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Integrating Copernicus land cover data into the i-Tree Cool Air model to evaluate and map urban heat mitigation by tree cover

Pace, Rocco ORCID iD icon 1; Chiocchini, Francesca ; Sarti, Maurizio; Endreny, Theodore A.; Calfapietra, Carlo; Ciolfi, Marco
1 Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)

Abstract:

Cities host more than half of the world’s population and due to global warming and land use change their vulnerability to deadly heat waves has increased. A healthy vegetated landscape can abate heat wave severity and diminish the related urban heat island through the process of evapotranspiration. This research aimed to develop a methodology for cities to use publicly available Copernicus land cover maps within the i-Tree Cool Air water and energy balance model to map air temperature and humidity. The manuscript presents proof of concept using Naples, Italy with its Mediterranean climate characterized by limited soil water for cooling via evapotranspiration. The approach achieved strong correlations between predicted and observed air temperatures across the city (r ≥ 0.89). During the warm season of 2020, forested land cover was 5°C cooler than land cover dominated by impervious cover. Simulated land cover change, limited to a 10% increase or decrease in tree cover, generated an inverse change of 0.2°C in maximum hourly air temperature, with more trees obtaining cooler air. Soil water limited the cooling, with the generally wetter spring season enabling greater cooling of air temperatures, and summer droughts without irrigation had constrained cooling. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000151036
Veröffentlicht am 27.09.2022
Originalveröffentlichung
DOI: 10.1080/22797254.2022.2125833
Scopus
Zitationen: 4
Web of Science
Zitationen: 4
Dimensions
Zitationen: 6
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2279-7254
KITopen-ID: 1000151036
HGF-Programm 12.11.24 (POF IV, LK 01) Adaptation of natural landscapes to climate change
Erschienen in European Journal of Remote Sensing
Verlag Taylor and Francis
Band 56
Heft 1
Seiten Art.-Nr.: 2125833
Projektinformation GrüneLunge 2.0 (BMBF, 01LR2015A)
Vorab online veröffentlicht am 26.09.2022
Nachgewiesen in Dimensions
Scopus
Web of Science
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