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<p>Understanding the changes in wind speed is crucial not for meteorological and climate forecasting but also for optimizing wind power systems in the context of climate change. The Equatorial region of Africa lacks basic information on this regard. Therefore, the present study investigates the characteristics of wind speeds of the region. Annual and seasonal historical climatologies and trends of surface winds speed as well as the projected changes were analysed under two shared socioeconomic pathways (SSP) scenarios—SSP2-4.5 and SSP5-8.5—for the three future periods (2020–2039, 2050–2069, and 2080–2099) relative to the historical baseline period (1950–2014). Overall, the NEX-GDDP-CMIP6 multi-model ensemble (MME) performs better than the individual models in representing the surface wind speed, suggesting that the MME offers a more balanced and reliable approach. The MME also effectively captures the spatial patterns of both annual and seasonal wind climatology. Long-term increasing trends were observed for annual and summer wind speed. Overall, the MME outperforms the individual CMIP6 GCMs capturing monthly, seasonal, and annual wind climatology. In addition, the MME reproduced both increasing and decreasing trends across different regions and seasons; however, these trends were not statistically significant. Surface wind speed is projected to increase over most parts of Equatorial Africa during the mid-century and late century under both SSP2-4.5 and SSP5-8.5 scenarios. These findings provide valuable insights into the region’s wind energy potential and its capacity to adapt to future changes in surface wind conditions.&#xa0;</p> Graphical Abstract <p></p> <p>The graphical abstract presents a study of wind climatology conducted over the African continent and the Arabian Peninsula. This analysis evaluates the performance of the NEX-GDDP CMIP6 models by comparing them with observational data to assess their agreement using several statistical metrics, including root mean square error (RMSE) and Nash-Sutcliffe. Additionally, statistical significance of trends and their magnitudes were quantified using the Mann-Kendall (MK) test and Theil-Sen’s slope estimator. Both spatial and temporal aspects of wind climatology were analyzed. The study analysis revealed that the RMSE ranged from 4.5 to 9.5%, and varying NSE skill scores of individual NEX-GDDP CMIP6 models, and MME. The spatial distribution of observed and mean MME wind speeds, as well as the monthly cycle for both observation and MME, were established. Long-term spatial and temporal trends were compared between MME and observational data. Projections for future wind speed changes were analyzed, covering the base period (1950–2014) and the projection period (2021–2099) under the SSP2-4.5 and SSP5-8.5 scenarios. The projected changes in annual mean wind speed, comparing the near future, mid-century, and end-of-century periods relative to current conditions, were examined for both SSP scenarios. Additionally, interannual wind speeds for future periods were compared with historical data under the SSP2-4.5 and SSP5-8.5 scenarios. The research highlights the need to identify regional hotspots where surface wind speed is projected to increase most significantly. This information plays a crucial role in shaping regional climate adaptation strategies, particularly in regional hotspots when designing wind energy production.</p>

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Historical and Future Projection of Wind Speed Based on NEX-GDDP CMIP6 Over Equatorial Africa

  • 期刊论文

  • 发表日期：

    2025年8月20日

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  • Isaac Kwesi Nooni,
  • Shuxiao Lu,
  • Fengyi Liu,
  • Faustin Katchele Ogou,
  • Abdoul Aziz Saidou Chaibou,
  • Nana Agyemang Prempeh,
  • Khant Hmu Paing,
  • Thomas Atta-Darkwa,
  • Samuel Koranteng Fianko,
  • Michael Oteng-Peprah,
  • Mawuli Dzapkpasu,
  • Zhongfang Jin,
  • Jiao Lu

摘要

Understanding the changes in wind speed is crucial not for meteorological and climate forecasting but also for optimizing wind power systems in the context of climate change. The Equatorial region of Africa lacks basic information on this regard. Therefore, the present study investigates the characteristics of wind speeds of the region. Annual and seasonal historical climatologies and trends of surface winds speed as well as the projected changes were analysed under two shared socioeconomic pathways (SSP) scenarios—SSP2-4.5 and SSP5-8.5—for the three future periods (2020–2039, 2050–2069, and 2080–2099) relative to the historical baseline period (1950–2014). Overall, the NEX-GDDP-CMIP6 multi-model ensemble (MME) performs better than the individual models in representing the surface wind speed, suggesting that the MME offers a more balanced and reliable approach. The MME also effectively captures the spatial patterns of both annual and seasonal wind climatology. Long-term increasing trends were observed for annual and summer wind speed. Overall, the MME outperforms the individual CMIP6 GCMs capturing monthly, seasonal, and annual wind climatology. In addition, the MME reproduced both increasing and decreasing trends across different regions and seasons; however, these trends were not statistically significant. Surface wind speed is projected to increase over most parts of Equatorial Africa during the mid-century and late century under both SSP2-4.5 and SSP5-8.5 scenarios. These findings provide valuable insights into the region’s wind energy potential and its capacity to adapt to future changes in surface wind conditions. 

Graphical Abstract

The graphical abstract presents a study of wind climatology conducted over the African continent and the Arabian Peninsula. This analysis evaluates the performance of the NEX-GDDP CMIP6 models by comparing them with observational data to assess their agreement using several statistical metrics, including root mean square error (RMSE) and Nash-Sutcliffe. Additionally, statistical significance of trends and their magnitudes were quantified using the Mann-Kendall (MK) test and Theil-Sen’s slope estimator. Both spatial and temporal aspects of wind climatology were analyzed. The study analysis revealed that the RMSE ranged from 4.5 to 9.5%, and varying NSE skill scores of individual NEX-GDDP CMIP6 models, and MME. The spatial distribution of observed and mean MME wind speeds, as well as the monthly cycle for both observation and MME, were established. Long-term spatial and temporal trends were compared between MME and observational data. Projections for future wind speed changes were analyzed, covering the base period (1950–2014) and the projection period (2021–2099) under the SSP2-4.5 and SSP5-8.5 scenarios. The projected changes in annual mean wind speed, comparing the near future, mid-century, and end-of-century periods relative to current conditions, were examined for both SSP scenarios. Additionally, interannual wind speeds for future periods were compared with historical data under the SSP2-4.5 and SSP5-8.5 scenarios. The research highlights the need to identify regional hotspots where surface wind speed is projected to increase most significantly. This information plays a crucial role in shaping regional climate adaptation strategies, particularly in regional hotspots when designing wind energy production.