Theoretic Studies in Geophysical Fluid Dynamics and Climate Dynamics

地球物理流体动力学和气候动力学理论研究

• 批准号: 1515024
• 负责人: Shouhong Wang
• 金额: $ 30.92万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1515024&HistoricalAwards=false
• 关键词: Theoretic; Studies; Geophysical; Fluid; Dynamics

The principal investigator develops and studies mathematical models of geophysical processes important for weather and climate. A major aim is to better understand sources of climate variability and the extent of their influences. The work involves new mathematical theory and techniques for dynamic transitions between states of a system described by a set of partial differential equations, and for memory effects -- differences in any particular state's features that depend on the chain of states through which the system arrives at that state. The system may be deterministic or stochastic. The mathematical issues are motivated by climate problems, and in turn the theory and the techniques are applied to the understanding of fundamental issues in climate dynamics and prediction. This project leads to improved predictions and new insights into weather, climate, and environmental phenomena of central importance to our economy. One such phenomenon to be studied in this project is the El Nino-Southern Oscillation (ENSO), which is the dominant mode of inter-annual climate variability, and which has global impacts on temperature, precipitation, tropical cyclones, human health, and even conflict. The project involves scientists as well as graduate students from the related scientific disciplines. Graduate students are included in the work of the project. The principal investigator and his collaborators work on dynamic transition theory for both deterministic partial differential equations and stochastic partial differential equations (SPDEs), and on developing theory and methods to establish effective non-Markovian reduced models for SPDEs. The goal is to quantify the sensitivity and dynamic transitions associated with typical sources of climate low frequency variability. Major goals include quantifying the role played by the memory effects, and identifying the key nonlinear interactions between low and high modes and the memory effects caused by noise. A few typical sources of climate variability that will be studied include ENSO, tropical convections, and the thermohaline circulations. Their variability, independently and interactively, may play a significant role in climate changes, past and future. The project involves specific collaborations with active atmosphere/ocean scientists in different institutions, and graduate students are included in the project work as well.

主要研究员开发和研究对天气和气候重要的地球物理过程的数学模型。 一个主要目的是更好地了解气候变异的来源及其影响的程度。 这项工作涉及新的数学理论和技术，用于由一组偏微分方程描述的系统状态之间的动态转换，以及记忆效应-任何特定状态特征的差异取决于系统到达该状态的状态链。 该系统可以是确定性的或随机的。 数学问题的动机是气候问题，反过来，理论和技术被应用到气候动力学和预测的基本问题的理解。 该项目导致改进的预测和新的见解天气，气候和环境现象的核心重要性，我们的经济。 本项目要研究的现象之一是厄尔尼诺-南方涛动，这是年际气候变化的主要模式，对气温、降水、热带气旋、人类健康甚至冲突都有全球性影响。 该项目涉及科学家以及相关科学学科的研究生。 研究生也参与了该项目的工作。 主要研究者和他的合作者致力于确定性偏微分方程和随机偏微分方程（SPDE）的动态过渡理论，并发展理论和方法来建立有效的非马尔可夫简化模型。 目标是量化与气候低频变率典型来源相关的敏感性和动态转换。 主要目标包括量化记忆效应所起的作用，识别低模和高模之间的关键非线性相互作用以及噪声引起的记忆效应。 将研究的气候变率的一些典型来源包括厄尔尼诺/南方涛动、热带对流和温盐环流。 它们的变异性，无论是独立的还是相互作用的，都可能在过去和未来的气候变化中发挥重要作用。 该项目涉及与不同机构活跃的大气/海洋科学家的具体合作，研究生也参与了项目工作。