Simulating the impact of climate change on heat stress using the discomfort index (DI) at Kerman station

Abstract

Simulating the thermal discomfort index is particularly important for predicting and understanding climate change and preventing its consequences, especially in arid and desert regions. This study simulates the impact of climate change on heat stress using the DI at Kerman Station, a representative arid region in Iran. Observed daily minimum and maximum temperatures along with relative humidity for the period 1991–2010 were obtained from the Iran Meteorological Organization. Six General Circulation Models (GCMs) including EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR, and CanESM2 were downscaled using the Long Ashton Research Station Weather Generator (LARS) and Statistical Downscaling Model (SDSM) to project future climate conditions under two representative concentration pathways scenarios (RCP4.5 and RCP8.5) for 2021–2047, 2048–2074, and 2075–2100. Trend analyses employed the Mann-Kendall test and Sen’s slope estimator. During the baseline period, summer months (June–August) showed the highest DI values (19.03–20.20). Projections indicate a significant rise in both minimum and maximum temperatures across all future periods, with steeper increases under RCP8.5 (0.04–0.08°C/year) than RCP4.5 (0.02–0.04°C/year). The lowest projected relative humidity (10.4%) occurred in July under GFDL-CM3 (LARS, RCP8.5, 2075–2100). DI and wet-bulb temperature rose most notably in GFDL-CM3, HadGEM2-ES, and CanESM2 during the late century. SDSM generally yielded higher projections than LARS. Model validation identified HadGEM2-ES as the most accurate. Results confirm a continuous, escalating trend in heat stress in Kerman, with serious implications for public health, urban infrastructure, and ecosystem resilience. These findings can inform climate adaptation strategies, early warning systems, and proactive health policies in vulnerable arid zones of the Middle East, where such assessments remain scarce.