Publication details
Vliv geometrie zástavby na pole teploty vzduchu a intenzitu tepelného ostrova města na příkladu Brna
| Title in English | The effect of buildings geometry on air temperature field and urban heat island intensity in Brno (Czech Republic) |
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| Authors | |
| Year of publication | 2012 |
| Type | Article in Periodical |
| Magazine / Source | Meteorologické zprávy |
| MU Faculty or unit | |
| Citation | |
| Field | Atmosphere sciences, meteorology |
| Keywords | air temperature; building geometry; sky view factor; urban heat island |
| Description | Detailed air temperature measurements from a network of 14 stations distributed in urbanized area of Brno (380 ths. inhabitants, complex terrain) are analyzed. Each station is characterized with two variants of Sky View Factor (SVF). This measure is commonly used in urban climatology to characterize amount of obstacles that reduce long-wave radiation process in built-up areas and it contributes to Urban Heat Island (UHI) formation in urban canopy layer. The two SVF variants measure either the influence of buildings only (SVFb) or consider all nearby objects such as buildings, trees, etc. (SVF). Stations represent either urban or rural environment. Temperature measurements from a set of 64 calm and sunny days (DJF – 6, MAM – 26, JJA – 21, SON – 11) made between March 2010 – May 2011 were used to characterize each station with Tavg, Tmin, Tmax and dT values. The dT value is defined as a difference between temperature measurement at individual station and average temperature measurements of rural stations. Thus dT can be used as a simple measure of UHI intensity. We found that in all seasons UHI clearly develops during night hours and also around noon while in morning and evening hours the temperature differences between urban and rural stations are close to zero. Maximum UHI intensity (about 2.5 deg. C) appears in summer midday, typical UHI intensities in night hours reach 1.0–1.5 deg. C in all seasons. From correlation analysis it follows that SVF and especially SVFb values significantly correlate with Tmin and dT in all seasons. It means that the role of vegetation in SVF calculation is minor compared to buildings. Also relations of station altitude to temperature characteristics are mostly not as significant as those of SVF. Multiple regression models using Tmin (dT) as dependent variable and SFVb and altitude as independent variables were constructed. These models explain significant percentage of Tmin variability in urban area (from 74 % in autumn to 82 % in spring). Corresponding values for dT vary from 62 % (winter) to 72 % (spring) respectively. We conclude that Sky View Factor can be successfully used to predict minimum temperatures in urban areas and intensity of UHI. |
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