Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error
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摘要: 本文用观测的风场资料和Zebiak-Cane模式研究了季节内振荡(MJO)作为外强迫对厄尔尼诺-南方涛动(ENSO)可预报性的影响。观测资料用连续小波变换(CWT)分析后用于提取MJO信号, MJO加入模式得到新的模式。在使用条件非线性最优扰动(CNOP)后, 得到了可发展成最大预报误差的初始误差、模式误差及其联合误差, 然后考察了三种误差的Nino-3指数和空间结构的演变发展。结果主要表明观测MJO对ENSO事件的最大预报误差影响较小, 初始误差比由MJO强迫产生的模式误差的影响大得多。这些说明初始误差很可能是产生ENSO预测不确定性的主要误差来源, 从而可为ENSO预测的适应性资料同化提供理论基础, 并对ENSO的目标观测做出贡献。
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关键词:
- 厄尔尼诺——南方涛动(ENSO) /
- 季节内振荡(MJO) /
- 最大预报误差 /
- 条件非线性最优扰动(CNOP)
Abstract: With the observational wind data and the Zebiak-Cane model, the impact of Madden-Julian Oscillation (MJO) as external forcing on El Niño-Southern Oscillation (ENSO) predictability is studied. The observational data are analyzed with Continuous Wavelet Transform (CWT) and then used to extract MJO signals, which are added into the model to get a new model. After the Conditional Nonlinear Optimal Perturbation (CNOP) method has been used, the initial errors which can evolve into maximum prediction error, model errors and their join errors are gained and then the Niño 3 indices and spatial structures of three kinds of errors are investigated. The results mainly show that the observational MJO has little impact on the maximum prediction error of ENSO events and the initial error affects much greater than model error caused by MJO forcing. These demonstrate that the initial error might be the main error source that produces uncertainty in ENSO prediction, which could provide a theoretical foundation for the adaptive data assimilation of the ENSO forecast and contribute to the ENSO target observation. -
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