인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
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.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-ECN-0101-2009-453-018780825