Nouri et al. (2026) Global Attribution of Anthropogenic Climate Change to Terrestrial Long-Term Droughts

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-01-01
• Authors: Milad Nouri, Mostafa Khorsandi
• DOI: 10.1007/s11269-025-04455-5

Research Groups

• Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
• University of Northern British Columbia, Prince George, BC, Canada

Short Summary

This study quantitatively attributes anthropogenic climate change (CC) to global terrestrial long-term droughts by comparing factual and counterfactual climate scenarios, revealing that CC has significantly increased drought frequency, multi-year drought occurrences, and shifted drought trends towards drying across substantial portions of the global land, with atmospheric evaporative demand (AED) playing a crucial role.

Objective

• To disentangle anthropogenic climate change signals from natural variability in shaping global drought frequency, multi-year droughts (MYDs), and trends.
• To clarify the role of atmospheric evaporative demand (AED) in drought intensification under climate change.
• To provide new insights into the mechanisms driving multi-year droughts, which represent severe long-term risks.
• To assess the uncertainties underlying the attribution results.

Study Configuration

• Spatial Scale: Global terrestrial land at a 0.5° × 0.5° spatial resolution.
• Temporal Scale: 1961–2019 (59 years).

Methodology and Data

• Models used:
  • Factual–counterfactual climate dataset pairs from ISIMIP3a: GSWP3-W5E5, 20CRv3-W5E5, and 20CRv3-ERA5.
  • ATTRICI method for generating counterfactual ("no-CC") climate scenarios.
  • Drought indices: 12-month Standardized Precipitation Index (SPI12) and 12-month Standardized Precipitation Evapotranspiration Index (SPEI12).
  • FAO Penman–Monteith equation for calculating potential evapotranspiration (PET) for SPEI12.
  • Statistical tests: Mann–Kendall (MK) test for trend significance and Sen’s Slope Estimator (SSE) for trend magnitude.
  • Uncertainty analysis: Bootstrapping algorithm (1000 iterations).
  • Sensitivity analysis: Perturbation-based approach for SPEI12 sensitivity to AED components.
• Data sources: Reanalysis-based daily climate variables (precipitation, temperature, wind speed, relative humidity, shortwave radiation) from the ISIMIP3a dataset pairs.

Main Results

• Climate change (CC) increased drought frequency across 49.1% (SPEI12) and 46.6% (SPI12) of global land.
• SPEI12-identified drought frequency increased by over 10% in the Middle East and North Africa (MENA), parts of Africa, and central/eastern Asia under factual conditions.
• Multi-year droughts (MYDs) were predominantly attributed to CC on 20% (SPI12) and 26% (SPEI12) of global land, with effects most pronounced in MENA.
• CC shifted drought trends from neutral/wetting towards drying in 11% (SPI12) and 15% (SPEI12) of global land, notably in parts of Africa, western Greenland, South America, and China.
• The influence of CC on droughts became more pronounced during the 21st century.
• SPEI12, which incorporates atmospheric evaporative demand (AED), was more responsive to CC than SPI12, especially in water-limited regions.
• Uncertainty analysis revealed high uncertainty in central Africa, parts of MENA (for SPI), and Greenland, where conflicting model signals rendered CC attribution ambiguous.
• SPEI12 sensitivity was highest to maximum temperature in most regions, but to relative humidity in high-latitude regions and wind speed in Western North America and Eastern Asia.

Contributions

• Provides the first global-scale quantitative attribution of anthropogenic climate change to long-term drought trends, frequency, and persistence (including multi-year droughts) using both precipitation-based and AED-inclusive indices within a unified factual–counterfactual framework.
• Quantitatively isolates climate change signals from natural variability to assess shifts in drought characteristics.
• Clarifies the critical role of atmospheric evaporative demand in drought intensification under climate change.
• Offers new insights into the mechanisms driving multi-year droughts and their lasting impacts.
• Integrates a comprehensive uncertainty assessment using a bootstrapping algorithm to evaluate the robustness of attribution results.

Funding

• Program: Understanding and Managing the Interactions between Climate Change, Soil and Water, and Agricultural Production
• Institution: Iran Soil and Water Research Institute

Citation

@article{Nouri2026Global,
  author = {Nouri, Milad and Khorsandi, Mostafa},
  title = {Global Attribution of Anthropogenic Climate Change to Terrestrial Long-Term Droughts},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-025-04455-5},
  url = {https://doi.org/10.1007/s11269-025-04455-5}
}