| 摘要: |
| 使用Zebiak-Cane 模式和条件非线性最优扰动(CNOP)方法, 研究初始误差和参数误差共同作用对ENSO 春季预报障碍现象的影响。选取模式中的8 个El Ni?o 事件, 包括4 次强事件和4 次弱事件, 每个El Ni?o 事件又分别从8 个不同的起始时间做1 a 的预报, 这样一共64 个预报实验。对每个实验分别计算CNOP误差(初始误差和参数误差同时存在时的最优误差), 通过分析误差增长, 发现CNOP误差引起的1 a 后的预报误差随着初始预报时间的不同有较大差异, 并且不同强度的El Ni?o 事件也会影响CNOP 误差的发展, 增长位相中强事件的预报误差要比弱事件的预报误差大一些; 而衰减位相中恰恰相反, 弱事件的预报误差要比强事件的预报误差要大一些; 同时也发现高频El Ni?o 事件对误差增长率的影响较大。本结论有助于提高Zebiak-Cane 模式预报ENSO 的技巧。 |
| 关键词: Zebiak-Cane 模式 条件非线性最优扰动 ENSO 春季预报障碍 |
| DOI：10.11759/hykx20130228001 |
| 分类号: |
| 基金项目:国家自然科学基金项目(41230420); 青岛市基础研究计划项目(11-1-4-95-jch) |
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| The impact of conditional nonlinear optimal perturbation on the ENSO spring predictability barrier in the Zebiak-Cane model |
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| Abstract: |
| In this paper, the impact of both the initial and parameter errors on the spring predictability barrier (SPB) of the Zebiak-Cane (ZC) model was investigated. We chose eight El Ni?o events in the ZC model, including four strong events and four weak ones, each with eight initial months for a total of 64 cases. Using the conditional nonlinear optimal perturbation (CNOP) approach, we calculated the CNOP errors (optimal errors when both initial and parameter errors were considered) for each event. By analyzing the error growth, we found that both the initial month and the intensity of the El Ni?o events can affect the one-year prediction errors of the CNOP errors. During the growing phase, the prediction errors of the strong events are larger than those of the weak events, while for the decaying phase, the weak events have larger prediction errors. In addition, the high-frequency events have a more noticeable impact on the seasonal error growth. This conclusion may help us improve the ENSO prediction using the ZC model. |
| Key words: the Zebiak-Cane model conditional nonlinear optimal perturbation ENSO spring predictability barrier |
