Simulation of sea ice and ocean variability in the arctic during 1955–2002 with an intermediate complexity model
Notice bibliographique
Résumé
Abstract A number of recent sea‐ice and ocean changes in the Arctic and subarctic regions are simulated using the global University of Victoria (UVic) Earth System Climate Model version 2.6. This is an intermediate complexity model which includes a three‐dimensional ocean model (MOM 2.2), an energy‐moisture balance model for the atmosphere with heat and moisture transport, and a dynamic‐thermodynamic sea‐ice model with elastic‐viscous‐plastic rheology. The model is first spun up for 1800 years with monthly wind stress forcing derived from the National Centers for Environmental Prediction (NCEP) climatology winds and a pre‐industrial atmospheric CO2 concentration of 280 ppm. After a second spin‐up for the period 1800–1947 with daily climatology winds‐tress forcing, and a linearly increasing atmospheric CO2 concentration, the model is run with interannually varying wind stresses for the period 1948–2002 with an average forcing interval of 2.5 days and an exponentially increasing atmospheric CO2 concentration varying from 315 to 365 ppm. However, the analysis of the model output is only carried out for the years 1955–2002. The simulated maximum and minimum sea‐ice areas for the Arctic are within 6% of the observed climatologies for the years 1978–2001. The model output also shows a small downward trend in sea‐ice extent, which, however, is smaller than has been observed during the past few decades. In addition, the model simulates a decrease in sea‐ice thickness in the SCICEX (SCientific ICe EXpeditions) measurement area in the central Arctic that is consistent with, but smaller than, that observed from submarine sonar profiling data. The observed variability and magnitude of the export of sea ice through Fram Strait is quite well captured in the simulation. The change in correlation between the North Atlantic Oscillation (NAO) index and the sea‐ice export around 1977 as found in a data study by Hilmer and Jung (2000) is also reproduced. Within the Arctic basin the model simulates well the patterns and the timing of the two major regimes of wind‐forced sea‐ice drift circulation (cyclonic and anticyclonic) as found earlier by Proshutinsky and Johnson (1997). The influence of variations in the Fram Strait ice export on the strength of the North Atlantic thermohaline circulation and surface air temperature are also determined. In particular, it is shown that 3–4 years after a large ice export, the maximum meridional overturning streamfunction decreases by more than 10%. The temperature and salinity increase at depths of 200–300 m, as observed in the eastern Arctic by Morison et al. (1998), between the USS Pargo cruise in 1993 and the Environmental Working Group (EWG) Joint USRussian Arctic Atlas climatology for the years 1948–87, are just visible in the model simulation. The increases are more noticeable, however, when the ocean model data are averaged over the pentade 1995–2000 and compared with model data averaged over the pentade 1955–60. The fact that these, and some of the other modelled changes, are smaller than the observed changes can likely be attributed to the relatively coarse resolution of the UVic Earth System Climate Model (3.6°E‐W and 1.8°N‐S). Nevertheless, the fact that the model captures qualitatively many of the recent sea‐ice and ocean changes in the Arctic suggests that it can be successfully used to investigate other Arctic‐North Atlantic Ocean climate interactions during past and future eras.
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 | 0,001 | 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 | 0,000 | 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 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 ».