Climatic Change

, Volume 120, Issue 1–2, pp 71–93 | Cite as

Future projections of temperature-related climate change impacts on the railway network of Great Britain

  • Erika J. PalinEmail author
  • Hazel E. Thornton
  • Camilla T. Mathison
  • Rachel E. McCarthy
  • Robin T. Clark
  • John Dora


Great Britain’s main line railway network is known to experience various temperature-related impacts, e.g. track buckling and overhead power line sag at high ambient temperatures. Climate change could alter the frequency of occurrence of these impacts. We have therefore investigated the climate change impact on various temperature-related issues, identified during workshops with rail industry specialists, using a perturbed physics ensemble (PPE) of the Met Office’s regional climate model (RCM), HadRM3. We have developed novel approaches to combine RCM data with railway industry knowledge, typically by identifying key meteorological thresholds of interest and analysing exceedance of these out to the 2040s. We performed a statistical analysis of the projected changes for each issue, via bootstrapping of the unperturbed PPE member. Although neither the PPE nor the bootstrapping analysis samples the full range of uncertainty in the projections, they nonetheless provide complementary perspectives on the suitability of the projections for use in decision-making. Our main findings include projected increases in the summertime occurrence of temperature conditions associated with (i) track buckling, (ii) overhead power line sag, (iii) exposure of outdoor workers to heat stress, and (iv) heat-related delays to track maintenance; and (v) projected decreases in the wintertime occurrence of temperatures conditions associated with freight train failure owing to brake problems. For (i), the statistical significance varied with track condition and location; for (ii) and (iii), with location; and for (iv) and (v), projected changes were significant across Great Britain. As well as assessing the changes in climate-related hazard, information about the vulnerability of the network to past temperature-related incidents has been summarised. Combining the hazard and vulnerability elements will eventually support a climate risk assessment for the industry.


Regional Climate Model Ensemble Member Track Condition Railway Network Network Rail 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was undertaken as part of “Tomorrow’s Railway and Climate Change Adaptation” (TRaCCA research project T925), a rail industry project supported by the industry’s Technical Strategy Leadership Group (TSLG) and funded by the Department for Transport (DfT) through the ‘Rail Industry Strategic Research Programme’ managed by the Rail Safety and Standards Board (RSSB). We acknowledge the support of RSSB, Network Rail and other rail stakeholders for their assistance, particularly through the various stakeholder workshops which took place throughout the project. Aspects of the follow-on analysis from TRaCCA research project T925 were funded by the Met Office.

We thank Richard Betts, Kate Brown, Lynsey McColl, Debbie Hemming and Elizabeth Kendon for useful discussions and advice during the project.

Supplementary material

10584_2013_810_MOESM1_ESM.pdf (266 kb)
(PDF 266 KB)


  1. Andrade C, Leite S, Santos J (2012) Temperature extremes in Europe: overview of their driving atmospheric patterns. Nat Hazards Earth Syst Sci 12:1671–1691CrossRefGoogle Scholar
  2. Baker CJ, Chapman L, Quinn A, Dobney K (2010) Climate change and the railway industry: a review. Proc Inst Mech Eng C—J Mech Eng Sci 224:519–528CrossRefGoogle Scholar
  3. Ballester J, Giorgi F, Rodo X (2010) Changes in European temperature extremes can be predicted from changes in PDF central statistics. Clim Change 98:277–284CrossRefGoogle Scholar
  4. Beniston M, Stephenson DB, Christensen OB, Ferro CAT, Frei C, Goyette S, Halsnaes K, Holt T, Jylha K, Koffi B, Palutikof J, Schoell R, Semmler T, Woth K (2007) Future extreme events in European climate: an exploration of regional climate model projections. Clim Change 81:71–95CrossRefGoogle Scholar
  5. Brown SJ, Caesar J, Ferro CAT (2008) Global changes in extreme daily temperature since 1950. J Geophys Res Atmos 113, article no. D05115Google Scholar
  6. Chapman L, Thornes JE, Huang Y, Cai X, Sanderson VL, White SP (2008) Modelling of rail surface temperatures: a preliminary study. Theor Appl Climatol 92:121–131CrossRefGoogle Scholar
  7. Clark RT, Brown SJ, Murphy JM (2006) Modeling northern hemisphere summer heat extreme changes and their uncertainties using a physics ensemble of climate sensitivity experiments. J Clim 19:4418–4435CrossRefGoogle Scholar
  8. Collins M, Booth BBB, Harris GR, Murphy JM, Sexton DMH, Webb MJ (2006) Towards quantifying uncertainty in transient climate change. Clim Dyn 27:127–147. doi: 10.1007/s00382-006-0121-0 CrossRefGoogle Scholar
  9. Cony M, Martin L, Hernandez E, Del Teso T (2010) Synoptic patterns that contribute to extremely hot days in Europe. Atmosfera 23:295–306Google Scholar
  10. Cook J (1988) Design for maintenance. In: Institution of Civil Engineers (ed) Urban railways and the civil engineer. Thomas Telford, London, pp 229–241Google Scholar
  11. Council for Science and Technology (2009) A national infrastructure for the 21st Century. Tech. rep., Accessed 23 April 2013
  12. Defra (2010) Adaptation reporting power—frequently asked questions and answers. Accessed 17 January 2013
  13. Dobney K (2010) Quantifying the effects of an increasingly warmer climate with a view to improving the resilience of the UK railway network: is a new stressing regime the answer? PhD thesis, The University of BirminghamGoogle Scholar
  14. Dobney K, Baker CJ, Quinn AD, Chapman L (2009) Quantifying the effects of high summer temperatures due to climate change on buckling and rail related delays in south-east United Kingdom. Meteorol Appl 16:245–251CrossRefGoogle Scholar
  15. Dobney K, Baker C, Chapman L, Quinn A (2010) The future cost to the United Kingdom’s railway network of heat-related delays and buckles caused by the predicted increase in high summer temperatures owing to climate change. Proc Inst Mech Eng F—J Rail and Rapid Transit 224: 25–34CrossRefGoogle Scholar
  16. Efron B (1979) Bootstrap methods: another look at the jackknife. Ann Stat 7(1):1–26CrossRefGoogle Scholar
  17. Fischer EM, Schaer C (2009) Future changes in daily summer temperature variability: driving processes and role for temperature extremes. Clim Dyn 33:917–935CrossRefGoogle Scholar
  18. Fischer EM, Rajczak J, Schaer C (2012) Changes in European summer temperature variability revisited. Geophys Res Lett 39, article no. L19702Google Scholar
  19. Frias MD, Minguez R, Gutierrez JM, Mendez FJ (2012) Future regional projections of extreme temperatures in Europe: a nonstationary seasonal approach. Clim Change 113:371–392CrossRefGoogle Scholar
  20. Friedlingstein P, Cox PM, Betts RA, Bopp L, von Bloh W, Brovkin V, Cadule P, Doney S, Eby M, Fung I, Bala G, John J, Jones CD, Joos F, Kato T, Kawamiya M, Knorr W, Lindsay K, Matthews HD, Raddatz T, Rayner P, Reick C, Roeckner E, Schnitzler KG, Schnur R, Strassmann K, Weaver AJ, Yoshikawa C, Zeng N (2006) Climate–carbon cycle feedback analysis, results from the C4MIP model intercomparison. J Clim 19:3337–3353CrossRefGoogle Scholar
  21. Giorgi F, Coppola E (2009) Projections of twenty-first century climate over Europe. In: Boutron C (ed) ERCA: from the human dimensions of global environmental change to the observation of the Earth from space, vol 8. EPJ web of conferences, vol 1, pp 29–46Google Scholar
  22. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA (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
  23. Hall J, Henriques J, Hickford A, Nicholls R (2012) A fast track analysis of strategies for infrastructure provision in Great Britain. Tech. rep., UK Infrastructure Transitions Research Consortium, Environmental Change Institute, University of Oxford. Accessed 23 April 2013
  24. Hashino T, Bradley AA, Schwartz SS (2007) Evaluation of bias-correction methods for ensemble streamflow volume forecasts. Hydrol Earth Syst Sci 11:939–950CrossRefGoogle Scholar
  25. Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095–1107CrossRefGoogle Scholar
  26. HR Wallingford (2012) The UK Climate Change Risk Assessment 2012. Accessed 23 April 2013
  27. Hunt GA (1994) An analysis of track buckling risk. Tech. Rep. RRTM013, British RailwaysGoogle Scholar
  28. IPCC (2012a) Managing the risks of extreme events and disasters to advance climate change adaptation. In: A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge/New York 582 ppGoogle Scholar
  29. IPCC (2012b) Summary for policymakers. In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner GK, Allen SK, Tignor M, Midgley PM (eds) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge/New York, pp 3–21Google Scholar
  30. Jenkins GJ, Perry MC, Prior MJ (2009) The climate of the United Kingdom and recent trends. Met Office Hadley Centre, ExeterGoogle Scholar
  31. Jones C, Thompson D (2001) Means of controlling noise at source. In: Krylov V (ed) Noise and vibration from high-speed trains. Thomas Telford, London, pp 163–184Google Scholar
  32. 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
  33. Koffi B, Koffi E (2008) Heat waves across Europe by the end of the 21st century: multiregional climate simulations. Clim Res 36:153–168CrossRefGoogle Scholar
  34. Mastrandrea MD, Field CB, Stocker TF, Edenhofer O, Ebi KL, Frame DJ, Held H, Kriegler E, Mach KJ, Matschoss PR, Plattner GK, Yohe GW, Zwiers FW (2010) Guidance note for lead authors of the IPCC 5th Assessment Report on consistent treatment of uncertainties. Intergovernmental Panel on Climate Change (IPCC). Accessed 17 January 2013
  35. McColl LJ, Palin EJ, Thornton HE, Sexton DMH, Betts R, Mylne K (2012) Assessing the potential impact of climate change on the UK’s electricity network. Clim Change 115:821–835CrossRefGoogle Scholar
  36. Murphy JM, Sexton DMH, Jenkins GJ, Boorman PM, Booth BBB, Brown CC, Clark RT, Collins M, Harris GR, Kendon EJ, Betts RA, Brown SJ, Howard TP, Humphrey KA, McCarthy MP, McDonald RE, Stephens A, Wallace C, Warren R, Wilby R, Wood RA (2009) UK climate projections science report: climate change projections. Met Office Hadley Centre, ExeterGoogle Scholar
  37. Nakićenović N, Alcamo J, David G, de Vries B, Fenhann J, Gaffin S, Gregory K, Grübler A, Jung TY, Kram T, Rovere ELL, Michaelis L, Mori S, Morita T, Pepper W, Pitcher H, Price L, Riahi K, Roehrl A, Rogner H, Sankovski A, Schlesinger M, Shukla P, Smith S, Swart R, van Rooijen S, Victor N, Dadi Z (2000) IPCC special report on emissions scenarios. Cambridge University Press, Cambridge/New YorkGoogle Scholar
  38. Network Rail (2006) NR/GN/ELP/27088 business process document, “Layout of overhead line equipment”Google Scholar
  39. Nguyen M, Wang X, Wang CH (2012) A reliability assessment of railway track buckling during an extreme heatwave. Proc Inst Mech Eng F—J Rail Rapid Transit 226:513–517CrossRefGoogle Scholar
  40. Nikulin G, Kjellstrom E, Hansson U, Strandberg G, Ullerstig A (2011) Evaluation and future projections of temperature, precipitation and wind extremes over Europe in an ensemble of regional climate simulations. Tellus Ser A—Dyn Meteorol Oceanogr 63:41–55CrossRefGoogle Scholar
  41. Orlowsky B, Seneviratne SI (2012) Global changes in extreme events: regional and seasonal dimension. Clim Change 110:669–696CrossRefGoogle Scholar
  42. Perry M, Hollis D (2005) The generation of monthly gridded datasets for a range of climatic variables over the United Kingdom. J Climatol 25:1041–1054CrossRefGoogle Scholar
  43. Perry M, Hollis D, Elms M (2009) The generation of daily gridded datasets for temperature and rainfall for the UK. Climate Memorandum no. 24, National Climate Information Centre. Accessed 17 January 2013
  44. 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
  45. Rail Accident Investigation Branch (2011) Rail accident report: derailment of a freight train at Carrbridge, Badenoch and Strathspey. Report no. 03/2011, 4 January 2010Google Scholar
  46. Royal Academy of Engineering (2011) Engineering the future: infrastructure, engineering and climate change adaptation—ensuring services in an uncertain future. Accessed 23 April 2013
  47. RSSB (2003) Safety implications of weather, climate and climate change. Issue 2, AEAT/RAIR/76148/R03/005.,%20climate%20and%20climate%20change.pdf. Accessed 17 January 2013
  48. RSSB (2006) T626 when to evacuate trains based on ambient temperatures—preliminary findings. Accessed 17 January 2013
  49. RSSB (2010) Tomorrow’s railway and climate change adaptation: Phase 1 report. Accessed 17 January 2013
  50. Rummukainen M (2012) Changes in climate and weather extremes in the 21st century. Wiley Interdiscip Rev—Clim Change 3:115–129CrossRefGoogle Scholar
  51. Scaife A, Folland C, Alexander L, Moberg A, Knight J (2008) European climate extremes and the North Atlantic Oscillation. J Clim 21:72–83CrossRefGoogle Scholar
  52. Simolo C, Brunetti M, Maugeri M, Nanni T (2011) Evolution of extreme temperatures in a warming climate. Geophys Res Lett 38, article no. L16701Google Scholar
  53. Taubenböck H, Post J, Roth A, Zosseder K, Strunz G, Dech S (2008) A conceptual vulnerability and risk framework as outline to identify capabilities of remote sensing. Nat Hazards Earth Syst Sci 8:409–420CrossRefGoogle Scholar
  54. Thornes J, Rennie M, Marsden H, Chapman L (2012) Climate Change Risk Assessment for the transport sector. Tech. Rep. EX 6426, HR WallingfordGoogle Scholar
  55. Thornton H, Mathison C, Palin E, Liggins F, Wilson M, Sanderson M, de Gusmão D, McCarthy R (2011) The impact of climate change on the GB rail network. Consultancy report, Met Office Hadley CentreGoogle Scholar
  56. van den Besselaar E, Klein Tank A, van der Schrier G (2010) Influence of circulation types on temperature extremes in Europe. Theor Appl Climatol 99:431–439CrossRefGoogle Scholar
  57. Willett KM, Sherwood S (2012) Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. Int J Climatol 32:161–177CrossRefGoogle Scholar
  58. Wood AW, Leung LR, Sridhar V, Lettenmaier DP (2004) Implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62:189–216CrossRefGoogle Scholar

Copyright information

© © Crown Copyright as represented by: Met Office 2013

Authors and Affiliations

  • Erika J. Palin
    • 1
    Email author
  • Hazel E. Thornton
    • 1
  • Camilla T. Mathison
    • 1
  • Rachel E. McCarthy
    • 1
  • Robin T. Clark
    • 1
  • John Dora
    • 2
  1. 1.Met Office Hadley CentreExeterUK
  2. 2.John Dora Consulting LimitedCharlburyUK

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