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자료유형
학술저널
저자정보
저널정보
한국기상학회 Asia-Pacific Journal of Atmospheric Sciences 한국기상학회지 제40권 제2호
발행연도
2004.4
수록면
135 - 146 (12page)

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One of the purposes of this study is to develope a new CGCM and another is to hindcast some El Nino/Southern Oscillation(ENSO) events using the CGCM. The CGCM developed in this study is composed of a flux coupler, an atmospheric general circulation model including a land surface model, an oceanic general circulation model, and a thermodynamic/dynamic sea ice model. The atmospheric component of the CGCM is the CCM3 with T42 spectral truncation and 18 vertical levels. The oceanic component model is based on the MOM3, which has 29 vertical levels and horizontal resolution of 2.8125° in longitude and between 0.70° and 2.8125° in latitude. The dynamic part of the sea ice model is based on the elastic- viscous-plastic(EVP) model and thermodynamic part is similar to the Semtner's 3-level sea ice model. The horizontal resolution of the sea ice model is exactly matched with that of the oceanic general circulation model. Coupled experiments comprise a control experiment and some ENSO hindcast experiments including 1982-1983, 1986-1987, 1997-1998 El Nino and 1984-1985 La Nina. To hindcast ENSO events, the CGCM is integrated for one year with lead times of 3, 6, 9, and 12 months. Flux correction is not applied in both control and ENSO hindcast experiments. In the control experiment, although the CGCM exhibits the climate drift, the CGCM can simulate the major features of climate system in terms of annual and seasonal mean climatology. To evaluate the performance of the model for ENSO hindcast, correlation coefficient(CC) and root mean square error(RMSE) with respect to observations are calculated for all lead time integrations. Based on the CC and RMSE, it is concluded that the model produce useful forecasts for long lead times down to 10 months. Hit rates and false alarm rates were calculated to access how well the model predict the various phase of ENSO(i.e., warm, cold, and near normal events). For long lead times down to 10 months, although the CGCM have difficulty predicting near normal events, the CGCM is skillful at predicting warm and cold events.

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Abstract
1. 서론
2. 접합 모형의 개요 및 실험 방법
3. 결과
4. 요약 및 결론
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