1980–2010 Variability in U.K. Surface Wind Climate

Nick Earl School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

Search for other papers by Nick Earl in
Current site
Google Scholar
PubMed
Close
,
Steve Dorling School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

Search for other papers by Steve Dorling in
Current site
Google Scholar
PubMed
Close
,
Richard Hewston Department of Meteorology, University of Hawaii at Manoa, Honolulu, Hawaii

Search for other papers by Richard Hewston in
Current site
Google Scholar
PubMed
Close
, and
Roland von Glasow School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom

Search for other papers by Roland von Glasow in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameter k spatially varying from 1.4 to 2.1, highlighting that the commonly assumed k = 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors' analyses place the particularly “low wind” year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.

Corresponding author address: Nick Earl, School of Environmental Sciences, University of East Anglia, Norwich, Norwich Research Park, Norwich NR4 7TJ, United Kingdom. E-mail: n.earl@uea.ac.uk

Abstract

The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameter k spatially varying from 1.4 to 2.1, highlighting that the commonly assumed k = 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors' analyses place the particularly “low wind” year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.

Corresponding author address: Nick Earl, School of Environmental Sciences, University of East Anglia, Norwich, Norwich Research Park, Norwich NR4 7TJ, United Kingdom. E-mail: n.earl@uea.ac.uk
Save
  • Atkinson, N., K. Harman, M. Lynn, A. Schwarz, and A. Tindal, 2006: Long-term windspeed trends in northwestern Europe. Garrad Hassan Tech. Rep., 4 pp. [Available online at http://www.gl-garradhassan.com/assets/downloads/Long_term_wind_speed_trends_in_northwestern_Europe.pdf.]

  • Barriopedro, D., R. García-Herrera, A. R. Lupo, and E. Hernández, 2006: A climatology of Northern Hemisphere blocking. J. Climate, 19, 10421063.

    • Search Google Scholar
    • Export Citation
  • Barriopedro, D., R. García-Herrera, and R. Huth, 2008: Solar modulation of Northern Hemisphere winter blocking. J. Geophys. Res., 113, D14118, doi:10.1029/2008JD009789.

    • Search Google Scholar
    • Export Citation
  • Boccard, N., 2009: Capacity factor of wind power realized values vs. estimates. Energy Policy, 37, 26792688.

  • Brayshaw, D. J., A. Troccoli, R. Fordham, and J. Methven, 2011: The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the U.K.. Renewable Energy, 36, 20872096.

    • Search Google Scholar
    • Export Citation
  • Brown, S., P. Boorman, R. McDonald, and J. Murphy, 2009: Interpretation for use of surface windspeed projections from the 11-member Met Office Regional Climate Model ensemble. UKCP09 Tech. Note, 22 pp. [Available online at http://ukclimateprojections.defra.gov.uk/media.jsp?mediaid=87947&filetype=pdf.]

  • Cattiaux, J., R. Vautard, C. Cassou, P. Yiou, V. Masson-Delmotte, and F. Codron, 2010: Winter 2010 in Europe: A cold extreme in a warming climate. Geophys. Res. Lett., 37, L20704, doi:10.1029/2010GL044613.

    • Search Google Scholar
    • Export Citation
  • Celik, A. N., 2004: A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey. Renewable Energy, 29, 593604.

    • Search Google Scholar
    • Export Citation
  • Cheng, X., S. Xie, H. Tokinaga, and Y. Du, 2011: Interannual variability of high-wind occurrence over the North Atlantic. J. Climate, 24, 65156527.

    • Search Google Scholar
    • Export Citation
  • Dacre, H. F., and S. L. Gray, 2009: The spatial distribution and evolution characteristics of North Atlantic cyclones. Mon. Wea. Rev., 137, 99115.

    • Search Google Scholar
    • Export Citation
  • Forster, D., M. Benzie, S. Winne, and R. Milnes, 2011: Evaluation of the climate risks for meeting the UK's carbon budgets. AEA Technology plc, Rep. for Committee on Climate Change ED56732- 3, 151 pp. [Available online at http://hmccc.s3.amazonaws.com/Progress%202011/ED56732_FinalReport_FINALv2.pdf.]

  • Gronas, S., 1995: The seclusion intensification of the New Year's Day storm 1992. Tellus, 47A, 733746.

  • Harrison, G., L. C. Cradden, and J. P. Chick, 2008: Preliminary assessment of climate change impacts on the U.K. onshore wind energy resource. Energy Sources, 30, 12861299.

    • Search Google Scholar
    • Export Citation
  • Hawkins, E., and R. Sutton, 2009: The potential to narrow uncertainty in regional climate predictions. Bull. Amer. Meteor. Soc., 90, 10951107.

    • Search Google Scholar
    • Export Citation
  • Hess, P., and H. Brezowsky, 1952: Katalog der Grosswetterlagen Europas. Berichte das Deutschen Wetterdienstes in der US-Zone 33, 39 pp.

  • Hewston, R., 2008: Weather, climate and the insurance sector. Ph.D. dissertation, University of East Anglia, 312 pp.

  • Hewston, R., and S. R. Dorling, 2011: An analysis of observed maximum wind gusts in the U.K.. J. Wind Eng. Ind. Aerodyn., 99, 845856, doi:10.1016/j.jweia.2011.06.004.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., Y. Kushnir, G. Ottersen, and M. Visbeck, 2003: The North Atlantic Oscillation: Climate Significance and Environmental Impact. Geophys. Monogr., Vol. 134, Amer. Geophys. Union, 279 pp.

  • Irwin, J. S., 1979: A theoretical variation of the wind profile power-law exponent as a function of surface roughness and stability. Atmos. Environ., 13, 191194.

    • Search Google Scholar
    • Export Citation
  • James, P. M., 2007: An objective classification method for Hess and Brezowsky Grosswetterlagen over Europe. Theor. Appl. Climatol., 88, 1742.

    • Search Google Scholar
    • Export Citation
  • Jamil, M., S. Parsa, and M. Majidi, 1995: Wind power statistics and an evaluation of wind energy density. Renewable Energy, 6, 623628.

    • Search Google Scholar
    • Export Citation
  • Jenkinson, A. F., and F. P. Collison, 1977: An initial climatology of gales over the North Sea. Met Office, Synoptic Climatology Branch Memo. 62, 18 pp.

  • Jones, P. D., M. Hulme, and K. R. Briffa, 1993: A comparison of Lamb circulation types with an objective classification scheme. Int. J. Climatol., 13, 655663.

    • Search Google Scholar
    • Export Citation
  • Jones, P. D., T. Jonsson, and D. Wheeler, 1997: Extension to the North Atlantic oscillation using early instrumental pressure observations from Gibraltar and south-west Iceland. Int. J. Climatol., 17, 14331450.

    • Search Google Scholar
    • Export Citation
  • Jung, T., F. Vitart, L. Ferranti, and J. Morcrette, 2011: Origin and predictability of the extreme negative and NAO winter of 2009/10. Geophys. Res. Lett., 38, L07701, doi:10.1029/2011GL046786.

    • Search Google Scholar
    • Export Citation
  • Justus, C. G., W. R. Hargraves, and A. Yalcin, 1976: Nationwide assessment of potential output from wind powered generators. J. Appl. Meteor., 15, 673678.

    • Search Google Scholar
    • Export Citation
  • Klawa, M., and U. Ulbrich, 2003: A model for the estimation of storm losses and the identification of severe winter storms in Germany. Nat. Hazards Earth Syst. Sci., 3, 725732.

    • Search Google Scholar
    • Export Citation
  • Kremer, E., 1998: Largest claims reinsurance premiums for the Weibull model. Blätter Dt. Ges. Versicherungsmath.,23, 279–284.

  • Lockwood, M., R. G. Harrison, T. Woolings, and S. K. Solanki, 2010: Are cold winters in Europe associated with low solar activity? Environ. Res. Lett., 5, 024001, doi:10.1088/1748-9326/5/2/024001.

    • Search Google Scholar
    • Export Citation
  • Lockwood, M., R. G. Harrison, M. J. Owens, L. Barnard, T. Woollings, and F. Steinhilber, 2011: The solar influence on the probability of relatively cold U.K. winters in the future. Environ. Res. Lett., 6, 034004, doi:10.1088/1748-9326/6/3/034004.

    • Search Google Scholar
    • Export Citation
  • Malmquist, D. L., Ed., 1999: European windstorms and the North Atlantic Oscillation: Impacts, characteristics, and predictability. RPI Series 2, Risk Prediction Initiative/Bermuda Biological Station for Research, 21 pp.

  • McCallum, E., 1990: The Burns' day storm, 25 January 1990. Weather, 45, 166173.

  • Motta, M., R. J. Barthelmie, and P. Vølund, 2005: The influence of non-logarithmic wind speed profiles on potential power output at Danish offshore sites. Wind Energy, 8, 219236.

    • Search Google Scholar
    • Export Citation
  • Munich Re, 2002: Winter storms in Europe (II): Analysis of 1999 losses and loss potentials. Munich Reinsurance Company, 72 pp.

  • Osborn, T. J., 2011: Winter 2009/2010 temperatures and a record-breaking North Atlantic Oscillation index. Weather, 66, 1921.

  • Oswald, J., M. Raine, and A. Ashraf-Ball, 2008: Will British weather provide reliable electricity? Energy Policy, 36, 32123225.

  • Petersen, E. L., N. J. Mortensen, L. Landberg, J. Højstrup, and P. F. Helmut, 1998: Wind power meteorology. Part I: Climate and turbulence. Wind Energy, 1, 2545.

    • Search Google Scholar
    • Export Citation
  • Pöyry, 2011: The challenges of intermittency in North West European power markets. Summary Rep., 16 pp.

  • Pryor, S. C., and R. J. Barthelmie, 2010: Climate change impacts on wind energy: A review. Renewable Sustainable Energy Rev., 14, 430437.

    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., M. Nielsen, R. J. Barthelmie, and J. Mann, 2004: Can satellite sampling of offshore wind speeds realistically represent wind speed distributions? Part II: Quantifying uncertainties associated with sampling strategy and distribution fitting methods. J. Appl. Meteor., 43, 739750.

    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., R. J. Barthelmie, N. E. Clausen, M. Drew, I. MacKellar, and E. Kjellström, 2012: Analyses of possible changes in intense and extreme windspeeds over northern Europe under climate change scenarios. Climate Dyn., 38, 189208, doi:10.1007/s00382-010-0955-3.

    • Search Google Scholar
    • Export Citation
  • Rodwell, M. J., D. P. Rowell, and C. K. Folland, 1999: Oceanic forcing of the wintertime North Atlantic Oscillation and European climate. Nature, 398, 320323.

    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and Coauthors, 2012: Climate change projections and stratosphere–troposphere interaction. Climate Dyn.,38, 2089–2097, doi:10.1007/s00382-011-1080-7.

  • Seguro, J. V., and T. W. Lambert, 2000: Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. J. Wind Eng. Ind. Aerodyn., 85, 7584.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., F. Carse, R. G. Barry, and J. C. Rogers, 1997: Icelandic low cyclone activity: Climatological features, linkages with the NAO, and relationships with recent changes in the Northern Hemisphere circulation. J. Climate, 10, 453464.

    • Search Google Scholar
    • Export Citation
  • Sinden, G., 2007: Characteristics of the U.K. wind resource: Long-term patterns and relationship to electricity demand. Energy Policy, 35, 112127.

    • Search Google Scholar
    • Export Citation
  • Swiss Re, 2011: Natural catastrophes and man-made disasters in 2010: A year of devastating and costly events. Sigma Rep. 1/2011, 36 pp. [Available online at http://media.swissre.com/documents/sigma1_2011_en.pdf.]

  • Takle, E. S., and J. M. Brown, 1978: Note on the use of Weibull statistics to characterize wind-speed data. J. Appl. Meteor., 17, 556559.

    • Search Google Scholar
    • Export Citation
  • Troccoli, A., K. Muller, P. Coppin, R. Davy, C. Russell, and A. L. Hirsch, 2012: Long-term wind speed trends over Australia. J. Climate, 25, 170183.

    • Search Google Scholar
    • Export Citation
  • UKMO, cited 2011: Met Office surface data users guide. [Available online at http://badc.nerc.ac.uk/data/ukmo-midas/ukmo_guide.html.]

  • Ulbrich, U., G. C. Leckebusch, and J. G. Pinto, 2009: Extra-tropical cyclones in the present and future climate: A review. Theor. Appl. Climatol., 96, 117131.

    • Search Google Scholar
    • Export Citation
  • Vautard, R., J. Cattiaux, P. Yiou, J. Thépaut, and P. Ciais, 2010: Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat. Geosci., 3, 756761, doi:10.1038/ngeo979.

    • Search Google Scholar
    • Export Citation
  • Wang, X. L., F. W. Zwiers, V. R. Swail, and Y. Feng, 2009: Trends and variability of storminess in the northeast Atlantic region, 1874–2007. Climate Dyn., 33, 11791195.

    • Search Google Scholar
    • Export Citation
  • Weisser, D., 2003: A wind energy analysis of Grenada: An estimation using the ‘Weibull' density function. Renewable Energy, 28, 18031812.

    • Search Google Scholar
    • Export Citation
  • Wheeler, D., and J. Mayes, 1997: Regional Climates of the British Isles. Routledge, 437 pp.

  • Wilks, D. S., 1990: Maximum likelihood estimation for the gamma distribution using data containing zeros. J. Climate, 3, 14951501.

  • Woollings, T., 2010: Dynamical influences on European climate: An uncertain future. Philos. Trans. Roy. Soc., 368A, 37333756, doi:10.1098/rsta.2010.0040.

    • Search Google Scholar
    • Export Citation
  • Woollings, T., M. Lockwood, G. Masato, C. Bell, and L. Gray, 2010: Enhanced signature of solar variability in Eurasian winter climate. Geophys. Res. Lett., 37, L20805, doi:10.1029/2010GL044601.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1185 305 14
PDF Downloads 1063 223 8