Version 1
: Received: 18 October 2022 / Approved: 21 October 2022 / Online: 21 October 2022 (07:38:27 CEST)
How to cite:
Mo, S.; Gu, J. Automatic Center Detection of Tropical Cyclone using Image Processing based on the Operational Radar Network. Preprints2022, 2022100322. https://doi.org/10.20944/preprints202210.0322.v1
Mo, S.; Gu, J. Automatic Center Detection of Tropical Cyclone using Image Processing based on the Operational Radar Network. Preprints 2022, 2022100322. https://doi.org/10.20944/preprints202210.0322.v1
Mo, S.; Gu, J. Automatic Center Detection of Tropical Cyclone using Image Processing based on the Operational Radar Network. Preprints2022, 2022100322. https://doi.org/10.20944/preprints202210.0322.v1
APA Style
Mo, S., & Gu, J. (2022). Automatic Center Detection of Tropical Cyclone using Image Processing based on the Operational Radar Network. Preprints. https://doi.org/10.20944/preprints202210.0322.v1
Chicago/Turabian Style
Mo, S. and Ji-Young Gu. 2022 "Automatic Center Detection of Tropical Cyclone using Image Processing based on the Operational Radar Network" Preprints. https://doi.org/10.20944/preprints202210.0322.v1
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, the TC’s motion vector is calculated from the continuous image change using optical flow, producing its rotation center as the TC’s center. The algorithm’s performance was verified for typhoons (TCs in the Northwestern Pacific) affecting the Korean Peninsula from 2018–2021 and showed a high detection rate of 80.8% within an error distance of 40 km compared to 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. ACTION easily calculates using Open Source Computer Vision, performs in real time, and can be directly applied to rapidly generated weather radar images; hence, 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.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
