10/8/2024 URBAN CLIMATOLOGY 3. The climate of Brno as an example (data, methods, main outcomes) The spatial variability of air temperature and nocturnal urban heat island intensity in the city of Brno, Czech Republic Petr DOBROVOLNÝ >\ Lukáš KRAHULA' https://is.muni.cz/auth/el/sci/podzim2024/ZA311/um/67875456/03 Dobrovolný Krahula MGR 2015.pdf 1 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 Pisálky, vodárna (90) Veveří U. (17) Královo Pole (59) Bystrc (18) Jeři nice (3) Čem:, Pole (2) Cacovice (27) Medián ky (21) německá iecHnika (32) Horní Herspice (10) Pisárky, Květná (54) česká technika (36) Komárov (43) Bchun i:e i~: Jundrov (42) Líšeň, velká Klajsavka í - Si -Veveři. Hrad (34) Husovice (Lesná) (67) Čemovice, letiště (24) Řečkovice (33) Komín (33) Kníničky, přehrada (73) Lužánky(9) Turany, letiště (55) Kraví Hora (13) Žabovřesky, Krortova (40) Židenice(15) ■370 I960 !S90 2000 2010 The network of meteorological stations (left) and its temporal evolution (right) in the Brno area in 1890-2012. „Compiled" Brno temperature and precipitation series start already in 1799 and 1803 respectively 3.2 History of meteorological measurements GRAPHISCH TABELLARÍSCHE UIBERSICH1 err liirlrarDlojiiirlifii lln1]iilliiL«f ft; 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 Geographical database (explanatory variables) m«tm HIV,1 0.1OT--Ü.IB7 ■1 1ST 0.0M :: !;:.^ q i . ncen a :n' 0.18S- 0.307 B 307 ■ 0.43C O.aM-0.553 :: n !v" 0.677- C.SOC flflow J fcrtflifr o/ tfitets (farther TLo$} epfcuhted for a rtgutar grid ($00 > Jdfl mj rrf the study area, altitude calculated for n regular grid (100* 3Ö0 rpj ''1 (fa" J hatmaiiitd Difference Viaetatior Inder (further UPVif 53 an indicator of uenvlntiun urnuunt nrjd vigar rrr Erna u/;'n 50% 8% 40% 20% MIR Red Mi! Red w ^ NDVI = Sky View Factor 10/8/2024 Special purpose measurements • Original 10 minute measurements compiled to daily, monthly and seasonal averages • For each day collected also synoptic situation • For Urban Heat Island intensity - only days with radiation driven type of weather: • Well-expressed daily course of air temperature • No rain • Cloudiness less than • mean wind speed less than 4 rns-1 precipitation 1 . Ill 5 -1,0 H-1-1-1-1-1-1-1-1-1-1-1-1-1-1-1- MEND BOTA FILO UKZU GEON KRAV VERO 8ISK KAPU VETE ZIDE ZAEO 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 Do Heat Waves Amplify the Urban Canopy Heat Island? • homogenized mean (Ta), maximum (Tx), and minimum (Tn) daily temperatures • 12 stations located in Brno during the 2011-2020 period • heat waves (HW) recognized as at least three consecutive • days with Tx 30° C • heat magnitude (HM) - difference of UHI intensities separately during and outside of HWs Spatial distribution of LCZs in Brno Do Heat Waves Amplify the Urban Canopy Heat Island? No of Heat Wave Days (DHW) the length of HW in days BISK FILO KRAV MEND Intensity of Heat Waves (IHW) sum of Tx during HW FILO Tim ) 200 ZOO 400 200 300 400 -TTL, 100 200 300 400 200 300 400 200 300 400 Mm* Do Heat Waves Amplify the Urban Canopy Heat Island? Urban heat island intensity (UHII) empirical density curves calculated from HW days (HW) and non-HW days (NHW). • The density curves outside the reference band (blue) indicate a significant difference in the two distributions (and vice versa). • Vertical lines are mean UHIIs, and their differences express the heat magnitude (HM). 3.5 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 - Mb NU - 6EON KRAV BOTA - UKZU - riLO - LISK - IUND - ZIDE - BISK KAPU - TU RA 20:30 21:00 21:30 22:00 22:30 23:00 23:30 2-1:00 (a) Examples of air temperature drop at stations during mobile measurements: 19. 4. 2011 - the same intensity of temperature decline; (b) 31. 1. 2012 - different temperature decline on urban (M) and rural (P) stations o — 22 T 1 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 10/8/2024 9 3.7 The role of explanatory variables Air temperature DENS IdeDdd JO 62 •/. s y y^' ° 89 % y 87% y y SVF \» a 53 % j 74 % >-^i . 68 % iV. . c 68% NDVI □_L i' 64 7. , • 86 % Sj 89 % >* o 86 % AT DJF .lull. &T MAM III Jl AT JJA ddjJddD AT S0N Lihu 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 „oDÉk , .■ Ml ill ■ v "-Tu -■ V' i. H i MOS.« SM ■ 2447.95 - 2701 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,S7 DEM -0,40 measurements and selected parameters of 9,5,2011 •0,44 0,45 0,04 environment along the traverses. NDVT represents 8.7.2011 -0,71 0,6S -0,44 amount and vigor of vegetation, DENS represents 3,8,2011 -0,46 0,41 -0,04 density of buildings calculated for 300 m square grid 13.9.2011 -0,GO 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 Brno climate modelling in the future RCP8.5 scenario 1971-2000 10,5 83,4 37,2 (100%) 2021-2050 17,8 93,2 52,3 (140%) 2071-2100 40,7 121,3 81,4 (220%) _Mean number of summer days (Tmax > 25°C) in Brno_ Role of the urban environment in changing climate To what extent did changes in land cover affect long-term air temperature measurements? Development of built up area in Brno in the 1870s, 1940s and at present Addressing the relocation bias in a long temperature record by means of land cover assessment 0.00 -L-ri-,-,-1-r- 50 300 500 80C 1000 Radius [mj Coefficients of determination for a) seasonal average and b) minimum temperatures correlated with selected types of land cover relative to different distances to the stations Addressing the relocation bias in a long temperature record by means of land cover assessment 1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 12 1850 1860 1870 1880 1890 1890 1910 1930 195C 1970 1990 Measured and corrected Brno MAM record from 1800 to 1812 and 1848 to 2000. Data from the nineteenth century (left) and twentieth century (right) are displayed separately to illustrate the strong corrections in the beginning and the minor changes in the later part. 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