Journal
THEORETICAL AND APPLIED CLIMATOLOGY
Volume 144, Issue 3-4, Pages 1181-1204Publisher
SPRINGER WIEN
DOI: 10.1007/s00704-021-03580-6
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Funding
- Austrian Federal Ministry of Education, Science and Research (BMBWF) as part of the ZAMG internal research project MoDuLus
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This study demonstrates the potential of using urban climate model simulations in prediction mode to provide detailed information on thermal conditions in Austrian cities. The results show that the MUKLIMO_3 microscale model can simulate the main thermal spatiotemporal patterns in urban areas, with a strong dependence on input data from mesoscale models. Urban climate model simulations using real atmospheric conditions can facilitate better understanding of day-to-day intra-urban variations in microclimate.
Extreme heat events are natural hazards affecting many regions of the world. This study uses an example of the six largest cities in Austria to demonstrate the potential of urban climate model simulations applied in prediction mode providing detailed information on thermal conditions. For this purpose, the urban climate model MUKLIMO_3 of the German Meteorological Service (DWD) coupled with the hydrostatic numerical weather prediction model, ALARO, is used to simulate the development of the urban heat island (UHI) in Austrian cities for the summer period of 2019 with a horizontal resolution of 100 m. In addition to the evaluation of UHI predicting skills, other relevant variables, such as humidity and wind characteristics on hourly basis, are also analysed in this paper. Model evaluation confirmed that the MUKLIMO_3 microscale model had the capacity to simulate the main thermal spatiotemporal patterns in urban areas; however, a strong dependence on the input data from the mesoscale model was found. Our results showed large benefit in prediction of maximum air temperatures in urban areas, while the relative humidity predictions of MUKLIMO_3 appear to be much less plausible and show large variety of model prediction skills. Urban climate model simulations using real atmospheric conditions can facilitate better quantification and understanding of day-to-day intra-urban variations in microclimate as well as provide a basis for evaluation of the microclimate prediction skills of mesoscale numerical models with urban extensions.
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