On the Sensitivity of Large Eddy Simulations of the Atmospheric Boundary Layer Coupled with Realistic Large Scale Dynamics

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
P. Giani, Paola Crippa
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Abstract

We present a new ensemble of 36 numerical experiments aimed at comprehensively gauging the sensitivity of nested Large Eddy Simulations (LES) driven by large scale dynamics. Specifically, we explore 36 multiscale configurations of the Weather Research and Forecasting (WRF) model to simulate the boundary layer flow over the complex topography at the Perdigão field site, with five nested domains discretized at horizontal resolutions ranging from 11.25 kilometers to 30 meters. Each ensemble member has a unique combination of the following input factors, (i) large-scale initial and boundary conditions, (ii) subgrid turbulence modeling in the gray zone of turbulence, (iii) subgrid-scale (SGS) models in LES simulations and (iv) topography and land cover datasets. We probe their relative importance for LES calculations of velocity, temperature and moisture fields. Variance decomposition analysis unravels large sensitivities to topography and land use datasets and very weak sensitivity to the LES SGS model. Discrepancies within ensemble members can be as large as 2.5 m s−1 for the time-averaged near-surface wind speed on the ridge, and as large as 10 m s−1 without time averaging. At specific time points, a large fraction of this sensitivity can be explained by the different turbulence models in the gray zone domains. We implement a horizontal momentum and moisture budget routine in WRF to further elucidate the mechanisms behind the observed sensitivity, paving the way for an increased understanding of the tangible effects of the gray zone of turbulence problem.
论大气边界层大涡模拟与现实大尺度动力学耦合的敏感性
我们展示了由 36 项数值实验组成的新组合,旨在全面衡量由大尺度动力学驱动的嵌套大涡流模拟(LES)的敏感性。具体来说,我们探索了气象研究和预报(WRF)模式的 36 种多尺度配置,以模拟佩迪冈野外复杂地形上的边界层流动,其中五个嵌套域的水平分辨率从 11.25 公里到 30 米不等。每个集合成员都有以下输入因素的独特组合:(i) 大尺度初始条件和边界条件;(ii) 湍流灰色区域的子网格湍流建模;(iii) LES 模拟中的子网格尺度(SGS)模型;(iv) 地形和土地覆盖数据集。我们探究了它们对 LES 速度场、温度场和湿度场计算的相对重要性。方差分解分析揭示了对地形和土地利用数据集的巨大敏感性,以及对 LES SGS 模式的极弱敏感性。对于山脊上的时间平均近地面风速而言,集合成员内部的差异可高达 2.5 m s-1,而在没有时间平均的情况下,差异可高达 10 m s-1。在特定的时间点,这种敏感性的很大一部分可以用灰区域的不同湍流模型来解释。我们在 WRF 中实施了水平动量和水分预算程序,以进一步阐明观测到的敏感性背后的机制,为进一步了解湍流灰带问题的实际影响铺平道路。
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来源期刊
Monthly Weather Review
Monthly Weather Review 地学-气象与大气科学
CiteScore
6.40
自引率
12.50%
发文量
186
审稿时长
3-6 weeks
期刊介绍: Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.
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