气候变化领域集成服务门户(CCPortal): Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution

CCPortal

DOI	10.1029/2018MS001446
	Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution
	Shi X.; Chow F.K.; Street R.L.; Bryan G.H.
发表日期	2019
ISSN	19422466
起始页码	818
结束页码	838
卷号	11 期号:3
英文摘要	Kilometer-scale grid spacing is increasingly being used in regional numerical weather prediction and climate simulation. This resolution range is in the terra incognita, where energetic eddies are partially resolved and turbulence parameterization is a challenge. The Smagorinsky and turbulence kinetic energy 1.5-order models are commonly used at this resolution range, but, as traditional eddy-diffusivity models, they can only represent forward-scattering turbulence (downgradient fluxes), whereas the dynamic reconstruction model (DRM), based on explicit filtering, permits countergradient fluxes. Here we perform large-eddy simulation of deep convection with 100-m horizontal grid spacing and use these results to evaluate the performance of turbulence schemes at 1-km horizontal resolution. The Smagorinsky and turbulence kinetic energy 1.5 schemes produce large-amplitude errors at 1-km resolution, due to excessively large eddy diffusivities attributable to the formulation of the squared moist Brunt-Väisälä frequency (N2m). With this formulation in cloudy regions, eddy diffusivity can be excessively increased in “unstable” regions, which produce downward (downgradient) heat flux in a conditionally unstable environment leading to destabilization and further amplification of eddy diffusivities. A more appropriate criterion based on saturation mixing ratio helps eliminate this problem. However, shallow clouds cannot be simulated well in any case at 1-km resolution with the traditional models, whereas DRM allows for countergradient heat flux for both shallow and deep convection and predicts the distribution of clouds and fluxes satisfactorily. This is because DRM employs an eddy diffusivity model that is dynamically adjusted and a reconstruction approach that allows countergradient fluxes. © 2019. The Authors.
英文关键词	cloud; cloud-resolving models; deep convection; large-eddy simulation; parameterization; turbulence
语种	英语
scopus关键词	Clouds; Diffusion; Forward scattering; Kinetic energy; Kinetics; Large eddy simulation; Natural convection; Parameterization; Turbulence; Weather forecasting; Cloud resolving model; Deep convection; Dynamic reconstruction models; Eddy-diffusivity models; Horizontal grid spacing; Regional numerical weather predictions; Turbulence kinetic energy; Turbulence parameterization; Heat flux; atmospheric convection; climate modeling; cloud condensation nucleus; heat flux; laminar-turbulent transition; large eddy simulation; parameterization; simulation; turbulence; weather forecasting
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156938
作者单位	Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong; Department of Civil and Environmental Engineering, University of California, Berkeley, CA, United States; Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States; National Center for Atmospheric Research, Boulder, CO, United States
推荐引用方式 GB/T 7714	Shi X.,Chow F.K.,Street R.L.,et al. Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution[J],2019,11(3).
APA	Shi X.,Chow F.K.,Street R.L.,&Bryan G.H..(2019).Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution.Journal of Advances in Modeling Earth Systems,11(3).
MLA	Shi X.,et al."Key Elements of Turbulence Closures for Simulating Deep Convection at Kilometer-Scale Resolution".Journal of Advances in Modeling Earth Systems 11.3(2019).