A multiscale modelling and simulation methodology for turbulent geophysical flows

湍流地球物理流的多尺度建模和模拟方法

• 批准号: RGPIN-2014-05831
• 负责人: Alam, Jahrul
• 金额: $ 0.8万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588646
• 关键词: multiscale; modelling; simulation; methodology; turbulent

We live and breathe at the bottom of an atmosphere that contains both gases and tiny particles of dust and smoke. Our health and environment are affected by the very complex mechanisms of the extremely turbulent atmosphere. On a sunny day, the land warms up faster than the ocean, which drags cool air from over the ocean to the land. Through this process, energy is exchanged via enhanced turbulent mixing. Turbulent kinetic energy of hurricanes (and other natural disasters) causes damage to lives and their environment. Answering environmental questions - such as why hurricanes develop, why global temperature increases, why the rate of melting polar ice has increased, or why sea level rises - leans heavily on the complete understanding of the turbulent mixing and transport in the atmosphere. For example, in order to project the future distribution of such vital ingredients as carbon-dioxide (CO2) or other pollutants, one needs to know their sources and sinks, and how these pollutants are mixed in the turbulent atmosphere. However, the turbulent mixing mechanism is brutally affected when atmospheric models (either air pollution or weather prediction) employ a typical mesoscale grid at 10-20 km resolution. Our current modelling and simulation techniques are inadequate for representing turbulence at this truncated resolution, and have yet to approach a comprehensive development for parameterizing the truncated physics across a wide range of scales; note, there is a factor of about 100 million between the scale at which energy is added and that at which turbulent mixing occurs. One way to move forward is through the development of turbulent models for the atmospheric boundary layer under various conditions, and to utilize the gathered detailed knowledge on turbulence to parameterize unresolved physics of mesoscale meteorological models. My research program encompasses fundamental developments on a wavelet based multiscale methodology and its application to explain the influence of turbulence and other small scale meteorological variability on forecasting meso-scale phenomena. The proposed research thus aims to develop and exploit a robust, reliable, and computationally efficient new wavelet based dynamical core for a non-hydrostatic multiscale meteorological methodology over complex terrains. In contrast to contemporary atmospheric models, the proposed mesoscale modelling approach will capture the significant proportion of the flow with a multi-scale wavelet basis, and the residual motion will be parameterized. A multiscale parameterization technique will be developed for a two-way nesting of energetic eddies within a mesoscale model, employing the second generation wavelet transform. This new wavelet method will explore both the sub-mesoscale and sub-LES scale phenomena, which is an important aspect of the proposed development. In the field of atmospheric modelling, a faithful parameterization of boundary layer eddies or other convective phenomena on a mesoscale grid of 10-20 km resolution is one of the most challenging and demanding topics. Similarly, meteorological data may be available on the mesoscale resolution from a satellite; however, incorporating the observed meteorological feedback into the prediction of sub-mesoscale (e.g. a tornado) or micro-scale (e.g. boundary layer eddies) phenomena is necessary and also challenging. The success of the proposed wavelet based multiscale methodology for dynamically nesting turbulence and other small scale meteorological variability in a mesoscale model will advance state-of-the-art contemporary atmospheric models, thereby paving a new avenue toward the prediction of the mesoscale and the microscale weather phenomena.

我们生活和呼吸在大气层的底部，大气层中既有气体，也有尘埃和烟雾的微小颗粒。我们的健康和环境受到极其动荡的大气层非常复杂的机制的影响。在阳光明媚的日子里，陆地升温的速度比海洋快，海洋将冷空气从海洋带到陆地。通过这个过程，能量通过增强的湍流混合进行交换。飓风（和其他自然灾害）的湍流动能对生命及其环境造成损害。许多环境问题--比如为什么飓风会发展，为什么全球气温会上升，为什么极地冰层融化的速度会加快，或者为什么海平面会上升--都很大程度上依赖于对大气中湍流混合和传输的全面理解。例如，为了预测二氧化碳或其他污染物等重要成分的未来分布，人们需要知道它们的源和汇，以及这些污染物如何在湍流大气中混合。 然而，当大气模型（无论是空气污染还是天气预报）采用10-20 km分辨率的典型中尺度网格时，湍流混合机制受到严重影响。我们目前的建模和模拟技术不足以在这种截断分辨率下表示湍流，并且还没有在广泛的尺度范围内对截断物理进行参数化的全面发展;注意，在能量增加的尺度和湍流混合发生的尺度之间存在大约1亿的因子。前进的一种方式是通过发展各种条件下大气边界层的湍流模型，并利用收集到的关于湍流的详细知识来参数化中尺度气象模型中未解决的物理问题。 我的研究项目包括基于小波的多尺度方法及其应用的基本发展，以解释湍流和其他小尺度气象变化对预测中尺度现象的影响。 因此，拟议的研究旨在开发和利用一个强大的，可靠的，计算效率高的新的小波为基础的动力核心的非静力多尺度气象方法在复杂的地形。与当代大气模型相比，建议的中尺度建模方法将捕获的流量与多尺度小波基础的显着比例，和剩余的运动将被参数化。本文将采用第二代小波变换，发展一种多尺度参数化技术，用于中尺度模式中能量涡旋的双向嵌套。这种新的小波方法将探索亚中尺度和亚LES尺度的现象，这是一个重要的方面，拟议的发展。 在大气建模领域，在10-20公里分辨率的中尺度网格上对边界层涡旋或其他对流现象进行忠实的参数化是最具挑战性和要求最高的课题之一。同样，卫星可以提供中尺度分辨率的气象数据;然而，将观测到的气象反馈纳入亚中尺度（例如龙卷风）或微尺度（例如边界层涡旋）现象的预测中是必要的，也是具有挑战性的。在中尺度模式中动态嵌套湍流和其他小尺度气象变率的基于小波的多尺度方法的成功，将推进最先进的当代大气模式，从而为中尺度和微尺度天气现象的预测铺平了新的途径。