Automatic Center Detection of Tropical Cyclone Using Image Processing Based on the Operational Radar Network

Abstract

This study presents the algorithm ACTION, defined as automatic center detection of tropical cyclone (TC) using image processing based on the operational radar network. Based on the high visibility of weather radar imagery, a TC’s motion vector is calculated from the continuous image change using optical flow, producing the TC’s rotation center. The algorithm performance was verified by analyzing the typhoons (TCs in the northwestern Pacific) that affected the Korean Peninsula from 2018–2021, demonstrating a high detection rate of 80.8% within an error distance of 40 km against the best track of the Korea Meteorological Administration (KMA). The detection rate was 100% for typhoons with temporally consistent morphological characteristics. ACTION automatically generates TC center information upon the TC’s initial entry inside the observation radius even in the absence of uniform radar data. As ACTION is capable of performing real-time calculations that are directly applied to rapidly generated weather radar images, it is currently being utilized by the KMA. The high temporal resolution TC center information calculated through ACTION is expected to improve the efficiency of TC forecasting.

Keywords

• TC center detection
• image processing
• optical flow
• operational radar network
• ACTION