Zhao, Zijie
ORCID: https://orcid.org/0000-0003-3403-878X; Holbrook, Neil J.
ORCID: https://orcid.org/0000-0002-3523-6254; Capotondi, Antonietta
ORCID: https://orcid.org/0000-0002-3594-5472; Cravatte, Sophie
ORCID: https://orcid.org/0000-0002-2439-8952; Kajtar, Jules B.
ORCID: https://orcid.org/0000-0003-0114-6610; Gupta, Alex Sen
ORCID: https://orcid.org/0000-0001-5226-871X; Behrens, Erik
ORCID: https://orcid.org/0000-0002-9713-7227; Doblin, Martina A.
ORCID: https://orcid.org/0000-0001-8750-3433; Feng, Ming
ORCID: https://orcid.org/0000-0002-2855-7092; Kiss, Andrew E.
ORCID: https://orcid.org/0000-0001-8960-9557; Spillman, Claire M.
ORCID: https://orcid.org/0000-0003-0853-8190.
2026
Toward a mechanistic characterisation of marine heatwaves.
Scientific Reports, 16 (1).
10.1038/s41598-026-40354-4
A mechanistic understanding of marine heatwaves (MHWs) requires robust frameworks for detection,
tracking, and attribution. Conventional pointwise definitions, which identify MHWs pixel by pixel
relative to fixed thresholds, have enabled global analyses but neglect the event-scale spatiotemporal
evolution and underlying drivers. Recent kinematic approaches overcome the evolution issue
by treating MHWs as evolving spatiotemporal objects. Here, we build on this framework by also
considering the drivers. We examine the MHW dynamics by quantifying the scale and driver
dependence of MHW objects, identifying dominant forcing mechanisms throughout their lifetimes,
and characterising key features linked to distinct drivers. We further introduce a normalisation
framework that preserves the event scale, while enabling composite analyses across multiple MHWs.
Applying this approach to the Tasman Sea, a region of complex atmosphere–ocean interactions,
we reveal distinct atmospheric and oceanic conditions that shape the MHW evolution at different
stages. By explicitly linking evolving MHW entities to their physical drivers, our method advances the
mechanistic characterisation of MHWs, enhances understanding of their spatiotemporal dynamics, and
informs prospects for improved prediction.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.
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NOC Research Groups 2025 > Global Climate
NOC Mission Networks > Hazards & Pollution
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