A Possible Role of Dust in Resolving the Holocene Temperature Conundrum
Bibliographic record
Abstract
Climate models generally fail to produce a warmer (by as much as 0.5 °C) early to mid-Holocene than the pre-industrial in the global annual temperature, which has been termed the Holocene temperature conundrum. Here we use a fully coupled atmosphere-ocean general circulation model to test whether the conundrum can be partially resolved by considering the fact that atmospheric dust loading was much reduced during the early to mid-Holocene. Our experiments show that the global annual mean surface temperature increases by 0.30 °C and 0.23 °C for the mid-Holocene (6 ka) and early Holocene (9 ka), respectively, if the dust is completely removed. The temperature increase scales almost linearly with the fraction of dust being removed, with the 50% dust reduction experiment for the 6 ka being the only one deviating from the linear trend. The indirect effect of dust, which is highly uncertain and is not included in the model, may further enhance the warming. Therefore, the neglect of dust reduction in the Holocene in climate models could contribute significantly to the model-data discrepancy, especially in the Northern Hemisphere.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".