Ogunrinde et al. (2025) Probabilistic quantification of global drought risk amplification from temperature-enhanced evapotranspiration under climate change

Identification

• Journal: Geoscience Frontiers
• Year: 2025
• Date: 2025-12-08
• Authors: Akinwale T. Ogunrinde, Paul Adigun, Xian Xue, Sabab Ali Shah, Adawa Ifeoluwa Seun
• DOI: 10.1016/j.gsf.2025.102235

Research Groups

• Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China
• Department of Engineering Mechanics and Energy, University of Tsukuba, Tsukuba, Japan
• Department of Space Environment, Institute of Basic and Applied Sciences, Egypt-Japan University of Science and Technology (E-JUST), New Borg El-Arab City, Alexandria, Egypt

Short Summary

This study develops a probabilistic framework using the Risk Ratio methodology and CMIP6 models to quantify global drought risk amplification from temperature-enhanced evapotranspiration under climate change. It reveals pervasive global drought intensification, particularly under high-emission scenarios, with over 90% of land grids projected to experience increased severity by the far-future period.

Objective

• To assess the accuracy of CMIP6 models in simulating meteorological, agricultural, and hydrological droughts compared to observed data.
• To project changes in global drought characteristics (duration, frequency, severity) under SSP2-4.5 and SSP5-8.5 scenarios.
• To demonstrate how a probabilistic framework using the Risk Ratio (RR) methodology can enhance the understanding of drought risk transitions under climate scenarios.

Study Configuration

• Spatial Scale: Global, with all model outputs and observational datasets regridded to a consistent 0.5° × 0.5° resolution.
• Temporal Scale:
  • Historical period for model evaluation: 1951–2014.
  • Baseline period for drought index parameter estimation: 1951–1980.
  • Near-future (NF) projection period: 2036–2065.
  • Far-future (FF) projection period: 2071–2100.
  • Drought characteristics analyzed at 3-month and 12-month timescales.

Methodology and Data

• Models used:
  • Multi-model ensemble (MME) from 16 Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs).
  • Penman-Monteith (PM) ETo model (ASCE standardized equation) for calculating potential evapotranspiration (PET).
  • Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI) for drought assessment.
  • Probabilistic framework employing the Risk Ratio (RR) methodology, integrated with extreme value theory and non-parametric statistical inference.
  • "Run theory" with a threshold of ≤ -1 for at least three consecutive months to characterize drought events.
• Data sources:
  • CMIP6 GCM outputs for precipitation (pr), surface temperature (tas, tasmin, tasmax), wind speed (sfcWind), surface relative humidity (hurs), and net incoming solar radiation (derived from rsds and rlds) under Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5).
  • University of East Anglia Climate Research Unit’s TS4.07 (CRU TS) monthly gridded dataset (precipitation, temperature, cloud cover, vapor pressure, and PET derived using the PM model) as an observational benchmark.

Main Results

• Pervasive Global Intensification: Over 90% of land grids are projected to exhibit positive drought severity shifts under the SSP5-8.5 scenario in the far-future (2071–2100).
• Dominance of Thermodynamic Drivers: Atmospheric evaporative demand (AED) is a primary driver, accounting for approximately 44% of the trends observed in the Standardized Precipitation Evapotranspiration Index (SPEI).
• Nonlinear Escalation of Extreme Events: Threshold-stratified Risk Ratio (RR) assessments reveal nonlinear escalations at higher percentiles (P90 vs. P75), with frequency risks increasing by 20%–30% more under high-emission pathways, compressing the return periods of extreme events.
• Regional Hotspots of Amplified Risk:
  • Regions including the Amazon basin, sub-Saharan Africa, southwestern North America, and Central Asian drylands show frequency risks amplified 4-fold or more.
  • Africa registers the highest absolute risks, with frequency ratios ranging from 4.4× at the 75th percentile (P75) to 6.2× at the 90th percentile (P90) under SSP5-8.5.
  • Central Asian drylands show frequency ratios rising from 3.6× at P75 to 5.7× at P90 under SSP5-8.5.
  • The Amazon basin (South America) shows frequency ratios reaching 3.1× at P75 to 4.4× at P90 under SSP5-8.5.
• Projected Drought Characteristic Changes (SPEI-based): Under SSP5-8.5 in the far-future, SPEI-3 severity changes approach 10 units and frequency increases up to 12 events. For SPEI-12, duration extensions are up to 12 months and severity shifts up to 18 units.
• Mitigation Potential: Lower-emission pathways (e.g., SSP2-4.5) could curtail drought risks by 15%–25% compared to high-emission scenarios (SSP5-8.5).
• Model Performance: CMIP6 multi-model ensemble (MME) broadly captures large-scale spatial patterns of drought characteristics but exhibits systematic biases (e.g., overestimation of SPEI-3 drought severity in the Amazon basin, underestimation in Southern Europe). MME shows good agreement (bias < 10%) over approximately 40% of land grids for SPEI-3.

Contributions

• Introduces a novel probabilistic framework for quantifying drought risk transitions using the Risk Ratio (RR) methodology, integrating extreme value theory and non-parametric statistical inference, which transcends traditional deterministic models by capturing non-stationary dynamics and threshold-dependent amplifications.
• Provides a precise delineation of risk compression across return periods, particularly for extreme events, offering a more dynamic and nuanced understanding of future drought risks.
• Quantifies the dominant role of thermodynamic drivers, specifically elevated atmospheric evaporative demand (AED), over precipitation variability in amplifying drought characteristics, showing AED contributes approximately 44% to SPEI trends.
• Offers critical insights for policymakers and stakeholders, informing targeted adaptive strategies (e.g., enhanced water storage capacity by 150%–250%, climate-smart agriculture) and underscoring the benefits of emissions mitigation to curtail cascading impacts on global food security, biodiversity, and economic stability.

Funding

The study was supported by the Northwest Institute of Ecological Environment and Resources, Chinese Academy of Science (grant number: E429020101).

Citation

@article{Ogunrinde2025Probabilistic,
  author = {Ogunrinde, Akinwale T. and Adigun, Paul and Xue, Xian and Dairaku, Koji and Shah, Sabab Ali and Seun, Adawa Ifeoluwa},
  title = {Probabilistic quantification of global drought risk amplification from temperature-enhanced evapotranspiration under climate change},
  journal = {Geoscience Frontiers},
  year = {2025},
  doi = {10.1016/j.gsf.2025.102235},
  url = {https://doi.org/10.1016/j.gsf.2025.102235}
}