An empirical model of tropical ocean dynamics
An empirical model of tropical ocean dynamics
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DOI：
10.1007/s00382-011-1034-0
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发表时间：
2011-11-01
期刊：
影响因子：
4.6
通讯作者：
Scott, James D.
中科院分区：
文献类型：
--
作者：
Newman, Matthew;Alexander, Michael A.;Scott, James D.
为了将热带海表温度（SST）变率的线性随机强迫模式推广到次表层海洋，利用SST、温跃层深度和纬向风应力的3个月运行平均距平的同时协方差和3个月滞后协方差，建立了一个线性反演模式（LIM）。这个LIM然后被用来识别的物理过程，以衡量它们的相对重要性ENSO演变的线性动力学。SST距平的最佳增长是由初始SST距平和赤道中太平洋温跃层距平共同触发的，后者在导致SST距平放大的同时缓慢向东传播。初始SST和温跃层异常各自产生大约一半的SST放大。如果在线性动力学算子中去除海面和温跃层之间的相互作用，则SST异常经历不太理想的增长，但也更持久，并且其位置从东太平洋转移到中太平洋。还发现最佳增长本质上是两个具有相似结构但不同2年和4年周期的稳定本征模从初始破坏性干涉演变为建设性干涉的结果。ENSO事件之间的变化可能是一个后果，而不是改变稳定性的特点，但随机激励这两个本征模式，这代表了不同的平衡之间的表面和地下耦合动力学。如在以前的研究中发现，附加变量对LIM SST预报的影响在短时间尺度上相对较小。然而，在大于约9个月的时间间隔，额外的变量都显着提高预测技能和预测滞后协方差和相关的功率谱，其更接近的协议与观测增强了线性模型的验证。此外，第二种类型的最佳增长存在，是不存在的LIM构建从SST单独，其中在西南热带太平洋和印度洋的初始SST异常发挥了更大的作用比在较短的时间尺度上，显然驱动持续离赤道风应力异常在东太平洋，导致更持久的赤道温跃层异常和更持久的（和可预测的）ENSO事件。
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.