Collaborative Research: Subgrid-scale Models for Large-eddy Simulation of Cloud Formation and Evolution

合作研究：云形成和演化大涡模拟的亚网格尺度模型

• 批准号: 1503860
• 负责人: Fotini Chow
• 金额: $ 40万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1503860&HistoricalAwards=false
• 关键词: Collaborative; Research; Subgrid; scale; Models; Collaborative; Research; Subgrid; scale; Models

Clouds are important to the earth's energy balance and a regulator of both climate and weather. The estimation of cloud formation, cloud cover, precipitation, etc., for both climate and weather prediction is accomplished with numerical simulations. Despite computational advances and for the foreseeable future, simulations of the real atmosphere for weather and climate prediction will feature results in which a significant fraction of the energy, heat and vapor fluxes, etc., will not be resolved and must be modeled. This project's goal is to develop, validate and make available to the community improved and more physically realistic turbulence models for the subgrid- and subfilter-scales in moist-atmosphere large-eddy simulation (LES) simulation codes, in collaboration between UC Berkeley, Stanford University, and NCAR scientists. Two new subgrid-scale (SGS) model sets (one using dynamic methods and one using a linear, algebraic model) will be developed for all elements of a cloud simulation, i.e., momentum, heat, water's liquid and vapor phases, graupel, the prognostic equations in the microphysics, etc. These SGS closures have improved mean fields and higher-order statistics in previous boundary layer simulations, but have yet to be applied to clouds. The SGS models will be constructed within the explicit filtering and reconstruction framework, which reduces numerical errors and provides a more physical representation of turbulent stresses. Intellectual Merit: The project aims to provide significantly improved models for the unresolved fields (including momentum, heat, water vapor, liquid, and other scalar fluxes), to yield deeper understanding of the physical processes being modeled, and to validate those models in test case simulations of realistic clouds. The other goal is to clarify the validity of using such subroutines in the Terra Incognita [TI] / Gray Zone of atmospheric simulations, i.e., the zone of grid resolution in which flow features such as convective thermals are partly resolved and partly sub-grid. This zone is becoming an ever greater challenge as numerical simulations cover more and more length scales. The role of SGS closures in the Terra Incognita is still largely unexplored, particularly in the case of clouds. Building upon prior research on SGS modeling, the research will (1) create new SGS equation sets for the moist atmosphere, (2) apply them in a priori tests and then (3) carry out simulations of field-scale situations covering clear convective boundary layers, trade-wind cumulus with and without precipitation, shallow cumulus, and deep convection. These simulations will be set up to assess the performance of the equation sets for their accuracy and efficiency and to assess model performance in the TI (or Gray Zone). Broader Impacts: There are two domains of broader impacts. First, successful completion of this work will yield improved predictions of cloud generation and evolution in the simulations. Because the code on which the work is based is widely used internationally, this will be a major benefit to the community. Given that accurate prediction of cloud formation and behavior is a critical element in weather and climate prediction and, in particular, rainfall, the work has the potential for significant impact across the weather domain. Previous experience suggests that the new SGS models will be easily transported to other codes as well, which will further broaden the impact of this work. Second, this project aims through its collaboration with NCAR to give broad and high quality training to a postdoctoral researcher, who will benefit from the exposure to the modeling expertise at Berkeley and Stanford and the modeling and microphysics expertise at NCAR. In addition, a Stanford undergraduate student will work on the project to complement the work of the postdoctoral researcher.

云对地球的能量平衡很重要，也是气候和天气的调节者。通过数值模拟来完成云形成，云层，降水等的估计。尽管计算进步和可预见的未来，但对天气和气候预测的真实大气的模拟将以结果为特征，其中大部分能量，热量和蒸气通量等将无法解析，必须对其进行建模。该项目的目标是在潮湿的大气大码大型模拟（LES）模拟代码中为社区改进，对社区改善，更现实的湍流模型，并在UC Berkeley，Stanford University，Stanford University和NCAR科学家之间进行协作。将针对云模拟的所有元素，即动量，热量，水的液体和蒸气阶段，graupel，graupel，graupel，Microphyssic to Croments to Crounder-eardifure and Execters nose difure and Execters novers nosedifure and Enderifuts，将开发两个新的亚网格尺度（SGS）模型集（一个使用动态方法，一种使用线性，代数模型）。应用于云。 SGS模型将在显式过滤和重建框架中构建，从而减少数值错误并提供更物理的湍流应力表示。智力优点：该项目旨在为未解决的领域（包括动量，热，水蒸气，液体和其他标量通量）提供显着改进的模型，以对正在建模的物理过程进行更深入的了解，并在现实云的测试案例模拟中验证这些模型。另一个目标是阐明在Terra Incognita [Ti] /大气模拟的灰色区域中使用此类子例程的有效性，即网格分辨率区域，在该区域中，在该区域中，诸如对流热诸如对流热的流动特征得到部分解决并部分解决。随着数值模拟越来越多的长度尺度，该区域正变得越来越大。 SGS封闭在Terra隐身中的作用仍未得到探索，尤其是在云的情况下。在先前对SGS建模的研究的基础上，研究将（1）为潮湿的气氛创建新的SGS方程组，（2）将它们应用于先验测试中，然后（3）进行现场尺度的模拟，涵盖了清晰的对流边界层，既有交易的cumulus cumulus，and and shallow cumulus and shallow cumulus and Deepection and shallow cornection and shallow cornection and shallow cornection and thecection cumulus。这些模拟将设置为评估方程组的精度和效率的性能，并评估Ti（或灰色区域）中的模型性能。更广泛的影响：有两个更广泛影响的领域。首先，这项工作的成功完成将改善模拟中云产生和演变的预测。因为该工作所基于的代码在国际上被广泛使用，所以这将是社区的主要好处。鉴于对云形成和行为的准确预测是天气和气候预测中的关键要素，尤其是降雨，这项工作有可能在整个天气领域产生重大影响。以前的经验表明，新的SGS模型也将很容易运输到其他代码，这将进一步扩大这项工作的影响。其次，该项目的目标是通过与NCAR的合作为博士后研究员提供广泛而高质量的培训，他们将受益于伯克利和斯坦福大学的建模专业知识以及NCAR的建模和微物理学专业知识。此外，斯坦福大学的本科生将努力研究该项目，以补充博士后研究员的工作。