10/10/2022
URBAN CLIMATOLOGY
3. The climate of Brno as an example (data, methods, main outcomes)
Paper to read
MORAVIAN GEOGRAPHICAL REPORTS 3/2015, Vol. 23
The spatial variability of air temperature and nocturnal urban heat island intensity in the city of Brno, Czech Republic
Petr DOBROVOLNÝ ■■, Lukáš KRAHULAa
https://is.muni.cz/auth/el/sci/podzim2022/ZX601/um/67875456/03 Dobrovolný Krahula
MGR 2015.pdf
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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
3.2 History of meteorological measurements
CBAPHISCH TABELLARISCHE UIBERSICHT
flrr mfltarDlniiisrhmllfihiilliiusr
(Sregor 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)
3.4 Atmospheric UHI derived from station measurements
Urban stations
Rural St.
MEND BOTA FILO UKZU GEON KRAV VERO BISK KAPU VETE ŽIDE ZABO JUND TROU LISK TURA
Intensity of AUHI (AT) defined as a difference of air temperature at a given station and mean air temperature at all rural stations
10/10/2022
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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
Correction of the mobile temperature measurements
- MEND
- (jbON KRAV
- BOTA
- UKZU
- FILO
- LISK
- BISK KAPU
- VERO
- MEND
- GEON KRAV BOTA
- UKZU
- FIIO
- IISK
- JUND
- ZIDE
- BISK KAPU
- TUR.A
20:30     21:00     21:30     22:00     22:30 23
Examples of air temperature drop at stations during mobile measurements: (a) 19. 4. 2011 - the same intensity of temperature decline; (b) 31. 1. 2012 - different temperature decline on urban (M) and rural (P) stations
20:20   20:35  20:50   21:05   21:20  21:35   21:50   22:12  22:27   22:42  22:57   23:12 23:27
Mobile air temperature measurements on 3 August 2011 in Brno area; a - original temperature measurements, b - values corrected for temperature decay with time
3.7 The role of explanatory variables
Air temperature
DENS	62 %              s J/'	89% y X	87 % =/	76 %          ~ 5^
SVF	3                53 % ,'	j,               74 %	0          68 7.	„  c        68 % •x °
NDVI □_LdDDdd	""\        '          64 %	„    •                    86 %	X                    89 %	86 %
	AT DJF . ii.rii.	£j MAM LuJ]	AT JJA ddjIdD	AT S0N ■■ihn
Linear regression between intensity of UHI (AT) and explanatory variables for individual seasons in Brno region; numbers represent percentage of explained variance
The role of explanatory variables
Land Surface Temperature
Linear regression between LST and explaining variables: (a) NDVT, (b) DENS, and (c) TLoS in Brno region; LST and NDVT data is from 15 June 2006 and R2 is explained variance
Pearson correlations between air temperature	Termin 19.4.2011	NDVI -0,66	DENS 0,57	DEM -0,40
measurements and selected parameters of	9.5.2011	-0,44	0,45	0.04
environment along the traverses. NDVI represents	8.7.2011	-0,71	0,65	-0,44
amount and vigor of vegetation, DENS represents	3.3.2011	-0,46	0,41	-0,04
density of buildings calculated for 300 m square grid	13.9.2011	-0,60	0,58	■0,38
and NV stands for altitude a.s.l. Significant	27.9.2011	-0,46	0,41	-0,07
correlations at a = 0.05 are in bold	1.11.2011	-0,30	0,34	0,14
	3.1.2012	-0,53	0,55	-0,35
NDVI is the best explanatory variable	31.1.2012	■0.61	0,61	-0,42
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 air temperature measurements in urban environment