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An ENSO prediction approach based on ocean conditions and ocean-atmosphere coupling

机译：基于海洋状况和海-气耦合的ENSO预测方法

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摘要

A simple statistical model for the El Nio-Southern Oscillation (ENSO) prediction is derived based on the evolution of the ocean heat condition and the oceanic Kelvin wave propagation associated with westerly wind events (WWEs) and easterly wind surges (EWSs) in the tropical Pacific. The multivariate linear regression model solely relies on the pentad thermocline depth anomaly evolution in 25 days along with the zonal surface wind modulation. It successfully hindcasts all ENSOs except for the 2000/01 La Nia, using the pentad (or monthly) mean tropical atmosphere ocean array data since 1994 with an averaged skill (measured by anomaly correlation) of 0.62 (or 0.67) with a 6-month lead. The exception is mainly due to the long-lasting cold sea surface temperature anomalies in the subtropics resulting from the strong 1998/99 La Nia, even though the tropical warm water volume (WWV) had rebounded and turned phases after 2000. We also note that the hindcast skill is comparable using pentad or monthly mean NCEP global ocean data assimilation system data for the same time period. The hindcast skill of the proposed statistical model is better than that based on the WWV index in terms of the monthly correlation, normalized RMSEs and ENSO occurrences, which suggest that including the evolution of the subsurface ocean temperature anomaly and the WWEs/EWSs in the central tropical Pacific can enhance the ability to predict ENSO. The hindcast skill is also comparable to the predictions using other dynamical and statistical models, indicating that these processes are the keys to ENSO development. The dynamics behind the statistical model are consistent with the physical processes of ENSO development as follows: the tropical WWV resulting from the interannually-varying meridional subtropical cell transport provides a sufficient heat source. When the seasonal phase lock of ocean-atmosphere coupling triggers the positive (negative) zonal wind anomaly in boreal summer and fall, an El Nio (a La Nia) will develop as evidenced by the Kelvin wave propagation. The triggering dynamic may be suppressed or enhanced by the influence of extratropical Pacific sea surface temperature.
机译：基于海洋热状况的演变以及与热带西风事件（WWE）和东风浪（EWS）相关的海洋开尔文波传播，得出了一个简单的厄尔尼诺-南方涛动（ENSO）预测统计模型。太平洋。多元线性回归模型仅依赖于25天五体温跃层深度异常演变以及纬向表面风调制。它成功地对除2000/01年拉尼亚以外的所有ENSO进行了预报，使用了1994年以来的五元组（或每月）热带平均海洋阵列数据，平均技能（通过异常相关性测得）为0.62（或0.67），为期6个月。铅。例外主要是由于1998/99年强La Nia在亚热带造成的长期冷海表面温度异常，尽管热带暖水量（WWV）在2000年之后已经反弹并转变了相态。我们也注意到使用同一时间的五元组或月均NCEP全球海洋数据同化系统数据，后预报技能具有可比性。在月相关性，归一化RMSE和ENSO发生方面，所提出的统计模型的后预报技术要优于基于WWV指数的后预报技术，这表明包括中部地下海温异常和WWE / EWS的演变。热带太平洋可以增强预报ENSO的能力。后播技能也可以与使用其他动力学和统计模型的预测相媲美，表明这些过程是ENSO发展的关键。统计模型背后的动态与ENSO发展的物理过程一致，如下所示：由子午向副热带间年际变化产生的热带WWV提供了足够的热源。当海洋-大气耦合的季节性锁相在北方夏季和秋季触发正（负）纬向风异常时，就会出现开尔文波传播所证明的厄尔尼诺现象（La Nia）。触发动力学可能会受到温带太平洋海面温度的影响而被抑制或增强。

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