CMG: Adaptive Mesh Refinement for Vortices in Climate and Weather-Forecasting: Comparing and Blending Finite Volume Methods with Vortex/Radial Basis Function Algorithms

CMG：气候和天气预报中涡旋的自适应网格细化：有限体积方法与涡旋/径向基函数算法的比较和混合

• 批准号: 0723440
• 负责人: John Boyd
• 金额: $ 42.39万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2010-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0723440&HistoricalAwards=false
• 关键词: CMG; Adaptive; Mesh; Refinement; Vortices

A collaborating team of mathematicians, computational algorithm experts and atmospheric dynamacists have prioritized a series of challenging and largely unresolved questions in the topic area of adaptive mesh refinement of vortex dominated flows encountered in numerical weather prediction and climate modeling. A common underlying theme being adopted seeks the improvement of adaptive, multi-scale methods to better resolve the finer features of intense vortices which dominate these kinds of geophysical flows. This semi-structured feature-based goal is different from simple nesting of higher resolution gridding of vortex cores. Suggested approaches which will be explored to answer these questions include comparing and blending well-established numerical algorithms, such as finite volume and vortex blob methods, along with radial basis function schemes, tree codes and less well explored hybridizations of these. Resolving fine structure in the representation of vortices is needed to strengthen predictive skill and long-time behavior in fields such as climate modeling and weather forecasting. Development of adaptive, multi-scale-resolving numerical schemes to treat vortex dominated flows are also expected to have wider application to areas outside of geophysics.

一个由数学家、计算算法专家和大气动态学家组成的合作小组优先考虑了数值天气预报和气候模拟中遇到的涡旋主导流动的自适应网格细化这一主题领域中一系列具有挑战性且基本上尚未解决的问题。正在通过的一个共同基本主题是寻求改进自适应、多尺度方法，以更好地解决主导这类地球物理流动的强烈涡旋的更精细特征。这种基于特征的半结构化目标不同于简单地嵌套更高分辨率的涡核网格。将探索的解决这些问题的建议方法包括比较和混合成熟的数值算法，如有限体积法和涡团方法，以及径向基函数格式、树编码和较少探索的混合算法。在气候模拟和天气预报等领域，需要解决涡旋表示的精细结构，以加强预测技能和长期行为。开发自适应、多尺度分辨率的数值方案来处理涡旋主导的流动也有望在地球物理以外的领域得到更广泛的应用。