Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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Aviation Convective Index for Deep Convective Area using the Global Unified Model of the Korean Meteorological Administration, Korea: Part 1. Development and Statistical Evaluation

안전한 항공기 운항을 위한 현업 전지구예보모델 기반 깊은 대류 예측 지수: Part 1. 개발 및 통계적 검증

  • Yi-June Park (School of Earth and Environmental Sciences, Seoul National University) ;
  • Jung-Hoon Kim (School of Earth and Environmental Sciences, Seoul National University)
  • 박이준 (서울대학교 지구환경과학부) ;
  • 김정훈 (서울대학교 지구환경과학부)
  • Received : 2023.09.12
  • Accepted : 2023.11.03
  • Published : 2023.11.30
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Abstract

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACIYrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACINoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACIYrOpt were higher than those of ACINoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

Keywords

Acknowledgement

본 논문의 질적 향상을 위해 좋은 의견들을 제시해 주신 두 심사위원 분들께 감사의 말씀을 전합니다. 이 연구는 기상·지진 See-At 기술개발연구사업(KMI2020-01910)의 지원과 기상청 「차세대 항공교통 지원 항공기상 기술개발(NARAE-Weather)」 (KMI2022-00310과 KMI2022-00410)의 지원으로 수행되었습니다.

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