Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 22, issue 2
Articles | Volume 22, issue 2
https://doi.org/10.5194/nhess-22-431-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-22-431-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 2
Research article
 | 
14 Feb 2022
Research article |  | 14 Feb 2022

Statistical estimation of spatial wave extremes for tropical cyclones from small data samples: validation of the STM-E approach using long-term synthetic cyclone data for the Caribbean Sea

Ryota Wada, Jeremy Rohmer, Yann Krien, and Philip Jonathan

Viewed

Total article views: 2,207 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,550 596 61 2,207 63 66
  • HTML: 1,550
  • PDF: 596
  • XML: 61
  • Total: 2,207
  • BibTeX: 63
  • EndNote: 66
Views and downloads (calculated since 29 Mar 2021)
Cumulative views and downloads (calculated since 29 Mar 2021)

Viewed (geographical distribution)

Total article views: 2,207 (including HTML, PDF, and XML) Thereof 2,072 with geography defined and 135 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 Jul 2025
Download
Short summary
Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near Guadeloupe is difficult because cyclones rarely pass near the location of interest. STM-E (space-time maxima and exposure) model utilizes wave data during cyclones on a spatial neighbourhood. Long-duration wave data generated from a database of synthetic tropical cyclones are used to evaluate the performance of STM-E. Results indicate STM-E provides estimates with small bias and realistic uncertainty.
Read more
Share
Special issue
Coastal hazards and hydro-meteorological extremes
Altmetrics
Final-revised paper
Preprint