Abstract
Climate change and the urban heat effect are expected to have a large influence on the energy consumption and thermal comfort of buildings. However, using meteorological data which incorporates effects of climate change and characteristics of cities is not currently a standard practice in building simulation. By default, data of nearby meteorological stations often outside cities are used. This may lead to important discrepancies between simulation results and actual energy consumption and/or indoor climate data for buildings in urban areas. These effects are analysed within building energy part of H2020 climate-fit.city project. First, adapted urban and future meteorological data modelled using the UrbClim model and standard meteorological data were compared. Second, these data were included within the Meteonorm software (version 7.3.2). This was carried out for current climates as well as for future scenarios (RCP 4.5 and 8.5, 2050) for the cities of Barcelona, Bern, Berlin, Bremen, Prague, Rome and Vienna. Like this Meteonorm includes a combination of urban and future climates accessible in a user friendly tool. In a third step the urbanized TMY data sets generated by Meteonorm were used to simulate energy consumption, peak loads and indoor climate conditions with models of several typical buildings. In this comparison we show a simulation for a multi-family house for current and future climates. The whole-year simulation runs were compared to the reference scenario - the standard TMY (available in Bern and Vienna). For current climates heating energy consumption is 10-25% lower within cities and cooling energy up to 60% higher (Barcelona). Even bigger changes are seen for future climates: Heating loads drop by up to 30% and cooling loads rise more than 100% (they are 2-3 times higher than heating loads in Barcelona by 2050).
Cite
CITATION STYLE
Remund, J., & Grossenbacher, U. (2019). Urban climate scenario data for European cities. In Journal of Physics: Conference Series (Vol. 1343). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1343/1/012019
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