Collaborative Research: CEDAR: Large Amplitude Variations & Instabilities due to Strong Interactions between Tides & Planetary Waves in the Upper Mesosphere and Lower Therm

合作研究：CEDAR：大振幅变化

• 批准号: 1042259
• 负责人: Richard Walterscheid
• 金额: $ 21万
• 依托单位: Aerospace Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-05-01 至 2015-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1042259&HistoricalAwards=false
• 关键词: Collaborative; Research; CEDAR; Large; Amplitude

This project is to characterize the role of nonlinear interactions, including instability, between tides and traveling and stationary planetary waves in generating variability in the upper mesosphere and lower thermosphere (MLT). The work will focus particularly on the two day wave (TDW) in the summertime southern hemisphere, including studies on its amplification due to resonance with a subharmonic of the diurnal tide and consequent generation of a parametric subharmonic instability (PSI) as well as on the apparent association between phase-locked TDWs and pronounced enhancements of airglow emission brightness. In addition, this project will investigate nonlinear forcing mechanisms which modulate tidal amplitude and/or produce non-migrating tides, particularly the westward semidiurnal tide which is dominant in the high-latitude upper mesosphere. This effort will utilize a systems science methodology which combines ground-based wind and airglow intensity measurements, temperature measurements from the NASA TIMED satellite, the TIME-GCM general circulation model, and a global data assimilation model. This work will be conducted as a collaboration between international and U.S. educational, research, and small business institutions.

该项目的特点是非线性相互作用的作用，包括不稳定性，潮汐和行波和定常行星波在产生变化的上层中间层和低热层（MLT）。 这项工作将特别侧重于两天波（TDW）在夏季南半球，包括其放大由于共振与分谐波的昼夜潮汐和随之产生的参数分谐波不稳定性（PSI），以及锁相TDW和气辉发射亮度的显着增强之间的明显关联的研究。 此外，本项目还将研究调制潮汐振幅和/或产生非迁移潮汐的非线性强迫机制，特别是在高纬度上层中层占主导地位的向西向半日潮。 这项工作将利用一种系统科学方法，将地面风和气辉强度测量、美国航天局TIMED卫星的温度测量、TIME-GCM大气环流模型和全球数据同化模型结合起来。 这项工作将作为国际和美国教育，研究和小企业机构之间的合作进行。