Observed heat wave assessment over Iran and its future projections through 2200 under SSP scenarios

Iran is experiencing an increasing frequency and intensity of heat waves, which pose significant socio-economic challenges and associated environmental risks. This study presents the first comprehensive analysis of heat wave trends across Iran from 1961 to 2023, along with future projections extending from 2031 to 2200 under multiple Shared Socioeconomic Pathway (SSP) scenarios. To ensure consistency between observational data and climate model outputs, a Quantile Mapping (QM) bias correction method was applied to daily maximum temperature data, significantly improving the Kling-Gupta Efficiency (KGE) values of all CMIP6 models from 0.60–0.76 to 0.81–0.95 during the historical period (1985–2014). Analysis of observed data reveals a significant increase in the frequency, duration, and intensity of heat waves over the past six decades, particularly in Tehran, southwestern Iran, and the central Zagros region. Future projections based on bias-corrected daily maximum temperatures indicate that under the high-emission SSP5-8.5 scenario, heat wave durations could extend from about one week to a month (under SSP1-2.6 scenario) and nearly a full season (under SSP5-8.5 scenario). Notably, the frequency of heat waves is projected to decrease under SSP5-8.5 scenario due to the prolonged duration of individual events. Under intermediate SSP scenarios, heat wave durations are expected to peak at approximately one season by the end of the 21st century, followed by a gradual decline through the 22nd century. In contrast, the optimistic scenarios project shorter heat waves, with peak durations around one month at the end of the 21st century, decreasing to roughly one week by the late 22nd century—similar to observed durations during the baseline period of 1961–1990. This study is the first to provide long-term, scenario-based projections of heat wave characteristics across diverse Iranian regions, highlighting significant spatial variability. Understanding these evolving patterns is critical for developing effective adaptation strategies. While bias-corrected models enhance projection accuracy, further refinement and socio-economic impact assessments are essential. Proactive urban planning and targeted mitigation measures will be vital to managing the escalating risks posed by more intense and prolonged heat waves under climate change.