The impacts of glacial runoff and pCO₂ on centennial-to millennial-scale climate variability during the last glacial cycle
Bibliographic record
Abstract
Freshwater is hypothesized to have a critical role in previous centennial-to millennial-scale climate variability(CMCV),e.g. Dansgaard Oeschger events, the Younger Dryas, and may play a central role in future climate change as ice sheet and glacier melt accelerates. Similarly, anthropogenic climate change demonstrates the need to understand the impact of carbon dioxide (pCO₂) on climate variability. The relationship between freshwater and rapid climate change in the paleoclimate records has been a subject of intense study, but past approaches have generally relied upon an approximation of freshwater entering the oceans via wide bands in the North Atlantic in `hosing' experiments. This design element of hosing experiments, which supports the relationship between freshwater and climate cooling, artificially amplifies the climate response by introducing freshwater directly over sites of deep water formation. As well, previous studies have yet to characterize the role of either pCO₂ or freshwater on CMCV under appropriate boundary conditions. This thesis explores the impact two likely controls of CMCV, freshwater and pCO₂ concentrations. I achieve this by first determining where coastally released freshwater is transported using an eddy permitting ocean model configured for the the Younger Dryas interval during the last deglaciation. It is found that by explicitly resolving features important for the transport of coastally released freshwater, such as mesoscale eddies, that hosing overestimates the amount of freshwater transported to sites of deepwater formation by 2-4x. Next, using these results I then derive a novel method of freshwater injection, the freshwater fingerprint, and examine the relative climate impact of different freshwater injection distributions. In comparing the fingerprint method against both conventional band hosing and regional injection methods I conclude that the fingerprint methodology allows for emulation of some features of the eddy permitting representation in a coarse resolution coupled climate model. Finally, I examine the impact that pCO₂ and freshwater has on a specific form of CMCV, Dansgaard-Oeschger events during Marine Isotope Stage 3 (MIS3), with boundary conditions consistent with the MIS3 interval. When examining characteristics of CMCV I find that both increasing freshwater and decreasing carbon dioxide levels lead to similar changes in interstadial & stadial durations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".