안전한 항공기 운항을 위한 현업 전지구예보모델 기반 깊은 대류 예측 지수: Part 1. 개발 및 통계적 검증
Aviation Convective Index for Deep Convective Area using the Global Unified Model of the Korean Meteorological Administration, Korea: Part 1. Development and Statistical Evaluation
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Deep convection can make adverse effects on safe and efficient aviation operationsby causing various weather hazards such as convectively-induced turbulence, icing, lightning,and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distributionof deep convective area near the airport and airspace. This study developed a newindex, the Aviation Convective Index (ACI), for deep convection, using the operational globalUnified Model of the Korea Meteorological Administration. The ACI was computed from combinationof three different variables: 3-hour maximum of Convective Available Potential Energy,averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logicalgorithm. In this algorithm, the individual membership function was newly developed followingthe cumulative distribution function for each variable in Korean Peninsula. This index wasvalidated and optimized by using the 1-yr period of radar mosaic data. According to theReceiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimizedACI (ACIYrOpt) based on the optimal weighting coefficients for 1-yr period shows a betterskill 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, showingthe improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.
Abstract
Deep convection can make adverse effects on safe and efficient aviation operationsby causing various weather hazards such as convectively-induced turbulence, icing, lightning,and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distributionof deep convective area near the airport and airspace. This study developed a newindex, the Aviation Convective Index (ACI), for deep convection, using the operational globalUnified Model of the Korea Meteorological Administration. The ACI was computed from combinationof three different variables: 3-hour maximum of Convective Available Potential Energy,averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logicalgorithm. In this algorithm, the individual membership function was newly developed followingthe cumulative distribution function for each variable in Korean Peninsula. This index wasvalidated and optimized by using the 1-yr period of radar mosaic data. According to theReceiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimizedACI (ACIYrOpt) based on the optimal weighting coefficients for 1-yr period shows a betterskill 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, showingthe improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.
참고문헌 (18)
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