Collaborative Research: Frameworks: Community-Based Weather and Climate Simulation With a Global Storm-Resolving Model
合作研究:框架:基于社区的天气和气候模拟以及全球风暴解决模型
基本信息
- 批准号:2004973
- 负责人:
- 金额:$ 199.33万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-08-01 至 2025-07-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Global Earth System Models (ESMs) use mathematical equations to simulate both weather and climate. ESMs include the dynamics of the atmosphere, oceans, land surface, ice, and vegetation. They can be used to make predictions of use to the public and policymakers. Today’s ESMs use coarse grids with cells about 100 km wide. Important weather systems like thunderstorms are too small to be simulated with such grids. One way to improve ESMs is to use finer grids that can directly simulate thunderstorms, but such models can only be run on very powerful computers. This project, called EarthWorks, will create an ESM capable of resolving storms by taking advantage of recent developments in high performance computing. EarthWorks will also use artificial intelligence to improve and speed up the model, and state-of-the-art methods to limit the amount of data produced as the model runs. The EarthWorks ESM will be built by spinning off and modifying a copy of the most recent version of the widely used Community Earth System Model. The modified model will represent the atmosphere, the oceans, and the land surface on a single very high-resolution grid, with grid cells about 4 km wide. It will have improved forecast skill, and produce more realistic simulations of past, present, and future climates. The project will make the model and its output openly available for use by all scientists.The open-source Community Earth System Model (CESM) is both developed and applied to scientific problems by a large community of researchers. It is critical infrastructure for the U.S. climate research community. In the atmosphere and ocean components of the CESM, the adiabatic terms of the partial differential equations that express conservation of mass, momentum, and thermodynamic energy are solved numerically using what is called a dynamical core. Atmosphere and ocean models also include parametric representations, called parameterizations, that are designed to include the effects of storm and cloud processes that occur on scales too small to be represented on the model's grid. Despite decades of work by many scientists, today's parameterizations are still problematic and limit the utility of ESMs for many applications of societal relevance. Fortunately, recent advances in computer power have made it possible to parameterize less, by using grid spacings on the order of a few kilometers over the entire globe. These "global storm-resolving models" (GSRMs) can only be run on today's fastest computers. GSRMs are under very active development at a dozen or so modeling centers around the world. Unfortunately, however, the current formulation of the CESM prevents it from being run as a GSRM. This project, called EarthWorks, will create a new, openly available GSRM by spinning off and intensively modifying a copy of the CESM. To accomplish this goal, the researchers will use recently developed and closely related dynamical cores for the atmosphere and ocean. All components of the model will use the same very high-resolution grid. This high resolution will make it possible to eliminate the particularly troublesome parameterization of deep cumulus convection (i.e., thunderstorms), and thereby reduce systematic biases that plague current ESMs. Earthworks will exploit the pre-exascale and exascale technologies now being brought to market by high performance computing vendors. The new exascale ESM will run the most computationally intensive components on powerful graphics processor units (GPUs), and exploit node-level task parallelism to execute the rest of the model asynchronously. The component model codes are close to completion and are currently being tested on GPUs. EarthWorks will use a simplified component-coupling approach, incorporate machine learning where feasible, and leverage lossy compression techniques and parallel I/O tools to deal with the enormous data volumes that will be generated as the model runs. The completed model will be simple, powerful, and well documented. The project will apply it to pressing scientific problems in both numerical weather prediction and climate simulation. The model and its input datasets will be made openly available to the broad research community, via GitHub.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
全球地球系统模式(esm)使用数学方程来模拟天气和气候。esm包括大气、海洋、陆地表面、冰和植被的动态。它们可以用来做出对公众和决策者有用的预测。今天的esm使用大约100公里宽的粗糙网格。像雷暴这样重要的天气系统太小了,无法用这样的网格来模拟。改善esm的一种方法是使用更精细的网格,可以直接模拟雷暴,但这样的模型只能在非常强大的计算机上运行。这个名为EarthWorks的项目将利用高性能计算的最新发展,创造一个能够解决风暴的ESM。EarthWorks还将使用人工智能来改进和加速模型,并使用最先进的方法来限制模型运行时产生的数据量。EarthWorks ESM将通过拆分和修改广泛使用的社区地球系统模型的最新版本来构建。修改后的模型将在一个非常高分辨率的网格上表示大气、海洋和陆地表面,网格单元宽约4公里。它将提高预报技能,对过去、现在和未来的气候进行更真实的模拟。该项目将使该模型及其产出公开供所有科学家使用。开源社区地球系统模型(CESM)是由大量研究人员开发并应用于科学问题的。它是美国气候研究界的关键基础设施。在CESM的大气和海洋分量中,表示质量、动量和热力学能量守恒的偏微分方程的绝热项使用所谓的动力核进行数值求解。大气和海洋模型还包括参数化表示,称为参数化,旨在包括风暴和云过程的影响,这些影响发生在太小的尺度上,无法在模型的网格上表示。尽管许多科学家进行了数十年的工作,但今天的参数化仍然存在问题,并且限制了esm在许多与社会相关的应用中的效用。幸运的是,最近计算机能力的进步使我们可以更少地参数化,通过在整个地球上使用大约几公里的网格间隔。这些“全球风暴解析模型”(GSRMs)只能在当今最快的计算机上运行。全球大约有十几个建模中心在积极开发gsrm。然而,不幸的是,CESM目前的形式阻止了它作为GSRM运行。这个名为EarthWorks的项目将通过剥离和大量修改CESM的副本,创建一个新的、公开可用的GSRM。为了实现这一目标,研究人员将使用最近开发的与大气和海洋密切相关的动力核心。模型的所有组件将使用相同的高分辨率网格。这种高分辨率将有可能消除特别麻烦的深积云对流(即雷暴)参数化,从而减少困扰当前esm的系统偏差。Earthworks将利用目前由高性能计算供应商推向市场的pre-exascale和exascale技术。新的exascale ESM将在强大的图形处理器单元(gpu)上运行最密集的计算组件,并利用节点级任务并行性异步执行模型的其余部分。组件模型代码已接近完成,目前正在gpu上进行测试。EarthWorks将使用简化的组件耦合方法,在可行的情况下结合机器学习,并利用有损压缩技术和并行I/O工具来处理模型运行时将生成的巨大数据量。完成的模型将是简单的、强大的和文档完备的。该项目将应用于数值天气预报和气候模拟的紧迫科学问题。该模型及其输入数据集将通过GitHub公开提供给广泛的研究社区。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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William Skamarock其他文献
Simulations With EarthWorks
使用 EarthWorks 进行模拟
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
David Randall;James Hurrell;Donald Dazlich;Lantao Sun;William Skamarock;Andrew Gettelman;Thomas Hauser;Sheri Mickelson;Mariana Vertenstein;Richard Loft - 通讯作者:
Richard Loft
William Skamarock的其他文献
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{{ truncateString('William Skamarock', 18)}}的其他基金
Collaborative Research: CMG: Adaptive High-Order Methods for Nonhydrostatic Numerical Weather Prediction
合作研究:CMG:非静水数值天气预报的自适应高阶方法
- 批准号:
0530845 - 财政年份:2005
- 资助金额:
$ 199.33万 - 项目类别:
Standard Grant
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