A 30 ‐Year Time Series of Transient Tracer‐Based Estimates of Anthropogenic Carbon in the Central Labrador Sea
Bibliographic record
Abstract
Abstract We use a 30‐year time series (1986–2016) of dichlorodifluoromethane (CFC‐12) concentrations with a refined transit time distribution (TTD) method, to estimate the temporal variation of anthropogenic carbon (C ant ) in the Central Labrador Sea. We determined that the saturation of CFC‐12 and sulfur hexafluroide (SF 6 ) in newly‐formed Labrador Sea Water had departed significantly from 100% and varied systematically with time. Multiple linear regression of the time‐varying saturation, with the tracer's atmospheric growth rate and the wintertime mixed layer depth as independent variables, allowed reconstruction of the saturation history of CFC‐12 and SF 6 in wintertime surface waters, which was implemented in the TTD method. Use of the time‐varying saturation for CFC‐12 gave C ant concentrations ∼7 μmol kg −1 larger than estimates obtained assuming a constant saturation of 100%. The resulting C ant column inventories were ∼20% larger and displayed lower interannual variability compared to conventional TTD‐based estimates. The column inventory of C ant increased at an average rate of 1.8 mol m −2 y −1 over the 30‐year period. However, the accumulation rate of C ant was higher than this average in the early 1990s and since 2013, whereas inventories remained almost unchanged between 2003 and 2012. The variation in the C ant accumulation rate is shown to be linked to temporal variability in the relative layer thickness of the annually ventilated Labrador Sea Water and the underlying Deep Intermediate Water. The non‐steady C ant accumulation highlights the importance of sampling frequency, especially in regions of variable deep mixing and high carbon inventories, and potential misinterpretation of C ant dynamics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".