CEDAR: Analysis of High Resolution Stratospheric Observations of Polar Mesospheric Clouds

CEDAR：极地中层云的高分辨率平流层观测分析

• 批准号: 1452183
• 负责人: Amber Miller
• 金额: $ 23.77万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1452183&HistoricalAwards=false
• 关键词: CEDAR; Analysis; Resolution; Stratospheric; Observations

A unique data set consisting of high-resolution optical images of Polar Mesospheric Clouds (PMCs) observed from a stratospheric balloon platform in January of 2013 will be analyzed. PMCs have proven to be excellent tracers of dynamics in the mesosphere and lower thermosphere (MLT). Complex morphological structures in their brightness distribution provide observable consequences of the deposition of energy and momentum by atmospheric gravity waves (GW) in the MLT. This high-resolution data set of optical images provides a unique window into the poorly understood instability and turbulent dynamics on the smallest scales (between roughly a meter and a few km). Through this analysis, morphological features identified in individual images will be compared with those predicted in numerical models in order to identify key dynamical features present in the data on these small scales. Despite the limited field of view available in these images, the analysis of this data set will enable the identification of features that show a range of dynamics, providing evidence for transitional scales and instability accompanying GW breaking or Kelvin-Helmholtz instabilities. It will also enable the identification of features that place bounds on the local Reynolds number, and therefore the background turbulence level. This project will provide research opportunities for graduate, undergraduate, and high school students.

将分析2013年1月从平流层气球平台观测到的由极地中间层云（PMC）高分辨率光学图像组成的独特数据集。PMCs已被证明是中间层和低热层（MLT）动力学的优秀示踪剂。复杂的形态结构，在其亮度分布提供了可观察到的后果，沉积的能量和动量的大气重力波（GW）在MLT。这种高分辨率的光学图像数据集提供了一个独特的窗口，可以在最小尺度上（大约一米到几公里之间）了解不稳定性和湍流动力学。通过这一分析，在个别图像中确定的形态特征将与数值模型中预测的形态特征进行比较，以确定这些小尺度数据中存在的关键动态特征。 尽管这些图像中的视野有限，但对该数据集的分析将能够识别显示一系列动态的特征，为伴随GW断裂或开尔文-亥姆霍兹不稳定性的过渡尺度和不稳定性提供证据。它还将能够识别对局部雷诺数设置界限的特征，从而识别背景湍流水平。这个项目将为研究生、本科生和高中生提供研究机会。