Towards more physically constrained freshwater injection via eddy permitting simulations of the last glacial cycle
Bibliographic record
Abstract
Freshwater, in the form of glacial runoff, is hypothesized to play a critical role in centennial to millennial scale climate variability, eg. the Younger Dryas and Dansgaard Oeschger events. Freshwater injection, or hosing, model experiments demonstrate that freshwater has the capability to generate abrupt climate transitions. However, in an attempt to mitigate the inability of most models to resolve the smaller-scale features relevant to freshwater transport (such as boundary currents and mesoscale eddies), these hosing experiments commonly apply the entirety of the freshwater directly to the regions of deepwater formation (DWF). Our results indicate that this can inflate the freshwater signal in those regions by as much as four times. We propose a novel method of freshwater injection for such low-resolution models that spatially distributes the freshwater in accord with the results of eddy-permitting modelling. Furthermore, this “freshwater fingerprint” method not only impacts the timing of simulated climate transitions but also can allow us to evaluate how much we are overestimating the effects of freshwater when injected directly into sites of DWF. The freshwater fingerprints we develop are based on a suite of freshwater injection experiments performed using an eddy permitting Younger Dryas configuration of the MITGCM. Freshwater injection locations include the Mackenzie River, Gulf of St. Lawrence, Gulf of Mexico and a location off the coast of Norway, with flux amounts bounded by glacial reconstructions. These simulations indicate that freshwater from the Mackenzie River and Fennoscandia have the largest impact on salinity in most of the conventional sites of DWF (GIN and Labrador Seas, and in these simulations, predominantly the northern North Atlantic due to extensive sea ice), while freshwater from the Gulf of St. Lawrence is effective at freshening only the northern North Atlantic. The Gulf of Mexico has little impact on any DWF region we consider, mostly because the lower but continual flux in our simulations does not allow freshwater to penetrate northward past the Gulf Stream. The dilution of the freshwater signal as it is transported from the site of injection to the DWF zones leads to a reduction in the effective freshwater forcing, making hosing directly over DWF zones even with realistic freshwater amounts unrealistic. Thus, we construct freshwater fingerprints from these simulations by extracting the freshwater anomaly spatial pattern averaged over the last 5 simulation years, vertically integrating the field and normalizing it. The freshwater fingerprint is then implemented in the COSMOS Earth Systems Model, which is run at resolutions typical for paleoclimate simulations (non-eddy permitting). Initial results show that freshwater from the Mackenzie River using our fingerprint method leads to a more gradual cooling than if the meltwater is released directly over the hosing region (50-70N). We conclude that hosing over DWF zones, even with realistic freshwater amounts, produces an unrealistically large climate response. Additional results for the remaining injection locations and with the fingerprint implemented in a simpler climate model will be presented.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".