Modeling Sea Ice Effects for Wave Energy Resource Assessments

Ruth Branch, Gabriel García-Medina, Zhaoqing Yang, Taiping Wang, Fadia Ticona Rollano and Lucia Hosekova
Additional contact information
Ruth Branch: Pacific Northwest National Laboratory, Coastal Sciences Division, Seattle, WA 98109, USA
Gabriel García-Medina: Pacific Northwest National Laboratory, Coastal Sciences Division, Seattle, WA 98109, USA
Zhaoqing Yang: Pacific Northwest National Laboratory, Coastal Sciences Division, Seattle, WA 98109, USA
Taiping Wang: Pacific Northwest National Laboratory, Coastal Sciences Division, Seattle, WA 98109, USA
Fadia Ticona Rollano: Pacific Northwest National Laboratory, Coastal Sciences Division, Seattle, WA 98109, USA
Lucia Hosekova: Applied Physics Laboratory, University of Washington, Seattle, WA 98105, USA

Energies, 2021, vol. 14, issue 12, 1-15

Abstract: Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

Keywords: wave energy resource; wave–ice interaction; Alaska Coast; SWAN; WW3 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/12/3482/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/12/3482/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:12:p:3482-:d:573622

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().