Assessing the variability of Irminger Water at AR7W between 1993 and 2022 using time-dependent property thresholds
Bibliographic record
Abstract
Irminger Water (IW) is a prominent water mass in the subpolar North Atlantic (SPNA). It is warm and saline and originates from the North Atlantic Current and the Irminger Current. The water mass delivers anomalously large amounts of heat and salt to the Labrador Sea. Like any other water mass, IW is subject to temporal and spatial variability, which needs to be adequately identified and tracked.To separate IW from ambient waters, previous studies identified IW at different times using static thresholds of salinity, temperature, and density (i.e., constant over time within the individual studies). However, given the tremendous variability in the region, such static definitions often do not detect IW sufficiently since these definitions do not account for shifts in the large-scale hydrographic state of the SPNA. To address this issue, this study aims to identify non-static thresholds (i.e., incorporating temporal variability) to analyze IW variability. We refer to the method of identifying IW based on non-static thresholds as the phenomenological approach. To do so, we utilize the observation-based data set ARMOR3D between 1993 and 2022. This new approach allows us to compare estimates of IW properties and volume transports to respective estimates obtained from the static approach.In the case of the static approach being applied to the AR7W section in the eastern part of the Labrador Sea as a test region, the water column was anomalously saline in years of high IW volume transport. Hence, the static approach identified more IW and thus overestimated its volume transport. In contrast, the water column was anomalously fresh in years when the static approach reveals a low IW volume transport. Hence, applying the static approach, less IW is identified, and thus its volume transport is underestimated. In contrast, the phenomenological approach reveals less pronounced decadal variability of the IW volume transport.Applying a static IW definition will likely create stronger gradients between IW and ambient water masses when both are fresher. In turn, these gradients may impose or modulate unrealistic changes in the IW volume transport simply because the actual boundary of IW does not coincide with a certain isohaline or isotherm. Any correlated change or shift in IW properties and, for example, Labrador Sea Water will relocate the IW boundary causing the transport to change. The phenomenological approach introduced in our study resolves this issue.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".