DOI: 10.1002/2015MS000488
Scopus记录号: 2-s2.0-84959508800
论文题名: Mean-state acceleration of cloud-resolving models and large eddy simulations
作者: Jones C ; R ; , Bretherton C ; S ; , Pritchard M ; S
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2015
卷: 7, 期: 4 起始页码: 1643
结束页码: 1660
语种: 英语
英文关键词: Atmospheric structure
; Atmospheric thermodynamics
; Boundary layers
; Climate change
; Climate models
; Clouds
; Cloud climate feedback
; Cloud resolving model
; Community atmosphere model
; Deep convective clouds
; Physical parameterization
; Spatial and temporal scale
; Superparameterization
; Time scale separation
; Large eddy simulation
; acceleration
; atmospheric modeling
; climate change
; climate modeling
; convective cloud
; large eddy simulation
; parameterization
; perturbation
; simulation
; spatiotemporal analysis
; stratocumulus
英文摘要: Large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate the evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2-16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM. © 2015. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75948
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Department of Atmospheric Sciences, University of Washington, Seattle, Washington, United States; Department of Earth System Science, University of California, Irvine, California, United States
Recommended Citation:
Jones C,R,, Bretherton C,et al. Mean-state acceleration of cloud-resolving models and large eddy simulations[J]. Journal of Advances in Modeling Earth Systems,2015-01-01,7(4)