Toward and Improved Understanding and Parameterization of the Stable Atomospheric Boundary Layer

对稳定大气边界层的理解和参数化的改进

• 批准号: 1500900
• 负责人: Zbigniew Sorbjan
• 金额: $ 37.5万
• 依托单位: Marquette University
• 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: 2015-09-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1500900&HistoricalAwards=false
• 关键词: Toward; Improved; Understanding; Parameterization; Stable

This study will use a database of very high-resolution model simulations of the lowest layers of the atmosphere to compare with known output from various models of the turbulent layer near the earth's surface. The goal of this research is to improve the way in which air flow is modeled in the very lowest layers of the atmosphere, near the ground. This study will add valuable insight into the success of various numerical prediction schemes and may ultimately lead to improvements in these schemes used in weather models. One undergraduate student will participate in this study and gain valuable research experience. This study will use a large-eddy simulation (LES) dataset, consisting of two hours of 0.39m resolution data, archived at one-minute intervals. The LES data are free of non-turbulent structures typically present in the real boundary layer. The proposed LES uses a two-part sub-grid scale model to span between LES and Reynolds-average Navier-Stokes (RANS) regimes. New insights will be gained through the development of improved turbulence closure schemes, from gradient-based scaling, for single-column models.

这项研究将使用一个非常高分辨率的大气最低层模型模拟数据库，与地球表面附近湍流层的各种模型的已知输出进行比较。这项研究的目标是改进大气最低层、靠近地面的空气流动的建模方式。这项研究将为各种数值预报方案的成功提供有价值的见解，并最终可能导致天气模式中使用的这些方案的改进。一名本科生将参加这项研究，并获得宝贵的研究经验。这项研究将使用大涡模拟(LES)数据集，由两个小时的0.39m分辨率数据组成，每隔一分钟存档一次。大涡模拟数据没有真实边界层中通常存在的非湍流结构。拟议的大涡模拟使用一个两部分的次网格尺度模式来跨越大涡模拟和雷诺平均纳维-斯托克斯(RANS)模式。通过改进湍流闭合方案的发展，将获得新的见解，从基于梯度的尺度，用于单柱模型。