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3. The climate of Brno as an example
(data, methods, main outcomes)
URBAN CLIMATOLOGY
Motivation
• What are the typical features of spatial and temporal
variability of the main meteorological elements?
• What is the intensity of urban heat island (UHI)
during days with the radiation-driven weather?
• What is the contribution of individual factors to UHI
formation?
3.1 Local geography • complex relief
• typical land use distribution
3.2 History of meteorological measurements
The network of meteorological stations (left) and its temporal evolution (right) in the Brno
area in 1890–2012.
3.2 History of meteorological measurements
Gregor Johann Mendel, the abbot of the Augustinian monastery in Brno and the most
famous person among Brno meteorological observers, and his graphic-table overview of
meteorological observations in Brno for 1862 (Mendel 1863)
3.3 Database
Meteorological data
Mobile measurements
Professional stations (blue) and
special-purpose measurements (red)
Thermal satellite imagery
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3.3 Database
Geographical database (explanatory variables)
altitude Sky View Factor
Intensity of AUHI (ΔT) defined as a difference of air temperature
at a given station and mean air temperature at all rural stations
Urban stations
Rural st.
3.4 Atmospheric UHI derived
from station measurements
winter
spring
summer
autumn
3.5 Intensity of surface
UHI in Brno area
Land surface temperatures,
15 July 2006
SUHI intensity 4,2 °C ~ 6,7 °CIndustrial areas most contribute to SUHI intensity
3.6 Nocturnal UHI intensity derived from
mobile measurements
Typical spatial distribution of air
temperature in central part of Brno in early
night hours; air temperature is expressed
as deviation (dT) from mean value of the
study area and is typical for clear and calm
weather during summer
3.7 The role of explanatory variables
Linear regression between intensity of UHI (ΔT) and explanatory variables for individual
seasons in Brno region; numbers represent percentage of explained variance
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The role of explanatory variables
Linear regression between LST and explaining variables: (a) NDVI, (b) DENS, and (c) TLoS
in Brno region; LST and NDVI data is from 15 June 2006 and R2 is explained variance
Pearson correlations between air temperature
measurements and selected parameters of
environment along the traverses. NDVI represents
amount and vigor of vegetation, DENS represents
density of buildings calculated for 300 m square grid
and NV stands for altitude a.s.l. Significant
correlations at α = 0.05 are in bold
NDVI is the best explanatory variable
3.8 Final remarks and questions
1. Why is it useful to have a long term meteorological
measurements?
2. What are the main data types we need for an analysis of urban
climate?
3. What parts of the city are most susceptible to higher
temperatures?
4. Compare positive/negative features of satellite thermal mapping
and mobile measurements used for UHI intensity estimate?