Heat load assessment in Central European cities using an urban climate model and observational monitoring data

Abstract

Diurnal variability of spatial pattern of air temperature was studied in five cities in Central Europe: Bratislava (Slovakia), Brno (Czech Republic), Kraków (Poland), Szeged (Hungary) and Vienna (Austria), during one of the heat waves in 2015 (4-14 August), with the application of micro-climate model MUK-LIMO_3. 8th August was chosen to study in detail the urban heat load at 10.0 0, 16.0 0, 22.0 0 and 4.00 CEST. Local Climate Zones concept was used to supply data for the model and for the interpretation of the results obtained. Model outcomes were validated with measurement data from 86 points belonging to the networks which operate in the cities studied. The results obtained show that among urban LCZ, the highest heat load was observed for LCZ 2 and 3 from 16.00 to 4.00, while at 10.00 there is no such clear pattern. Unlike forested areas, open green areas can contribute to the generation of high air temperature: > 35 °C during day time and > 30 °C during night time. Important factors controlling the intra-zonal and inter-zonal variability of air temperature in particular LCZs are the local environmental conditions. During the day time, diversified relief in the area of the city and its vicinities generates higher heat load in the valleys' floors than in areas located above, both in rural and urban areas. The same landforms experience lower heat load during the night time due to air temperature inversions effect.

Applying urban climate model in prediction mode—evaluation of MUKLIMO_3 model performance for Austrian cities based on the summer period of 2019

“…The thermodynamical version of the MUKLIMO_3 atmospheric flow model has been developed for microscale urban climate and planning applications (Sievers and Zdunkowski 1986;Sievers 1990) by using a dynamical-statistical downscaling technique called cuboid method (Früh et al 2011) and was applied mainly for climatological studies so far. Bokwa et al (2019) evaluated for the first time the performance of MUKLIMO_3 predicting skills for a heat wave period from 2015 for different Central European cities. MUKLIMO_3 provides a tool for various scientific applications on the urban scale (e.g.…”

“…Fig. 2 Schematic structure of the MUKLIMO_3 modelling approach in prediction mode, illustrating the main model components (center), required input data (left), and information in terms of data preparation (right) after Bokwa et al (2019) The model prediction skills for urban areas was evaluated using different methods illustrating a statistical comparison with the observations. The Taylor diagram (Taylor 2001) in Fig.…”

Urban heat island studies in Szeged, Hungary

“…Heat load assessment in Central European cities using an urban climate model and observational monitoring data (Bokwa et al 2019):…”

Spatial variability of soil temperature in an urban area: A case study for a medium-sized European city

“…In the studies of urban climate, emphasis is given to the characteristics of anthropogenic surfac-es and their accurate parametrisation (Mohajerani et al, 2017). Soils represent a considerable part of active surface in urban areas (Kopp & Raška, 2017); however, their characteristics are strongly generalized (Sievers et al, 1983;Bokwa et al, 2019;Feranec et al, 2019;Resler et al, 2020) considering the range of factors influencing temperature and thermal regimes of soils (Lehnert, 2014) and the general variability of soils in urban areas (Milošević et al 2014;Sobocká et al, 2020). This leads to significant inaccuracies in the presumed radiative balance of active surface, and to differences between simulated and observed/real heat fluxes (Christen and Vogt, 2004).…”