Classification of Meteorological Fields Characterized by Baiu Season Using Self-Organizing Map

Abstract

In this study, complicated atmospheric patterns in a rainy season (BAIU) in the southwestern Japan was classified into eight groups, using the Self-Organizing Map (SOM) algorithm, which converts complex nonlinear features into simple two-dimensional relationships. The groups can be basically represented by five meteorological fields;(1) dry air masses, (2) anti-cyclonic flow due to the Pacific high pressure, (3) the existence of the BAIU front between dry and wet regions, (4) the intrusion of a large amount of water vapor, (5) passages of typhoon and low pressure system. One of the groups has notable feature represented by high precipitable water accompanied by strong wind components (Low Level Jet), which is a typical meteorological field that causes disastrous heavy rainfall events in the northern Kyushu. Therefore, it may be expected that the classification of meteorological fields and associated extraction of heavy rainfall phases contribute to determining whether heavy rainfall occurs or not in a target area as well as the enhancement of the accuracy for the rainfall prediction.