Modeling the variability of the liquid freshwater export from the Arctic Ocean
Notice bibliographique
Résumé
In this thesis an analysis of the variability of the liquid freshwater (FW) export from the Arctic Ocean on annual and seasonal timescales is presented. Due to missing long-term observations, the variability of the liquid FW export is not well known or understood. Model simulations are therefore currently the only way to study the variability of the FW export from the Arctic. To investigate the role of the atmospheric forcing for the variability of the liquid FW export, a model simulation for 1950-2007 from the University of Victoria Earth System Climate Model (UVic ESCM) is analyzed. It is shown that large-scale atmospheric circulation changes generally control the variability of the FW export through changes in the FW storage in the Beaufort Gyre. These changes have a large influence on the variability of the FW export through the Canadian Arctic Archipelago (CAA), whereas the Fram Strait FW export is also influenced by changes in the FW storage in the Eurasian basin. In order to better understand the differences between the mechanisms driving the export variability through Fram Strait and the CAA, passive dye tracers are added to the ocean module of a state-of-the-art global general circulation model, the Community Climate System Model Version 3 (CCSM3). These tracers allow the identification of FW from different sources, and therefore the individual investigation of the export variability of FW from individual sources. It is shown that the Fram Strait FW export is made up mainly of Eurasian runoff and Pacific FW, whereas the FW exported through the CAA comes primarily from Pacific FW and North American runoff. The variability of the FW exports from individual sources is largely in phase in the CAA, as the CAA FW export is mainly driven by velocity anomalies, not FW concentration anomalies. In Fram Strait on the other hand, FW concentration anomalies contribute as much to the FW export variability as velocity anomalies. The variability of the Fram Strait FW concentrations from the two main FW sources is not in phase, as Pacific FW and Eurasian runoff have different pathways to Fram Strait and their variability is governed by different mechanisms. Whereas the Eurasian runoff export depends strongly on the release of FW from the Eurasian shelf during years with an anticyclonic circulation anomaly (negative Vorticity index), the variability of the Pacific export is mainly controlled by changes in the Pacific FW stored in the Beaufort Gyre, with increased export during years with a cyclonic circulation anomaly (positive Vorticity index). A high vertical resolution of the ocean model is found to be important to resolve the role of FW concentration changes for the Fram Strait FW export variability. The model simulation also shows that in contrast to the interannual variability, the seasonal variability of the Fram Strait FW export is driven almost entirely by the seasonal cycle of sea-ice melt, with a smaller influence of velocity changes or advected FW concentration changes. The disappearance of the summer sea-ice cover in the Arctic during the 21st century might therefore affect the seasonal cycle of the Fram Strait FW export.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».