Observations of Open-Ocean Deep Convection in the Labrador Sea from Subsurface Floats*
Bibliographic record
Abstract
The occurrence and extent of deep convection in the Labrador Sea in winters 1996/97 and 1997/98 is investigated from measurements of over 200 neutrally buoyant subsurface Profiling Autonomous Lagrangian Circulation Explorer (PALACE) and Sounding Oceanographic Lagrangian Observer (SOLO) floats. In addition to providing drift velocity data and vertical profiles of temperature and salinity, 55 floats are equipped with vertical current meters (VCMs). Time series of vertical velocity (derived from measured pressure and vertical flow past the float) and temperature are obtained from the VCM floats. Mixed layer depths estimated from profile measurements indicate that convection reached depths greater than 1300 m in 1997, but no deeper than 1000 m in 1998. Deep mixed layers were concentrated in the western basin, although a number of deep mixed layers were observed southwest of Cape Farewell and also north of 60°N. The highest variance in vertical velocity and the lowest mean temperatures were found in the western basin, suggesting that this area is the main site of deep convection. Deep mixed layers and large vertical velocities were observed as late as April and May, despite the fact that surface forcing appears to have ceased. Estimates of mean vertical velocity appear to be affected by a float sampling bias, whereby floats preferentially sample convergent regions. The effect of this bias, which is dependent on the float depth within the convective layer, is to sample upward flow in early winter and downward flow in late winter when the convective layer has deepened. A one-dimensional heat balance model is examined, whereby the winter surface heat flux, estimated from temperature profiles, is balanced by the turbulent vertical heat flux associated with deep convection, estimated from time series measurements. The plume-scale vertical heat flux can only account for roughly −80 of −350 W m−2 measured at 400-m depth. The vertical heat flux at longer timescales is investigated, but cannot be resolved with this dataset. Failure to balance the surface heat flux by plume-scale motions, combined with an observed high variance of w and T at low frequencies, suggests that motion at these longer timescales contributes to the one-dimensional heat budget in winter.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".