Development, data processing and preliminary results of an urban human comfort monitoring and information system

In this study, the infrastructure development and operation of an urban human comfort monitoring network and information system in Szeged and the related preliminary research results are discussed. The selection of the representative sites of the network is based primarily on the pattern of the local climate zones in and around the city. After the processing of the incoming data (air temperature and relative humidity, as well as global radiation and wind speed), a human comfort index (PET) is calculated from the four meteorological parameters are with a neural network method (MLP), then the measured and calculated parameters interpolated linearly into a regular grid with 500 m resolution. As public information, maps and graphs about the thermal and human comfort conditions appear in 10-minute time steps as a real-time visualisation on the internet. As the preliminary case studies show, the largest intra-urban thermal differences between the LCZ areas in a two-day period occurred in the nocturnal hours reaching even 5 oC in early spring. In the spatial distribution of human comfort conditions, there are distinct differences in the strength of the loading or favorable environmental conditions between the neighborhoods during the daytime. Finally, the utilization possibilities of the results in the future are detailed. Key-words: local climate zones (LCZ), representative measurement sites, monitoring network, psychologically equivalent temperature (PET), multilayer perceptron, thermal and human comfort maps, real-time visualization, Szeged, Hungary