Climate Variability and Extreme Precipitation Analysis in Iran

Iran occupies a climatically diverse region stretching from arid deserts to humid Caspian coasts, rendering it highly sensitive to shifts in temperature, precipitation and atmospheric circulation. Over recent decades, analyses of long‐term meteorological records have revealed warming trends, altered seasonal rainfall patterns and increasing incidence of extreme precipitation events. These changes are linked to evolving large‐scale drivers such as the North Atlantic Oscillation and El Niño–Southern Oscillation, as well as local land‐use changes and orographic effects. Extreme rainfall episodes now more frequently overwhelm drainage systems, while prolonged dry spells exacerbate drought risk across agricultural and water‐scarce regions. Understanding the spatiotemporal variability of these extremes is critical for flood management, drought mitigation and the design of adaptive infrastructure. Advances in high‐resolution climate modelling and observational networks have enabled finer detection of trends and projections under different emissions pathways, informing both national water policy and broader studies of mid‐latitude hydro-climatic change.

Research from Nature Portfolio

Recent studies have employed ensembles of high‐resolution climate models to project future extremes of temperature and precipitation across Iran. One foundational investigation utilised multiple regional climate simulations to assess changes in the frequency and duration of extreme hot days and heavy rainfall events. The analysis indicates that, by mid-century under moderate to high emission scenarios, southern and western regions will experience extended dry spells punctuated by intense precipitation pulses, elevating flood risk. Meanwhile, temperature extremes are projected to shift both thresholds and durations, suggesting a compound effect of heat and moisture stress. This body of work underscores the need for regionally tailored adaptation strategies that account for simultaneous shifts in drought and flood regimes.

Climate Variability and Extreme Precipitation Analysis in Iran publication trend

The graph below shows the total number of articles in climate variability and extreme precipitation analysis in iran across all publications each year (not limited to Nature Index journals).

Technical terms

Standardized Precipitation Index (SPI): A normalised index that quantifies precipitation deficits or surpluses over multiple time scales to characterise meteorological drought.

Representative Concentration Pathway (RCP): A greenhouse-gas concentration trajectory adopted by climate modellers to project future radiative forcing and associated climate change scenarios.

General Circulation Model (GCM): A numerical model representing the earth’s atmosphere, oceans and land surface to simulate climate dynamics and predict future climate states.

De Martonne Aridity Index: A climatic metric defined as precipitation divided by temperature+10, used to classify regions from humid to arid conditions.

Extreme Precipitation Indices: Statistical measures, such as the annual maximum one-day rainfall or counts of days above the 90th percentile, employed to track changes in heavy rainfall events.

References

1. The spatiotemporal trend changes of extreme temperature-humidity variables and their impact on climatic comfort changes. Ecological Indicators (2024).
2. Spatial evaluation of climate change-induced drought characteristics in different climates based on De Martonne Aridity Index in Iran. Applied Water Science (2023).
3. The future of extreme climate in Iran. Scientific Reports (2019).
4. Assessment of climate variations in temperature and precipitation extreme events over Iran. Theoretical and Applied Climatology (2015).
5. Trends in Extreme Precipitation Indices in Iran: 1951–2007. Advances in Meteorology (2016).
6. Drought trend, frequency and extremity across a wide range of climates over Iran. Meteorological Applications (2020).
7. Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices. ISPRS International Journal of Geo-Information (2020).