Multiscale wavelet modelling of turbulent flows in the atmosphere and oceans

大气和海洋湍流的多尺度小波建模

• 批准号: 217003-2013
• 负责人: Kevlahan, Nicholas
• 金额: $ 1.38万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635604
• 关键词: Multiscale; wavelet; modelling; turbulent; flows

Numerical weather forecasting helps Canadians manage their lives and businesses day-to-day, and climate modelling helps Canada plan for the future. The effects of extreme weather events, such as storms, floods and droughts, can be mitigated, but only if they are accurately predicted far enough in advance. Operational models use static computational grids, which are not able to adapt to resolve rapidly developing storms or coarsen where less accuracy is needed. This means that computational resources are not used efficiently and that the resulting error is not uniform in space and time. It is also difficult to increase resolution where more accuracy is needed, for example over densely populated areas, or over environmentally sensitive habitats. The goal of this proposed research is to develop an experimental atmosphere and ocean model that will use innovative wavelet techniques to dynamically modify the grid resolution to maintain the desired level of accuracy, or to make optimal use of the available computational resources. The resolution could also be adapted statically to improve predictions in areas of special interest. The first stage of this project is to develop a computer code that adaptively solves the rotating shallow water equations on the sphere. The second stage is to extend the two-dimensional shallow water model to a three-dimensional multilayer hydrostatic model. At this point the computer code will form a so-called "dynamical core" on which more physical effects (e.g. radiation, clouds, the effect of topography, vegetation) can be added to build a true climate model. The final stage of this project will be to extend the multiscale computational model to a multiscale multi-physics model to account for important subgrid scale physical effects, such as cloud formation. This proposal is part of an international effort to develop the next generation of weather and climate models that will use dynamic adaptivity and multiscale modelling to improve computational efficiency and prediction accuracy. Canada has been a world leader in numerical weather prediction and climate modelling, and the knowledge gained in this research project will keep Canada at the forefront as new models are developed to deal with emerging challenges.

数值天气预报帮助加拿大人管理他们的日常生活和业务，气候模型帮助加拿大规划未来。风暴、洪水和干旱等极端天气事件的影响是可以减轻的，但前提是必须提前足够准确地预测它们。操作模型使用静态计算网格，无法适应快速发展的风暴或不太需要精度的粗糙天气。这意味着计算资源没有得到有效的利用，并且产生的误差在空间和时间上不均匀。在需要更高精度的地方，例如人口稠密地区或环境敏感栖息地，也很难提高分辨率。本研究的目标是开发一个实验大气和海洋模型，该模型将使用创新的小波技术来动态修改网格分辨率，以保持所需的精度水平，或使可用的计算资源得到最佳利用。该决议还可以静态地进行调整，以改进特别感兴趣领域的预测。该项目的第一阶段是开发一种自适应求解球体上旋转浅水方程的计算机代码。第二阶段是将二维浅水模型扩展为三维多层流体静力模型。在这一点上，计算机代码将形成一个所谓的“动力核心”，在此基础上可以添加更多的物理效应（如辐射、云层、地形、植被的影响）来建立一个真正的气候模型。该项目的最后阶段将是将多尺度计算模型扩展到多尺度多物理模型，以考虑重要的亚网格尺度物理效应，如云的形成。这一建议是开发下一代天气和气候模式的国际努力的一部分，这些模式将使用动态适应性和多尺度建模来提高计算效率和预测精度。加拿大在数值天气预报和气候模型方面一直处于世界领先地位，在这个研究项目中获得的知识将使加拿大在开发新模型以应对新出现的挑战时保持领先地位。