Inverse Models and Orthogonal Decompositions in Geophysical Flow

地球物理流中的反演模型和正交分解

• 批准号: 9312760
• 负责人: Sue Ellen Haupt
• 金额: $ 19.86万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-12-15 至 1998-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9312760&HistoricalAwards=false
• 关键词: Inverse; Models; Orthogonal; Decompositions; Geophysical

ATM-9312760 Haupt, Sue Ellen University of Colorado, Boulder Title: Inverse Models and Orthogonal Decompositions in Geophysical Flow The purpose of this project is to simultaneously apply proper orthogonal decomposition and linear inverse methods to produce simple, easy-to-run, fast models which reproduce the statistics of more complicated models. First, a linear inverse model based on the empirical orthogonal functions (EOFs) of a series of runs of the Shallow Water Equations (SWE) will be developed. The SWE were chosen for ease of comparison with previous and ongoing studies. This simple inverse model will include the EOFs, their tendencies, and statistical noise. EOFs will then be used to construct an inverse model of the Community Climate Model of NCAR. Such an inverse model has not yet been applied to climate models to our knowledge. Thus a simple (fast, easy-to-run) climate model with statistics identical to the full climate model on which it was based will be constructed. Such a model will be useful for instances where the statistics need be to reproduced, but for which the exact time development is not essential. Various sensitivity analyses will be performed to determine the best methods to construct these models. This line of research will lead to a new method to decrease the number of degrees of freedom necessary to obtain adequate resolution in some geophysical models. In addition, it will give new insight into the interactions of the empirical modes of motion. This work is preliminary to developing s fully nonlinear climate model based on orthogonal projections. It is important because it would facilitate the testing of climate hypotheses which require credible but simple (computationally cheap) climate models. This research is funded under the NSF USGCRP CMAP program.

题目：地球物理流中的逆模型和正交分解本项目的目的是同时应用适当的正交分解和线性逆方法来生成简单、易于运行、快速的模型，这些模型可以再现更复杂模型的统计数据。首先，建立了基于浅水方程（SWE）一系列运行的经验正交函数（EOFs）的线性逆模型。选择SWE是为了便于与以前和正在进行的研究进行比较。这个简单的逆模型将包括EOFs、它们的趋势和统计噪声。然后，EOFs将用于构建NCAR群落气候模型的逆模型。据我们所知，这样一个逆模型还没有应用到气候模型中。因此，一个简单（快速、易于运行）的气候模型将被构建，其统计数据与作为其基础的完整气候模型相同。这样的模型对于需要复制统计数据的实例是有用的，但是对于这些实例来说，精确的时间开发不是必需的。将进行各种敏感性分析，以确定构建这些模型的最佳方法。这一研究路线将导致一种新的方法，以减少在某些地球物理模型中获得足够分辨率所需的自由度数量。此外，它将为运动的经验模式的相互作用提供新的见解。这项工作为建立一个基于正交预估的完全非线性气候模型奠定了基础。它之所以重要，是因为它将有助于测试需要可靠但简单（计算成本低）的气候模型的气候假设。本研究由NSF USGCRP CMAP项目资助。