Net energy dissipation in the tropical ocean and ENSO dynamics: modeling and theoretical study.

该项目力求估计热带太平洋在从次年到十年的广泛频率范围内的净能量耗散，并探讨能量耗散如何影响厄尔尼诺/南方涛动现象的某些特征(其周期、幅度和其他特性)。该项目有四个相互关联的部分：(1)计算与热带海洋大尺度运动有关的净耗散速率；(2)系统地探索控制这些速率的各种物理机制和模式参数化的作用；(3)研究这些速率的不同值如何影响最先进的海-气耦合大气环流模式模拟ENSO；(4)利用中间耦合模式和理论考虑，阐明海洋能量耗散对厄尔尼诺现象特性的影响。该项目的最终任务是将能量学发展成为大气环流模式的标准诊断工具。智力上的优点：先前对ENSO的研究已经确定，在连续振荡中，拉尼娜对应于最大可用势能状态(APE)，厄尔尼诺对应于最小能量状态，因为APE是热带海洋温跃层斜率的量度。风在海洋上所做的工作改变了海洋环流和浮力通量，从而创造或摧毁了类人猿。海洋中的能量耗散往往会减少这一功。描述这种能量平衡的方程包含了系统固有的非线性动力学，从而为研究非线性振荡提供了一个方便的数学工具。能量学还在处理不同模型时提供了一种标准的统一方法。能量平衡将被用来研究模式的不同特征如何影响能量耗散率，另一方面，能量耗散的变化如何影响ENSO的性质。初步的理论结果支持耗散在控制或影响ENSO的主要特征方面的重要性。最终，了解与热带大范围海洋运动相关的净能量耗散率将有助于解决热带气候理论的一个悬而未决的问题--ENSO循环是自我维持的还是受阻的。更广泛的影响：该项目旨在探索在自然界中观察到的和通过耦合气候模式模拟的控制ENSO动态的基本机制。这将使大气环流模式(GCM)更好地模拟厄尔尼诺现象。用于模拟季节和年际气候波动的耦合模式的开发进展迅速，但可靠的厄尔尼诺预测的目标仍然遥不可及。该项目的一部分是通过评估耦合模式海洋部分的大尺度耗散特性，使耦合模式的发展更加系统化。将以能源为基础的办法转变为耦合全球气候模式的诊断工具，将有助于不同模式的比较，并有助于在对季节到年际气候变率进行现实模拟方面取得进展。这将对气候预测具有直接的价值。该项目的另一个重要部分是在耶鲁大学发展全球气候模拟能力，这将通过向研究生和本科生介绍气候研究中的现代数值方法而使他们受益。这些建模能力将用于由PI指导的学生的研究工作，以及本科高级项目，而通过这项建议产生的研究成果将用于目前由首席调查员教授或正在开发的班级。建模能力还将有助于与耶鲁其他教职员工的合作研究，并将用于更广泛的耶鲁社区的教育用途。拟议的教育计划包括对一名气候动力学博士生的教育。

This project seeks to estimate net energy dissipation in the tropical Pacific ocean in a broad range of frequencies from sub-annual to decadal and to explore how energy dissipation affects certain characteristics of the El Nino / Southern Oscillation (ENSO) phenomenon (its period, amplitude and other properties). The project has four interconnected components: (i) to compute net dissipation rates associated with large-scale motion in the tropical ocean; (ii) to systematically explore the role of various physical mechanisms, and model parameterizations, that control those rates; (iii) to investigate how different values of those rates affect the simulation of ENSO by state-of-the-art coupled ocean-atmosphere general circulation models; and (iv) to use intermediate coupled models and theoretical considerations to elucidate the effect of oceanic energy dissipation on the properties of El Nino. The ultimate task of this project is to develop the energetics into a standard diagnostic tool for general circulation models.Intellectual Merit:Prior studies of ENSO have established that in a continual oscillation, La Nina corresponds to a state of maximum Available Potential Energy (APE), El Nino to a state of minimum energy, since APE is a measure of the thermocline slope in the tropical ocean. The work done on the ocean by the winds modifies the ocean circulation and buoyancy fluxes, thus creating or destroying APE. Energy dissipation in the ocean tends to reduce this work. The equation describing this energy balance encompasses intrinsic nonlinear dynamics of the system and thus provides a convenient mathematical tool for studying nonlinear oscillations. The energetics also offer a standard unifying approach when dealing with different models. The energy balance will be used to investigate how different characteristics of the models affect the energy dissipation rates, and, on the other hand, how changes in energy dissipation affect the properties of ENSO. Preliminary theoretical results support the importance of dissipation in controlling or influencing the main characteristics of ENSO. Ultimately, knowing the net energy dissipation rates associated with large-scale oceanic motion in the tropics will help to resolve an unsettled problem of the tropical climate theory - whether the ENSO cycle is self-sustained or damped. Broader Impacts:The project is aimed at exploring fundamental mechanisms that control the dynamics of ENSO as observed in nature and as simulated by coupled climate models. It will lead to a better simulation of El Nino by general circulation models (GCM). The development of coupled models for the simulation of seasonal and inter-annual climate fluctuations is progressing rapidly but the goal of a reliable El Nino prediction is still out of reach.. A part of this project is to make the development of coupled GCMs more systematic by evaluating large-scale dissipative properties of the oceanic component of coupled models. Transforming the energy-based approach into a diagnostic tool for coupled GCMs will facilitate comparison of different models and contribute to the progress towards a realistic simulation of seasonal-to-inter-annual climate variability. This will be of direct value for climate prediction. Another important part of this project is to develop global climate modeling capacities at Yale University, which will benefit both graduate and undergraduate students by introducing them to modern numerical approaches in climate research. These modeling capacities will be used in the research work of the students supervised by the PI, and in undergraduate senior projects, while research results originated through this proposal will be used in the classes currently taught or being developed by the Principal Investigator. The modeling capabilities will also contribute to collaborative research with other Yale faculty, and will be made available for educational use to the broader Yale community. The proposed educational plan includes the education of a Ph.D. student in climate dynamics.