Impacts immédiats et saisonniers de tempêtes estivales sur l'océan et la glace de mer en Arctique
Bibliographic record
Abstract
In the Arctic, storms play a critical role in affecting sea ice and ocean dynamics by enhancing air-sea interactions, mixing, and ice deformation. However, their longerterm seasonal impacts, particularly in summer when sea ice is reduced, remain unclear.This thesis explores the seasonal influence of summer storms in the Canadian Basin using two coupled ice-ocean models. First, a onedimensional model (NEMO-SI3) is used to assess the effects of idealized storms, revealing that anomalies in mixed layer depth and heat content can persist for weeks, delaying autumn sea ice formation and accelerating winter sea ice growth. Then, a three-dimensional model (NEMO-LIM3) is used to show that while one-dimensional processes dominate in the initial weeks after a synthetic Arctic cyclone occurs, advective processes gradually attenuate these anomalies over time. Thus, delay in the freeze up date may be observed due to a cyclone, but long-term impacts in sea ice thickness are less pronounced. These findings highlight the complex interplay between storms and ice-ocean systems, with implications for seasonal ice forecasting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".