The complex basal morphology and ice dynamics of the Nansen Ice Shelf, East Antarctica
Bibliographic record
Abstract
Abstract. Ice shelf dynamics and morphology play an important role in the stability of floating bodies of ice by driving fracturing that can lead to calving, in turn impacting the ability of the ice shelf to buttress upstream grounded ice. Following a 2016 calving event at the Nansen Ice Shelf (NIS), East Antarctica, we collected airborne and ground-based radar data to map ice thickness across the shelf. We combine these data with published satellite-derived data to examine the spatial variations in ice shelf draft, the cause and effects of ice shelf strain rates, and the possibility that a suture zone may be channelizing ocean water and altering patterns of sub-ice-shelf melt and freeze-on. We also use our datasets to assess limitations that may arise from relying on hydrostatic-balance equations applied to ice surface elevation to determine ice draft morphology. We find that the Nansen Ice Shelf has a highly variable basal morphology driven primarily by the formation of basal fractures near the onset of the ice shelf suture zone. This morphology is reflected in the ice shelf strain rates but not in the calculated hydrostatic-balance thickness, which underestimates the scale of variability at the ice shelf base. Enhanced melt rates near the ice shelf terminus and in steep regions of the channelized suture zone, along with relatively thin ice in the suture zone, appear to represent vulnerable areas in the NIS. This morphology, combined with ice dynamics, induce strain that has led to the formation of transverse fractures within the suture zone, resulting in large-scale calving events. Similar transverse fractures at other Antarctic ice shelves may also be driven by highly variable morphology, and predicting their formation and evolution could aid projections of ice shelf stability.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".