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Peer-reviewedCC BYCommunications Earth & Environment

A semi-automated framework for global detection of previously undocumented submarine calderas

  • Andrea Verolino1
  • Christopher Lee2
  • Susanna F. Jenkins3
  • Martin Jutzeler4
  • Adam D. Switzer3
4 affiliations
  1. 1Géosciences Paris Saclay (GEOPS), Université Paris-Saclay
  2. 2Department of Physics, University of Toronto
  3. 3Earth Observatory of Singapore, Nanyang Technological University
  4. 4Centre for Ore Deposit and Earth Sciences (CODES) and School of Natural Sciences, University of Tasmania
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Abstract

Submarine calderas are far less documented than their subaerial counterparts, yet recent events highlight their potential for impactful geohazards. Their detection has been limited by the scarcity of high-resolution bathymetry data. Here we apply a hybrid framework to the low-resolution but globally available General-Bathymetric-Chart-of-the-Ocean, combining an automated algorithm for detecting depressions on the seafloor, expert (user-based) classification, and Principal Component Analysis validation to systematically identify previously undocumented submarine calderas. We identify 78 calderas spanning a wide range of water depths (to 5,600 m), diameters (to 20 km), and tectonic settings (divergent, convergent, intraplate), of which only five were previously known. A sensitivity test shows that under-detection of known calderas is largely associated with low circularity indexes ( < 50%). Despite this limitation, our dataset fills a major observational gap and provides a reproducible, upgradeable framework for submarine volcano characterisation, underscoring the need to incorporate submarine calderas into future global volcanic assessments.

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Cite

BibTeXRIS
BibTeX
@article{verolino2026semiautomated,
  title = {{A semi-automated framework for global detection of previously undocumented submarine calderas}},
  author = {Andrea Verolino and Christopher Lee and Susanna F. Jenkins and Martin Jutzeler and Adam D. Switzer},
  journal = {Communications Earth \& Environment},
  year = {2026},
  month = jul,
  doi = {10.1038/s43247-026-03779-3},
  url = {https://doi.org/10.1038/s43247-026-03779-3},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - A semi-automated framework for global detection of previously undocumented submarine calderas
AU  - Andrea Verolino
AU  - Christopher Lee
AU  - Susanna F. Jenkins
AU  - Martin Jutzeler
AU  - Adam D. Switzer
PY  - 2026
DA  - 2026/07/01
JO  - Communications Earth & Environment
DO  - 10.1038/s43247-026-03779-3
UR  - https://doi.org/10.1038/s43247-026-03779-3
AB  - Submarine calderas are far less documented than their subaerial counterparts, yet recent events highlight their potential for impactful geohazards. Their detection has been limited by the scarcity of high-resolution bathymetry data. Here we apply a hybrid framework to the low-resolution but globally available General-Bathymetric-Chart-of-the-Ocean, combining an automated algorithm for detecting depressions on the seafloor, expert (user-based) classification, and Principal Component Analysis validation to systematically identify previously undocumented submarine calderas. We identify 78 calderas spanning a wide range of water depths (to 5,600 m), diameters (to 20 km), and tectonic settings (divergent, convergent, intraplate), of which only five were previously known. A sensitivity test shows that under-detection of known calderas is largely associated with low circularity indexes ( < 50%). Despite this limitation, our dataset fills a major observational gap and provides a reproducible, upgradeable framework for submarine volcano characterisation, underscoring the need to incorporate submarine calderas into future global volcanic assessments.
SN  - 2662-4435
ER  -