The Influence of Local Sea Ice and Remote Northern Hemisphere Teleconnections on Cyclones in Baffin Bay, Davis Strait, and Labrador Sea
Notice bibliographique
Résumé
Cyclones are a primary mode of energy transport between the midlatitudes and the polar region in the Northern Hemisphere (NH). Due to the North Atlantic experiencing some of the highest frequencies of cyclones, this region has been extensively researched. However, Baffin Bay (BB), Davis Strait (DS), and Labrador Sea (LS) are also part of the North Atlantic, yet limited literature exists regarding cyclones and the influences of local and remote drivers on their variability in these subregions. This thesis focuses on determining the influence of local sea ice cover and remote NH teleconnections on cyclone variability in BB, DS, and LS from 1980-2015. To represent the local sea ice area driver, the NH’s monthly sea ice cover was subsetted for each subregion. To establish the remote atmospheric driver, the North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Pacific Decadal Oscillation, Pacific North American Pattern, Polar Eurasian Pattern, and East Atlantic/West Russia Pattern’s monthly indices were obtained for 1980-2015. Cyclone variability was represented with the annual count, central pressure, cyclogenesis and cyclolysis events, local laplacian, latitude, and longitude from NSIDC’s NH Cyclone Locations and Characteristics record. Local drivers, remote drivers, and cyclone variables were analyzed using linear least-squares regression trends, compared using correlations (95% confidence interval), and all were seasonally standardized and detrended before each cyclone variable was compared with each local and remote driver at the long-term and individual monthly timescales. Results indicate that sea ice area in BB, DS, and LS decreased significantly, but at lower rates than the NH. Furthermore, each subregion’s sea ice variability is unique from the NH’s and from the other subregions, however periods of similar sea ice area deviation occurs across all subregions. The overall study area’s (BB-DS-LS) total number of cyclogenesis events had the only significant trend (positive) out of all cyclone variables. Comparing subregions, cyclone variability was noticeably different (especially between BB and LS). At the long-term and individual monthly timescales, local drivers had the most significant correlations mainly with the longitudinal position and cyclolysis stage of cyclones while the remote drivers had the most with their central pressures in all subregions. Overall, the NAO and AO had the most frequent and strongest correlations. While local sea ice area was significantly related with certain cyclone variables, these associations were typically weaker and less frequent. Therefore, overall cyclone variability in BB, DS, and LS is influenced more by remote atmospheric forcing than by local sea ice cover. Comparing BB, DS, and LS, it appears that, although they are geographically connected, each experiences unique cyclone variability. Finally, because each subregion’s cyclone variability is significantly related with local sea ice cover and remote teleconnections at different magnitudes and times, these subregions should be considered independently from one another and from the North Atlantic, to better capture atmospheric variability and interactions with the local environment.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».