THE USE OF ALONG-TRACK CENTRAL PRESSURE AND MOVEMENT SPEED IN SIMILAR TYPHOON IDENTIFICATION FOR RAINFALL PREDICTION

Abstract

 In the statistical prediction of typhoon-induced rainfall, Fuzzy C Means (FCM) has been widely utilized to identify similar typhoons based on track positions (latitude and longitude). However, despite the potential impact of additional variables on rainfall distribution (e.g., low central pressure and slow movement speed resulting in high mean rainfall), their inclusion in similar typhoon identification using FCM has been largely unexplored. This is particularly relevant given the increasing strength and slowing down of typhoons due to climate change. To address this gap, we conducted a study incorporating these additional variables alongside track positions and evaluated their performance using various statistical measures. Our findings indicate that including central pressure and/or movement speed has little to no impact on the accuracy of rainfall prediction. The statistical measure values do not directly point to the direction of improvement or degradation of accuracy. As we confront the challenges of climate change, new and improved techniques will be necessary for accurate rainfall predictions.