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논문 기본 정보

자료유형
학위논문
저자정보

김동진, 허철구 (제주대학교, 제주대학교 대학원)

지도교수
許喆九
발행연도
2013
저작권
제주대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (3)

초록· 키워드

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After the Joint Typhoon Warning Center (JTWC) began issuing official five-day tropical cyclone (TC) forecasts in 2003, the Korea Meteorological Administration (KMA) started issuing official five-day forecasts of TCs in
May 2012 after 2 year of beta test. Forming a selective consensus (SCON) by proper removal of a likely erroneous track forecast is hypothesized to be more accurate than the non-selective consensus (NCON) of all model tracks that are used for the five-day forecasts. Conceptual models describing large
track error mechanisms, which are related to known tropical cyclone motion processes being misrepresented in the dynamical models, are applied to forecasts during the 2012 western North Pacific typhoon season by the Global Data Assimilation and Prediction System (GDAPS (UM N512 L70)). This model tracks are consensus members used in making KMA’s five-day forecasts and thus knowledge of its track error tendencies would be useful in forming a SCON forecast. All 72-h track errors greater than 320 km are examined following the approach developed by Carr and Elsberry (2000a, b).
Tropical influences caused 37% (47 times / 126 erroneous forecasts) of the GDAPS (UM N512 L70) large track forecast errors primarily because an incorrect beta effect-related process depicted by the model contributed to the erroneous forecasts. Midlatitude influences accounted for 63% (79 times / 126 error cases) in the GDAPS (UM N512 L70) erroneous forecasts mainly due to an incorrect forecast of the midlatitude system evolutions. It is proposed that KMA will be able to issue more reliable TC track information if a likely model track error is recognized by optimum use of conceptual models by Carr and Elsberry (2000a, b) and a selective consensus track is then the basis for an improved warning.

목차

Ⅰ 서론 1
Ⅱ 이론적 배경 3
2.1. 태풍과 태풍의 진로예측 방법 3
2.2. 태풍의 진로예측 모델 4
2.3. GDAPS(UM) 5
2.4. 개념모델(Conceptual Model) 7
Ⅲ 연구방법 19
3.1. 분석자료 및 기간 19
3.2. 분석사례 선정방법 19
3.3. 개념모델을 이용한 태풍진로예보오차 원인 평가 20
Ⅳ 결과 및 고찰 21
4.1. 2012년 진로예보오차 특성 21
4.2. 열대관련 진로오차 원인 평가 27
4.3. 중위도관련 진로오차 원인 평가 35
Ⅴ 결론 48
참고문헌 50

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