Further Studies of Ocean-Atmosphere Coupled Dynamics in the Tropical Pacific

这个项目是对热带太平洋海洋-大气耦合系统年际和年代际变化背后的一些基本过程的调查。提出的研究的一个重点是在不同的频段是否存在能量耦合模式：“快”-大约1年；“中间”- ENSO模式；“慢”—一个年代际模式，以及这些模式和它们的非线性相互作用是否能产生在热带太平洋中看到的一些复杂的时间依赖性。将使用几种方法来研究这个问题。首先，确定不同线性化耦合模型的线性模态。这些模式中最复杂的是一个耦合的MOM3多层海洋和一个多层光谱大气模式，在稳定状态下线性化。线性化模型对高频随机强迫的响应也将被检验。这些模式的上层海洋能量收支将被诊断，以便了解每个模式的动力学。Cane-Zebiak中间模型的修改版本将用于检查不同模式之间的非线性相互作用。预计ENSO模态与快速耦合模态的相互作用主要通过纬向平流对温度的影响，而ENSO模态与年代际模态的相互作用主要通过海洋温跃层位移。还将研究使用更一般的随机风应力和热通量强迫（使用观测到的空间EOFs，其振幅为白噪声过程）的影响。过程建模方法将通过与东京大学的木本博士合作，对气候模型输出的年代际变化进行分析。这项研究很重要，因为它有可能提高对热带太平洋海洋-大气耦合气候现象观测行为的物理理解，从而预测厄尔尼诺等气候现象。

This project is an investigation of some of the fundamental processes behind interannual and decadal variability in the coupled ocean-atmosphere system of the tropical Pacific. One focus of the proposed research is whether there are energetic coupled modes in different frequency bands: "fast" - on the order of 1 year; "intermediate" - the ENSO mode; "slow" - a decadal mode, and whether, together these modes and their nonlinear interactions can produce some of the complex time dependence seen in the tropical Pacific. Several approaches will be used to study the problem. First, the linear modes of a hierarchy of different linearized coupled models will be determined. The most complex of these models is a coupled MOM3 multi-level ocean and a multi-level spectral atmospheric model, linearized around a steady state. The response of the linearized models to high-frequency stochastic forcing will also be examined. The upper-ocean energy budgets of these models will be diagnosed in order to understand the dynamics responsible for each mode. A modified version of the Cane-Zebiak intermediate model will be used to examine nonlinear interactions between the different modes. It is anticipated that the fast coupled mode and the ENSO mode will interact primarily through the effects of zonal advection on temperature while the ENSO and decadal mode will interact through ocean thermocline displacement. The effects of using more general stochastic wind stress and heat flux forcing (using observed spatial EOFs with amplitudes that are white noise processes) will also be examined. The process modeling approach will be augmented with analysis of decadal variability in climate model output through a collaboration with Dr. Kimoto of Tokyo University (CCSR). This research is important because it has the potential to improve the physical understanding of the observed behavior of coupled ocean-atmosphere climate phenomena in the tropical Pacific and, hence, projections of climate phenomena such as El Nino.