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<p>Climate change poses a significant threat to human society and natural ecosystems. Therefore, assessing the historical and future climate variables is crucial for implementing effective adaptation and mitigation strategies. Hence, this study evaluates the performance of CMIP6 climate models and projects future climate variables over the Amhara National Regional State, Ethiopia. The study was used observed data for model evaluation and bias correction. Fifteen CMIP6 climate models were used to project future climate variables under medium (SSP2-4.5) and high (SSP5-8.5) emission scenarios. The study also used Mann–Kendall and Sen’s slope tests were employed to detect trends and magnitude of change. The finding of the study revealed that model EC-Earth3-CC was the most reliable model for precipitation with R<sup>2</sup> = 0.86 and r = 0.93, while model AWI-ESM-1–1-LR performed best for temperature with R<sup>2</sup> ≈ 0.77–0.63 and r ≈ 0.88–0.81. The result also showed an increase in rainfall amount by about 82.3&#xa0;mm (7.3%) under SSP2-4.5 scenario and 199.7&#xa0;mm (17.6%) under SSP5-8.5 from the period 2015–2100. In addition, mean annual maximum temperature over the study area is projected to increase by 0.7&#xa0;°C and 0.9&#xa0;°C under SSP2-4.5 and SSP5-8.5, respectively. Similarly, the mean annual minimum temperature is estimated to increase by 0.7&#xa0;°C and 1.0&#xa0;°C under SSP2-4.5 and SSP5-8.5, respectively. During the period between 2075–2100, temperature increases relative to the baseline period (1990–2014) could reach 1.0&#xa0;°C and 0.9&#xa0;°C (SSP2-4.5) and 1.4&#xa0;°C and 1.6&#xa0;°C (SSP5-8.5), respectively. The spatial analysis shows maximum and minimum temperature were observed in northwestern and southern part of the study area, respectively. Hence, the finding of this study is vital for developing evidence-based and targeted climate adaptation strategies and highlight the need for improving climate models to better assess future climate change impacts and understanding of regional climate variability and extremes in the region.</p>

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Assessing the performance of CMIP6 climate models and future projections of climate variables over the Amhara National Regional State, Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Daniel Ayalew Mengistu,
  • Fekadie Bazie Enyew,
  • Daniel Asfaw Bekele,
  • Agumassie Genet Gela,
  • Dejene Sahlu,
  • Simachew Bantigegn Wassie

摘要

Climate change poses a significant threat to human society and natural ecosystems. Therefore, assessing the historical and future climate variables is crucial for implementing effective adaptation and mitigation strategies. Hence, this study evaluates the performance of CMIP6 climate models and projects future climate variables over the Amhara National Regional State, Ethiopia. The study was used observed data for model evaluation and bias correction. Fifteen CMIP6 climate models were used to project future climate variables under medium (SSP2-4.5) and high (SSP5-8.5) emission scenarios. The study also used Mann–Kendall and Sen’s slope tests were employed to detect trends and magnitude of change. The finding of the study revealed that model EC-Earth3-CC was the most reliable model for precipitation with R2 = 0.86 and r = 0.93, while model AWI-ESM-1–1-LR performed best for temperature with R2 ≈ 0.77–0.63 and r ≈ 0.88–0.81. The result also showed an increase in rainfall amount by about 82.3 mm (7.3%) under SSP2-4.5 scenario and 199.7 mm (17.6%) under SSP5-8.5 from the period 2015–2100. In addition, mean annual maximum temperature over the study area is projected to increase by 0.7 °C and 0.9 °C under SSP2-4.5 and SSP5-8.5, respectively. Similarly, the mean annual minimum temperature is estimated to increase by 0.7 °C and 1.0 °C under SSP2-4.5 and SSP5-8.5, respectively. During the period between 2075–2100, temperature increases relative to the baseline period (1990–2014) could reach 1.0 °C and 0.9 °C (SSP2-4.5) and 1.4 °C and 1.6 °C (SSP5-8.5), respectively. The spatial analysis shows maximum and minimum temperature were observed in northwestern and southern part of the study area, respectively. Hence, the finding of this study is vital for developing evidence-based and targeted climate adaptation strategies and highlight the need for improving climate models to better assess future climate change impacts and understanding of regional climate variability and extremes in the region.