Legese et al. (2026) Spatiotemporal analysis of extreme precipitation and temperature variability, trends, and vulnerability hotspots in coffee growing districts of Ilubabor zone, Ethiopia

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2026
• Date: 2026-03-12
• Authors: Eshetu Bekele Legese, Girma Mamo Diga, Alemayehu Regassa Tolossa, Gudina Legese Feyisa
• DOI: 10.1007/s00704-026-06081-6

Research Groups

• Department of Natural Resources Management, Jimma University, Jimma, Ethiopia
• Ethiopian Institute of Agricultural Research, Climate and Computational Science Research Directorate, Addis Ababa, Ethiopia
• Centers for Environmental Science, Addis Ababa University, Addis Ababa, Ethiopia

Short Summary

This study analyzed 42 years of daily temperature and precipitation data in coffee-growing districts of Ethiopia's Ilubabor Zone to assess spatiotemporal variability, trends, and ecological vulnerability hotspots, revealing significant warming, declining heavy rainfall, increasing dry spells, and identifying Bure and Mettu districts as highly vulnerable.

Objective

• To estimate the spatiotemporal variability of extreme temperature and precipitation across the study regions.
• To identify trends in extreme precipitation and temperature over the study period.
• To identify vulnerable ecological systems to climate extremes in the study regions.

Study Configuration

• Spatial Scale: Ilubabor Zone, Southwest Ethiopia, covering an area of 10,376 km². The study focused on five specific districts: Gore, Yayu, Hurumu, Didu, and Bure, with meteorological stations located between 1,601 meters and 2,085 meters above sea level.
• Temporal Scale: 42 years (1981–2023) of daily temperature and precipitation data.

Methodology and Data

• Models used:
  • Extreme climate indices: 14 indices (8 temperature, 6 precipitation) defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), computed using the Rclimpact2 software interface.
  • Outlier detection: Z-score method (values outside ±3 standard deviations).
  • Homogeneity test: Variance-based F-test.
  • Variability analysis: Coefficient of Variation (CV).
  • Trend detection: Parametric (linear regression) and non-parametric (Mann-Kendall (MK) test and Sen’s slope estimator).
  • Vulnerability assessment: Normalization of input data (0-1 scale), weight determination (Iyengar and Sudarshan, 1982), and calculation of vulnerability indices.
  • Spatial interpolation: Inverse Distance Weighting (IDW).
  • Spatial analysis: Zonal statistics.
  • Contribution analysis: Principal Component Analysis (PCA).
• Data sources: Daily temperature and precipitation data from five meteorological stations (Bure, Didu, Gore, Mettu, and Yayo) provided by the Ethiopian Meteorological Institute (EMI).

Main Results

• Variability: Rainfall-related extreme indices (R95P, R99P, CDD, CWD) showed significantly higher variability (CVs up to 75.50%) than temperature indices, particularly nighttime extremes (TN90P, TN10P) with CVs up to 92.23%. Absolute temperature extremes (TXx, TNx, TXn, TNn) exhibited very low variability.
• Trends:
  • Precipitation: Significant decreasing trends in very wet days (R95P) in Bure and Didu districts. A sharp increase in consecutive dry days (CDD) was observed in Bure, with a notable upward trend overall. Total annual precipitation (PRCPtot) showed a mild decline of –5.49 mm/year.
  • Temperature: Significant increasing trends in warm nights (TN90P) and warm days (TX90P). Cold nights (TN10P) and cold days (TX10P) showed decreasing trends. Warmest daily maximum temperature (TXx) exhibited significant upward trends in Bure and Didu.
• Spatial Vulnerability Hotspots:
  • Bure district was identified as extremely vulnerable (score of 0.72), driven by high consecutive dry days (CDD), heavy rainfall days (R10mm), lowest minimum temperature (TNn), and very wet days (R99P).
  • Mettu district was also highly vulnerable, characterized by high total annual precipitation (PRCPtot), lowest minimum temperature (TNn), and consecutive dry days (CDD).
  • Gore district showed moderate vulnerability, influenced by R10mm, TNn, and warmest maximum temperature (TXx).
  • Yayo and Didu districts were found to be slightly vulnerable.
• Primary Drivers of Climate Variability: Total annual precipitation (PRCPtot) was the dominant climatic driver, contributing approximately 15% to the total variance. Warm night percentile (TN90P) and heavy rain days (R10mm) each contributed over 12%.

Contributions

• This study provides the first comprehensive district-level spatiotemporal analysis of extreme precipitation and temperature variability, trends, and vulnerability hotspots in the coffee-growing regions of Ilubabor Zone, Southwest Ethiopia, addressing a critical research gap.
• It quantifies the magnitude and direction of climate trends using both parametric and non-parametric methods, offering robust insights into local climate dynamics.
• The identification of specific vulnerability hotspots (e.g., Bure and Mettu districts) provides evidence-based information crucial for developing targeted climate-resilient farming practices and policy interventions to sustain coffee production and livelihoods.

Funding

• Jimma University

Citation

@article{Legese2026Spatiotemporal,
  author = {Legese, Eshetu Bekele and Diga, Girma Mamo and Tolossa, Alemayehu Regassa and Feyisa, Gudina Legese},
  title = {Spatiotemporal analysis of extreme precipitation and temperature variability, trends, and vulnerability hotspots in coffee growing districts of Ilubabor zone, Ethiopia},
  journal = {Theoretical and Applied Climatology},
  year = {2026},
  doi = {10.1007/s00704-026-06081-6},
  url = {https://doi.org/10.1007/s00704-026-06081-6}
}