Quantifying climate change-driven variations in projected wind condition in the Gulf of Guinea

被引：0
作者：
Dahunsi, Adeola M. [1 ]
Bonou, Frederic [1 ,2 ,3 ]
Dada, Olusegun A. [4 ]
Baloitcha, Ezinvi [1 ]
机构：
[1] Univ Abomey Calavi, Int Chair Math Phys & Applicat ICMPA, Cotonou, Benin
[2] Univ Natl Sci Technol Ingn & Math, Goho Abomey, France
[3] Intitut Rech Halieut & Oceanol Benin, Lab Hydrol Marine & Cotiere, LIST, Cotonou, France
[4] Fed Univ Technol Akure, Dept Marine Sci & Technol, Akure 340252, Nigeria
来源：
DYNAMICS OF ATMOSPHERES AND OCEANS | 2025年 / 110卷
关键词：
Gulf of Guinea; Wind condition; Projections; Ensemble; Climate change; RCP scenario; SURFACE WIND; SPEED; RESOURCES; IMPACT;
D O I：
10.1016/j.dynatmoce.2025.101543
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Understanding wind climate dynamics in the Gulf of Guinea (GoG) is critical for addressing climate-related challenges and supporting sustainable development in the region. This study evaluates the wind climate using observational buoy data from the PIRATA network and multiple General Circulation Models (GCMs) under historical and future Representative Concentration Pathway (RCP 8.5) scenarios. An ensemble dataset, constructed as the average of GCM outputs, was validated against PIRATA buoy measurements and demonstrated better performance to individual GCMs. The study revealed distinct temporal and spatial variability in wind conditions across the dry and rainy seasons during the baseline period (1961-2014). Projections under RCP 8.5 for mid-century (2026-2060) and end-century (2066-2100) consistently indicate increasing wind speeds, with the most significant changes projected during the rainy season. These findings highlight the critical role of ensemble modelling in mitigating biases inherent in individual datasets and its contribution to a robust understanding of wind dynamics in the region. The observed trends have significant implications for coastal upwelling, maritime safety, renewable energy development, and climate resilience strategies in the GoG. This study highlights the necessity of fine-scale spatio-temporal modelling to improve predictions and guide evidence-based adaptive strategies to mitigate climate change impacts on coastal ecosystems and vulnerable communities.
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页数：19
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共 67 条
[1]  
Alizadeh M.J., Kavianpour M.R., Kamranzad B., Etemad-Shahidi A., A Weibull distribution based technique for downscaling of climatic wind field, Asia-Pac. J. Atmos. Sci., 55, pp. 685-700, (2019)
[2]  
Alizadeh M.J., Kavianpour M.R., Kamranzad B., Etemad-Shahidi A., A distributed wind downscaling technique for wave climate modeling under future scenarios, Ocean Model., 145, (2020)
[3]  
Almar R., Kestenare E., Reyns J., Jouanno J., Anthony E.J., Laibi R., Hemer M., Du Penhoat Y., Ranasinghe R., Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing, Part1: Wave climate variability and impacts on the longshore sediment transport, Cont. Shelf Res., 110, pp. 48-59, (2015)
[4]  
Almar R., Stieglitz T., Addo K.A., Ba K., Ondoa G.A., Bergsma E.W.J., Bonou F., Dada O., Angnuureng D., Arino O., Coastal Zone Changes in West Africa: Challenges and Opportunities for Satellite Earth Observations, Surv. Geophys., (2022)
[5]  
Alory G., Da-Allada C.Y., Djakoure S., Dadou I., Jouanno J., Loemba D.P., Coastal upwelling limitation by onshore geostrophic flow in the Gulf of Guinea around the Niger River plume, Front. Mar. Sci., 7, (2021)
[6]  
Alves B., Angnuureng D.B., Morand P., Almar R., A review on coastal erosion and flooding risks and best management practices in West Africa: what has been done and should be done, J. Coast. Conserv., 24, 3, (2020)
[7]  
Alves J.-H.G.M., Wittmann P., Sestak M., Schauer J., Stripling S., Bernier N.B., McLean J., Chao Y., Chawla A., Tolman H., The NCEP–FNMOC combined wave ensemble product: expanding benefits of interagency probabilistic forecasts to the oceanic environment, Bull. Am. Meteorol. Soc., 94, 12, pp. 1893-1905, (2013)
[8]  
Baghanian S., Alizadeh M.J., Wave climate projection in the Persian Gulf: An ensemble of statistically downscaled CMIP6-GCMs, Ocean Eng., 266, (2022)
[9]  
Basakin E.E., Ekmekcioglu O., Cıtakoglu H., Ozger M., A new insight to the wind speed forecasting: robust multi-stage ensemble soft computing approach based on pre-processing uncertainty assessment, Neural Comput. Appl., 34, 1, pp. 783-812, (2022)
[10]  
Berrisford P., Dee D., Poli P., Brugge R., Fielding K., Fuentes M., Kallberg P., Kobayashi S., Uppala S., Simmons A., The ERA-Interim archive, version, 2, (2011)
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