The spatial distribution of the annual mean urban heat island (UHI) intensity was simulated applying empirical models based on datasets from urban areas of Szeged and Debrecen, using simple and easily determinable urban surface cover variables. These two cities are situated on the Alföld (Great Hungarian Plain) and have similar topographic and climatic conditions. Temperature field measurements were carried out, Landsat satellite images were evaluated, and then one‐ and multiple variable models were constructed using linear regression techniques. The selected multiple‐parameter models were verified using independent datasets from three urban settlements. In order to obtain some impression of the mean UHI patterns in other cities with no temperature measurements available, the better model was extended to urban areas of four other cities situated in geographical environments similar to Szeged and Debrecen. The main shortcoming of typical empirical models, namely that they are often restricted to a specific location, is overcome by the obtained model since it is not entirely site but more region specific, and valid in a large and densely populated area with several settlements. Copyright © 2009 Royal Meteorological Society

Increasing summertime air temperature deteriorates human health especially in cities where the warming tendency is exacerbated by urban heat island. Human-biometeorological studies shed light on the primary role of radiation conditions in the development of summertime heat stress. However, only a limited number of field investigations have been conducted up to now. Based on a 26-hour long complex radiation measurement, this study presents the evolved differences within a medium-sized rectangular square in Szeged, Hungary. Besides assessing the impact of woody vegetation and façade orientation on the radiation heat load, different modeling software programs (ENVI-met, SOLWEIG, and RayMan) are evaluated in reproducing mean radiant temperature (Tmrt). Although daytimeTmrtcan reach an extreme level at exposed locations (65–75°C), mature shade trees can reduce it to 30–35°C. Nevertheless, shading from buildings adjacent to sidewalks plays also an important role in mitigating pedestrian heat stress. Sidewalks facing SE, S, and SW do not benefit from the shading effect of buildings; therefore, shading them by trees or artificial shading devices is of high importance. The measurement–model comparison revealed smaller or larger discrepancies that raise awareness of the careful adaptation of any modeling software and of the relevance of fine-resolution field measurements.

Urban areas are among those most endangered with the potential global climate changes. The studies concerning the impact of global changes on local climate of cities are of a high significance for the urban inhabitants' health and wellbeing. This paper is the final report of a project (Urban climate in Central European cities and global climate change) with the aim to raise the public awareness on those issues in five Central European cities: Szeged (Hungary), Brno (Czech Republic), Bratislava (Slovakia), Kraków (Poland) and Vienna (Austria). Within the project, complex data concerning local geomorphological features, land use and long-term climatological data were used to perform the climate modelling analyses using the model MUKLIMO_3 provided by the German Weather Service (DWD).

This study evaluates the pattern of a nighttime climate index namely the tropical nights (Tmin ≥ 20ºC) during the 21st century in several different sized cities in the Carpathian Basin. For the modelling, MUKLIMO_3 microclimatic model and the cuboid statistical method were applied. In order to ensure the proper representation of the thermal characteristics of an urban landscape, the Local Climate Zone (LCZ) system was used as landuse information. For this work, LCZ maps were produced using WUDAPT methodology. The climatic input of the model was the Carpatclim dataset for the reference period (1981–2010) and EURO-CORDEX regional model outputs for the future time periods (2021–2050, 2071–2100) and emission scenarios (RCP4.5, RCP8.5). As results show, there would be a remarkable increase in the number of tropical nights along the century, and there is a clearly recognizable increase owing to urban landform. In the near past, the number of the index was 6–10 nights higher in the city core than the rural area where the number of this index was negligible. In the near future this urban-rural trend is the same, however, there is a slight increase (2–5 nights) in the index in city cores. At the end of the century, the results of the two emission scenarios become distinct. In the case of RCP4.5 the urban values are about 15–25 nights, what is less stressful compared to the 30–50 nights according to RCP8.5. The results clearly highlight that the effect of urban climate and climate change would cause serious risk for urban dwellers, therefore it is crucial to perform climate mitigation and adaptation actions on both global and urban scales.