DOI QR코드

DOI QR Code

Analysis of Upper-Level Aviation Turbulence Observational Data and Performance Evaluation of Prediction Models (KTG and GKTG) over the Korean Peninsula for 5 years (2019~2023)

한반도 상층의 5년간(2019~2023) 항공 난류 관측자료 분석 및 예측모델(KTG와 GKTG) 성능 평가

  • Yujeong Kang (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Hee-Wook Choi (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Yuna Choi (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Sang-Sam Lee (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Hyoung-Seuk Lee (Forecast Division, Aviation Meteorological Office) ;
  • Eun-Sook Kim (Forecast Division, Aviation Meteorological Office) ;
  • Seungbum Kim (Research Applications Department, National Institute of Meteorological Sciences)
  • 강유정 (국립기상과학원 기상응용연구부) ;
  • 최희욱 (국립기상과학원 기상응용연구부) ;
  • 최유나 (국립기상과학원 기상응용연구부) ;
  • 이상삼 (국립기상과학원 기상응용연구부) ;
  • 이형석 (항공기상청 예보과) ;
  • 김은숙 (항공기상청 예보과) ;
  • 김승범 (국립기상과학원 기상응용연구부)
  • Received : 2024.10.16
  • Accepted : 2024.12.04
  • Published : 2025.02.28

Abstract

This study conducted a statistical analysis of turbulence events using in-situ eddy dissipation rate (EDR) observation data collected above 20,000 feet over the Korean Peninsula from 2019 to 2023. Additionally, the performances of two operational turbulence prediction models from the Korea Aviation Meteorological Office, which are the Korean Aviation Turbulence Guidance (KTG) and Global KTG (GKTG) systems, were evaluated against the same in-situ EDR observations. The verification process employed the probability of detection (POD) method, allowing for an objective assessment of prediction accuracy. The statistical analysis results of in-situ EDR data revealed that data was primarily collected along flight routes, with observations increasing over time. The moderate-or-greater (MOG) turbulence was observed frequently during the daytime, and was most prevalent in spring. The comparison of the characteristics of PIREP and in-situ EDR observations showed similar seasonal trends. The evaluation results compared with these EDR data showed both KTG and GKTG demonstrated performance levels applicable for aviation industry professionals (0.809 and 0.805 respectively). Accuracy at the MOG threshold was evaluated by analyzing the correlation between the area under the curve (AUC) and true skill statistic (TSS) values. The KTG model showed relatively higher accuracy. Based on these results, model improvements were implemented, enhancing the TSS of GKTG by 0.22 through threshold adjustment. Considering that models currently used by the Korea Aviation Meteorological Office mainly focus on predicting clear air turbulence and mountain wave turbulence, future research should aim to improve prediction capabilities for convectively-induced and near-cloud turbulence.

Keywords

Acknowledgement

본 논문의 개선을 위해 좋은 의견을 제시해 주신 두 분의 심사위원께 감사를 드립니다. 이 연구는 기상청 국립기상과학원 수요자 맞춤형 기상정보 산출기술 개발사업(KMA2018-00622)의 지원으로 수행되었습니다.