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Record W7021105181

Model-observation and reanalyses comparison at key locations for heat transport to the Arctic: Assessment of key lower latitude influences on the Arctic and their simulation

2020· other· en· W7021105181 on OpenAlexaboutno aff

Bibliographic record

VenueNERC Open Research Archive (Natural Environment Research Council) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsArgoArcticLatitudeClimate modelOcean heat contentAtmosphere (unit)The arcticPrecipitationClimate change
DOInot available

Abstract

fetched live from OpenAlex

Blue-Action Work Package 2 (WP2) focuses on lower latitude drivers of Arctic change, with a focus on
\nthe influence of the Atlantic Ocean and atmosphere on the Arctic. In particular, warm water travels from
\nthe Atlantic, across the Greenland-Scotland ridge, through the Norwegian Sea towards the Arctic. A
\nlarge proportion of the heat transported northwards by the ocean is released to the atmosphere and
\ncarried eastward towards Europe by the prevailing westerly winds. This is an important contribution to
\nnorthwestern Europe's mild climate. The remaining heat travels north into the Arctic. Variations in the
\namount of heat transported into the Arctic will influence the long term climate of the Northern
\nHemisphere. Here we assess how well the state of the art coupled climate models estimate this
\nnorthwards transport of heat in the ocean, and how the atmospheric heat transport varies with changes
\nin the ocean heat transport. We seek to improve the ocean monitoring systems that are in place by
\nintroducing measurements from ocean gliders, Argo floats and satellites.
\nThese state of the art computer simulations are evaluated by comparison with key trans-Atlantic
\nobservations. In addition to the coupled models ‘ocean-only’ evaluations are made. In general the
\ncoupled model simulations have too much heat going into the Arctic region and the transports have too
\nmuch variability. The models generally reproduce the variability of the Atlantic Meridional Ocean
\nCirculation (AMOC) well. All models in this study have a too strong southwards transport of freshwater
\nat 26°N in the North Atlantic, but the divergence between 26°N and Bering Straits is generally
\nreproduced really well in all the models.
\n
\nAltimetry from satellites have been used to reconstruct the ocean circulation 26°N in the Atlantic, over
\nthe Greenland Scotland Ridge and alongside ship based observations along the GO-SHIP OVIDE Section.
\nAlthough it is still a challenge to estimate the ocean circulation at 26°N without using the RAPID 26°N
\narray, satellites can be used to reconstruct the longer term ocean signal. The OSNAP project measures
\nthe oceanic transport of heat across a section which stretches from Canada to the UK, via Greenland.
\nThe project has used ocean gliders to great success to measure the transport on the eastern side of the
\narray. Every 10 days up to 4000 Argo floats measure temperature and salinity in the top 2000m of the
\nocean, away from ocean boundaries, and report back the measurements via satellite. These data are
\nemployed at 26°N in the Atlantic to enable the calculation of the heat and freshwater transports.
\nAs explained above, both ocean and atmosphere carry vast amounts of heat poleward in the Atlantic. In
\nthe long term average the Atlantic ocean releases large amounts of heat to the atmosphere between
\nthe subtropical and subpolar regions, heat which is then carried by the atmosphere to western Europe
\nand the Arctic. On shorter timescales, interannual to decadal, the amounts of heat carried by ocean and
\natmosphere vary considerably. An important question is whether the total amount of heat transported,
\natmosphere plus ocean, remains roughly constant, whether significant amounts of heat are gained or
\nlost from space and how the relative amount transported by the atmosphere and ocean change with
\ntime. This is an important distinction because the same amount of anomalous heat transport will have
\n
\nvery different effects depending on whether it is transported by ocean or the atmosphere. For example
\nthe effects on Arctic sea ice will depend very much on whether the surface of the ice experiences
\nanomalous warming by the atmosphere versus the base of the ice experiencing anomalous warming
\nfrom the ocean. In Blue-Action we investigated the relationship between atmospheric and oceanic heat
\ntransports at key locations corresponding to the positions of observational arrays (RAPID at 26°N,
\nOSNAP at ~55N, and the Denmark Strait, Iceland-Scotland Ridge and Davis Strait at ~67N) in a number of
\ncutting edge high resolution coupled ocean-atmosphere simulations. We split the analysis into two
\ndifferent timescales, interannual to decadal (1-10 years) and multidecadal (greater than 10 years). In the
\n1-10 year case, the relationship between ocean and atmosphere transports is complex, but a robust
\nresult is that although there is little local correlation between oceanic and atmospheric heat transports,
\nCorrelations do occur at different latitudes. Thus increased oceanic heat transport at 26°N is
\naccompanied by reduced heat transport at ~50N and a longitudinal shift in the location of atmospheric
\nflow of heat into the Arctic. Conversely, on longer timescales, there appears to be a much stronger local
\ncompensation between oceanic and atmospheric heat transport i.e. Bjerknes compensation.

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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)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0010.000
Open science0.0030.002
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.282
GPT teacher head0.424
Teacher spread0.142 · 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; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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