Asadi-RahimBeygi et al. (2025) Near-term climate extremes in Iran based on compound hazards analysis

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-12-15
• Authors: Narges Asadi-RahimBeygi, Abbas Mofidi, Azar Zarrin, Abbasali Dadashi-Roudbari
• DOI: 10.1038/s41598-025-29026-x

Research Groups

• Department of Geography, Faculty of Letters and Humanities, Ferdowsi University of Mashhad, Mashhad, Iran

Short Summary

This study investigates climate-related hazards from precipitation and temperature in Iran for hindcast (1991–2019) and near-term forecast (2023–2028) periods using the Near-term Climate Prediction (NTCP) project. Results project a significant rise in drought frequency and heat wave events, with high-risk areas increasing by approximately 10% and encompassing over 36% of Iran’s total area by 2028, necessitating urgent adaptation planning.

Objective

• To investigate compounding climate-related hazards associated with precipitation and temperature in Iran during 1991–2019 (hindcast) and 2023–2028 (forecast) using the Near-term Climate Prediction (NTCP) project.
• To predict near-term climate extremes and assess the severity and importance of compound weather and climate extremes in Iran.

Study Configuration

• Spatial Scale: Country-wide analysis of Iran, with specific focus on regions including the Zagros Mountains, Caspian Sea coast, central, eastern, southeastern, western, and northwestern Iran.
• Temporal Scale: Hindcast period (1991–2019) and Forecast period (2023–2028).

Methodology and Data

• Models used: CMIP6-DCPP multi-model ensemble (MME) comprising BCC-CSM2-MR, MPI-ESM1-2-HR, and MRI-ESM2-0. Bias correction was applied using the Delta Change (DC) method. A weighted multi-model mean was generated using the Independent Weighted Mean (IWM) method.
• Data sources:
  • Daily minimum and maximum near-surface air temperature and precipitation data from 70 synoptic stations provided by the Iran Meteorological Organization (IRIMO).
  • CMIP6-DCPP model outputs for daily precipitation (pr), maximum daily temperature (tasmax), and minimum daily temperature (tasmin).
  • Climate extreme indices from the Expert Team on Climate Change Detection and Indices (ET-SCI): Number of days with heavy precipitation (R10mm), Simple Precipitation Intensity Index (SDII), Heat Wave Frequency (HWF), Heat Wave Duration (HWD), Cold Wave Frequency (CWF), and Cold Wave Duration (CWD).
  • Standardized Precipitation Evapotranspiration Index (SPEI-12) for drought characteristics: Drought Frequency (DF), Drought Duration (DD), Drought Severity (DS), and Drought Intensity (DI), derived using Run Theory with a threshold of ≤ -1.
  • Heat and cold waves were assessed using the Excess Heat Factor (EHF) and Excess Cold Factor (ECF).
  • Köppen-Geiger climate classification maps and Shuttle Radar Topography Mission (SRTM) digital elevation data.

Main Results

• The CMIP6-DCPP models successfully reproduced the overall spatial patterns and seasonal cycles of climate extremes across Iran, with minor discrepancies in arid and mountainous regions due to data limitations.
• Droughts: A significant projected increase in drought frequency (DF) is anticipated across Iran, particularly in central, eastern, and southeastern regions, exceeding 42% during the forecast period. Conversely, drought duration (DD), severity (DS), and intensity (DI) are expected to decrease, indicating more frequent but shorter and less intense drought events.
• Heat Waves: Both heat wave frequency (HWF) and duration (HWD) are projected to increase significantly across Iran. Western Iran, including parts of the Zagros Mountains, is expected to experience HWF exceeding 20 days (an anomaly of over 15 days). HWD in Dasht-e-Lut is predicted to increase by 3.4 days. High-altitude areas are projected to experience accelerated warming (Elevation-Dependent Warming).
• Heavy Precipitation: The Zagros Mountains and southwest regions are projected to become major hotspots for heavy rainfall events, with R10mm increasing by up to 1.3 days per year and SDII by 2 to 6 millimeters per day. Northeastern Iran also shows positive anomalies. In contrast, the southern Caspian Sea and northwest Iran are projected to experience a slight decrease in R10mm and SDII.
• Cold Waves: A general decrease in cold wave frequency (CWF) and duration (CWD) is predicted for the near-term, particularly in northwestern and Zagros mountainous regions (CWD decrease of 1.2 to 4.4 days, CWF decrease of 3.3 to 9.1 days). However, northeastern Iran and parts of the arid central regions are projected to experience an increase in CWD (up to 3.6 days) and CWF (up to 3.4 days).
• Compound Hazards: Areas classified as low to moderate climate risk are projected to decrease by approximately 15.7%, while high-risk areas are expected to increase by roughly 10%, covering over 36% of Iran’s total area by 2028. High to very high compound climate hazard levels are projected across large parts of western, southern Zagros, and eastern regions.
• Sensitivity analysis confirmed the spatial robustness and statistical significance of the identified multi-hazard hotspots, with temperature-related hazards becoming dominant drivers of risk in the forecast period.

Contributions

• This study is the first to predict compound climate-related hazards in Iran using the Near-term Climate Prediction (NTCP) framework, specifically leveraging the CMIP6-DCPP multi-model ensemble.
• It identifies and maps regional hotspots of multi-hazard exposure across Iran, providing critical insights for targeted climate adaptation planning in a region highly susceptible to natural hazards but often under-addressed in existing literature.
• The research enhances understanding of the spatial and temporal evolution of extreme climate events and their compound impacts, offering valuable information for future mitigation strategies.
• It employs a robust methodology, including a weighted multi-model ensemble approach and comprehensive sensitivity analyses of hazard weighting and hotspot confidence levels, to ensure the reliability and statistical significance of its findings.

Funding

• Decadal Climate Prediction Program (DCPP panel) administered by WCRP

Citation

@article{AsadiRahimBeygi2025Nearterm,
  author = {Asadi-RahimBeygi, Narges and Mofidi, Abbas and Zarrin, Azar and Dadashi-Roudbari, Abbasali},
  title = {Near-term climate extremes in Iran based on compound hazards analysis},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-29026-x},
  url = {https://doi.org/10.1038/s41598-025-29026-x}
}