Field data on sea ice restoration by artificial flooding in subarctic Canada
Notice bibliographique
Résumé
A field campaign in the Milan Arm of Pistolet Bay in Newfoundland, Canada was conducted to gather data on sea ice restoration by artificial flooding between February and May of 2025. Sea ice thickening was initiated by pumping sea water from below the first-year sea ice onto the surface without significantly modifying the overall snow cover beforehand. Pumping consisted of 84 discrete events, for which GPS location, pumping start time and duration, and local snow and ice thicknesses were recorded. Remote data collection and monitoring were executed by three thermistor chains, three radiation sensors, and one anemometer. All remote measurement systems remained in the field until recovery of the floating systems following ice breakup in late spring. Additionally, coring systems were used to extract 10 ice cores for analysis of temperature and bulk salinity profiles through the ice depth to assess the effect of artificial flooding on sea ice formation and ablation. Two of the ice cores were used and three seawater samples were collected for analysis of the biological content of phytoplankton. Transects of surface composition across select flooded sites were assessed for the formation and solidification of ice and slush layers. Snow thickness and density data were sampled for a representative region of the entire site to assess spatial variability. All these data were complemented by timelapse camera imaging from each monitoring station and aerial drone imaging, including thermal imaging, of the entire region. The dataset can be used to investigate the physical processes involved in sea ice growth before, during, and after flooding. The dataset can be used, in a limited manner, to understand the formation, growth, and ablation of snow ice. The radiation data can be used to analyze the surface radiation fluxes of the parent, flooded, and melting ice. The data gathered during the melting season can be used to investigate the melting of thickened sea ice in comparison to that of natural sea ice. The data on bulk salinity can be used to investigate short-term brine migration. The data on phytoplankton content can be used to assess its change due to the impact of flooding. Combining the various data, thermodynamic ice growth and melt models of sea ice, including snow, slush, and snow ice, can be validated. The understanding of rain and meltwater drainage events could be improved and flow models for simulation of artificial flooding of snow-covered first-year sea ice could be further developed using the data. Aerial imagery obtained by drone provides insights into the flooding behavior of water over snow-covered ice, allowing for the detection and temporal tracking of both visibly impacted and visually concealed areas that may not be apparent to the naked eye.
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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».