CORP – Competence Center of Urban and Regional Planning
Doi
Abstract
The recently developed microscale model for urban applications PALM-4U was used to simulate the thermal
variability in Vienna on different spatial scales and to evaluate its ability to capture thermal characteristics in
real urban environment.
The model simulations cover the entire city of Vienna with a spatial resolution of 20 m. The static data
related to geographical information and urban infrastructure are based on GIS data provided by the city
administration of Vienna, available as spatial multi-purpose maps (Flächen-Mehrzweckkarte - FMZK), street
tree cadastre, Digital Elevation Model and Digital Surface Model, which were combined with the national
land cover data (Land Information System Austria - LISA) to account for the unresolved vegetation and
Open Street Map to include building properties in the surrounding region (Lower Austria) of the model
domain. The simulations were performed for a selected clear-sky hot day in August 2022.
The results for hourly air temperature were evaluated with conventional weather stations of the national
weather service and the city of Vienna and with quality-controlled data from citizen weather stations from
the company NETATMO. The results show high intra-urban variability during daytime, but distinct spatial
patterns at night with higher air temperatures in urban regions. In addition, spatial patterns of surface
temperature were compared to remote sensing data from ECOsystem Spaceborne Thermal Radiometer
Experiment on Space Station (ECOSTRESS) and with the modelling results from previous studies, but with
coarser grid spacing (e.g. urban climate model MUKLIMO_3 with 100 m spatial resolution).
The results indicate that the microscale model PALM-4U shows general agreement with observations and is
able to simulate atmospheric processes in urban regions. However, during the night a strong temperature
inversion is present in the model, which can be related to the choice of model configuration and requires
further investigations. The spatial patterns in urban-rural temperature gradient are similar as found in coarser
scale model simulations and remote-sensing data, but show higher variation in surface temperature
amplitude