Theoretical and Applied Climatology

, Volume 128, Issue 1–2, pp 43–61 | Cite as

Spatio-temporal variance and meteorological drivers of the urban heat island in a European city

  • Daniela Arnds
  • Jürgen Böhner
  • Benjamin BechtelEmail author
Original Paper


Urban areas are especially vulnerable to high temperatures, which will intensify in the future due to climate change. Therefore, both good knowledge about the local urban climate as well as simple and robust methods for its projection are needed. This study has analysed the spatio-temporal variance of the mean nocturnal urban heat island (UHI) of Hamburg, with observations from 40 stations from different suppliers. The UHI showed a radial gradient with about 2 K in the centre mostly corresponding to the urban densities. Temporarily, it has a strong seasonal cycle with the highest values between April and September and an inter-annual variability of approximately 0.5 K. Further, synoptic meteorological drivers of the UHI were analysed, which generally is most pronounced under calm and cloud-free conditions. Considered were meteorological parameters such as relative humidity, wind speed, cloud cover and objective weather types. For the stations with the highest UHI intensities, up to 68.7 % of the variance could be explained by seasonal empirical models and even up to 76.6 % by monthly models.


Wind Speed Cloud Cover Urban Heat Island Weather Type Urban Climate 
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.



We would like to thank in particular T. Langkamp and C. Daneke for the HUCDB and their dedicated support, the reviewers for their constructive and detailed comments on the first manuscript, as well as M. Tamminga for support with the cartography. Furthermore, we would like to express thanks to the suppliers of the used data, especially H. Schmack (DWD), D. Matzen and P. Kirschner (BSU/HaLm), U. Dietze, H. J. Winkel and T. Nass (Streudienst), I. Lange and B. Brümmer (Weather Mast), S. Wiesner and F. Ament (HUSCO) as well as J. Böttcher, A. Hansen and J. Tzschaschel (school network). This research was supported by the Cluster of Excellence ‘CliSAP’ (EXC177), University of Hamburg, funded through the German Science Foundation (DFG).


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Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  • Daniela Arnds
    • 1
  • Jürgen Böhner
    • 1
  • Benjamin Bechtel
    • 1
    Email author
  1. 1.Institute of GeographyUniversity of HamburgHamburgGermany

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