Influence of urban land-use change on cold-air path occurrence and spatial distribution

The urban population is predicted to reach a 70 % share of global population by mid-century. Future urbanization might be directed along several development typologies, e.g. sprawling urbanization, more compact cities, greener cities, or a combination of different typologies. These developments induce urban land-use change that will impact urban climate and might reinforce phenomena such as the urban heat island and thermal discomfort of urban residents. A planning-based mitigation approach to ensure thermal comfort of residents are urban cold-air paths, i.e. low-roughness areas enabling drainage and transport of colder air masses from rural surroundings. This dataset shows how urban land-use change scenarios influence cold-air path occurrence probability and spatial distribution in a mid-European city using the machine learning approach boosted regression trees. Four scenarios were calculated: Urban Sprawl Scenario (USS), Green City Scenario (GCS), Compact Green City Scenario (CGCS) and Compact City Scenario (CCS). The used method allows for the identification of priority areas for cold-air path preservation in urban planning.