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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2022
Research article |
| 14 Feb 2022
| 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
CORRESPONDING AUTHOR
Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
Jeremy Rohmer
BRGM, Orleans, France
Yann Krien
SHOM, DOPS/HOM/REC, Toulouse, France
Philip Jonathan
Shell Research Limited, London SE1 7NA, United Kingdom
Department of Mathematics and Statistics, Lancaster University LA1 4YF, United Kingdom
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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.
Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near...
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