Editorial Type:
Article
Article Type:
Research Article

Forecasting of Surface Winds over Eastern Canada Using the Canadian Offline Land Surface Modeling System

Lily Ioannidou Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment Canada, Dorval, Quebec, Canada

Search for other papers by Lily Ioannidou in
Current site
Google Scholar
PubMed Close
,
Wei Yu Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment Canada, Dorval, Quebec, Canada

Search for other papers by Wei Yu in
Current site
Google Scholar
PubMed Close
, and
Stéphane Bélair Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment Canada, Dorval, Quebec, Canada

Search for other papers by Stéphane Bélair in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jul 2014
DOI:
https://doi.org/10.1175/JAMC-D-12-0284.1
Page(s):
1760–1774
Restricted access

Abstract

The capability of the Canadian land surface external modeling system known as the Global Environmental Multiscale Surface (GEM-SURF) system with respect to surface wind predictions is evaluated. Based on the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme, and an exponential power law adjusted to the local stability conditions for the prediction of surface winds, the system allows decoupling of surface processes from those of the free atmosphere and enables high resolutions at the surface as dictated by the small-scale heterogeneities of the surface boundary. The simulations are driven by downscaled forecasts from the Regional Deterministic Prediction System, the 15-km Canadian regional operational modeling system. High-resolution, satellite-derived datasets of orography, vegetation, and soil cover are used to depict the surface boundary. The integration domains cover Canada’s eastern provinces at resolutions ranging from that of the driving model to resolutions similar to those of the geophysical datasets. The GEM-SURF predictions outperform those of the driving operational model. Reduction of the standard error and improvement of the model skill is seen as resolution increases, for all wind speeds. Further, the bias error is reduced in association with a rise in the corresponding value of the roughness length. For all examined resolutions GEM-SURF’s predictions are shown to be superior to those obtained through a simple statistical downscaling. In the prospect of the future development of a multicomponent system that provides wind forecasts at levels of wind energy generation, GEM-SURF’s potential for improved scores at the surface and its limited requirements in computer resources make it a suitable surface component of such a system.

Corresponding author address: Lily Ioannidou, Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment Canada, 2121 Trans-Canada, Dorval QC H9P 1J3 Canada. E-mail: lilyioan@yahoo.com

Abstract

The capability of the Canadian land surface external modeling system known as the Global Environmental Multiscale Surface (GEM-SURF) system with respect to surface wind predictions is evaluated. Based on the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme, and an exponential power law adjusted to the local stability conditions for the prediction of surface winds, the system allows decoupling of surface processes from those of the free atmosphere and enables high resolutions at the surface as dictated by the small-scale heterogeneities of the surface boundary. The simulations are driven by downscaled forecasts from the Regional Deterministic Prediction System, the 15-km Canadian regional operational modeling system. High-resolution, satellite-derived datasets of orography, vegetation, and soil cover are used to depict the surface boundary. The integration domains cover Canada’s eastern provinces at resolutions ranging from that of the driving model to resolutions similar to those of the geophysical datasets. The GEM-SURF predictions outperform those of the driving operational model. Reduction of the standard error and improvement of the model skill is seen as resolution increases, for all wind speeds. Further, the bias error is reduced in association with a rise in the corresponding value of the roughness length. For all examined resolutions GEM-SURF’s predictions are shown to be superior to those obtained through a simple statistical downscaling. In the prospect of the future development of a multicomponent system that provides wind forecasts at levels of wind energy generation, GEM-SURF’s potential for improved scores at the surface and its limited requirements in computer resources make it a suitable surface component of such a system.

Corresponding author address: Lily Ioannidou, Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment Canada, 2121 Trans-Canada, Dorval QC H9P 1J3 Canada. E-mail: lilyioan@yahoo.com
Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Abramowitz, G., A. Pitman, H. Gupta, E. Kowalczyk, and Y. Wang, 2007: Systematic bias in land surface models. J. Hydrometeor., 8, 989–1001, doi:10.1175/JHM628.1.

    • Search Google Scholar
    • Export Citation

  • Bélair, S., L.-P. Crevier, J. Mailhot, B. Bilodeau, and Y. Delage, 2003a: Operational implementation of the ISBA land surface scheme in the Canadian regional weather forecast model. Part I: Warm season results. J. Hydrometeor., 4, 352–370, doi:10.1175/1525-7541(2003)4<352:OIOTIL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bélair, S., R. Brown, J. Mailhot, B. Bilodeau, and L.-P. Crevier, 2003b: Operational implementation of the ISBA land surface scheme in the Canadian regional weather forecast model. Part II: Cold season results. J. Hydrometeor., 4, 371–386, doi:10.1175/1525-7541(2003)4<371:OIOTIL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bernier, N. B., and S. Bélair, 2012: High horizontal and vertical resolution limited-area model: Near-surface and wind energy forecast applications. J. Appl. Meteor. Climatol., 51, 1061–1078, doi:10.1175/JAMC-D-11-0197.1.

    • Search Google Scholar
    • Export Citation

  • Bernier, N. B., S. Bélair, B. Bilodeau, and L. Tong, 2011: Near-surface and land surface forecast system of the Vancouver 2010 Winter Olympic and Paralympic Games. J. Hydrometeor., 12, 508–530, doi:10.1175/2011JHM1250.1.

    • Search Google Scholar
    • Export Citation

  • Boone, A., J.-C. Calvet, and J. Noilhan, 1999: Inclusion of a third soil layer in a land surface scheme using the force–restore method. J. Appl. Meteor., 38, 1611–1630, doi:10.1175/1520-0450(1999)038<1611:IOATSL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Boone, A., V. Masson, T. Meyers, and J. Noilhan, 2000: The influence of the inclusion of soil freezing on simulations by a soil–vegetation–atmosphere transfer scheme. J. Appl. Meteor., 39, 1544–1569, doi:10.1175/1520-0450(2000)039<1544:TIOTIO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Carrera, M. L., S. Bélair, V. Fortin, B. Bilodeau, D. Charpentier, and I. Doré, 2010: Evaluation of snowpack simulations over the Canadian Rockies with an experimental hydrometeorological modeling system. J. Hydrometeor., 11, 1123–1140, doi:10.1175/2010JHM1274.1.

    • Search Google Scholar
    • Export Citation

  • Cheng, W. Y., and W. J. Steenburgh, 2005: Evaluation of surface sensible weather forecasts by the WRF and the Eta models over the western United States. Wea. Forecasting, 20, 812–821, doi:10.1175/WAF885.1.

    • Search Google Scholar
    • Export Citation

  • De Haan, L.-L., M. Kanamitsu, C.-H. Lu, and J. O. Roads, 2007: A comparison of the Noah and OSU land surface models in the ECPC Seasonal Forecast Model. J. Hydrometeor., 8, 1031–1048, doi:10.1175/JHM629.1.

    • Search Google Scholar
    • Export Citation

  • Delage, Y., 1997: Parameterising sub-grid scale vertical transport in atmospheric models under statically stable conditions. Bound.-Layer Meteor., 82, 23–48, doi:10.1023/A:1000132524077.

    • Search Google Scholar
    • Export Citation

  • Delage, Y., and C. Girard, 1992: Stability functions correct at the free convection limit and consistent for both the surface and Ekman layers. Bound.-Layer Meteor., 58, 19–31, doi:10.1007/BF00120749.

    • Search Google Scholar
    • Export Citation

  • Dodson, R., and D. Marks, 1997: Daily air temperature interpolated at high spatial resolution over a large mountainous region. Climate Res., 8, 1–20, doi:10.3354/cr008001.

    • 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, doi:10.1175/JAMC-D-11-084.1.

    • Search Google Scholar
    • Export Citation

  • Lazić, L., G. Pejanović, and M. Živković, 2010: Wind forecasts for wind power generation using the Eta Model. Renewable Energy, 35, 1236–1243, doi:10.1016/j.renene.2009.10.028.

    • Search Google Scholar
    • Export Citation

  • Leroyer, S., S. Bélair, J. Mailhot, and I. B. Strachan, 2011: Microscale numerical prediction over Montreal with the Canadian external urban modeling system. J. Appl. Meteor. Climatol., 50, 2410–2428, doi:10.1175/JAMC-D-11-013.1.

    • Search Google Scholar
    • Export Citation

  • Mailhot, J., and Coauthors, 2006: The 15-km version of the Canadian regional forecast system. Atmos.–Ocean, 44, 133–149, doi:10.3137/ao.440202.

    • Search Google Scholar
    • Export Citation

  • Mass, C., and D. Ovens, 2010: WRF model physics: Problems, progress and perhaps some solutions. Proc. 11th WRF Users Workshop, Boulder, CO, NCAR, 4.1. [Available online at http://www2.mmm.ucar.edu/wrf/users/workshops/WS2010/presentations/session%204/4-1_WRFworkshop2010Final.pdf.]

  • Noilhan, J., and S. Planton, 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536–549, doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Noilhan, J., and J.-F. Mahfouf, 1996: The ISBA land surface parameterisation scheme. Global Planet. Change, 13, 145–159, doi:10.1016/0921-8181(95)00043-7.

    • Search Google Scholar
    • Export Citation

  • Roux, G., Y. Liu, L. D. Monache, R. S. Shey, and T. T. Warner, 2008: Verification of high resolution WRF-STFDDA surface forecasts over mountains and plains. Extended Abstracts, Ninth WRF Users Workshop, Boulder, CO, NCAR, 5B05. [Available online at http://www2.mmm.ucar.edu/wrf/users/workshops/WS2009/abstracts/5B-05.pdf.]

  • Santos-Alamillos, F. J., D. Pozo-Vázquez, J. A. Ruiz-Arias, V. Lara-Fanego, and J. Tovar-Pescador, 2013: Analysis of WRF model wind estimate sensitivity to physics parameterization choice and terrain representation in Andalusia (southern Spain). J. Appl. Meteor. Climatol., 52, 1592–1609, doi:10.1175/JAMC-D-12-0204.1.

    • Search Google Scholar
    • Export Citation

  • Schulz, J.-P., L. Dümenil, J. Polcher, C.-A. Schlosser, and Y. Xue, 1998: Land surface energy and moisture fluxes: Comparing three models. J. Appl. Meteor., 37, 288–307, doi:10.1175/1520-0450(1998)037<0288:LSEAMF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sheridan, P., S. Smith, A. Brown, and S. Vosper, 2010: A simple height-based correction for temperature downscaling in complex terrain. Meteor. Appl., 17, 329–339, doi:10.1002/met.177.

    • Search Google Scholar
    • Export Citation

  • Stahl, K., R. D. Moore, J. A. Floyer, M. G. Asplin, and I. G. McKendry, 2006: Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density. Agric. For. Meteor., 139, 224–236, doi:10.1016/j.agrformet.2006.07.004.

    • Search Google Scholar
    • Export Citation

  • Wyszogrodzki, A. A., Y. Liu, N. Jacobs, P. Childs, Y. Zhang, G. Roux, and T. T. Warner, 2013: Analysis of the surface temperature and wind forecast errors of the NCAR-AirDat operational CONUS 4-km WRF forecasting system. Meteor. Atmos. Phys., 122, 125–143, doi:10.1007/s00703-013-0281-5.

    • Search Google Scholar
    • Export Citation

  • Zhang, H., Z. Pu, and X. Zhang, 2013: Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain. Wea. Forecasting, 28, 893–914, doi:10.1175/WAF-D-12-00109.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 212 55 2
PDF Downloads 75 18 2