A Study of Forecast System for Clear-Air Turbulence in Korea Part I: Korean Integrated Turbulence Forecasting Algorithm (KITFA)

한국의 청천난류 예보 시스템에 대한 연구 Part I: 한국형 통합 난류 예측 알고리즘

  • Jang, Wook (Department of Atmospheric Sciences, Yonsei University) ;
  • Chun, Hye-Yeong (Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Jung-Hoon (Department of Atmospheric Sciences, Yonsei University)
  • Received : 2009.08.04
  • Accepted : 2009.09.02
  • Published : 2009.09.01

Abstract

Based on the pilot reports (PIREPs) collected in South Korea from 2003 to 2008 and corresponding Regional Data Assimilation and Prediction System (RDAPS) analysis data of 30 km resolution, we validate the Korean Integrated Turbulence Forecasting Algorithm (KITFA) system that predicts clear-air turbulence (CAT) above the Korean peninsula. The CATs considered in this study are the upper level (higher than 20000 ft) turbulence excluding convectively induced turbulences. In the KITFA system, there are two main processes for predicting CATs: to select CAT indices and to determine their weighting scores. With the PIREPs observed for much longer period than those used in the current operational version of the KITFA system (March 4-April 8 of 2002), three improvable processes of the current KITFA system, re-calculation of weighting scores, change of method to calculate weighting scores, and re-selection of CAT indices, are tested. The largest increase of predictability is presented when CAT indices are selected by using longer PIREP data, with the minor change using different methods in calculation of weighting scores. The predictability is the largest in wintertime, and it is likely due to that most CAT indices are related to the jet stream that is strongest in wintertime. This result suggests that selecting proper CAT indices and calculating their weighting scores based on the longer PIREPs used in this study are required to improve the current KITFA.

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