Quantifying the impact of vertical resolution on the representation of marine boundary layer physics for global-scale models

IF 2.8 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
M. Smalley, M. Lebsock, J. Teixeira
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引用次数: 0

Abstract

While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a Single Column Model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of a Single Column Model (SCM) against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rain water from Large Eddy Simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the co-variability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine-scales often used in parameterization development and large eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ~5 when vertical grid spacing is improved from 120 m to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement.
量化垂直分辨率对全球尺度模型海洋边界层物理表示的影响
虽然近年来GCM的水平分辨率得到了大部分的尺度改进,但充分的证据表明,模型的垂直分辨率对其准确模拟海洋边界层物理的能力有很大的控制作用。在这里,我们表明,无论参数调整如何,当垂直分辨率提高时,单柱模型模拟亚热带海洋边界层的能力都会提高。我们引入了一种新的目标调整技术,根据大涡模拟(LES)中的温度和湿度及其湍流通量、水平风、云水和雨水的分布来优化单柱模型(SCM)的参数。我们使用这种方法来确定模拟海洋层积云和浅积云的最佳参数。新的调整方法利用了一个客观的性能指标,该指标考虑了LES输出的不确定性,包括模型变量之间的协变性。对于不同的垂直网格间距和时间步长值,从当前全局模型中常用的粗尺度(120m,180s)到参数化开发和大涡模拟中常用的细尺度(10m,15s),都可以独立进行优化。当垂直网格间距从120m提高到10m时,SCM和LES之间的不确定性加权分歧减少了约5倍,时间步长的减少是次要的。模型性能显示在20米的垂直网格间距处收敛,进一步细化到10米后几乎没有进一步改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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