Two-way coupling between ice flow and channelized subglacial drainage enhances modeled marine-ice-sheet retreat
Bibliographic record
Abstract
Abstract. Ice-sheet models used to predict sea-level rise often neglect subglacial hydrology. However, theory and observations suggest that ice flow and subglacial water flow are bidirectionally coupled: ice geometry affects hydraulic potential, hydraulic potential modulates basal shear stress via the basal water pressure, and ice flow advects the subglacial drainage system. This coupling could impact rates of ice mass change but remains poorly understood. We develop a coupled ice–subglacial-hydrology model to investigate the effects of coupling on the long-term evolution of marine-terminating ice sheets. We combine a one-dimensional channelized subglacial hydrology model with a depth-integrated marine-ice-sheet model, incorporating each component of the coupling listed above, yielding a set of differential equations that we solve using a finite-difference, implicit time-stepping approach. We conduct a series of experiments with this model, using either bidirectional or unidirectional coupling. These experiments generate profiles of channel cross-sectional area, channel flow rate, channel effective pressure, ice thickness, and ice velocity. We discuss how the profiles shape one another, resulting in the effective pressure reaching a local maximum in a region near the grounding line. We also describe the impact of bidirectional coupling on the transient retreat of ice sheets through a comparison of our coupled model with ice-flow models that have imposed static basal conditions. We find that including coupled subglacial hydrology leads to grounding-line retreat that is virtually absent when static basal conditions are assumed. This work highlights the role time-evolving subglacial drainage may have in ice-sheet change and informs efforts to include it in ice-sheet models. This work also supplies a physical basis for a commonly used parameterization which assumes that the subglacial water pressure is set by the bed's depth beneath the sea surface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".