Urban heat island intensity prediction in the context of heat waves

• Verfasst von: Martinez-Soto, Aner [VerfasserIn]
• Verfasst von: Fürle, Johannes [VerfasserIn]
• Verfasst von: Zipf, Alexander [VerfasserIn]
• Titel: Urban heat island intensity prediction in the context of heat waves
• Titelzusatz: an evaluation of model performance
• Verf.angabe: Aner Martinez-Soto, Johannes Fürle and Alexander Zipf
• E-Jahr: 2023
• Jahr: 12 July 2023
• Umfang: 6 S.
• Fussnoten: Gesehen am 23.06.2025
• Titel Quelle: Enthalten in: Engineering proceedings
• Ort Quelle: Basel : MDPI, 2020
• Jahr Quelle: 2023
• Band/Heft Quelle: 39(2023), 1, Artikel-ID 80, Seite 1-6
• ISSN Quelle: 2673-4591
• DOI: doi:10.3390/engproc2023039080
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: heat waves
• Sach-SW: prediction model
• Sach-SW: urban heat islands
• K10plus-PPN: 1928888321

Abstract

Urban heat islands, characterized by higher temperatures in cities compared to surrounding areas, have been studied using various techniques. However, during heat waves, existing models often underestimate the intensity of these heat islands compared to empirical measurements. To address this, an hourly time-series-based model for predicting heat island intensity during heat wave conditions is proposed. The model was developed and validated using empirical data from the National Monitoring Network in Temuco, Chile. Results indicate a strong correlation (r > 0.98) between the model’s predictions and actual monitoring data. Additionally, the study emphasizes the importance of considering the unique microclimatic characteristics and built environment of each city when modelling urban heat islands. Factors such as urban morphology, land cover, and anthropogenic heat emissions interact in complex ways, necessitating tailored modelling approaches for the accurate representation of heat island phenomena.