A new wave-vortex decomposition method for one-dimensional spectra

一种新的一维谱波涡分解方法

• 批准号: 1516324
• 负责人: Oliver Buhler
• 金额: $ 33.85万
• 依托单位: New York 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: 2015-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1516324&HistoricalAwards=false
• 关键词: new; wave; vortex; decomposition; method

BuhlerDMS-1516324 This project systematically extends a recently discovered data analysis method that allows a precise wave-vortex decomposition of flow measurements along a fast-moving aircraft, ship, or satellite trajectory. Such a decomposition is crucial for the understanding of the observed data in many cases, especially in atmosphere and ocean fluid dynamics, where we are often presented with a complex jigsaw puzzle of waves and vortices far beyond the threshold of our contemporary simulation and observation tools. For example, this is highly relevant for extracting the maximum value out of expensive measurements obtained by aircraft, ships, and satellite-based remote sensing. The method plays fundamentally into our understanding of difficult fluid-mechanical processes that are highly relevant for climate dynamics. Graduate students are included in the work of the project. The new method is generally applicable to any fluid mechanical problem that involves stable stratification and/or Coriolis forces due to background rotation. Preliminary results with the new technique have been promising, but the technique is limited by a number of restrictive assumptions that had to be made to derive it cleanly. These include assumptions about horizontal isotropy and three-dimensional spatial homogeneity of the data as well as an assumed lack of statistical correlations between waves and vortices. The present project seeks to remove these restrictions, to make the new technique much more broadly applicable. This is achieved through a combination of theoretical analysis, modelling, and numerical simulation, as well as comparison and testing with real data from the atmosphere and ocean. Graduate students are included in the work of the project.

BuhlerDMS-1516324 该项目系统地扩展了最近发现的数据分析方法，该方法允许沿着快速移动的飞机，船舶或卫星轨迹对流量测量进行精确的波涡分解。 在许多情况下，这种分解对于理解观测数据至关重要，特别是在大气和海洋流体动力学中，我们经常面临远远超出当代模拟和观测工具阈值的复杂波浪和漩涡拼图。 例如，这对于从飞机、船舶和卫星遥感获得的昂贵测量值中提取最大值具有高度相关性。 这种方法从根本上帮助我们理解与气候动力学高度相关的困难的流体力学过程。 研究生也参与了该项目的工作。 新方法一般适用于任何流体力学问题，涉及稳定分层和/或科里奥利力由于背景旋转。 新技术的初步结果是有希望的，但该技术受到一些限制性假设的限制，这些假设必须清楚地推导出来。 这些假设包括水平各向同性和三维空间均匀性的数据，以及假设缺乏统计相关性波和涡。 本项目旨在消除这些限制，使新技术更广泛地适用。 这是通过理论分析、建模和数值模拟相结合，以及与大气和海洋的真实的数据进行比较和测试来实现的。 研究生也参与了该项目的工作。