• Ahmed, S., 1994: Gust factors within frontal depressions at Rio, Greece. Meteor. Appl., 1, 205208.

  • Beniston, M., and Coauthors, 2007: Future extreme events in European climate: An exploration of regional climate model projections. Climatic Change, 81, 7195, doi:10.1007/s10584-006-9226-z.

    • Search Google Scholar
    • Export Citation
  • Bernstein, L., and Coauthors, Eds., 2007: Climate Change 2007: Synthesis Report. Cambridge University Press, 104 pp.

  • Cechet, R. P., , and L. A. Sanabria, 2010: Extreme-value time-series analysis of Australian Region A gust wind speeds to examine instrument bias. IOP Conf. Ser.: Earth Environ. Sci., 11, 012016, doi:10.1088/1755-1315/11/1/012016.

    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., 1980: Climatology of high damaging winds in the Midwest. Investigation Rep. 95, Illinois State Water Survey, Champaign, IL, 54 pp.

  • Changnon, S. A., 2009: Temporal and spatial distributions of wind storm damages in the United States. Climatic Change, 94, 473482, doi:10.1007/s10584-008-9518-6.

    • Search Google Scholar
    • Export Citation
  • Cheng, C. S., , G. Li, , Q. Li, , and H. Auld, 2008: Statistical downscaling of hourly and daily climate scenarios for various meteorological variables in south-central Canada. Theor. Appl. Climatol., 91, 129147, doi:10.1007/s00704-007-0302-8.

    • Search Google Scholar
    • Export Citation
  • Cheng, C. S., , G. Li, , Q. Li, , and H. Auld, 2010: A synoptic weather typing approach to simulate daily rainfall and extremes in Ontario, Canada: Potential for climate change projections. J. Appl. Meteor. Climatol., 49, 845866.

    • Search Google Scholar
    • Export Citation
  • Cvitan, L., 2003: Determining wind gusts using mean hourly speed. Geofizika, 20, 6374.

  • Davis, F. K., , and H. Newstein, 1968: The variation of gust factors with mean wind speed and with height. J. Appl. Meteor., 7, 372378.

    • Search Google Scholar
    • Export Citation
  • Dore, M. H. I., 2003: Forecasting the conditional probabilities of natural disasters in Canada as a guide for disaster preparedness. Nat. Hazards, 28, 249269.

    • Search Google Scholar
    • Export Citation
  • Environment Canada, 1977: MAMOBS: Manual of surface weather observations. 7th ed. Meteorological Service of Canada, Environment Canada, Toronto, ON, Canada, 386 pp.

  • Environment Canada, cited 2010: Public alerting criteria. [Available online at http://www.ec.gc.ca/meteo-weather/default.asp?lang=En&n=D9553AB5-1.]

  • Graybeal, D. Y., 2006: Relationships among daily mean and maximum wind speeds, with application to data quality assurance. Int. J. Climatol., 26, 2943.

    • Search Google Scholar
    • Export Citation
  • Jungo, P., , S. Goyette, , and M. Beniston, 2002: Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation. Int. J. Climatol., 22, 485499.

    • Search Google Scholar
    • Export Citation
  • Katz, R. W., 2002: Techniques for estimating uncertainty in climate change scenarios and impact studies. Climate Res., 20, 167185.

  • Lambert, S. J., , and J. C. Fyfe, 2006: Changes in winter cyclone frequencies and strengths simulated in enhanced greenhouse warming experiments: Results from the models participating in the IPCC diagnostic exercise. Climate Dyn., 26, 713728.

    • Search Google Scholar
    • Export Citation
  • Lopes, A., , S. Oliveira, , M. Fragoso, , J. A. Andrade, , and P. Pedro, 2009: Wind risk assessment in urban environments: The case of falling trees during windstorm events in Lisbon. Bioclimatology and Natural Hazards, K. Strelcová et al., Eds., Springer, 55–74.

  • Meehl, G. A., and Coauthors, 2007: Global climate projections. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 747–845.

  • Mitsuta, Y., , and O. Tsukamoto, 1989: Studies on spatial structure of wind gust. J. Appl. Meteor., 28, 11551160.

  • Moyer, M., 2009: The way the wind blows. Sci. Amer., 301 (October), 2728.

  • Paulsen, B. M., , and J. L. Schroeder, 2005: An examination of tropical and extratropical gust factors and the associated wind speed histograms. J. Appl. Meteor., 44, 270280.

    • Search Google Scholar
    • Export Citation
  • PCMDI, cited 2008: WCRP CMIP3 multi-model dataset. [Available online at http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php.]

  • Pinto, J. G., , C. P. Neuhaus, , G. C. Leckebusch, , M. Reyers, , and M. Kerschgens, 2010: Estimation of wind storm impacts over western Germany under future climate conditions using a statistical–dynamical downscaling approach. Tellus, 62A, 188201.

    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., , J. T. Schoof, , and R. J. Barthelmie, 2005: Climate change impacts on wind speeds and wind energy density in northern Europe: empirical downscaling of multiple AOGCMs. Climate Res., 29, 183198.

    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., , J. T. Schoof, , and R. J. Barthelmie, 2006: Winds of change?: Projections of near-surface winds under climate change scenarios. Geophys. Res. Lett., 33, L11702, doi:10.1029/2006GL026000.

    • Search Google Scholar
    • Export Citation
  • Ren, D., 2010: Effects of global warming on wind energy availability. J. Renewable Sustainable Energy, 2, 052301, doi:10.1063/1.3486072.

    • Search Google Scholar
    • Export Citation
  • Sanabria, L. A., , and R. P. Cechet, 2010: Severe wind hazard using dynamically downscaled climate simulations. IOP Conf. Ser.: Earth Environ. Sci., 11, 012021, doi:10.1088/1755-1315/11/1/012021.

    • Search Google Scholar
    • Export Citation
  • Schwierz, C., , P. Köllner-Heck, , E. Z. Mutter, , D. N. Bresch, , P.-L. Vidale, , M. Wild, , and C. Schär, 2010: Modelling European winter wind storm losses in current and future climate. Climatic Change, 101, 485514, doi:10.1007/s10584-009-9712-1.

    • Search Google Scholar
    • Export Citation
  • Shen, S. S. P., , P. Dzikowski, , G. Li, , and D. Griffith, 2001: Interpolation of 1961–97 daily temperature and precipitation data onto Alberta polygons of ecodistrict and soil landscapes of Canada. J. Appl. Meteor., 40, 21622177.

    • Search Google Scholar
    • Export Citation
  • Sparks, P. R., , and Z. Huang, 2001: Gust factors and surface-to-gradient wind-speed ratios in tropical cyclones. J. Wind Eng. Ind. Aerodyn., 89, 10471058.

    • Search Google Scholar
    • Export Citation
  • Weggel, J. R., 1999: Maximum daily wind gusts related to mean daily wind speed. J. Struct. Eng., 125, 465468.

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Possible Impacts of Climate Change on Wind Gusts under Downscaled Future Climate Conditions over Ontario, Canada

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  • 1 Atmospheric Science and Applications Unit, Meteorological Service of Canada Branch, Environment Canada, Toronto, Ontario, Canada
  • 2 Adaptation and Impacts Research Division, Science and Technology Branch, Environment Canada, Toronto, Ontario, Canada
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Abstract

Hourly/daily wind gust simulation models and regression-based downscaling methods were developed to assess possible impacts of climate change on future hourly/daily wind gust events over the province of Ontario, Canada. Since the climate/weather validation process is critical, a formal model result verification process has been built into the analysis to ascertain whether the methods are suitable for future projections. The percentage of excellent and good simulations among all studied seven wind gust categories ranges from 94% to 100% and from 69% to 95%, respectively, for hourly and daily wind gusts, for both model development and validation.

The modeled results indicate that frequencies of future hourly/daily wind gust events are projected to increase late this century over the study area under a changing climate. For example, across the study area, the annual mean frequency of future hourly wind gust events ≥28, ≥40, and ≥70 km h−1 for the period 2081–2100 derived from the ensemble of downscaled eight-GCM A2 simulations is projected to be about 10%–15%, 10%–20%, and 20%–40% greater than the observed average during the period 1994–2007, respectively. The corresponding percentage increase for future daily wind gust events is projected to be <10%, ~10%, and 15%–25%. Inter-GCM-model and interscenario uncertainties of future wind gust projections were quantitatively assessed. On average, projected percentage increases in frequencies of future hourly/daily wind gust events ≥28 and ≥40 km h−1 are about 90%–100% and 60%–80% greater than inter-GCM-model–interscenario uncertainties, respectively. For wind gust events ≥70 km h−1, the corresponding projected percentage increases are about 25%–35% greater than the interscenario uncertainties and are generally similar to inter-GCM-model uncertainties.

Corresponding author address: Chad Shouquan Cheng, Atmospheric Science and Applications Unit, Meteorological Service of Canada Branch, Environment Canada, 4905 Dufferin Street, Toronto ON M3H 5T4, Canada. E-mail: shouquan.cheng@ec.gc.ca

Abstract

Hourly/daily wind gust simulation models and regression-based downscaling methods were developed to assess possible impacts of climate change on future hourly/daily wind gust events over the province of Ontario, Canada. Since the climate/weather validation process is critical, a formal model result verification process has been built into the analysis to ascertain whether the methods are suitable for future projections. The percentage of excellent and good simulations among all studied seven wind gust categories ranges from 94% to 100% and from 69% to 95%, respectively, for hourly and daily wind gusts, for both model development and validation.

The modeled results indicate that frequencies of future hourly/daily wind gust events are projected to increase late this century over the study area under a changing climate. For example, across the study area, the annual mean frequency of future hourly wind gust events ≥28, ≥40, and ≥70 km h−1 for the period 2081–2100 derived from the ensemble of downscaled eight-GCM A2 simulations is projected to be about 10%–15%, 10%–20%, and 20%–40% greater than the observed average during the period 1994–2007, respectively. The corresponding percentage increase for future daily wind gust events is projected to be <10%, ~10%, and 15%–25%. Inter-GCM-model and interscenario uncertainties of future wind gust projections were quantitatively assessed. On average, projected percentage increases in frequencies of future hourly/daily wind gust events ≥28 and ≥40 km h−1 are about 90%–100% and 60%–80% greater than inter-GCM-model–interscenario uncertainties, respectively. For wind gust events ≥70 km h−1, the corresponding projected percentage increases are about 25%–35% greater than the interscenario uncertainties and are generally similar to inter-GCM-model uncertainties.

Corresponding author address: Chad Shouquan Cheng, Atmospheric Science and Applications Unit, Meteorological Service of Canada Branch, Environment Canada, 4905 Dufferin Street, Toronto ON M3H 5T4, Canada. E-mail: shouquan.cheng@ec.gc.ca
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