Stochastic and deterministic kinetic energy backscatter parameterizations for simulation of the two-dimensional turbulence

被引:7
作者
Perezhogin, Pavel A. [1 ]
Glazunov, Andrey V. [1 ]
Gritsun, Andrey S. [1 ]
机构
[1] Russian Acad Sci, Marchuk Inst Numer Math, Moscow 119333, Russia
基金
俄罗斯基础研究基金会;
关键词
Two-dimensional turbulence; stochastic parameterization; kinetic energy backscatter; subgrid scale modelling; scale-similarity; EDDY VISCOSITY; EQUILIBRIUM STATES; MODEL; CLIMATE; ORDER; SCHEMES; DISSIPATION; CIRCULATION; DYNAMICS;
D O I
10.1515/rnam-2019-0017
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The problem of modelling 2D isotropic turbulence in a periodic rectangular domain excited by the forcing pattern of prescribed spatial scale is considered. This setting could be viewed as the simplest analogue of the large scale quasi-2D circulation of the ocean and the atmosphere. Since the direct numerical simulation (DNS) of this problem is usually not possible due to the high computational costs we explore several possibilities to construct coarse approximation models and corresponding subgrid closures (deterministic or stochastic). The necessity of subgrid closures is especially important when the forcing scale is close to the cutoff scale of the coarse model that leads to the significant weakening of the inverse energy cascade and large scale component of the system dynamics. The construction of closures is based on the a priori analysis of the DNS solution and takes into account the form of a spatial approximation scheme used in a particular coarse model. We show that the statistics of a coarse model could be significantly improved provided a proper combination of deterministic and stochastic closures is used. As a result we are able to restore the shape of the energy spectra of the model. In addition the lagged auto correlations of the model solution as well as its sensitivity to external perturbations fit the characteristics of the DNS model much better.
引用
收藏
页码:197 / 213
页数:17
相关论文
共 70 条
[1]  
Achatz U, 1999, J ATMOS SCI, V56, P3140, DOI 10.1175/1520-0469(1999)056<3140:ATLMWE>2.0.CO
[2]  
2
[3]   Fluctuation-Dissipation Supplemented by Nonlinearity: A Climate-Dependent Subgrid-Scale Parameterization in Low-Order Climate Models [J].
Achatz, Ulrich ;
Loebl, Ulrike ;
Dolaptchiev, Stamen I. ;
Gritsun, Andrey .
JOURNAL OF THE ATMOSPHERIC SCIENCES, 2013, 70 (06) :1833-1846
[4]   Random forcing of three-dimensional homogeneous turbulence [J].
Alvelius, K .
PHYSICS OF FLUIDS, 1999, 11 (07) :1880-1889
[5]  
[Anonymous], 2 GFDL OC GROUP
[6]  
[Anonymous], 1966, Proceedings of the IBM Scientific Computing Symposium on Environmental Sciences, DOI DOI 10.5065/D62R3PMM
[7]  
[Anonymous], 2001, STAT ANAL CLIMATE RE
[8]  
Arakawa A., 1966, J. Comput. Phys., V1, P119, DOI [DOI 10.1016/0021-9991(66)90015-5, 10.1016/0021-9991(66)90015-5]
[9]  
Arakawa A., 1977, METHODS COMPUTATIONA, V17, P173, DOI [DOI 10.1016/B978-0-12-460817-7.50009-4, https://doi.org/10.1016/B978-0-12-460817-7.50009-4]
[10]  
BARDINA J., 1980, 801357 AIAA