Detection and regional analysis of heatwave characteristics in İstanbul

Abstract

Understanding heatwave characteristics is crucial for mitigating their adverse effects in İstanbul, a densely populated metropolis characterized by a high concentration of buildings, concrete structures, and limited green spaces. This study aims to develop a methodology for defining heatwaves by identifying appropriate thermal indicators. Utilizing the Distributed Lag Nonlinear Model (DLNM), this research investigates the complex and delayed effects of daily mean, maximum, and minimum temperatures, along with seven thermal indices, on daily mortality rates during the summer months of 2013–2017, leveraging the DLNM approach's flexibility in modeling the nonlinear exposure-response relationships. Heatwaves are defined based on the Minimum Mortality Temperature (MMT) and 90th percentile thresholds, and heatwave maps are constructed by their frequency, intensity, duration, and cumulative intensity characteristics. PETmean emerges as the optimal thermal index, exhibiting the lowest Akaike's Information Criteria (AIC: 3553) and estimates relative risk (RR) of 1.080 (95% CI: 1.051–1.110) for a 1°C increase above the 90th percentile. Additionally, Tmean, Tmax, PETmax, and Tmrtmean indices demonstrate favorable characteristics, with low AIC values and high RR estimates. Notably, heatwaves are intense and frequent in Çatalca despite low urban land use and abundant forests, but their duration was short due to fast adaptation capability of the region.