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Wave climate and energy resources in American Samoa from a 42-year high-resolution hindcast

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  • García Medina, Gabriel
  • Yang, Zhaoqing
  • Li, Ning
  • Cheung, Kwok Fai
  • Lutu-McMoore, Elinor

Abstract

This paper presents an analysis of the wave climate and a characterization of the wave energy resources in American Samoa, a U.S. territory covering seven south central Pacific islands and atolls. A numerical wave model based on WAVEWATCH III® and unstructured SWAN was developed, validated, and executed for 1979–2020 to generate a hindcast dataset suitable for resource characterization. Model-data comparisons were performed with measurements collected in situ and from satellite-based altimeters. The model was found to perform well with a bias in significant wave height of −0.14 m and −0.06 m against buoy and altimeters, respectively. The multimodal sea state of American Samoa is investigated by identifying the sources of energy reaching the islands and partitioning the wave spectrum accordingly. The wave resources characterization follows the International Electrotechnical Commission Technical Specifications to be compatible with studies performed for other U.S. regions. The average omnidirectional wave power at 2 km from shore around Tutuila, the main island of American Samoa, is 14 kW/m. Locations east and west of the islands have a more consistent resource throughout the year because the northwest and southwest swells that are dominant during different seasons complement each other.

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  • García Medina, Gabriel & Yang, Zhaoqing & Li, Ning & Cheung, Kwok Fai & Lutu-McMoore, Elinor, 2023. "Wave climate and energy resources in American Samoa from a 42-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 210(C), pages 604-617.
    • Handle: RePEc:eee:renene:v:210:y:2023:i:c:p:604-617
    DOI: 10.1016/j.renene.2023.03.031
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    1. Robertson, Bryson R.D. & Hiles, Clayton E. & Buckham, Bradley J., 2014. "Characterizing the near shore wave energy resource on the west coast of Vancouver Island, Canada," Renewable Energy, Elsevier, vol. 71(C), pages 665-678.
    2. Arinaga, Randi A. & Cheung, Kwok Fai, 2012. "Atlas of global wave energy from 10 years of reanalysis and hindcast data," Renewable Energy, Elsevier, vol. 39(1), pages 49-64.
    3. Allahdadi, M. Nabi & Gunawan, Budi & Lai, Jonathan & He, Ruoying & Neary, Vincent S., 2019. "Development and validation of a regional-scale high-resolution unstructured model for wave energy resource characterization along the US East Coast," Renewable Energy, Elsevier, vol. 136(C), pages 500-511.
    4. García-Medina, Gabriel & Yang, Zhaoqing & Wu, Wei-Cheng & Wang, Taiping, 2021. "Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 170(C), pages 595-612.
    5. Yang, Zhaoqing & García-Medina, Gabriel & Wu, Wei-Cheng & Wang, Taiping, 2020. "Characteristics and variability of the nearshore wave resource on the U.S. West Coast," Energy, Elsevier, vol. 203(C).
    6. Guillou, Nicolas & Chapalain, Georges, 2018. "Annual and seasonal variabilities in the performances of wave energy converters," Energy, Elsevier, vol. 165(PB), pages 812-823.
    7. Yang, Zhaoqing & Neary, Vincent S. & Wang, Taiping & Gunawan, Budi & Dallman, Annie R. & Wu, Wei-Cheng, 2017. "A wave model test bed study for wave energy resource characterization," Renewable Energy, Elsevier, vol. 114(PA), pages 132-144.
    8. Lin, Yifan & Dong, Sheng & Wang, Zhifeng & Guedes Soares, C., 2019. "Wave energy assessment in the China adjacent seas on the basis of a 20-year SWAN simulation with unstructured grids," Renewable Energy, Elsevier, vol. 136(C), pages 275-295.
    9. Guillou, Nicolas & Chapalain, Georges, 2015. "Numerical modelling of nearshore wave energy resource in the Sea of Iroise," Renewable Energy, Elsevier, vol. 83(C), pages 942-953.
    10. Ozkan, Cigdem & Mayo, Talea, 2019. "The renewable wave energy resource in coastal regions of the Florida peninsula," Renewable Energy, Elsevier, vol. 139(C), pages 530-537.
    11. Defne, Zafer & Haas, Kevin A. & Fritz, Hermann M., 2009. "Wave power potential along the Atlantic coast of the southeastern USA," Renewable Energy, Elsevier, vol. 34(10), pages 2197-2205.
    12. Canals Silander, Miguel F. & García Moreno, Carlos G., 2019. "On the spatial distribution of the wave energy resource in Puerto Rico and the United States Virgin Islands," Renewable Energy, Elsevier, vol. 136(C), pages 442-451.
    13. Carlo Lo Re & Giorgio Manno & Giuseppe Ciraolo & Giovanni Besio, 2019. "Wave Energy Assessment around the Aegadian Islands (Sicily)," Energies, MDPI, vol. 12(3), pages 1-20, January.
    14. Li, Ning & García-Medina, Gabriel & Cheung, Kwok Fai & Yang, Zhaoqing, 2021. "Wave energy resources assessment for the multi-modal sea state of Hawaii," Renewable Energy, Elsevier, vol. 174(C), pages 1036-1055.
    15. Ahn, Seongho & Neary, Vincent S. & Allahdadi, Mohammad Nabi & He, Ruoying, 2021. "Nearshore wave energy resource characterization along the East Coast of the United States," Renewable Energy, Elsevier, vol. 172(C), pages 1212-1224.
    16. Wu, Wei-Cheng & Wang, Taiping & Yang, Zhaoqing & García-Medina, Gabriel, 2020. "Development and validation of a high-resolution regional wave hindcast model for U.S. West Coast wave resource characterization," Renewable Energy, Elsevier, vol. 152(C), pages 736-753.
    17. Lokuliyana, R.L.K. & Folley, M. & Gunawardane, S.D.G.S.P. & Wickramanayake, P.N., 2020. "Sri Lankan wave energy resource assessment and characterisation based on IEC standards," Renewable Energy, Elsevier, vol. 162(C), pages 1255-1272.
    18. García-Medina, Gabriel & Özkan-Haller, H. Tuba & Ruggiero, Peter, 2014. "Wave resource assessment in Oregon and southwest Washington, USA," Renewable Energy, Elsevier, vol. 64(C), pages 203-214.
    19. Wei-Cheng Wu & Zhaoqing Yang & Taiping Wang, 2018. "Wave Resource Characterization Using an Unstructured Grid Modeling Approach," Energies, MDPI, vol. 11(3), pages 1-15, March.
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    Cited by:

    1. Li, Ning & García Medina, Gabriel & Yang, Zhaoqing & Cheung, Kwok Fai & Hitzl, David & Chen, Yi-Leng, 2023. "Wave climate and energy resources in the Mariana Islands from a 42-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 215(C).
    2. Yang, Zhaoqing & García Medina, Gabriel & Neary, Vincent S. & Ahn, Seongho & Kilcher, Levi & Bharath, Aidan, 2023. "Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters," Renewable Energy, Elsevier, vol. 212(C), pages 803-817.

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