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Record W7000974693

How rising ocean temperatures are influencing our weather

2024· other· en· W7000974693 on OpenAlexaboutno aff

Bibliographic record

VenueNERC Open Research Archive (Natural Environment Research Council) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAtmosphere (unit)LatitudeOcean heat contentSea surface temperatureGlobal warmingAtmospheric temperatureClimate changeMoistureAir temperature
DOInot available

Abstract

fetched live from OpenAlex

Globally, surface air and ocean temperatures have warmed by about 1°C since 1900. More than 90% of the additional heat contained in the climate system (atmosphere, ocean, land) due to global warming is stored in the ocean, so what do these increased ocean temperatures mean for our weather?
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\nThe ocean stores significantly more heat than the atmosphere: the top few metres of the ocean contain more thermal energy than the entire atmosphere. There is a continuous exchange of heat between the ocean and atmosphere and the weather we experience is intrinsically linked to the heat contained in the ocean.
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\nAs atmospheric winds flow over the ocean, they typically pick up moisture and either gain or release heat. At mid-latitudes, and depending on the season, maritime air masses are usually either comparatively mild and humid (winter) or cool and humid (summer). Regions such as western Europe or the north-western US and western Canada experience maritime climates. These are characterized by reduced seasonal temperature extremes compared to locations at similar latitudes in the interior and along the east coasts of the continents as the prevalent westerly winds either come from the ocean (west coasts) or the interior of the continents (east coasts).

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.

How this classification was reachedexpand

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)0.047
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0470.010
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0020.003
Scholarly communication0.0120.001
Open science0.0110.020
Research integrity0.0010.024
Insufficient payload (model declined to judge)0.0030.052

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 head0.133
GPT teacher head0.370
Teacher spread0.237 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueNERC Open Research Archive (Natural Environment Research Council)French-language works237,207