A Steady Regime of Volume and Heat Transports in the Eastern Arctic Ocean in the Early 21st Century
Bibliographic record
Abstract
Mooring observations in the eastern Eurasian Basin of the Arctic Ocean showed that mean 2013–2018 along-slope volume and heat (calculated relative to the freezing temperature) transports in the upper 800 m were 4.8 ± 0.1 Sv (1 Sv = 10 6 m 3 /s) and 34.8 ± 0.6 TW, respectively. Volume and heat transports within the Atlantic Water (AW) layer (∼150–800 m) in 2013–2018 lacked significant temporal shifts at annual and longer time scales: averaged over the two periods of mooring deployment in 2013–2015 and 2015–2018, volume transports were 3.1 ± 0.1 Sv, while AW heat transports were 31.3 ± 1.0 TW and 34.8 ± 0.8 TW. Moreover, the reconstructed AW volume transports over longer, 2003–2018, period of time showed strong interannual variations but lacked a statistically significant trend. However, we found a weak positive trend of 0.08 ± 0.07 Sv/year in the barotropic AW volume transport estimated using dynamic ocean topography (DOT) measurements in 2003–2014 – the longest period spanned by the DOT dataset. Vertical coherence of 2013–2018 transports in the halocline (70–140 m) and AW (∼150–800 m) layers was high, suggesting the essential role of the barotropic forcing in constraining along-slope transports. Quantitative estimates of transports and their variability discussed in this study help identify the role of atlantification in critical changes of the eastern Arctic Ocean.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".