Chanie (2025) Evaluation of CMIP6 model performance and future climate projections over the Genale dawa river basin, Ethiopia

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-12-04
• Authors: Fetene Muluken Chanie
• DOI: 10.1038/s41598-025-29498-x

Research Groups

Department of Meteorological Data and Climatology, Ethiopian Meteorology Institute, Addis Ababa, Ethiopia.

Short Summary

This study evaluated 12 CMIP6 models for historical climate simulation (1985–2014) and future projections (2021–2080) of precipitation and temperature over the Genale Dawa River Basin, Ethiopia. It found that the multi-model ensemble outperformed individual models and projected significant warming (up to 1.8 °C for Tmax and Tmin) and pronounced seasonal precipitation shifts (e.g., March decline, November increase) under high-emission scenarios.

Objective

• Evaluate the performance of 12 CMIP6 Global Climate Models (GCMs) in simulating historical precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) over the Genale Dawa River Basin (GDRB) for 1985–2014, and project future changes for 2021–2050 and 2051–2080 under SSP2-4.5 and SSP5-8.5 scenarios.

Study Configuration

• Spatial Scale: Genale Dawa River Basin (GDRB) in southeastern Ethiopia, covering approximately 171,050 km². Model outputs were resampled to 0.05° × 0.05° (approximately 5 km × 5 km) resolution.
• Temporal Scale: Historical period: 1985–2014 (30 years). Future projection periods: 2021–2050 (near-term, 30 years) and 2051–2080 (mid-term/far-term, 30 years).

Methodology and Data

• Models used: 12 CMIP6 Global Climate Models (GCMs) including BCC-CSM2-MR, CanESM5, CNRM-CM6-1, FGOALS-g3, GFDL-CM4, GFDL-ESM4, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, and a Multi-Model Ensemble (MME).
• Data sources:
  • Observational: Enhancing National Climate Services (ENACTS) gridded data (4 km × 4 km resolution) and daily measurements from 60 ground-based meteorological stations, both from the Ethiopian Meteorological Institute (EMI).
  • Model: CMIP6 GCM data from the Earth System Grid Federation (ESGF) archives.
  • Methodology:
    • Spatial resampling of GCM outputs to 0.05° × 0.05° resolution using bilinear interpolation.
    • Bias correction using the quantile mapping (QM) method, applied to basin-averaged climate variables.
    • Model performance evaluation using Mean Bias Error (MBE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (r), and Taylor Skill Score (TSS).
    • Future climate projections analyzed under Shared Socioeconomic Pathways (SSPs): SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions).
    • Trend analysis using the Mann–Kendall (MK) test, Modified Mann–Kendall (MMK) test, and Sen’s slope estimator.
    • Key variables: Daily precipitation (pr), maximum temperature (tasmax), and minimum temperature (tasmin).

Main Results

• The Multi-Model Ensemble (MME) consistently outperformed individual GCMs in simulating historical climate patterns, achieving Taylor Skill Scores (TSS) of 0.80 for precipitation, 0.98 for maximum temperature (Tmax), and 0.99 for minimum temperature (Tmin).
• Among individual models, CNRM-CM6-1 performed best for precipitation, GFDL-CM4 and NorESM2-MM for Tmax, and FGOALS-g3 and MRI-ESM2-0 for Tmin.
• Most models reproduced observed spatial and temporal patterns well but showed a systematic cold bias in Tmin before bias correction, while Tmax was more accurately simulated.
• Under the SSP5-8.5 mid-century (2051–2080) scenario, Tmax and Tmin are projected to increase by approximately 1.8 °C, and precipitation by 11.1% (5.4 mm).
• Future projections indicate Tmin will increase more rapidly than Tmax. March rainfall is projected to decline by over 60%, while November rainfall may see increases exceeding 120%, suggesting significant intra-annual variability shifts.
• Trend analysis confirmed statistically significant warming trends for Tmin during 2021–2050 under both SSP2-4.5 (p = 0.04) and SSP5-8.5 (p = 0.01). Tmax showed a significant increasing trend only under SSP5-8.5 during 2051–2080 (p = 0.03). Rainfall trends remained statistically insignificant across all future scenarios.

Contributions

• This study provides the first detailed assessment of CMIP6 model performance and future climate projections over the Genale Dawa River Basin (GDRB), a highly vulnerable and understudied region in southeastern Ethiopia.
• It addresses a key research gap by evaluating the latest CMIP6 datasets at a basin scale, incorporating high-resolution ENACTS data and in-situ station records for a robust dual-layer validation approach.
• The research identifies the most reliable CMIP6 models for the region and provides localized, bias-corrected climate projections, which are crucial for improving climate risk assessment, adaptation planning, and sustainable water resource management in the GDRB.
• The findings offer critical insights for national adaptation strategies, regional water policy coordination, and climate-resilient development in a region heavily dependent on rain-fed agriculture and transboundary water resources.

Funding

The author did not receive any funds for this study.

Citation

@article{Chanie2025Evaluation,
  author = {Chanie, Fetene Muluken},
  title = {Evaluation of CMIP6 model performance and future climate projections over the Genale dawa river basin, Ethiopia},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-29498-x},
  url = {https://doi.org/10.1038/s41598-025-29498-x}
}