Sensitivity of the last glacial inception to initial and boundary conditions: lessons from a coupled climate-ice sheet model
Bibliographic record
Abstract
Proxy data indicate that the last glacial inception started at approximately 115ka BP when boreal summer insolation reached its minimum. At that time, large ice sheets started to form in Northern Canada. A number of models of different complexities have been employed to simulate the last glacial inception; however, complex climate models did not incorporate interactive ice sheets. Here, a state-of-art Earth System Model AWI-ESM-2.2 (Gierz et al., 2020, GMDD), composed of AWI-ESM-2.0 (Sidorenko et al., 2019) that now includes the Parallel Ice Sheet Model PISM (The PISM authors, 2016), was utilized to study the potential causes of the inception. By conducting different sensitivity experiments, we investigated the effect of initial conditions, different surface mass balance schemes, greenhouse gas (GHG) concentration, ocean circulation, and model resolution on the last glacial inception. Two experiments were conducted under 115 ka BP orbital and radiative forcing to examine the effect of initial conditions: one without interactive ice sheets but with fixed preindustrial topography, and the other with interactive ice sheets that include initial snow cover over two small regions in northeastern and northwestern Canada. The first experiment failed to produce a permanent appearance of snow over North America. The second experiment simulated a further growth of ice sheets over northeastern and northwestern Canada. In these experiments, the initial ice sheets provide important feedbacks to cause North America ice sheet growth: the snow-albedo feedback and elevation effect of orography reinforce the cooling in the region initially covered by snow or ice. We compared an empirically-based positive-degree-day (PDD) scheme, which estimates surface melt as a function of temperature, with a more physically-based diurnal energy balance model (dEBM) (Krebs-Kanzow et al., 2018), which also takes changes in shortwave radiation into account and implicitly resolves a diurnal freeze-melt cycle. Both simulations showed a tendency of ice sheet growth in Northern Canada ice sheet. The experiment employing the dEBM model for surface mass balance had a larger magnitude in SMB, resulting in faster development of the ice sheet. Another experiment with a lowered GHG concentration was carried out to investigate the role of GHG, suggesting that GHG changes also contribute to a cooling state. Two additional experiments also explored the effect of changed ocean circulation and atmosphere dynamics and their contribution to the inception, as well as the effect of an improved resolution in the atmosphere model. In summary, our findings imply that initial conditions have a significant impact on simulating the inception. We conclude that the incorporation of an ice sheet model into the Earth system is an important step forward to provide a more realistic simulation of glacial inception and to uncover its potential causes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".