کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6426493 1634215 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model
چکیده انگلیسی


- The performance of MJO prediction in BCC_AGCM2.2 has been evaluated.
- This atmospheric model has fairly high prediction skill and predictability of MJO.
- The teleconnections of the MJO can be reasonably reproduced by BCC_AGCM2.2.

This study evaluates performance of Madden-Julian oscillation (MJO) prediction in the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM2.2). By using the real-time multivariate MJO (RMM) indices, it is shown that the MJO prediction skill of BCC_AGCM2.2 extends to about 16-17 days before the bivariate anomaly correlation coefficient drops to 0.5 and the root-mean-square error increases to the level of the climatological prediction. The prediction skill showed a seasonal dependence, with the highest skill occurring in boreal autumn, and a phase dependence with higher skill for predictions initiated from phases 2-4. The results of the MJO predictability analysis showed that the upper bounds of the prediction skill can be extended to 26 days by using a single-member estimate, and to 42 days by using the ensemble-mean estimate, which also exhibited an initial amplitude and phase dependence. The observed relationship between the MJO and the North Atlantic Oscillation was accurately reproduced by BCC_AGCM2.2 for most initial phases of the MJO, accompanied with the Rossby wave trains in the Northern Hemisphere extratropics driven by MJO convection forcing. Overall, BCC_AGCM2.2 displayed a significant ability to predict the MJO and its teleconnections without interacting with the ocean, which provided a useful tool for fully extracting the predictability source of subseasonal prediction.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Dynamics of Atmospheres and Oceans - Volume 75, September 2016, Pages 78-90
نویسندگان
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