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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.
이 논문의 연구 히스토리 (6)
2018
2017
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초록· 키워드
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In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.
목차
Abstract
1. 서론
2. 자료
3. 컨센서스 모델 구성
4. 예측성능 검증
5. 토의
6. 요약 및 결론
REFERENCES
참고문헌 (15)
참고문헌 신청
[보고서] - Cangialosi, J. P. / 2013 / 2012 National hurricane center forecast verification report, 79
[단행본] - Davis, C. E. / 1986 / Modern Statistical Methods in Chronic Disease Epidemiology / Wiley : 140 ~ 147
[학술지(정기간행물)] - Mark DeMaria / 2005 / Further Improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS) / Weather and Forecasting 20 (4) : 531 ~ 543
[학술지(정기간행물)] - Goerss, J. S. / 2000 / Tropical cyclone track forecast using an ensemble of dynamical models / Mon. Wea. Rev. 128 : 1187 ~ 1193
[학술지(정기간행물)] - Russell L. Elsberry / 2014 / Advances in Research and Forecasting of Tropical Cyclones from 1963-2013 / 한국기상학회지 50 (1) : 3 ~ 16
[단행본] - Davis, C. E. / 1986 / Modern Statistical Methods in Chronic Disease Epidemiology / Wiley : 140 ~ 147
[학술지(정기간행물)] - Mark DeMaria / 2005 / Further Improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS) / Weather and Forecasting 20 (4) : 531 ~ 543
[학술지(정기간행물)] - Goerss, J. S. / 2000 / Tropical cyclone track forecast using an ensemble of dynamical models / Mon. Wea. Rev. 128 : 1187 ~ 1193
[학술지(정기간행물)] - Russell L. Elsberry / 2014 / Advances in Research and Forecasting of Tropical Cyclones from 1963-2013 / 한국기상학회지 50 (1) : 3 ~ 16
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UCI(KEPA) : I410-ECN-0101-2018-453-003600957