Improved representation of horizontal variability and turbulence in mesoscale simulations of an extended cold-air pool event

Journal Article · 24 February 2022 · Journal of Applied Meteorology and Climatology

DOI: https://doi.org/10.1175/jamc-d-21-0138.1 · OSTI ID:1962971

Arthur, Robert S. ^[1]; Juliano, Timothy W. ^[2]; Adler, Bianca ^[3]; Krishnamurthy, Raghavendra ^[4]; Lundquist, Julie K. ^[5]; Kosović, Branko ^[2]; Jiménez, Pedro A. ^[2]

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1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2. National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
3. Univ. of Colorado, Boulder, CO (United States); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
5. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States); Renewable and Sustainable Energy Institute, Boulder, Colorado (United States)

Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models, in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared to runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3 km/750 m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared to observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution, and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Lastly, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length scale formulation in the 3D PBL parameterization is also explored.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office; National Science Foundation (NSF); National Aeronautics and Space Administration (NASA)
• Grant/Contract Number: AC52-07NA27344; AC36-08GO28308; AC05-76RL01830; AGS-1554055; 80NSSC20M0162
• OSTI ID: 1962971
• Alternate ID(s): OSTI ID: 1871790; OSTI ID: 1872314; OSTI ID: 1876011
• Report Number(s): PNNL-SA-161944; LLNL-JRNL-821755; NREL/JA-5000-80885
• Journal Information: Journal of Applied Meteorology and Climatology, Vol. 61, Issue 6; ISSN 1558-8424
• Publisher: American Meteorological SocietyCopyright Statement
• Country of Publication: United States
• Language: English