Statistical Modeling in Wavelet Domain with Application in Turbulence

这项合作建议涉及发展多分辨率模型的统计概念、理论和方法，以及大气湍流中的测量和结构分析。它借鉴了贝叶斯多尺度模拟的最新发展，以了解湍流的时间尺度方面，其中尺度和等级的概念是内在的。多分辨率统计建模方法被应用于空气质量现场实验和模拟产生的大量地球物理测量，以确定对臭氧等标量输送负责的大气湍流的关键结构特征。为了实现这些目标，一组在统计建模和多尺度方法(M.Pensky和B.Vidakovic)以及大气湍流测量和建模(G.Katul)方面具有专长的研究人员正在共同合作。该项目的实用性是通过新的统计技术提高对大气传输的基本理解。大气传输是描述空气质量的关键，是一种复杂的现象，它涉及到湍流的模拟，而湍流是污染物扩散的原因。建议的方法的适用性将直接在北卡罗来纳州达勒姆的杜克森林收集的高频速度、温度和臭氧浓度测量上进行测试。该奖项的部分支持是由大气科学部的物理气象计划提供的。

This collaborative proposal involves development of statistical concepts, theories and methods for multiresolution models and analyses of measurements and structures in atmospheric turbulence. It draws on recent developments in Bayesian multiscale modeling to understand the time-scale aspects of turbulence where the notions of scale and hierarchy are intrinsic. Multiresolution statistical modeling approaches are applied to vast geophysical measurements arising from air quality field experiments and simulations in order to identify key structural properties of atmospheric turbulence responsible for the transport of scalars, such as ozone. To achieve these objectives a team of researchers with expertise in statistical modeling and multiscale methods (M. Pensky and B. Vidakovic) and measurement and modeling of atmospheric turbulence (G. Katul) are jointly collaborating together.The aplicability of this project is improved fundamental understanding of atmospheric transport via novel statistical techniques. Atmospheric transport, key to describing air-quality, is a complex phenomena involving modeling of turbulence which is responsible for the dispersion of polutants. The applicability of the proposed methodology will be directly tested on high frequency velocity, temperature, and ozone concentration measurements collected at Duke Forest, Durham, North Carolina. Partial support for this award is provided by the Physical Meteorology Program in the Division of Atmospheric Sciences.