Using urban climate modelling and improved land use classifications to support climate change adaptation in urban environments: A case study for the city of Klagenfurt, Austria

Oswald, S.M., Hollosi, B., Žuvela-Aloise, M., See, L. ORCID: https://orcid.org/0000-0002-2665-7065, Guggenberger, S., Hafner, W., Prokop, G., Storch, A., & Schieder, W. (2020). Using urban climate modelling and improved land use classifications to support climate change adaptation in urban environments: A case study for the city of Klagenfurt, Austria. Urban Climate 31 e100582. 10.1016/j.uclim.2020.100582.

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Abstract

This study outlines the results of current and future climate scenarios, and potentially realizable climate adaptation measures, for the city of Klagenfurt, Austria. For this purpose, we used the microscale urban climate model (MUKLIMO_3), in conjunction with the cuboid method, to calculate climate indices such as the average number of summer and hot days per year. For the baseline simulation, we used meteorological measurements from 1981 to 2010 from the weather station located at Klagenfurt Airport. Individual building structures and canopy cover from several land monitoring services were used to derive accurate properties for land use classes in the study domain. To characterize the effectiveness of climate adaptation strategies, we compared changes in the climate indices for several (future) climate adaptation scenarios to the reference simulation. Specifically, we considered two major adaptation pathways: (i) an increase in the albedo values of sealed areas (i.e., roofs, walls and streets) and (ii) an increase in green surfaces (i.e., lawns on streets and at roof level) and high vegetated areas (i.e., trees). The results indicate that some climate adaptation measures show higher potential in mitigating hot days than others, varying between reductions of 2.3 to 11.0%. An overall combination of adaptation measures leads to a maximum reduction of up to 44.0%, indicating a clear potential for reduction/mitigation of urban heat loads. Furthermore, the results for the future scenarios reveal the possibility to remain at the current level of urban heat load during the daytime over the next three decades for the overall combination of measures.

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