气候变化领域集成服务门户(CCPortal): Optimization of the Eddy-Diffusivity/Mass-Flux Shallow Cumulus and Boundary-Layer Parameterization Using Surrogate Models

CCPortal

DOI	10.1029/2018MS001449
	Optimization of the Eddy-Diffusivity/Mass-Flux Shallow Cumulus and Boundary-Layer Parameterization Using Surrogate Models
	Langhans W.; Mueller J.; Collins W.D.
发表日期	2019
ISSN	19422466
起始页码	402
结束页码	416
卷号	11 期号:2
英文摘要	Physical parameterizations in global atmospheric and ocean models typically include free parameters that are not theoretically or empirically constrained. New methods are required to determine the optimal parameter combinations for such models in an objective, exhaustive, yet computationally feasible manner. Here we propose to apply computationally inexpensive radial basis function (RBF) surrogate models to minimize a “cost,” or error, function of an atmospheric model or a physical parameterization. The RBF is iteratively updated as more input-output pairs are obtained during the optimization. The approach is used to optimize the eddy-diffusivity/mass-flux boundary-layer parameterization of the convective boundary-layer in a single-column model framework. The optimization based on surrogate models is able to identify parameter combinations that reduce the error of the untuned default setting by 41%. The probability to detect a low-error solution increases rapidly especially over the first tens of single-column model evaluations. In comparison, a quadratic polynomial model only yields an error reduction of 17% since (a) high-order parameter interactions are not accounted for and (b) the construction of the polynomial is not based on an iterative sampling approach. The RBF surrogate models achieve this 17% error reduction for 40% of the polynomial model's cost. Interestingly, one of the emerging optimal settings describes a pure mass flux parameterization without eddy-diffusivity component. A second optimal solution is characterized by a plume fractional area of 20–30% and an eddy-mixing time scale of ∼700 s. ©2019. The Authors.
英文关键词	boundary-layer parameterization; convective boundary layer; EDMF; numerical optimization; radial basis functions; surrogate models
语种	英语
scopus关键词	Boundary layer flow; Boundary layers; Diffusion; Errors; Functions; Heat conduction; Image segmentation; Iterative methods; Optimization; Polynomials; Radial basis function networks; Convective boundary layers; EDMF; Numerical optimizations; Radial basis functions; Surrogate model; Parameterization; atmosphere-ocean coupling; atmospheric modeling; boundary layer; climate modeling; cumulus; model; optimization
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/156958
作者单位	Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States; Department of Earth and Planetary Science, University of California, Berkeley, CA, United States
推荐引用方式 GB/T 7714	Langhans W.,Mueller J.,Collins W.D.. Optimization of the Eddy-Diffusivity/Mass-Flux Shallow Cumulus and Boundary-Layer Parameterization Using Surrogate Models[J],2019,11(2).
APA	Langhans W.,Mueller J.,&Collins W.D..(2019).Optimization of the Eddy-Diffusivity/Mass-Flux Shallow Cumulus and Boundary-Layer Parameterization Using Surrogate Models.Journal of Advances in Modeling Earth Systems,11(2).
MLA	Langhans W.,et al."Optimization of the Eddy-Diffusivity/Mass-Flux Shallow Cumulus and Boundary-Layer Parameterization Using Surrogate Models".Journal of Advances in Modeling Earth Systems 11.2(2019).