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Title: Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain

Abstract

The assumption of subgrid-scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Here in this paper, the turbulence kinetic energy (TKE) budget equation is used to study the spatiotemporal variability in two types of terrain—complex [Columbia Basin Wind Energy Study (CBWES) site, northeastern Oregon] and flat [Scaled Wind Farm Technology (SWiFT) site, west Texas]—using the Weather Research and Forecasting (WRF) Model. In each case, six nested domains [three domains each for mesoscale and large-eddy simulation (LES)] are used to downscale the horizontal grid spacing from ~10 km to ~10 m using the WRF Model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants of the LES domain. The budget terms calculated along the planes and the mean profile of budget terms show larger spatial variability at the CBWES site than at the SWiFT site. The contribution of the horizontal derivative of the shearmore » production term to the total shear production was found to be ≈45% and ≈15% at the CBWES and SWiFT sites, respectively, indicating that the horizontal derivatives applied in the budget equation should not be ignored in mesoscale model parameterizations, especially for cases with complex terrain with <10-km scale.« less

Authors:
 [1];  [1];  [1];  [1];  [2];  [3];  [4]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. National Center for Atmospheric Research, Boulder, CO (United States)
  3. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  4. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4WE)
OSTI Identifier:
1415063
Alternate Identifier(s):
OSTI ID: 1488818
Report Number(s):
LLNL-JRNL-739279
Journal ID: ISSN 1558-8424; 892534
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Journal Article: Published Article
Journal Name:
Journal of Applied Meteorology and Climatology
Additional Journal Information:
Journal Volume: 56; Journal Issue: 12; Journal ID: ISSN 1558-8424
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Atmosphere; Kinetic energy; Large eddy simulations; Mesoscale models; Numerical weather prediction/forecasting

Citation Formats

Rai, Raj K., Berg, Larry K., Pekour, Mikhail, Shaw, William J., Kosovic, Branko, Mirocha, Jeffrey D., and Ennis, Brandon L. Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain. United States: N. p., 2017. Web. doi:10.1175/JAMC-D-17-0124.1.
Rai, Raj K., Berg, Larry K., Pekour, Mikhail, Shaw, William J., Kosovic, Branko, Mirocha, Jeffrey D., & Ennis, Brandon L. Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain. United States. doi:10.1175/JAMC-D-17-0124.1.
Rai, Raj K., Berg, Larry K., Pekour, Mikhail, Shaw, William J., Kosovic, Branko, Mirocha, Jeffrey D., and Ennis, Brandon L. Thu . "Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain". United States. doi:10.1175/JAMC-D-17-0124.1.
@article{osti_1415063,
title = {Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain},
author = {Rai, Raj K. and Berg, Larry K. and Pekour, Mikhail and Shaw, William J. and Kosovic, Branko and Mirocha, Jeffrey D. and Ennis, Brandon L.},
abstractNote = {The assumption of subgrid-scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Here in this paper, the turbulence kinetic energy (TKE) budget equation is used to study the spatiotemporal variability in two types of terrain—complex [Columbia Basin Wind Energy Study (CBWES) site, northeastern Oregon] and flat [Scaled Wind Farm Technology (SWiFT) site, west Texas]—using the Weather Research and Forecasting (WRF) Model. In each case, six nested domains [three domains each for mesoscale and large-eddy simulation (LES)] are used to downscale the horizontal grid spacing from ~10 km to ~10 m using the WRF Model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants of the LES domain. The budget terms calculated along the planes and the mean profile of budget terms show larger spatial variability at the CBWES site than at the SWiFT site. The contribution of the horizontal derivative of the shear production term to the total shear production was found to be ≈45% and ≈15% at the CBWES and SWiFT sites, respectively, indicating that the horizontal derivatives applied in the budget equation should not be ignored in mesoscale model parameterizations, especially for cases with complex terrain with <10-km scale.},
doi = {10.1175/JAMC-D-17-0124.1},
journal = {Journal of Applied Meteorology and Climatology},
issn = {1558-8424},
number = 12,
volume = 56,
place = {United States},
year = {2017},
month = {12}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1175/JAMC-D-17-0124.1

Citation Metrics:
Cited by: 2 works
Citation information provided by
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Figures / Tables:

TABLE 1. TABLE 1.: Data and schemes used in WRF-Meso (mesoscale) and WRF-LES (microscale) models.

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