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Enregistrement W6931860417 · doi:10.5281/zenodo.7541028

Review of air-ice-ocean processes in the Margial Ice Zone of importance for offshore activities in the Barents Sea region

2007· report· en· W6931860417 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2007
Typereport
Langueen
DomaineEngineering
ThématiquePower System Optimization and Stability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSea iceSubmarine pipelineArctic ice packArcticDrift iceAntarctic sea iceArctic sea ice declineCircumpolar star

Résumé

récupéré en direct d'OpenAlex

In this report we have reviewed air-ice-ocean processes in the Marginal Ice Zone (MIZ) of importance for offshore operations and related environmental issues.<br> The MIZ is a characteristic feature of the circumpolar Arctic and sub-Arctic seas, i.e., the European, Russian, US and<br> Canadian parts of the Arctic. The focus has been on the Barents Sea and adjacent regions where offshore exploration plans are quite extensive. The Barents Sea is partly ice- covered in the winter season in the northern and eastern regions. The sea ice in combination with wind, waves and currents provide harsh environmental conditions, especially in the winter. The MIZ can be defined as the zone extending from typical 100 km outside the ice edge to 100 km inside the ice edge, where certain air-ice-ocean processes dominate and have significant impact in the environment. The physical environment is determined by an integrated system of atmospheric, oceanic and sea ice processes, including wind, waves, ocean eddies, jets and current features, convergence/divergences, sea ice processes and their variability. Many of the processes are not well understood, because observations and modeling capability is not yet well developed. The uncertainty in description of many physical processes is a major reason for the large discrepancy between different climate model simulations in the Arctic.<br> It is described first the general environmental and climate processes of the Arctic Ocean, providing and overview of scientific issues to be considered by offshore operators. The main atmospheric processes are reviewed regarding climate as well as meteorological conditions for operations in Arctic and sub-Arctic seas. The sea ice conditions are of major importance because the MIZ is defined by the extent and variability of the ice edge region. Sea ice is also the main constraint for offshore operations and transportation in the Arctic, and improved monitoring and forecasting of sea ice is therefore a major task to ensure safe and cost-efficient operations. The<br> sea ice extent, drift and thickness are determined by dynamic and thermodynamic forcing from the atmosphere and the ocean. A warming of the ocean in the Arctic regions has been observed in recent years, contributing to reduced extent and thickness of sea ice observed in the last two – three decades. In the last few years, the Barents Sea has had less ice in the winter than the average, and this can be attributed to higher ocean temperature as well as to warmer air masses in the region. Sea level change in combination with storm surges and waves will have impact on coastal constructions, vessels and offshore operations. More storms and extreme sea level height and wave height can be expected in the future. In the Barents Sea area, icebergs originating from calving glaciers in Svalbard, Franz Josef Land and Novaya Zemlya represent one of the main hazard factors for offshore operations. The amount of icebergs drifting into the drilling areas varies considerable from year to year. An extreme event of many icebergs drifting into the Shtokman area was observed in May 2003. Prediction of iceberg occurrence in regions of offshore operations is<br> not feasible. It is therefore important to develop good monitoring and forecasting systems for icebergs. The report describes the main elements of the oil spill problem in the MIZ, including observation and modeling of oil spills as well as recovery solutions. Finally, some elements of primary production in the MIZ is described.

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)0,004
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,932
Score d'incertitude au seuil0,657

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
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 Opus0,052
Tête enseignante GPT0,278
Écart entre enseignants0,226 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
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
Publié2007
Routes d'admission1
Résumé présentoui

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