High-resolution isotopic evidence for a potential Saharan provenance of Greenland glacial dust
Bibliographic record
Abstract
Dust concentrations in Greenland ice show pronounced glacial/interglacial variations with almost two orders of magnitude increase during the Last Glacial Maximum. Greenland glacial dust was previously sourced to two East Asian deserts: the Taklimakan and Gobi deserts. Here we report the first high-resolution Pb and Sr isotopic evidence for a significant Saharan dust influence in Greenland during the last glacial period, back to ~31 kyr ago, from the Greenland NEEM ice core. We find that during Greenland Stadials 3-5.1 (~31 to 23 kyr ago), the primary dust provenance was East Asia, as previously proposed. Subsequently, the Saharan isotopic signals emerge during Greenland Stadials 2.1a-2.1c (~22.6 to 14.7 kyr ago) and from the late Bølling-Allerød to the Younger Dryas periods (~13.6 to 12 kyr ago), coincident with increased aridity in the Sahara and efficient northward transport of dust during these cold periods. A mixing isotopic model proposes the Sahara as an important source, accounting for contribution to Greenland glacial dust of up to 50%, particularly during Greenland Stadial 2.1b and the late Bølling-Allerød to the Younger Dryas periods. Our findings provide new insights into climate-related dust provenance changes and essential paleoclimatic constraints on dust-climate feedbacks in northern high latitudes.
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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 | 0.001 | 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".