超强厄尔尼诺事件“春季可预报性障碍”及其误差增长动力学分析

发布时间：2018-03-28 07:06

本文选题：/超强El　切入点：Ni泺o事件　出处：《中国科学:地球科学》2017年09期

【摘要】：基于一个中等复杂程度模式(ICM)集合预报系统(EPS)产生的海表温度距平(SSTA)预报产品,从误差增长的角度探讨了2015/16超强El Ni泺o事件的"春季可预报性障碍"(SPB)问题.通过分析集合预报成员预报误差的增长倾向,发现了2015/16 El Ni泺o事件的预报误差增长呈现显著的季节依赖性,且在春/夏季具有最大增长率,表明ICM-EPS对2015/16 El Ni泺o事件的预报发生了明显的SPB现象.进一步分析表明,上述SPB现象不是由ICM初始场的不确定性引起,而是由其模式误差导致,而ICM-EPS集合预报成员的平均滤掉了部分模式误差的影响,减弱了SPB现象,从而使得2015/16 El Ni泺o事件的预报产生较小的预报误差.通过探讨由海温方程的倾向误差表征的模式误差,该研究揭示了导致SPB现象发生的倾向误差的主要空间特征,并阐明了ICM-EPS低估2015/16El Ni泺o事件强度的原因.此外,本文也揭示了导致显著SPB现象,尤其是导致最大预报误差的SSTA倾向误差的结构特征.该倾向误差的SSTA分量具有赤道中东太平洋负异常,西太平洋正异常的纬向偶极子结构,与Duan等提出的最敏感非线性强迫奇异向量(NFSV)-倾向误差高度相似,从而表明NFSV-型倾向误差也存在于实际的El Ni泺o预报中.该研究也探讨了其他超强El Ni泺o事件,如1982/83和1997/98事件,得到了类似的结果.因此,如果利用NFSV-型倾向误差校正ICM模式误差,ICM-EPS可大大提高超强El Ni泺o事件的预报技巧.
[Abstract]:Based on the sea surface temperature anomaly (SST) prediction product produced by an ICM ensemble prediction system (EPSs), In this paper, the problem of "Spring predictability obstacle" of 2015 / 16 super-strong El Ni Roo event is discussed from the point of view of error growth. By analyzing the increasing tendency of forecast error of ensemble forecast members, It is found that the error growth of the 2015 / 16 El Ni Roo event is seasonally dependent and has the maximum growth rate in spring / summer, indicating that the ICM-EPS forecast of the 2015 / 16 El Ni Luo event has a significant SPB phenomenon. The SPB phenomenon mentioned above is not caused by the uncertainty of the initial ICM field, but by the model error. The average of the members of the ICM-EPS ensemble predictor filters out the effect of partial model errors and weakens the SPB phenomenon. Therefore, the prediction error of the 2015 / 16 El Ni Roo event is smaller. By discussing the model error represented by the tendency error of the SST equation, this study reveals the main spatial characteristics of the tendency error that leads to the occurrence of the SPB phenomenon. The reason why ICM-EPS underestimated the intensity of the 2015/16El Ni Luo event is explained. In addition, the paper also reveals the significant SPB phenomenon. In particular, the structural characteristics of the SSTA inclination error, which leads to the maximum prediction error, have the SSTA component of the equatorial Middle Pacific negative anomaly and the zonal dipole structure of the western Pacific positive anomaly. It is similar to the most sensitive nonlinear forced singular vector proposed by Duan et al., which indicates that the NFSV-type inclination error also exists in the actual El Ni Luoo prediction. The other super El Ni Loro events are also discussed in this study. For example, the 1982 / 83 and 1997 / 98 events have obtained similar results. Therefore, if the ICM model error is corrected by NFSV- type tendency error, ICM-EPS can greatly improve the prediction technique of super El Ni Luo events.
【作者单位】：中国科学院大气物理研究所大气科学和地球流体力学数值拟国家重点实验室;中国科学院大学;中国科学院大气物理研究所国际气候与环境科学中心;国家海洋局第二海洋研究所;
【基金】：国家自然科学基金项目(批准号:41230420、41525017) 国家公益气象行业专向项目(编号:GYHY201306018)资助
【分类号】：P732

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