International Journal of Biometeorology

, Volume 59, Issue 7, pp 799–814 | Cite as

The effect of urban geometry on mean radiant temperature under future climate change: a study of three European cities

  • Kevin Ka-Lun LauEmail author
  • Fredrik Lindberg
  • David Rayner
  • Sofia Thorsson
Original Paper


Future anthropogenic climate change is likely to increase the air temperature (T a ) across Europe and increase the frequency, duration and magnitude of severe heat stress events. Heat stress events are generally associated with clear-sky conditions and high T a , which give rise to high radiant heat load, i.e. mean radiant temperature (T mrt ). In urban environments, T mrt is strongly influenced by urban geometry. The present study examines the effect of urban geometry on daytime heat stress in three European cities (Gothenburg in Sweden, Frankfurt in Germany and Porto in Portugal) under present and future climates, using T mrt as an indicator of heat stress. It is found that severe heat stress occurs in all three cities. Similar maximum daytime T mrt is found in open areas in all three cities despite of the latitudinal differences in average daytime T mrt . In contrast, dense urban structures like narrow street canyons are able to mitigate heat stress in the summer, without causing substantial changes in T mrt in the winter. Although the T mrt averages are similar for the north–south and east–west street canyons in each city, the number of hours when T mrt exceeds the threshold values of 55.5 and 59.4 °C—used as indicators of moderate and severe heat stress—in the north–south canyons is much higher than that in the east–west canyons. Using statistically downscaled data from a regional climate model, it is found that the study sites were generally warmer in the future scenario, especially Porto, which would further exacerbate heat stress in urban areas. However, a decrease in solar radiation in Gothenburg and Frankfurt reduces T mrt in the spring, while the reduction in T mrt is somewhat offset by increasing T a in other seasons. It suggests that changes in the T mrt under the future scenario are dominated by variations in T a . Nonetheless, the intra-urban differences remain relatively stable in the future. These findings suggest that dense urban structure can reduce daytime heat stress since it reduces the number of hours of high T mrt in the summer and does not cause substantial changes in average and minimum T mrt in the winter. In dense urban settings, a more diverse urban thermal environment is also preferred to compensate for reduced solar access in the winter. The extent to which the urban geometry can be optimized for the future climate is also influenced by local urban characteristics.


Mean radiant temperature Radiant heat load SOLWEIG Urban geometry Statistical downscaling 



This work is financially supported by FORMAS, the Swedish Research Council for Environment, Agriculture Sciences and Spatial Planning, within the European Commission programme Urban-NET.


  1. Ali-Toudert F, Mayer H (2006) Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate. Build Environ 41:94–108CrossRefGoogle Scholar
  2. Andrade H, Alcoforado MJ (2008) Microclimatic variation of thermal comfort in a district of Lisbon (Telheiras) at night. Theor Appl Climatol 92(3–4):225–237CrossRefGoogle Scholar
  3. Andreou E (2013) Thermal comfort in outdoor spaces and urban canyon microclimate. Renew Energ 55:182–188CrossRefGoogle Scholar
  4. Benestad RE, Hanssen-Bauer I, Chen D (2008) Empirical-statistical downscaling. World Scientific Publishing, SingaporeCrossRefGoogle Scholar
  5. Christensen JH, Hewitson B, Busuioc A et al (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USAGoogle Scholar
  6. Cohen P, Potchter O, Matzarakis A (2012) Daily and seasonal climatic conditions of green urban open spaces in the Mediterranean climate and their impact on human comfort. Build Environ 51:285–295CrossRefGoogle Scholar
  7. D’Ippoliti D, Michelozzi P, Marino C et al (2010) The impact of heat waves on mortality in 9 European cities: results from the EuroHEAT project. Environ Health 9(1):37CrossRefGoogle Scholar
  8. Emmanuel R, Johansson E (2006) Influence of urban morphology and sea breeze on hot humid microclimate: the case of Colombo, Sri Lanka. Clim Res 30:189–200CrossRefGoogle Scholar
  9. Emmanuel R, Rosenlund H, Johansson E (2007) Urban shading - a design option for the tropics? A study in Colombo, Sri Lanka. Int J Climatol 27:1995–2004CrossRefGoogle Scholar
  10. Gulyás A, Unger J, Matzarakis A (2006) Assessment of the microclimatic and human comfort conditions in a complex urban environment: modelling and measurements. Build Environ 41:1713–1722CrossRefGoogle Scholar
  11. Holst J, Mayer H (2011) Impacts of street design parameters on human-biometeorological variables. Meteorol Z 20:541–552CrossRefGoogle Scholar
  12. Höppe P (1992) Ein neues Verfahren zur Bestimmung der mittleren Strahlungstemperatur in Frien. Wetter und Leben 44:147–151Google Scholar
  13. Johansson E, Emmanuel R (2006) The influence of urban design on outdoor thermal comfort in the hot, humid city of Colombo, Sri Lanka. Int J Biometeorol 51:119–133CrossRefGoogle Scholar
  14. Katzschner L (2010) Outdoor thermal comfort under consideration of global climate change and urban development strategies. In: Proceedings of adapting to change: new thinking on comfort, WINDSOR 2010, Windsor, UK, 9–11 April 2010Google Scholar
  15. Khan SM, Simpson RW (2001) Effect of a heat island on the meteorology of a complex urban airshed. Bound-Lay Meteorol 100:487–506CrossRefGoogle Scholar
  16. Kjellström E, Bärring L, Gollvik S et al. (2005) A 140-year simulation of European climate with the new version of the Rossby Centre regional atmospheric climate model (RCA3). SMHI reports meteorology and climatology no. 108, SMHI, SE-60176. SMHI, Norrköping, SwedenGoogle Scholar
  17. Krüger EL, Minella FO, Rasia F (2011) Impact of urban geometry on outdoor thermal comfort and air quality from field measurements in Curitiba, Brazil. Build Environ 46:621–634CrossRefGoogle Scholar
  18. Lindberg F, Grimmond CSB (2011) Nature of vegetation and building morphology characteristics across a city: influence on shadow patterns and mean radiant temperatures in London. Urban Ecosyst 14:617–634CrossRefGoogle Scholar
  19. Lindberg F, Holmer B, Thorsson S (2008) SOLWEIG 1.0 - modelling spatial variations of 3D radiant fluxes and mean radiant temperature in complex urban settings. Int J Biometeorol 52(7):697–713CrossRefGoogle Scholar
  20. Lindberg F, Holmer B, Thorsson S, Rayner D (2013) Characteristics of the mean radiant temperature in high latitude cities - implications for sensitive climate planning applications. Int J Biometeorol. doi: 10.1007/s00484-013-0638-y Google Scholar
  21. Masmoudi S, Mazouz S (2004) Relation of geometry, vegetation and thermal comfort around buildings in urban settings, the case of hot arid regions. Energ Buildings 36(7):710–719CrossRefGoogle Scholar
  22. Meehl GA, Stocker TF, Collins WD et al (2007) Global climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USAGoogle Scholar
  23. Monteiro A, Carvalho V, Sousa C (2012) Excess mortality and morbidity during July 2006 heat wave in Porto, Portugal - T mrt efficiency to anticipate negative effects on health. Proceedings of the 8th international conference on urban climates, Dublin, Ireland, 6–10 August 2012Google Scholar
  24. Moss RH, Edmonds JA, Hibbard KA et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756CrossRefGoogle Scholar
  25. Müller N, Kuttler W, Barlag AB (2014) Counteracting urban climate change: adaptation measures and their effect on thermal comfort. Int J Biometeorol 115:243–257Google Scholar
  26. Oke TR (1987) Boundary layer climates. Routledge, CambridgeGoogle Scholar
  27. Oliveira S, Andrade H, Vaz T (2011) The cooling effect of green spaces as a contribution to the mitigation of urban heat: a case study in Lisbon. Build Environ 46:2186–2194CrossRefGoogle Scholar
  28. Onomura S, Grimmond CSB, Lindberg F, Holmer B, Thorsson S (2014) Meteorological forcing data for urban outdoor thermal comfort models from a coupled convective boundary layer and surface energy balance scheme. Urban Clim, submitted manuscriptGoogle Scholar
  29. Papanastasiou DK, Melas D, Bartzanas T, Kittas C (2010) Temperature, comfort and pollution levels during heat waves and the role of sea breeze. Int J Biometeorol 54:307–317CrossRefGoogle Scholar
  30. Pearlmutter D, Berliner P, Shaviv E (2007a) Integrated modeling of pedestrian energy exchange and thermal comfort in urban street canyons. Build Environ 42:2396–2409CrossRefGoogle Scholar
  31. Pearlmutter D, Berliner P, Shaviv E (2007b) Urban climatology in arid regions: current research in the Negev desert. Int J Climatol 27:1875–1885CrossRefGoogle Scholar
  32. Rayner D, Lindberg F, Thorsson S, Holmer B (2014) A statistical downscaling algorithm for thermal comfort applications. Theor Appl Climatol, submitted manuscriptGoogle Scholar
  33. Reindl DT, Beckman WA, Duffie JA (1990) Diffuse fraction correlations. Sol Energy 45(1):1–7CrossRefGoogle Scholar
  34. Rivington M (2008) Evaluating regional climate model estimates against site-specific observed data in the UK. Clim Chang 88:157–185CrossRefGoogle Scholar
  35. Roeckner E, Bäuml G, Bonaventura L et al (2003) The atmospheric general circulation model ECHAM5, Part I: model description. Max-Planck-Institut für Meteorologie, HamburgGoogle Scholar
  36. Ryu YH, Baik JJ (2013) Daytime local circulations and their interactions in the Seoul Metropolitan Area. J Appl Meteorol Climatol 52:784–801CrossRefGoogle Scholar
  37. Shashua-Bar L, Hoffman ME (2000) Vegetation as a climatic component in the design of an urban street: an empirical model for predicting the cooling effect of urban green areas with trees. Energ Buildings 31:221–235CrossRefGoogle Scholar
  38. Stocker TF, Qin D, Plattner GK et al (2013) Technical summary. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate Change 2013: the physical science basis. Contribution of Working Group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USAGoogle Scholar
  39. Teutschbein C, Seibert J (2010) Regional climate models for hydrological impact studies at the catchment scale: a review of recent modeling strategies. Geogr Compass 4(7):834–860CrossRefGoogle Scholar
  40. Thorsson S, Lindqvist M, Lindqvist S (2004) Thermal bioclimatic conditions and patterns of behaviour in an urban park in Göteborg, Sweden. Int J Biometeorol 48(3):149–156CrossRefGoogle Scholar
  41. Thorsson S, Lindberg F, Eliasson I, Holmer B (2007) Different methods for estimating the mean radiant temperature in an outdoor urban setting. Int J Climatol 27(14):1983–1993CrossRefGoogle Scholar
  42. Thorsson S, Lindberg F, Björklund J, Holmer B, Rayner D (2011) Potential changes in outdoor thermal comfort conditions in Gothenburg, Sweden due to climate change: the influence of urban geometry. Int J Climatol 31:324–335CrossRefGoogle Scholar
  43. Thorsson S, Rocklöv J, Konarska J, Lindberg F, Holmer B, Dousset B, Rayner D (2014) Mean radiant temperature – a predictor of heat related mortality. Urban Clim. doi: 10.1016/j.uclim.2014.01.004 Google Scholar
  44. Van Der Linden P, Mitchell J (2009) ENSEMBLES - climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, UKGoogle Scholar
  45. Watkiss P, Horrocks L, Pye S, Searl A, Hunt A (2009) Impacts of climate change in human health in Europe. PESETA-Human health study. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  46. Yang W, Andréasson J, Graham LP et al (2010) Distribution-based scaling to improve usability of regional climate model projections for hydrological climate change impacts studies. Hydrol Res 41(3–4):211–229CrossRefGoogle Scholar

Copyright information

© ISB 2014

Authors and Affiliations

  • Kevin Ka-Lun Lau
    • 1
    Email author
  • Fredrik Lindberg
    • 1
  • David Rayner
    • 1
  • Sofia Thorsson
    • 1
  1. 1.Department of Earth SciencesUniversity of GothenburgGothenburgSweden

Personalised recommendations