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| Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO Prediction | |
| Dai, Guokun1,2; Mu, Mu3; Jiang, Zhina4 | |
| 2016 | |
| 发表期刊 | JOURNAL OF THE ATMOSPHERIC SCIENCES
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| 卷号 | 73期号:1页码:293-317 |
| 文章类型 | Article |
| 摘要 | Based on a viewpoint that the North Atlantic Oscillation (NAO) is a nonlinear initial-value problem, the predictability of NAO event onset is studied through investigation of the relationship between the optimal precursor (OPR) to its onset and the optimally growing initial error (OGE) in onset prediction. The problem is explored by the method of conditional nonlinear optimal perturbation with a triangular T21, three-level, quasigeostrophic global spectral model.For the NAO onset, there are two types of OGEs. Numerical results show that, with the optimization time of 3 days, a type-1 OGE bears a great resemblance to OPR, and the similarity coefficient between them is 0.98 for both positive (NAO+) and negative NAO (NAO-). A type-2 OGE is also characterized by a similar pattern to OPR, but with an opposite sign. With the extension of the optimization time to 7 days, the similarity coefficient between OPR and type-1 (type 2) OGE gradually decreases to 0.82 (-0.81) for NAO- and 0.87 (-0.57) for NAO+. However, in the linear regime, such high similarity between OPR and OGE can only be found with an optimization time of 3 days.Further analysis reveals that a type-1 (type 2) OGE has a similar growth behavior to that of the corresponding OPR of the same-phase (opposite phase) NAO event, both of which develop into a dipole NAO anomaly pattern. This similarity between OPR and OGE suggests that the nonlinear process plays an important role in the NAO event, which simultaneously provides a theoretical foundation for its targeted observations. |
| DOI | 10.1175/JAS-D-15-0109.1 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000367398300001 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.qdio.ac.cn/handle/337002/86632 |
| 专题 | 海洋环流与波动重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China 4.Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China |
| 推荐引用方式 GB/T 7714 | Dai, Guokun,Mu, Mu,Jiang, Zhina. Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO Prediction[J]. JOURNAL OF THE ATMOSPHERIC SCIENCES,2016,73(1):293-317. |
| APA | Dai, Guokun,Mu, Mu,&Jiang, Zhina.(2016).Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO Prediction.JOURNAL OF THE ATMOSPHERIC SCIENCES,73(1),293-317. |
| MLA | Dai, Guokun,et al."Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO Prediction".JOURNAL OF THE ATMOSPHERIC SCIENCES 73.1(2016):293-317. |
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| Relationships betwee（5657KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 浏览 | |
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