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Enregistrement 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 sur OpenAlexaboutno aff

Notice bibliographique

RevueNERC Open Research Archive (Natural Environment Research Council) · 2020
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésArgoArcticLatitudeClimate modelOcean heat contentAtmosphere (unit)The arcticPrecipitationClimate change
DOInon disponible

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,681
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0170,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,003
Communication savante0,0010,000
Science ouverte0,0030,002
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,282
Tête enseignante GPT0,424
Écart entre enseignants0,142 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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