Eastern equatorial Pacific cold tongue during the Last Glacial Maximum as seen from alkenone paleothermometry
Bibliographic record
Abstract
We present new alkenone‐based sea surface temperature (SST) estimates from the eastern equatorial Pacific (EEP) for the last 30 kyr. By combining these new results with recently published records from the region, we reconstruct the spatial pattern of changes in SST during the Last Glacial Maximum (LGM). Alkenone‐based SST estimates show a greater glacial cooling in the upwelling environment of the cold tongue than in sites located further north in the equatorial front and eastern Pacific Warm Pool. This result agrees with the paradigm of stronger glacial winds, increased upwelling, steeper zonal thermocline tilt, and stronger advection of cold water in the Peru Current. Furthermore, we investigate possible changes in glacial surface hydrography by using the alkenone‐based SST reconstructions to correct planktonic foraminifera δ18O for the temperature effect. After additional correction for the global ice volume effect, the residual changes in seawater δ18O show a clear latitudinal pattern that would be consistent with a southward shift of the Intertropical Convergence Zone. We thus suggest that changes in sea surface salinities could explain contrasting SST reconstructions based on planktonic foraminifera δ18O, which implied a weakening of the cold tongue. The controversial LGM dynamics of the EEP reconstructed by different proxies, i.e., a weakening or a strengthening of the cold tongue, highlight the necessity to better assess the influence of various biases on these proxies.
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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 | 0.000 | 0.000 |
| 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 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".