A1 Refereed original research article in a scientific journal
The impact of environmental factors on urban temperature variability in the coastal city of Turku, SW Finland
Authors: Suomi Juuso, Käyhkö Jukka
Publisher: WILEY-BLACKWELL
Publication year: 2012
Journal: International Journal of Climatology
Journal name in source: INTERNATIONAL JOURNAL OF CLIMATOLOGY
Journal acronym: INT J CLIMATOL
Number in series: 3
Volume: 32
Issue: 3
First page : 451
Last page: 463
Number of pages: 13
ISSN: 0899-8418
DOI: https://doi.org/10.1002/joc.2277
Web address : http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0088
Temporal and spatial characteristics of temperature were studied in and around the city of Turku (175,000 inh.). The main aim was to unravel the spatial diurnal and seasonal temperature differences during the observation period of 20022007 and the behaviour of observed temperature differences in relation to land use, topography and the vicinity of water bodies. The material consisted of a temperature data set from a network of 36 Hobo H8 temperature loggers that monitor T at 30 min interval. A buffer analysis of landscape parameters surrounding the loggers was employed for spatial analysis, and their relative importance was assessed with a stepwise multiple regression analysis. Spatial temperature difference in the area for warmest and coldest average temperatures was 1.9 degrees C. The differences were largest among the daily minimum temperatures (3.6 degrees C). The respective difference in daily maximum temperatures was 1.0 degrees C, and in the diurnal temperature ranges 3.4 degrees C. The spatial differences in temperatures were largest at the end of summer and smallest during the cold season. On average, the market square in the city centre was the warmest place. In autumn, a relatively warm zone was formed along the coast due to the remnant heat released by the sea. In spring, daytime maximum temperatures were typically highest in rural inland areas resulting in an urban cold island. The results of the linear regression model indicate that it is the daily minimum temperatures that can best be explained by the combination of land use, topography and water bodies. The explanatory force of the model was weakest in case of maximum temperatures. Land use was the most significant factor causing spatial differences in minimum and average temperatures as well as diurnal temperature range in the study area. Copyright (c) 2011 Royal Meteorological Society