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An empirical model of tropical ocean dynamics

机译：热带海洋动力学的经验模型

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To extend the linear stochastically forced paradigm of tropical sea surface temperature (SST) variability to the subsurface ocean, a linear inverse model (LIM) is constructed from the simultaneous and 3-month lag covariances of observed 3-month running mean anomalies of SST, thermocline depth, and zonal wind stress. This LIM is then used to identify the empirically-determined linear dynamics with physical processes to gauge their relative importance to ENSO evolution. Optimal growth of SST anomalies over several months is triggered by both an initial SST anomaly and a central equatorial Pacific thermocline anomaly that propagates slowly eastward while leading the amplifying SST anomaly. The initial SST and thermocline anomalies each produce roughly half the SST amplification. If interactions between the sea surface and the thermocline are removed in the linear dynamical operator, the SST anomaly undergoes less optimal growth but is also more persistent, and its location shifts from the eastern to central Pacific. Optimal growth is also found to be essentially the result of two stable eigenmodes with similar structure but differing 2- and 4-year periods evolving from initial destructive to constructive interference. Variations among ENSO events could then be a consequence not of changing stability characteristics but of random excitation of these two eigenmodes, which represent different balances between surface and subsurface coupled dynamics. As found in previous studies, the impact of the additional variables on LIM SST forecasts is relatively small for short time scales. Over time intervals greater than about 9 months, however, the additional variables both significantly enhance forecast skill and predict lag covariances and associated power spectra whose closer agreement with observations enhances the validation of the linear model. Moreover, a secondary type of optimal growth exists that is not present in a LIM constructed from SST alone, in which initial SST anomalies in the southwest tropical Pacific and Indian ocean play a larger role than on shorter time scales, apparently driving sustained off-equatorial wind stress anomalies in the eastern Pacific that result in a more persistent equatorial thermocline anomaly and a more protracted (and predictable) ENSO event.
机译：为了将热带海面温度（SST）变异性的线性随机强迫范式扩展到海表下海洋，根据观测到的SST的3个月运行平均异常的同时和3个月滞后协方差构建了线性逆模型（LIM），跃层深度和纬向风应力。然后，该LIM用于通过经验确定物理过程的线性动力学，以衡量它们对ENSO演化的相对重要性。最初的SST异常和赤道中部太平洋赤道热异常都触发了SST异常在数月内的最佳生长，该异常在向东传播的同时缓慢地向东传播，同时导致放大的SST异常。最初的SST和温跃层异常分别产生大约一半的SST放大倍数。如果在线性动力算子中消除了海面和温跃层之间的相互作用，则海温异常将不那么理想地增长，但也将更加持久，其位置将从东部太平洋向中太平洋转移。还发现最佳增长本质上是两种稳定的本征模式的结果，这些本征模式具有相似的结构，但从初始破坏性干扰到建设性干扰逐渐演变为2年和4年周期。 ENSO事件之间的变化可能不是稳定性特征变化的结果，而是这两种本征模式的随机激发的结果，这两种特性模式代表了表面和地下耦合动力学之间的不同平衡。如先前的研究中所发现的，对于短期尺度而言，附加变量对LIM SST预测的影响相对较小。但是，在大于大约9个月的时间间隔内，其他变量既可以显着提高预测技能，又可以预测滞后协方差以及相关的功率谱，其与观测值的更紧密一致性增强了线性模型的有效性。此外，存在仅由SST构造的LIM中不存在的次要类型的最佳生长，其中西南热带太平洋和印度洋的初始SST异常比短时间尺度上起更大的作用，显然推动了持续的赤道外东太平洋的风应力异常导致赤道热跃层异常更加持久，ENSO事件也更加持久（可预测）。

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