Do the large-eddy simulations yield deeper atmospheric boundary layers in comparison to the RANS model simulations?

被引:1
作者
Roshny, S. [1 ,2 ]
Subrahamanyam, D. Bala [1 ]
机构
[1] Govt India, Indian Space Res Org, Space Phys Lab, Vikram Sarabhai Space Ctr,Dept Space, Thiruvananthapuram 695022, Kerala, India
[2] Cochin Univ Sci & Technol, Cochin 682022, Kerala, India
关键词
Atmospheric boundary layer; Convection; COSMO model; LES; PALM model; RANS; Tropical cyclone; Turbulence; NUMERICAL WEATHER PREDICTION; BREEZE CIRCULATION; ARABIAN SEA; PALM; TURBULENCE; MESOSCALE; LES; STORAGE; THUMBA; FLOWS;
D O I
10.1016/j.jastp.2022.105954
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In this article, we address the behaviour of a RANS and an LES model in the simulation of the diurnally evolving atmospheric boundary layer (ABL) over Thiruvananthapuram, a coastal station in India, for contrasting sky conditions during the passage of a tropical cyclone Ockhi. Based on the prevailing meteorological conditions over this experimental site, 5 December 2017 and 1 December 2017 are chosen as representative days for the clear-sky and cloudy conditions, respectively. The Consortium for small-scale modelling (COSMO), a regional numerical weather prediction model is chosen to represent the RANS technique, and a mesoscale-to-LES nested configuration of the Parallelized LES Model (PALM) is taken to represent the LES technique. The LES experiments are performed at 30 m and 100 m grid spacings. The main objective of these experiments is to assess the individual model biases of nested LES in conjunction with a RANS model with a special emphasis on the diurnal evolution of ABL heights. The ABL heights inferred from the LES experiments were found to be deeper than that in the RANS experiments. The decay of ABL during the evening hours was rapid in the LES experiments, whereas it was more smooth in the RANS experiment. The study also evaluates the sensitivity of the PALM to the grid spacing in a mesoscale-to-LES nesting configuration.
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页数:16
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