Monitoring Labrador Current Transport Variability With Satellite Gravity
Bibliographic record
Abstract
Abstract The Labrador Current is a major pathway for export of North Atlantic Deep Water across 53°N. While direct measurements of the integrated transport of the current were made from 1997 to 2014 at the 53°N Moored Observatory and since 2014 as part of the Overturning in the Subpolar North Atlantic Program (OSNAP), the calculations of integrated transport are typically delayed by years due to the time to recover and process moored instrumentation. Here, we examine a method to compute variations in the transport from ocean bottom pressure gradients determined from the GRACE and GRACE‐FO satellite missions since 2002, which will allow near‐real‐time monitoring. After verifying the method using an ocean state estimate that captures the mean and variable transport similar to the observations, we calculate the variability using the satellite observations. While there is a notable degradation at the end of the GRACE mission after 2012, results from 2002 to 2011 are consistent with interannual variations seen in the 53°N Moored Observatory and results from the GRACE Follow‐on mission (starting in 2018) are consistent with observations made by the OSNAP array. Monthly differences are of the order of 3–4 Sv compared to overall variability of ±6 Sv (one standard deviation). No statistically significant trend since 2002 was found.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".