Jan Geletič, Petr Dobrovolný Empirical and modelling approaches for heat risk assessment in Urban Climate under Climate Change (a case study for Brno, Czech Republic) Jan Geletič, Petr Dobrovolný Global Climate Change Research Center and Department of Geography Masaryk University

Outline Motivation and basic terms Study area and compiled database Main results of empirical studies intensity of urban heat island from mobile temperature measurements intensity of urban heat island analyzed from satellite data Urban climate modelling Model MUKLIMO and cuboid method First results of modelling approach Outlook for a near future

Motivation High temperatures in cities may be problem under global climate change Development of urban heat island (UHI) belongs to the most characteristic expressions of urban climate The factors that affect variability in spatiotemporal air temperature and UHI intensity are known However, the role of any one of these factors may vary from city to city with respect to geographical position, size, number of inhabitants, and more. Main aim is to quantify the effects of a number of factors on the air temperature field in Brno area and to estimate UHI intensity Besides various types of direct measurements numerical modelling offers an alternative for urban climate analysis

UHI types Boundary layer UHI Canopy layer UHI Surface UHI

Study area Brno as an example of medium- sized city Complex terrain Database of factors affecting temperature spatial variability

Atmospheric UHI intensity estimation Mobile measurements Air temperature variability along mobile transects: a) 8 July 2011; b) 31 January 2012; c) elevation profile; d) distribution of main land use categories.

Atmospheric UHI intensity estimation

Surface UHI intensity estimation

Summary of empirical studies Atmospheric 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 in all seasons. From regression analysis it follows that air temperatures and UHI intensity depend especially on amount of vegetation fraction represented by NDVI values Air temperatures interpolated from mobile measurements and NDVI values indicate that the mean UHI intensity in the early night in summer is at its highest (approx. 5°C) in the city center and decreases towards the suburban areas. The highest LST values typically occur in industrial and commercial areas, which contribute significantly to surface UHI intensity that reached 4.2 °C and 6.7 °C The amount of vegetation cover (NDVI) is the main factor forming LST spatial variability (56–67% of explained variance); the degree of urbanization as represented by density of buildings explains 37–40% of LST variance.

Urban Climate Modelling Numerical modelling – simulation of atmospheric flow fields in urban areas MUKLIMO_3 = Mikroskaliges urbanes Klima-Modell, 3-dim. Model developed at DWD (Deutscher Wetterdienst) Simulates atmospheric conditions with pronounced influence of local land-use properties Cloud processes and precipitation are not considered

MUKLIMO_3 model system

CUBOID method

First results: T CUBOID 101 (Tmax, Rhmin, vmax) CUBOID 100 (Tmax, Rhmin, vmin) CUBOID 101 (Tmax, Rhmin, vmax)

First results: AUHI CUBOID 101 (Tmax, Rhmin, vmax); time steps: 9h, 12h, 18h

Outlooks Model output validation - the model reproduces the spatial variability of air temperature well, but values of some temperature characteristics are overestimated Local Climate Zones definition – input parameter that may significantly improve results Implementation od 3D building model International cooperation - Central European 2020 found (Vienna, Szeged, Bratislava and Krakow) Cooperation with Brno authorities

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