Understanding the interplay between ENSO and related tropical SST variability using linear inverse models
Understanding the interplay between ENSO and related tropical SST variability using linear inverse models
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DOI：
10.1007/s00382-022-06484-x
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发表时间：
2022-09
期刊：
影响因子：
4.6
通讯作者：
S. Kido;I. Richter;T. Tozuka;P. Chang
中科院分区：
文献类型：
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作者：
S. Kido;I. Richter;T. Tozuka;P. Chang
利用热带太平洋（PO）、大西洋（AO）和印度洋（IO）的海表温度（SST）和海表高度异常的线性逆模型（LIM）框架，评估了热带海盆间相互作用（TBI）对热带海表温度（SST）特征和可预测性的影响。TBI途径被证明是成功地隔离在随机强迫模拟，修改非对角元素的线性算子。TBI的消除导致厄尔尼诺-南方涛动（ENSO）和相关变率的幅度大幅增加。部分去耦实验，消除特定的耦合组件显示，PO-IO相互作用是主要的贡献者，而PO-AO和AO-IO相互作用发挥次要作用。一系列不同算子的回顾性预报试验表明，解耦导致ENSO预报技巧的大幅下降，特别是在较长的提前期。个体路径对预测技能的相对贡献与随机强迫实验的结果基本一致。定性相似的结果是从一个额外的一组预测实验，部分应用初始条件在特定的盆地，但也发现了一些重要的差异，由于在每个TBI途径的代表性的差异。最后，利用LIM预报试验对1982/83年和1997/98年极端厄尔尼诺事件后AO上空海温异常的原因进行了分析，以验证LIM预报方法的有效性和灵活性。
The impacts of tropical interbasin interaction (TBI) on the characteristics and predictability of sea surface temperature (SST) in the tropics are assessed with a linear inverse modelling (LIM) framework that uses SST and sea surface height anomalies in the tropical Pacific (PO), Atlantic (AO), and Indian Ocean (IO). The TBI pathways are shown to be successfully isolated in stochastically-forced simulations that modify off-diagonal elements of the linear operators. The removal of TBI leads to a substantial increase in the amplitude of El Niño-Southern Oscillation (ENSO) and related variability. Partial decoupling experiments that eliminate specific coupling components reveal that PO-IO interaction is the dominant contributor, whereas PO-AO and AO-IO interactions play a minor role. A series of retrospective forecast experiments with different operators shows that decoupling leads to a substantial decrease in ENSO prediction skill especially at longer lead times. The relative contributions of individual pathways to forecast skill are generally consistent with the results from the stochastically-forced experiments. Qualitatively similar results are obtained from an additional set of forecast experiments that partially apply initial conditions over specific basins, but several important differences were also found due to differences in the representations of each TBI pathway. Finally, the cause of contrasting SST anomalies over the AO after the extreme 1982/83 and 1997/98 El Niño events is explored using LIM forecast experiments to demonstrate the strength and flexibility of our LIM-based approach.