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Record W3101881145 · doi:10.1038/s41598-020-75445-3

Drivers and impacts of the most extreme marine heatwave events

2020· article· en· W3101881145 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDalhousie University
FundersNatural Environment Research CouncilClimate ExtremesUK Research and InnovationMarie CurieMarine Environmental Observation Prediction and Response NetworkAustralian Research CouncilNational Oceanic and Atmospheric AdministrationSight Research UKNatural Sciences and Engineering Research Council of CanadaWoods Hole Oceanographic InstitutionAndrew W. Mellon Foundation
KeywordsEnvironmental scienceMarine ecosystemSea surface temperatureSubtropicsClimatologyExtreme weatherLatitudeProductivityEcosystemOceanographyClimate changeGeologyEcology

Abstract

fetched live from OpenAlex

Prolonged high-temperature extreme events in the ocean, marine heatwaves, can have severe and long-lasting impacts on marine ecosystems, fisheries and associated services. This study applies a marine heatwave framework to analyse a global sea surface temperature product and identify the most extreme events, based on their intensity, duration and spatial extent. Many of these events have yet to be described in terms of their physical attributes, generation mechanisms, or ecological impacts. Our synthesis identifies commonalities between marine heatwave characteristics and seasonality, links to the El Niño-Southern Oscillation, triggering processes and impacts on ocean productivity. The most intense events preferentially occur in summer, when climatological oceanic mixed layers are shallow and winds are weak, but at a time preceding climatological maximum sea surface temperatures. Most subtropical extreme marine heatwaves were triggered by persistent atmospheric high-pressure systems and anomalously weak wind speeds, associated with increased insolation, and reduced ocean heat losses. Furthermore, the most extreme events tended to coincide with reduced chlorophyll-a concentration at low and mid-latitudes. Understanding the importance of the oceanic background state, local and remote drivers and the ocean productivity response from past events are critical steps toward improving predictions of future marine heatwaves and their impacts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.219
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it