Intraseasonal and interannual variability of sea ice in the Gulf of St.Lawrence
Notice bibliographique
Résumé
Intraseasonal and interannual variability of sea-ice cover (SIC) in the Gulf of St. Lawrence, including the time of first ice presence (TFIP), time of last ice presence (TLIP), and sea-ice duration (SID), were investigated, using weekly sea ice observations from 1963--1996. For the intraseasonal variations of sea ice, it was found that SIC in different sub-regions displays contrasting features. The largest intraseasonal variations of SIC occur in the Strait of Belle Isle region and in the southwestem Gulf, where the mean SIC is largest and SID is longest. For the interannual variability of sea ice, the largest variability of SIC occurs in the area off mid-Newfoundland, where the mean SIC is small. For the TFIP and TLIP, the largest interannual variability occurs in the area off western Newfoundland and along coasts in the northeast sector of the Gulf, respectively. In addition, sea ice appeared earlier in the coastal regions and disappeared later over the entire Gulf in severe ice years; while sea ice appeared later in the central and eastern Gulf and disappeared earlier over the entire Gulf in light ice years. Several of the forcing factors influencing sea ice variability in the Gulf of St. Lawrence were examined and mechanisms controlling this variability were discussed. It was found that surface air temperature (SAT), the eastward wind component (u-wind), sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), total river runoff, the ocean circulation pattern, and sea-ice advection from the Labrador Sea, all play important roles in explaining sea ice variability in the Gulf. However, the relative contributions of these factors to the observed sea ice variability differ in different subregions. Quantitative relationships between sea ice variability and various forcing factors were investigated using statistical analysis and a simplified Hibler's sea-ice model. Both approaches indicated that the December--April averaged SAT, u-wind, and November SST all contribute to the variability of December--June SIC in the Gulf, with SAT playing the most important role. The analysis also indicated that the dependence of SIC on various forcing factors varies with geographical location. For example, SAT influences sea ice variability mainly in the central Gulf, while the u-wind component effects SIC mainly in the eastern Gulf. In addition, statistical analyses also suggest that SSS values present in the previous November play an important role in determining SIC variability. The linear regression between SIC and three independent variables: December--April SAT, November SST and SSS, accounts for 81% of the total SIC variance. The statistical analysis and model study also indicated that December SAT, u-wind, November SST, and MLD control the time of first ice presence, with SAT and SST playing the dominant role. The linear regression between TFIP and three independent variables (u-wind, SST, and SSS) accounts for 76% of the total TFIP variance. For TLIP, both SAT and u-wind play an important role.
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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 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 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 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 ».