Global S&T Development Trend Analysis Platform of Resources and Environment
项目编号 | 1654831 |
The Spectrum of Gravity Waves Radiating from Tropical Cyclones with Observations, Simulations, and Theoretical Modeling | |
David Nolan | |
主持机构 | University of Miami Rosenstiel School of Marine&Atmospheric Sci |
项目开始年 | 2017 |
2017-09-01 | |
项目结束日期 | 2020-08-31 |
资助机构 | US-NSF |
项目类别 | Continuing grant |
项目经费 | 180847(USD) |
国家 | 美国 |
语种 | 英语 |
英文摘要 | The deep moist convection in the cores of tropical cyclones (TCs) generates gravity waves which are seen radiating outwards in trailing spiral patterns. Evidence for these waves have been clearly presented in surface and aircraft observations hundreds of kilometers from real storms. This project will investigate these waves, with a focus on determining which physical processes in the eyewall region are responsible for generating the dominant (and most observable) waves. The research will also explore the extent to which the wave frequencies and amplitudes can be correlated with intensity or intensity changes of the storm. Intellectual Merit: Theoretical understandings of atmospheric convection and TC dynamics require that tropical cyclones radiate gravity waves; these are becoming more and more frequently visible in satellite images. A number of studies have considered whether these waves play some role in the angular momentum or energy budgets of TCs, or in the formation and propagation of rainbands, but most results have been either negative, contradictory, or inconclusive. With recent increases in computer power and data storage, numerical simulations can be regularly per- formed with 1-km grid spacing and 2 minute output. The field of radiating gravity waves, with several different radial wavelengths and vertical structures simultaneously, can be clearly seen in the vertical wind fields of these simulations. Power spectral analyses of simulated time series of surface pressure and surface wind speed suggest these waves can also be detected from fixed surface instruments. Along with the output of full-physics simulations, a linear model of vortex dynamics in the atmosphere will be used to explore the relationships between convection and/or vortex dynamics in the eyewall and the properties of the radiating waves. Furthermore, evidence for these same waves were seen in high frequency observations of pressure and wind from instruments in the Pacific ocean during the passage of typhoons at distances of several hundred kilometers, and also in flight level data from NOAA research aircraft. These preliminary results call for a broader investigation to understand the relationships between TC intensity, TC motion, and the frequencies and amplitudes of their radiating gravity waves. Broader Impacts: The research will further extend our understanding of physical and dynamical processes in the eyewall regions of tropical cyclones, where heat energy is converted into the kinetic energy of the broader wind field. The research will also identify differences between the waves produced in numerical simulations and observed waves. Understanding these differences can lead to improvements in hurricane forecast models and their intensity predictions, which ultimately benefit the society. This work will seek to identify distinct relationships between TC intensity, TC motion, and the properties of the radiating waves, which are already found to be observable in surface observations hundreds of kilometers from the storm center. This project will further advance our methods using a community model (WRF) that allows user to simulate TCs of different intensities and sizes. The high-frequency model output will be made available to the community, and could be used to study other physical processes. The project will support the training of a post-doc and a graduate student. |
URL | 查看原文 |
文献类型 | 项目 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/71742 |
专题 | 环境与发展全球科技态势 |
推荐引用方式 GB/T 7714 | David Nolan.The Spectrum of Gravity Waves Radiating from Tropical Cyclones with Observations, Simulations, and Theoretical Modeling.2017. |
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