Climatic Change

, Volume 115, Issue 3–4, pp 821–835 | Cite as

Assessing the potential impact of climate change on the UK’s electricity network

  • Lynsey McColl
  • Erika J. Palin
  • Hazel E. Thornton
  • David M. H. Sexton
  • Richard Betts
  • Ken Mylne
Article

Abstract

We investigate how weather affects the UK’s electricity network, by examining past data of weather-related faults on the transmission and distribution networks. By formalising the current relationship between weather-related faults and weather, we use climate projections from a regional climate model (RCM) to quantitatively assess how the frequency of these faults may change in the future. This study found that the incidences of both lightning and solar heat faults are projected to increase in the future. There is evidence that the conditions that cause flooding faults may increase in the future, but a reduction cannot be ruled out. Due to the uncertainty associated with future wind projections, there is no clear signal associated with the future frequency of wind and gale faults, however snow, sleet and blizzard faults are projected to decrease due to a reduction in the number of snow days.

Supplementary material

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10584_2012_469_MOESM3_ESM.pdf (373 kb)
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References

  1. Berrisford P, Dee D, Fielding K et al (2009) The ERA-Interim archive. ERA Report Series 1, European Centre for Medium Range Forecasting (ECMWF)Google Scholar
  2. CEH (1999) Flood estimation handbook. Institute of Hydrology, WallingfordGoogle Scholar
  3. Collins M, Booth BBB, Harris GR et al (2006) Towards quantifying uncertainty in transient climate change. Clim Dyn 27(2–3):127–147. doi:10.1007/s00382-006-0121-0 CrossRefGoogle Scholar
  4. Collins M, Booth BBB, Bhaskaran B et al (2011) A comparison of perturbed physics and multi-model ensembles: Model errors, feedbacks and forcings. Clim Dyn 36:1737–1766CrossRefGoogle Scholar
  5. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597CrossRefGoogle Scholar
  6. Efron B (1979) Bootstrap methods: another look at the jackknife. Ann Stat 7(1):1–26CrossRefGoogle Scholar
  7. Friedlingstein P, Cox PM, Betts RA et al (2006) Climate–carbon cycle feedback analysis, results from the C4MIP model intercomparison. J Climate 19(14):3337–3353. doi:10.1175/JCLI3800.1 CrossRefGoogle Scholar
  8. Gordon C, Cooper C, Senior CA et al (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168CrossRefGoogle Scholar
  9. Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90(8):1095–1107CrossRefGoogle Scholar
  10. Jones RG, Murphy JM, Noguer M (1995) Simulation of climate change over Europe using a nested regional–climate model. I: assessment of control climate, including sensitivity to location of lateral boundaries. Q J R Meteorol Soc 121:1413–1449Google Scholar
  11. Li H, Sheffield J, Wood EF (2010) Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching. J Geophys Res 115:187–192Google Scholar
  12. Mauran D, Wetterhall F, Ireson AM et al (2010) Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48:RG3003Google Scholar
  13. Murphy JM, Sexton DMH, Jenkins GJ et al (2009) UK climate projections science report: climate change projectionsGoogle Scholar
  14. Nakicenovic N, Alcamo J, David G et al (2000) IPCC special report on emissions scenarios. Cambridge University Press, Cambridge and New YorkGoogle Scholar
  15. Perry M, Hollis D (2005) The generation of monthly gridded datasets for a range of climatic variables over the United Kingdom. Int J Climatol 25:1041–1054CrossRefGoogle Scholar
  16. Perry M, Hollis D, Elms M (2009) The generation of daily gridded datasets for temperature and rainfall for the UK. Climate memorandum no 24, NCICGoogle Scholar
  17. Piani C, Haerter JO, Coppola E (2010) Statistical bias correction for daily precipitation in regional climate models over Europe. Theor Appl Climatol 99:187–192CrossRefGoogle Scholar
  18. Thornton H, Mathison C, Palin E et al (2011) The impact of climate change on the GB rail network. Consultancy report, Met Office Hadley CentreGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Lynsey McColl
    • 1
  • Erika J. Palin
    • 1
  • Hazel E. Thornton
    • 1
  • David M. H. Sexton
    • 1
  • Richard Betts
    • 1
  • Ken Mylne
    • 1
  1. 1.Met Office Hadley CentreExeterUK

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