Accurate representation of the stable atmospheric surface layer (ASL) in numerical models has been a challenging task due to the occurrence of different physical processes such as radiative transport, turbulent mixing, and the coupling of vegetation with the atmosphere and underlying soil, as well as aspects of land use heterogeneity, etc. The Monin-Obukhov similarity theory has been widely used to parameterize surface turbulent fluxes in numerical models, which utilize similarity functions to account for the effect of atmospheric stability. Over the years, researchers have proposed various forms of similarity functions, depending on different field experiment datasets around the globe. This study incorporates some of the well-established non-linear similarity functions under stable stratification in the revised MM5 surface layer scheme in the Weather Research and Forecasting (WRF) Model version 4.2.2 and hence develop a scheme that has various functional forms of similarity functions for computing surface turbulent fluxes under stable stratification. The proposed scheme has been evaluated in simulating near-surface atmospheric variables and surface turbulent fluxes over the domain centered around the location of the Ranchi dataset site (23.412oN, 85.440oE; India) and the CASES-99 experiment site (37.38oN, 96.44oW; Kansas, USA) during the months of January 2009 and October 1999, respectively. The modified scheme is also evaluated for the three contrasting nights representative of intermittently turbulent, fully turbulent, and radiative ASL based on the CASES-99 dataset. In general, all the newly installed similarity functions are found to be consistent in predicting surface turbulent fluxes as well as near-surface atmospheric variables with respect to the default surface layer scheme and the observed data derived from the flux towers over the two domains. However, this study reveals that all the similarity functions are found to be inconsistent during the fully turbulent night while they seem comparable for the first and last nights based on the CASES-99 dataset.

中文翻译：

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WRF 建模系统中稳定大气表层的各种非线性相似函数的实现——CASES-99 数据集中三个对比夜晚的评价


在数值模型中准确表示稳定的大气表层 （ASL） 一直是一项具有挑战性的任务，因为发生了不同的物理过程，例如辐射传输、湍流混合、植被与大气和下垫土壤的耦合，以及土地利用异质性等方面。Monin-Obukhov 相似性理论已被广泛用于在数值模型中参数化表面湍流通量，该模型利用相似函数来解释大气稳定性的影响。多年来，研究人员根据全球不同的田间实验数据集提出了各种形式的相似性函数。本研究在天气研究和预报 （WRF） 模型 4.2.2 版中结合了修订后的 MM5 表层方案中一些成熟的稳定分层下的非线性相似函数，从而开发了一种具有各种函数形式的相似函数的方案，用于计算稳定分层下的表面湍流通量。在模拟以兰契数据集站点位置为中心的域上的近地表大气变量和表面湍流通量（23.412oN，85.440oE;印度）和 CASES-99 实验场（37.38oN，96.44oW;美国堪萨斯州）分别在 2009 年 1 月和 1999 年 10 月期间进行。基于 CASES-99 数据集，还针对代表间歇性湍流、完全湍流和辐射 ASL 的三个对比夜晚评估了修改后的方案。 一般来说，所有新安装的相似函数在预测表面湍流通量以及近地表大气变量方面，相对于默认表层方案和从两个域上的通量塔得出的观测数据是一致的。然而，这项研究表明，在完全湍流的夜晚，发现所有的相似性函数都是不一致的，而根据 CASES-99 数据集，它们在第一晚和最后一晚似乎具有可比性。