Ocean Science
Ocean Science
OS
Articles | Volume 18, issue 2
Articles | Volume 18, issue 2
https://doi.org/10.5194/os-18-419-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-419-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 2
Research article
 | 
28 Mar 2022
Research article |  | 28 Mar 2022

Forecasting hurricane-forced significant wave heights using a long short-term memory network in the Caribbean Sea

Brandon J. Bethel, Wenjin Sun, Changming Dong, and Dongxia Wang

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Short summary
Ocean surface waves forced by tropical cyclones can cause tremendous damage to offshore structures and coastal communities. As such, forecasting their evolution is of utmost importance. This study investigates the usage of a long short-term memory neural network to forecast hurricane-forced waves in the Caribbean Sea. Results strongly suggest that forecasts can be performed to a high degree of accuracy up to 12 h at minimal computational expense and even outperform a wave model.
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