Towards a new generation of adaptive climate and weather models

迈向新一代自适应气候和天气模型

• 批准号: RGPIN-2018-05586
• 负责人: Kevlahan, Nicholas
• 金额: $ 3.35万
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=759015
• 关键词: Towards; new; generation; adaptive; climate

Wavelet multiresolution analysis is one of the most significant mathematical breakthroughs of the last 30 years. The impact of wavelet methods in both pure and applied mathematics was recognized when Yves Meyer was awarded the 2017 Abel Prize for “his pivotal role in the development of the mathematical theory of wavelets.”Wavelet methods are now common in analysis, statistics and approximation theory. This proposal applies the multiscale formalism of wavelet analysis to adaptively solve nonlinear partial differential equations (PDEs) on the sphere. In particular, I will use the mathematical tools I develop to build a full climate model. This innovative climate model will be applied to investigate open problems in the physics of atmospheres and oceans. The research program will impact both numerical analysis (adaptive numerical methods for PDEs in spherical topology) and climate modelling.Weather and climate models use static computational grids which are unable to adapt to resolve rapidly developing storms or coarsen where less accuracy is needed. This means that computational resources are used inefficiently and that the resulting errors are not uniformly bounded in space and time. It is also difficult to increase resolution where more accuracy is needed, for example over densely populated areas. The first objective extends our adaptive 2D shallow water model to a 3D multilayer hydrostatic model. At this point it will form a so-called "dynamical core" on which physical effects (e.g. radiation, clouds, the effect of topography, vegetation) can be added to build a true climate model. This will be the first dynamically adaptive dynamical core for both atmospheres and oceans.The second objective develops a scale aware physics model to account for subgrid scale physical effects, such as cloud formation and solar radiation transfer. These processes occur on scales varying from ten thousand kilometres to submillimeter and from centuries to milliseconds. Weather models use data assimilation to optimally incorporate observations of temperature, wind etc. into the numerical simulation. The third objective is to develop new techniques in data assimilation that take advantage of the dynamic adaptive of our numerical model.I will train 11 Highly Qualified Personnel (1 post-doctoral fellow, 2 PhD students, 3 MSc students and 5 BSc students) over the five-year span of this research program.This proposal contributes to an international effort (e.g. by Environment Canada, ECMWF, NCAR, Météo France) to develop the next generation of weather and climate models. 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.

小波多分辨率分析是过去 30 年来最重大的数学突破之一，Yves Meyer 因其“在数学发展中的关键作用”而被授予 2017 年阿贝尔奖，由此认识到了小波方法在纯数学和应用数学中的影响。小波方法现在在分析、统计和逼近理论中很常见。该建议应用小波分析的多尺度形式来自适应求解非线性偏微分方程（PDE）。特别是，我将使用我开发的数学工具建立一个完整的气候模型，该模型将应用于研究大气和海洋物理学中的开放问题。球形拓扑中偏微分方程的数值方法）和气候建模。天气和气候模型使用静态计算网格，这些网格无法适应解决快速发展的风暴或在需要较低精度的情况下进行粗化，这意味着计算资源的使用效率低下，并且由此产生的结果。错误在需要更高精确度的情况下也很难提高分辨率，例如在人口稠密的区域，第一个目标将我们的自适应 2D 浅水模型扩展到 3D 多层静水模型。将形成一个所谓的“动力核心”，可以在其中添加物理效应（例如辐射、云、地形、植被的影响）以构建真正的气候模型，这将是第一个针对大气和气候的动态自适应动力核心。第二个目标是开发一个尺度感知物理模型，以解释亚网格尺度的物理效应，例如云的形成和太阳辐射传输，这些过程发生的尺度从一万公里到亚毫米，天气模型使用的数据从几个世纪到毫秒。同化以最佳地将温度、风等观测结果纳入数值模拟中。第三个目标是开发利用我们数值模型的动态自适应性的数据同化新技术。我将训练 11 高度。本研究项目为期五年的合格人员（1 名博士后研究员、2 名博士生、3 名硕士生和 5 名理学士学位生）。该提案有助于国际努力（例如加拿大环境部、ECMWF、NCAR、Météo）法国）开发下一代天气和气候模型 加拿大在数值天气预报和气候建模方面一直处于世界领先地位，在该研究项目中获得的知识将使加拿大在开发新模型来应对气候变化方面保持领先地位。新出现的挑战。