Using Self-Organizing Maps to understand the effects of synoptic configurations on West Pacific typhoons
The vertical wind shear (VWS) within the tropical cyclone (TC) range is a crucial factor affecting the track and intensity of the TCs. Classic theories in the 1950s proposed that weaker vertical wind shear favors the development of TCs. Several studies have investigated the physical linkages between the VWS and TCs, and it was confirmed by Shi et al (2021) that local shear near the inner core of the TC is more related with TC intensity change than environmental shear. However, TC local vertical wind shear is essentially a part of the larger environment, subject to the configuration of synoptic fields and weather patterns. Little research has focused on how the environmental fields adjust and influence the VWS and TC properties. In this study, we try to understand what effects the synoptic backgrounds have on VWS, and how they interact with TC intensity and intensity changes.
A machine learning method called “self-organizing maps” was applied in this study to identify and classify the spatial distribution of meteorological variables. 309 storms during 2010~2019 were examined, and several factors were used for SOM training. This presentation will compare the results for different input variables, and offer a potential explanation for the linkage between synoptic configuration and TC behaviors, as well as implications for TC forecasts.
https://illinois.zoom.us/j/88283770092?pwd=bHB0WjM2Znc1cUdvYnY3dVREbWxGUT09
