Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 10, issue 2
Articles | Volume 10, issue 2
https://doi.org/10.5194/ascmo-10-69-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-10-69-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 2
22 Jul 2024
 | 22 Jul 2024

Spatiotemporal methods for estimating subsurface ocean thermal response to tropical cyclones

Addison J. Hu, Mikael Kuusela, Ann B. Lee, Donata Giglio, and Kimberly M. Wood

Viewed

Total article views: 1,413 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,151 188 74 1,413 101 94 127
  • HTML: 1,151
  • PDF: 188
  • XML: 74
  • Total: 1,413
  • Supplement: 101
  • BibTeX: 94
  • EndNote: 127
Views and downloads (calculated since 22 Jul 2024)
Cumulative views and downloads (calculated since 22 Jul 2024)

Viewed (geographical distribution)

Total article views: 1,434 (including HTML, PDF, and XML) Thereof 1,434 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Oct 2025
Download
Short summary
We introduce a new statistical framework to estimate the change in subsurface ocean temperature following the passage of a tropical cyclone (TC). Our approach combines tools handling seasonal variations and spatial dependence in the data, culminating in a three-dimensional characterization of the interaction between TCs and the ocean. Our work allows us to obtain new scientific insights, and we expect it to be generally applicable to studying the impact of TCs on other ocean phenomena.
Read more
Share