论文

从Niño-3指数看MJO不确定性对ENSO可预报性的影响

  • 徐卫星 ,
  • 彭跃华 ,
  • 朱文超 ,
  • 邓明 ,
  • 杨慧志
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  • 广东省开平市气象局, 开平 529300;2. 海军大连舰艇学院, 大连 116018;3. 广东省台山市气象局, 台山 529200

收稿日期: 2012-12-27

  网络出版日期: 2014-08-28

Impact of the MJO Uncertainty on ENSO Predictability in Terms of the Niño-3 Indices Evolution

  • XU Weixing ,
  • PENG Yuehua ,
  • ZHU Wenchao ,
  • DENG Ming ,
  • YANG Huizhi
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  • Kaiping Meteorological Bureau of Guangdong Province, Kaiping 529300, China;2. Dalian Naval Academy, Dalian 116018, China;3. Taishan Meteorological Bureau of Guangdong Province, Taishan 529200, China

Received date: 2012-12-27

  Online published: 2014-08-28

摘要

通过在Zebiak-Cane数值模式中引入参数化MJO随机外强迫,着重从Niño-3指数的演变发展探讨了MJO不确定性对ENSO可预报性的影响。结果表明,对Zebiak-Cane模式而言,MJO不确定性对由条件非线性最优扰动(CNOP)导致的ENSO事件最大预报误差影响较小;与初始误差相比,由MJO不确定性产生的模式误差在ENSO预报不确定性的产生中具有较小作用,对ENSO可预报性的影响不显著。该结果强调了初始误差在ENSO预报不确定性中的主要作用,从而为ENSO预测的资料同化提供了理论基础。

关键词: MJO; ENSO; CNOP; 模式误差

本文引用格式

徐卫星 , 彭跃华 , 朱文超 , 邓明 , 杨慧志 . 从Niño-3指数看MJO不确定性对ENSO可预报性的影响[J]. 高原气象, 2014 , 33(4) : 1002 -1011 . DOI: 10.7522/j.issn.1000-0534.2012.00201

Abstract

In order to study the impact of the uncertainties of MJO on ENSO predictability, using Zebiak-Cane model and an parametric stochastic representation intra-seasonal forcing, with the method called conditional nonlinear optimal perturbation (CNOP), the effects of the initial errors and those of the uncertainties caused by stochastic MJO forcing on ENSO predictability are compared from the perspective of evolving Niño-3 indices. The results show that: For Zebaik-Cane model, the uncertainties of MJO have little effect on the maximum prediction error for ENSO events caused by CNOPs; compared with CNOP-type initial error, the model error caused by the uncertainties of MJO leads to less prediction uncertainty of ENSO and its influence over ENSO predictability is not significant. In fact, this result suggests that initial error may be the main error source yielding ENSO prediction uncertainty which could provide a theoretical foundation of data assimilation for ENSO forecast.

Key words: MJO; ENSO; CNOP; Model error

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