although the hook-shape PV streamers were linked to a weaker cut-off low, the extent of upward motion and precipitation was nearly double that of the treble-clef category. In contrast, the ordinary PV streamer was primarily associated with tropopause Rossby wave breaking and exhibited relatively shallow characteristics, which resulted in moderate upward motion and precipitation to 500 km to its east.