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Title: Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations

Abstract

Coupling between mesoscale and large eddy simulation (LES) is critically important for many atmospheric model applications, from predictions of wind energy to fire propagation. The grid-nesting technique enables bridging between vastly different scales without incurring prohibitive computational costs. Yet, the transition from coarser to finer resolutions often requires a large number of grid points from inflow boundaries for the development of fine-scale turbulence features in the LES domain. Recently, the cell perturbation method (CPM) was developed to reduce the turbulence development region with high computational efficiency. Herein, we explore a new method based on the CPM that uses force perturbations in both the horizontal and vertical directions (Force Cell Perturbation Method) instead of the potential temperature perturbations in the original CPM, as an attempt to further explore the performance of the random perturbation techniques. This method is tested for a neutral and a convective atmospheric boundary layer under idealized conditions. Overall, similar performance is found between the optimal configurations of the CPM and the Force Cell Perturbation Method pointing to the robustness of this family of perturbation methods in accelerating turbulence generation in nested domains. Vertical force perturbations performed better than horizontal force perturbations for both atmospheric stability conditions. Themore » CPM performed best under convective stability conditions. The combination of the force and potential temperature perturbations is found to provide no additional performance improvement over the stand-alone application of the individual methods.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [2]
  1. Univ. of Colorado, Boulder, CO (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. National Center for Atmospheric Research, Boulder, CO (United States)
  4. Univ. of Colorado, Boulder, CO (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office; National Science Foundation (NSF)
OSTI Identifier:
1558077
Report Number(s):
LA-UR-19-27259
Journal ID: ISSN 1942-2466
Grant/Contract Number:  
89233218CNA000001; AGS‐1565498
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 11; Journal Issue: 7; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; multiscale modeling; turbulence; perturbation methods; WRF; large eddy simulation; atmospheric boundary layers

Citation Formats

Mazzaro, L. J., Koo, E., Muñoz‐Esparza, D., Lundquist, J. K., and Linn, R. R. Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations. United States: N. p., 2019. Web. doi:10.1029/2019MS001608.
Mazzaro, L. J., Koo, E., Muñoz‐Esparza, D., Lundquist, J. K., & Linn, R. R. Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations. United States. https://doi.org/10.1029/2019MS001608
Mazzaro, L. J., Koo, E., Muñoz‐Esparza, D., Lundquist, J. K., and Linn, R. R. Thu . "Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations". United States. https://doi.org/10.1029/2019MS001608. https://www.osti.gov/servlets/purl/1558077.
@article{osti_1558077,
title = {Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations},
author = {Mazzaro, L. J. and Koo, E. and Muñoz‐Esparza, D. and Lundquist, J. K. and Linn, R. R.},
abstractNote = {Coupling between mesoscale and large eddy simulation (LES) is critically important for many atmospheric model applications, from predictions of wind energy to fire propagation. The grid-nesting technique enables bridging between vastly different scales without incurring prohibitive computational costs. Yet, the transition from coarser to finer resolutions often requires a large number of grid points from inflow boundaries for the development of fine-scale turbulence features in the LES domain. Recently, the cell perturbation method (CPM) was developed to reduce the turbulence development region with high computational efficiency. Herein, we explore a new method based on the CPM that uses force perturbations in both the horizontal and vertical directions (Force Cell Perturbation Method) instead of the potential temperature perturbations in the original CPM, as an attempt to further explore the performance of the random perturbation techniques. This method is tested for a neutral and a convective atmospheric boundary layer under idealized conditions. Overall, similar performance is found between the optimal configurations of the CPM and the Force Cell Perturbation Method pointing to the robustness of this family of perturbation methods in accelerating turbulence generation in nested domains. Vertical force perturbations performed better than horizontal force perturbations for both atmospheric stability conditions. The CPM performed best under convective stability conditions. The combination of the force and potential temperature perturbations is found to provide no additional performance improvement over the stand-alone application of the individual methods.},
doi = {10.1029/2019MS001608},
journal = {Journal of Advances in Modeling Earth Systems},
number = 7,
volume = 11,
place = {United States},
year = {2019},
month = {6}
}

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