WRF Model Study of the Great Plains Low-Level Jet: Effects of Grid Spacing and Boundary Layer Parameterization

Elizabeth N. Smith School of Meteorology, and Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Jeremy A. Gibbs Department of Mechanical Engineering, University of Utah, Salt Lake City, Utah

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Evgeni Fedorovich School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Petra M. Klein School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Abstract

Previous studies have shown that the Weather Research and Forecasting (WRF) Model often underpredicts the strength of the Great Plains nocturnal low-level jet (NLLJ), which has implications for weather, climate, aviation, air quality, and wind energy in the region. During the Lower Atmospheric Boundary Layer Experiment (LABLE) conducted in 2012, NLLJs were frequently observed at high temporal resolution, allowing for detailed documentation of their development and evolution throughout the night. Ten LABLE cases with observed NLLJs were chosen to systematically evaluate the WRF Model’s ability to reproduce the observed NLLJs. Model runs were performed with 4-, 2-, and 1-km horizontal spacing and with the default stretched vertical grid and a nonstretched 40-m vertically spaced grid to investigate which grid configurations are optimal for NLLJ modeling. These tests were conducted using three common boundary layer parameterization schemes: Mellor–Yamada Nakanishi Niino, Yonsei University, and Quasi-Normal Scale Elimination. It was found that refining horizontal spacing does not necessarily improve the modeled NLLJ wind. Increasing the number of vertical levels on a non-stretched grid provides more information about the structure of the NLLJ with some schemes, but the benefit is limited by computational expense and model stability. Simulations of the NLLJ were found to be less sensitive to boundary layer parameterization than to grid configuration. The Quasi-Normal Scale Elimination scheme was chosen for future NLLJ simulation studies.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth N. Smith, elizabeth.n.smith@ou.edu

Abstract

Previous studies have shown that the Weather Research and Forecasting (WRF) Model often underpredicts the strength of the Great Plains nocturnal low-level jet (NLLJ), which has implications for weather, climate, aviation, air quality, and wind energy in the region. During the Lower Atmospheric Boundary Layer Experiment (LABLE) conducted in 2012, NLLJs were frequently observed at high temporal resolution, allowing for detailed documentation of their development and evolution throughout the night. Ten LABLE cases with observed NLLJs were chosen to systematically evaluate the WRF Model’s ability to reproduce the observed NLLJs. Model runs were performed with 4-, 2-, and 1-km horizontal spacing and with the default stretched vertical grid and a nonstretched 40-m vertically spaced grid to investigate which grid configurations are optimal for NLLJ modeling. These tests were conducted using three common boundary layer parameterization schemes: Mellor–Yamada Nakanishi Niino, Yonsei University, and Quasi-Normal Scale Elimination. It was found that refining horizontal spacing does not necessarily improve the modeled NLLJ wind. Increasing the number of vertical levels on a non-stretched grid provides more information about the structure of the NLLJ with some schemes, but the benefit is limited by computational expense and model stability. Simulations of the NLLJ were found to be less sensitive to boundary layer parameterization than to grid configuration. The Quasi-Normal Scale Elimination scheme was chosen for future NLLJ simulation studies.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth N. Smith, elizabeth.n.smith@ou.edu
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  • Ardanuy, P., 1979: On the observed diurnal oscillation of the Somali jet. Mon. Wea. Rev., 107, 16941700, https://doi.org/10.1175/1520-0493(1979)107<1694:OTODOO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Astling, E. G., J. Paegle, E. Miller, and C. J. O’Brien, 1985: Boundary layer control of nocturnal convection associated with a synoptic scale system. Mon. Wea. Rev., 113, 540552, https://doi.org/10.1175/1520-0493(1985)113<0540:BLCONC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baines, P., 1980: The dynamics of the Southerly Buster. Aust. Meteor. Mag., 28, 175200.

  • Blackadar, A. K., 1957: Boundary layer wind maxima and their significance for the growth of nocturnal inversions. Bull. Amer. Meteor. Soc., 38, 283290, https://doi.org/10.1175/1520-0477-38.5.283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonin, T. A., 2015: Nocturnal boundary layer and low-level jet characteristics under different turbulent regimes. Ph.D. thesis, The University of Oklahoma, 190 pp., https://shareok.org/handle/11244/14623.

  • Bonin, T. A., W. G. Blumberg, P. M. Klein, and P. B. Chilson, 2015: Thermodynamic and turbulence characteristics of the southern Great Plains nocturnal boundary layer under differing turbulent regimes. Bound.-Layer Meteor., 157, 401420, https://doi.org/10.1007/s10546-015-0072-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonner, W. D., 1966: Case study of thunderstorm activity in relation to the low-level jet. Mon. Wea. Rev., 94, 167178, https://doi.org/10.1175/1520-0493(1966)094<0167:CSOTAI>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonner, W. D., 1968: Climatology of the low level jet. Mon. Wea. Rev., 96, 833850, https://doi.org/10.1175/1520-0493(1968)096<0833:COTLLJ>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brook, R. R., 1985: The Koorin nocturnal low-level jet. Bound.-Layer Meteor., 32, 133154, https://doi.org/10.1007/BF00120932.

  • Chang, J., and S. Hanna, 2004: Air quality model performance evaluation. Meteor. Atmos. Phys., 87, 167196, https://doi.org/10.1007/s00703-003-0070-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clark, A. J., and Coauthors, 2012: An overview of the 2010 Hazardous Weather Testbed experimental forecast program spring experiment. Bull. Amer. Meteor. Soc., 93, 5574, https://doi.org/10.1175/BAMS-D-11-00040.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fernando, H. J. S., and J. C. Weil, 2010: Whither the stable boundary layer? Bull. Amer. Meteor. Soc., 91, 14751484, https://doi.org/10.1175/2010BAMS2770.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gebauer, J. G., A. Shapiro, E. Fedorovich, and P. K. Klein, 2018: Convection initiation caused by heterogeneous low-level jets over the Great Plains. Mon. Wea. Rev., 146, 26152637, https://doi.org/10.1175/MWR-D-18-0002.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geerts, B., and Coauthors, 2017: The 2015 Plains Elevated Convection at Night field project. Bull. Amer. Meteor. Soc., 98, 767786, https://doi.org/10.1175/BAMS-D-15-00257.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibbs, J. A., E. Fedorovich, and A. M. Van Eijk, 2011: Evaluating Weather Research and Forecasting (WRF) Model predictions of turbulent flow parameters in a dry convective boundary layer. J. Appl. Meteor. Climatol., 50, 24292444, https://doi.org/10.1175/2011JAMC2661.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., 1999: Hypothesis tests for evaluating numerical precipitation forecasts. Wea. Forecasting, 14, 155167, https://doi.org/10.1175/1520-0434(1999)014<0155:HTFENP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holton, J. R., 1967: The diurnal boundary layer wind oscillation above sloping terrain. Tellus, 19, 199205, https://doi.org/10.1111/j.2153-3490.1967.tb01473.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holtslag, A. A. M., and Coauthors, 2013: Stable atmospheric boundary layers and diurnal cycles: Challenges for weather and climate models. Bull. Amer. Meteor. Soc., 94, 16911706, https://doi.org/10.1175/BAMS-D-11-00187.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103120, https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jahn, D. E., W. Gallus, and E. S. Takle, 2014: Evaluation of the MYNN PBL scheme closure constants for low-level jets in a stable boundary layer. Proc. 21st Symp. on Boundary Layers and Turbulence, Leeds, United Kingdom, Amer. Meteor. Soc., 16B.5, https://ams.confex.com/ams/21BLT/webprogram/Paper247664.html.

  • Johnson, A., X. Wang, F. Kong, and M. Xue, 2013: Object-based evaluation of the impact of horizontal grid spacing on convection-allowing forecasts. Mon. Wea. Rev., 141, 34133425, https://doi.org/10.1175/MWR-D-13-00027.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., and Coauthors, 2008: Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Wea. Forecasting, 23, 931952, https://doi.org/10.1175/WAF2007106.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, P., and Coauthors, 2015: LABLE: A multi-institutional, student-led, atmospheric boundary layer experiment. Bull. Amer. Meteor. Soc., 96, 17431764, https://doi.org/10.1175/BAMS-D-13-00267.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klein, P., X.-M. Hu, A. Shapiro, and M. Xue, 2016: Linkages between boundary-layer structure and the development of nocturnal low-level jets in central Oklahoma. Bound.-Layer Meteor., 158, 383408, https://doi.org/10.1007/s10546-015-0097-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • LeMone, M. A., M. Tewari, F. Chen, and J. Dudhia, 2013: Objectively determined fair-weather CBL depths in the ARW-WRF Model and their comparison to CASES-97 observations. Mon. Wea. Rev., 141, 3054, https://doi.org/10.1175/MWR-D-12-00106.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maddox, R. A., 1983: Large-scale meteorological conditions associated with midlatitude, mesoscale convective complexes. Mon. Wea. Rev., 111, 14751493, https://doi.org/10.1175/1520-0493(1983)111<1475:LSMCAW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahrt, L., 1998: Stratified atmospheric boundary layers and breakdown of models. Theor. Comput. Fluid Dyn., 11, 263279, https://doi.org/10.1007/s001620050093.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahrt, L., 1999: Stratified atmospheric boundary layers. Bound.-Layer Meteor., 90, 375396, https://doi.org/10.1023/A:1001765727956.

  • Markowski, P., and Y. Richardson, 2011: Mesoscale Meteorology in Midlatitudes. John Wiley and Sons, 430 pp.

    • Crossref
    • Export Citation
  • Mirocha, J., B. Kosovic, and G. Kirkil, 2014: Resolved turbulence characteristics in large-eddy simulations nested within mesoscale simulations using the Weather Research and Forecasting Model. Mon. Wea. Rev., 142, 806831, https://doi.org/10.1175/MWR-D-13-00064.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mirocha, J., M. D. Simpson, J. D. Fast, L. K. Berg, and R. Baskett, 2016: Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting Model. Wind Energy, 19, 739762, https://doi.org/10.1002/we.1862.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mittermaier, M. P., 2008: The potential impact of using persistence as a reference forecast on perceived forecast skill. Wea. Forecasting, 23, 10221031, https://doi.org/10.1175/2008WAF2007037.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakanishi, M., and H. Niino, 2009: Development of an improved turbulence closure model for the atmospheric boundary layer. J. Meteor. Soc. Japan, 87, 895912, https://doi.org/10.2151/jmsj.87.895.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • National Research Council, 1983: Low-Altitude Wind Shear and Its Hazard to Aviation. National Academies Press, 112 pp.

  • Olson, J., and J. M. Brown, 2012: Modifications in the MYNN PBL/surface layer scheme for WRF-ARW. Proc. WRF Users Workshop 2012, Boulder, CO, NCAR, http://www2.mmm.ucar.edu/wrf/users/workshops/WS2012/ppts/3.3.pdf.

  • Pan, Z., M. Segal, and R. W. Arritt, 2004: Role of topography in forcing low-level jets in the central United States during the 1993 flood-altered terrain simulations. Mon. Wea. Rev., 132, 396403, https://doi.org/10.1175/1520-0493(2004)132<0396:ROTIFL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pitchford, K. L., and J. London, 1962: The low-level jet as related to nocturnal thunderstorms over midwest United States. J. Appl. Meteor., 1, 4347, https://doi.org/10.1175/1520-0450(1962)001<0043:TLLJAR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salmond, J. A., and I. G. McKendry, 2005: A review of turbulence in the very stable nocturnal boundary layer and its implications for air quality. Prog. Phys. Geogr., 29, 171188, https://doi.org/10.1191/0309133305pp442ra.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schwartz, C. S., and Coauthors, 2009: Next-day convection-allowing WRF Model guidance: A second look at 2-km versus 4-km grid spacing. Mon. Wea. Rev., 137, 33513372, https://doi.org/10.1175/2009MWR2924.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., and E. Fedorovich, 2009: Nocturnal low-level jet over a shallow slope. Acta Geophys., 57, 950980, https://doi.org/10.2478/s11600-009-0026-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., and E. Fedorovich, 2010: Analytical description of a nocturnal low-level jet. Quart. J. Roy. Meteor. Soc., 136, 12551262, https://doi.org/10.1002/qj.628.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., E. Fedorovich, and S. Rahimi, 2016: A unified theory for the Great Plains nocturnal low-level jet. J. Atmos. Sci., 73, 30373057, https://doi.org/10.1175/JAS-D-15-0307.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sisterson, D. L., and P. Frenzen, 1978: Nocturnal boundary-layer wind maxima and the problem of wind power assessment. Environ. Sci. Technol., 12, 218221, https://doi.org/10.1021/es60138a014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., doi:10.5065/D68S4MVH.

    • Crossref
    • Export Citation
  • Smagorinsky, J., 1963: General circulation experiments with the primitive equations: I. The basic experiment. Mon. Wea. Rev., 91, 99164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, E. N., P. M. Klein, E. Fedorovich, J. A. Gibbs, and J. G. Gebauer, 2018: The Great Plains low-level jet during PECAN: Observed and simulated characteristics. Proc. Special Symp. on Plains Elevated Convection at Night (PECAN), Austin, TX, Amer. Meteor. Soc., 2.6, https://ams.confex.com/ams/98Annual/webprogram/Paper331142.html.

    • Crossref
    • Export Citation
  • Steeneveld, G.-J., 2014: Current challenges in understanding and forecasting stable boundary layers over land and ice. Front. Environ. Sci., 2, 16, https://doi.org/10.3389/fenvs.2014.00041.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steeneveld, G.-J., T. Mauritsen, E. I. F. de Bruijn, J. Vilà-Guerau de Arellano, G. Svensson, and A. Holtslag, 2008: Evaluation of limited-area models for the representation of the diurnal cycle and contrasting nights in CASES-99. J. Appl. Meteor. Climatol., 47, 869887, https://doi.org/10.1175/2007JAMC1702.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stensrud, D. J., 1996: Importance of low-level jets to climate: A review. J. Climate, 9, 16981711, https://doi.org/10.1175/1520-0442(1996)009<1698:IOLLJT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Storm, B., J. Dudhia, S. Basu, A. Swift, and I. Giammanco, 2009: Evaluation of the Weather Research and Forecasting Model on forecasting low-level jets: Implications for wind energy. Wind Energy, 12, 8190, https://doi.org/10.1002/we.288.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stull, R. B., 2012: An Introduction to Boundary Layer Meteorology. Springer, 670 pp.

  • Sukoriansky, S., B. Galperin, and V. Perov, 2005: Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice. Bound.-Layer Meteor., 117, 231257, https://doi.org/10.1007/s10546-004-6848-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified Noah land surface model in the WRF Model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 11–15, https://ams.confex.com/ams/84Annual/webprogram/Paper69061.html.

  • Trier, S. B., C. A. Davis, D. A. Ahijevych, M. L. Weisman, and G. H. Bryan, 2006: Mechanisms supporting long-lived episodes of propagating nocturnal convection within a 7-day WRF Model simulation. J. Atmos. Sci., 63, 24372461, https://doi.org/10.1175/JAS3768.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, D., and U. Löhnert, 2014: Information content and uncertainties in thermodynamic profiles and liquid cloud properties retrieved from the ground-based Atmospheric Emitted Radiance Interferometer (AERI). J. Appl. Meteor. Climatol., 53, 752771, https://doi.org/10.1175/JAMC-D-13-0126.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vanderwende, B. J., J. K. Lundquist, M. E. Rhodes, E. S. Takle, and S. L. Irvin, 2015: Observing and simulating the summertime low-level jet in central Iowa. Mon. Wea. Rev., 143, 23192336, https://doi.org/10.1175/MWR-D-14-00325.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Whiteman, C. D., X. Bian, and S. Zhong, 1997: Low-level jet climatology from enhanced rawinsonde observations at a site in the southern Great Plains. J. Appl. Meteor. Climatol., 36, 13631376, https://doi.org/10.1175/1520-0450(1997)036<1363:LLJCFE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita.” J. Atmos. Sci., 61, 18161826, https://doi.org/10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhong, S., J. D. Fast, and X. Bian, 1996: A case study of the Great Plains low-level jet using wind profiler network data and a high-resolution mesoscale model. Mon. Wea. Rev., 124, 785806, https://doi.org/10.1175/1520-0493(1996)124<0785:ACSOTG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, B., J. S. Simon, and F. K. Chow, 2014: The convective boundary layer in the terra incognita. J. Atmos. Sci., 71, 25452563, https://doi.org/10.1175/JAS-D-13-0356.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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