Editorial Type:
Article
Article Type:
Research Article

On the Ability of the WRF Model to Reproduce the Surface Wind Direction over Complex Terrain

Pedro A. Jiménez División de Energías Renovables, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain, and Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research,* Boulder, Colorado

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Jimy Dudhia Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research,* Boulder, Colorado

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Print Publication:
01 Jul 2013
DOI:
https://doi.org/10.1175/JAMC-D-12-0266.1
Page(s):
1610–1617
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Abstract

The ability of the Weather Research and Forecasting (WRF) model to reproduce the surface wind direction over complex terrain is examined. A simulation spanning a winter season at a high horizontal resolution of 2 km is compared with wind direction records from a surface observational network located in the northeastern Iberian Peninsula. A previous evaluation has shown the ability of WRF to reproduce the wind speed over the region once the effects of the subgrid-scale topography are parameterized. Hence, the current investigation complements the previous findings, providing information about the model's ability to reproduce the direction of the surface flow. The differences between the observations and the model are quantified in terms of scores explicitly designed to handle the circular nature of the wind direction. Results show that the differences depend on the wind speed. The larger the wind speed is, the smaller are the wind direction differences. Areas with more complex terrain show larger systematic differences between model and observations; in these areas, a statistical correction is shown to help. The importance of the grid point selected for the comparison with observations is also analyzed. A careful selection is relevant to reducing comparative problems over complex terrain.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Pedro A. Jimenez, Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, 3450 Mitchell Ln., Boulder, CO 80301. E-mail: jimenez@ucar.edu

Abstract

The ability of the Weather Research and Forecasting (WRF) model to reproduce the surface wind direction over complex terrain is examined. A simulation spanning a winter season at a high horizontal resolution of 2 km is compared with wind direction records from a surface observational network located in the northeastern Iberian Peninsula. A previous evaluation has shown the ability of WRF to reproduce the wind speed over the region once the effects of the subgrid-scale topography are parameterized. Hence, the current investigation complements the previous findings, providing information about the model's ability to reproduce the direction of the surface flow. The differences between the observations and the model are quantified in terms of scores explicitly designed to handle the circular nature of the wind direction. Results show that the differences depend on the wind speed. The larger the wind speed is, the smaller are the wind direction differences. Areas with more complex terrain show larger systematic differences between model and observations; in these areas, a statistical correction is shown to help. The importance of the grid point selected for the comparison with observations is also analyzed. A careful selection is relevant to reducing comparative problems over complex terrain.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Pedro A. Jimenez, Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, 3450 Mitchell Ln., Boulder, CO 80301. E-mail: jimenez@ucar.edu
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  • Bao, L., T. Gnetting, E. P. Grimit, P. Guttorp, and A. Raftery, 2010: Bias correction and Bayesian model averaging for ensemble forecasts of surface wind direction. Mon. Wea. Rev., 138, 1811–1821.

    • Search Google Scholar
    • Export Citation

  • Beljaars, A. C. M., A. R. Brown, and N. Wood, 2004: A new parametrization of turbulent orographic form drag. Quart. J. Roy. Meteor. Soc., 130, 1327–1347.

    • Search Google Scholar
    • Export Citation

  • Carvalho, D., A. Rocha, M. Gomez-Gesteira, and C. Santos, 2012: A sensitivity study of the WRF model in wind simulation for an area of high wind energy. Environ. Model. Software, 33, 23–24.

    • Search Google Scholar
    • Export Citation

  • Davies, B. M., and D. J. Thomson, 1999: Comparisons of some parameterizations of wind direction variability with observations. Atmos. Environ., 33, 4909–4917.

    • Search Google Scholar
    • Export Citation

  • Grimit, E. P., T. Gneiting, V. J. Berrocal, and N. A. Johnson, 2006: The continuous ranked probability score for circular variables and its application to mesoscale forecast ensemble verification. Quart. J. Roy. Meteor. Soc., 132, 2925–2942.

    • Search Google Scholar
    • Export Citation

  • Jiménez, P. A., and J. Dudhia, 2012: Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model. J. Appl. Meteor. Climatol., 51, 300–316.

    • Search Google Scholar
    • Export Citation

  • Jiménez, P. A., J. F. González-Rouco, J. P. Montávez, E. García-Bustamante, and J. Navarro, 2009: Climatology of wind patterns in the northeast of the Iberian Peninsula. Int. J. Climatol., 29, 501–525.

    • Search Google Scholar
    • Export Citation

  • Jiménez, P. A., J. F. González-Rouco, E. García-Bustamante, J. Navarro, J. P. Montávez, J. Vilà-Guerau de Arellano, J. Dudhia, and A. Roldán, 2010a: Surface wind regionalization over complex terrain: Evaluation and analysis of a high-resolution WRF numerical simulation. J. Appl. Meteor. Climatol., 49, 268–287.

    • Search Google Scholar
    • Export Citation

  • Jiménez, P. A., J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2010b: Quality assurance of surface wind observations from automated weather stations. J. Atmos. Oceanic Technol., 27, 1101–1122.

    • Search Google Scholar
    • Export Citation

  • Jiménez, P. A., J. Dudhia, and J. Navarro, 2011: On the surface wind speed probability density function over complex terrain. Geophys. Res. Lett., 38, L22803, doi:10.1029/2011GL049669.

    • Search Google Scholar
    • Export Citation

  • Joffre, S., and T. Laurila, 1988: Standard deviations of wind speed and direction from observations over smooth surface. J. Appl. Meteor., 27, 550–561.

    • Search Google Scholar
    • Export Citation

  • Lazić, L., G. Pejanović, and M. Živković, 2010: Wind forecasts for wind power generation using the Eta Model. Renew. Energy, 35, 1236–1243.

    • Search Google Scholar
    • Export Citation

  • Mahrt, L., 2011: Surface wind direction variability. J. Appl. Meteor. Climatol., 50, 144–152.

  • Mardia, R. V., and P. E. Jupp, 1999: Directional Statistics. John Wiley and Sons, 429 pp.

  • Mesinger, F., R. L. Wobus, and M. E. Baldwin, 1996: Parameterization of form drag in the Eta Model at the National Centers for Environmental Prediction. Preprints, 11th Conf. on Numerical Weather Predition, Norfolk, VA, Amer. Meteor. Soc., 324–326.

  • Pielke, R. A., 2002: Mesoscale Meteorological Modeling. Academic Press, 676 pp.

  • Rife, D. R., and C. A. Davis, 2005: Verification of temporal variations in mesoscale numerical wind forecast. Mon. Wea. Rev., 133, 3368–3381.

    • Search Google Scholar
    • Export Citation

  • Rife, D. R., C. A. Davis, Y. Liu, and T. T. Warner, 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132, 2533–2569.

    • Search Google Scholar
    • Export Citation

  • Rontu, L., 2006: A study on parameterization of orography-related momentum fluxes in a synoptic-scale NWP model. Tellus, 58A, 69–81.

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Rep. TN-475+STR, 113 pp.

  • Whiteman, C. D., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, 355 pp.

  • Wood, N., A. Brown, and R. Hewer, 2001: Parametrizing the effects of orography on the boundary layer: An alternative to effective roughness lengths. Quart. J. Roy. Meteor. Soc., 127, 759–777.

    • Search Google Scholar
    • Export Citation

  • Zagar, N., M. Zagar, J. Cedilnik, G. Gregoric, and J. Rakovec, 2006: Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA40 over complex terrain. Tellus, 58A, 445–455.

    • Search Google Scholar
    • Export Citation
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