Improvement of Visibility and Severe Sea State Forecasting on the Grand Banks of Newfoundland and Labrador
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Notice bibliographique
Résumé
Abstract Fog in northern climates and Arctic environs can be a risk to helicopter operations and shipping interests, as are high seas from severe storms that frequent these regions. Visibility conditions and forecasts determine whether helicopters can safely land on offshore facilities, or if personnel will need to be transferred by ship. High sea state conditions can affect offshore oil and gas exploration and production operations, including drilling, logistics, crane operations and emergency response. A workshop on Metocean Monitoring and Forecasting for the Newfoundland & Labrador Offshore, held 22-24 September 2014, identified the need of improving the visibility and severe sea state forecasting for Grand Banks which can have a positive contribution to safety and operations in the harsh North Atlantic Canada offshore environment. This has led to an open and collaborative multi-year Metocean Research and Development Project that is presently in its third year. Some twenty government, academic, and industry agencies are participating in this project. Detailed buoy and offshore installations-based scientific measurements have been collected over the past three years where previously there has been a lack of good quality observations. A climatology of low visibility (less than 1km) events shows a high frequency (about 55% of the time) during summer months. A "conceptual model" of Grand Banks fog has been developed, that defines the physical conditions under which fog develops, is maintained, moves and dissipates. The conceptual model will be the basis for the development of new visibility prediction systems which currently are not well established or verified. High seas, with wave heights over 6m, occur more frequently during winter. Sea state prediction systems are being evaluated for severe ocean wave conditions where they have reduced predictive skill. Currently, work is underway to establish the accuracy and consistency of several existing visibility and sea state prediction systems. This paper will illustrate results from the climatological studies and some of the unique metocean monitoring data being collected. The forecasting techniques (e.g. numerical atmospheric and oceanic prediction models, satellite-based schemes, and rules based systems) being evaluated, are outlined.
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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 | 0,000 | 0,001 |
| 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)
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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 découle