Measuring Height Change Around the Periphery of the Greenland Ice Sheet With Radar Altimetry
Bibliographic record
Abstract
Ice loss measurements around the periphery of the Greenland Ice Sheet can provide key information on the response to climate change. Here we use the excellent spatial and temporal coverage provided by the European Space Agency (ESA) CryoSat satellite, together with NASA airborne Operation IceBridge and automatic weather station data, to study the influence of changing conditions on the bias between the height estimated by the satellite radar altimeter and the ice sheet surface. Surface and near-surface conditions on the ice sheet periphery change with season and geographic position in a way that affects the returned altimeter waveform and can therefore affect the estimate of the surface height derived from the waveform. Notwithstanding the possibility of a varying bias between the derived and real surface, for the lower accumulation regions in the western and northern ice sheet periphery (< ~1 m snow accumulation yearly) we show that the CryoSat altimeter can measure height change throughout the year, including that associated with ice dynamics, summer melt and winter accumulation. Further, over the 9-year CryoSat lifetime it is also possible to relate height change to change in speed of large outlet glaciers, for example, there is significant height loss upstream of two branches of the Upernavik glacier in NW Greenland that increased in speed during this time, but much less height loss over a third branch that slowed in the same time period. In contrast to the west and north, winter snow accumulation in the south-east periphery can be 2 - 3 m and the average altimeter height for this area can decrease by up to 2 m during the fall and winter when the change in the surface elevation is much smaller. We show that vertical downward movement of the dense layer from the last summer melt coupled with overlying dry snow, are responsible for the anomalous altimeter height change. However, it is still possible to estimate year-to-year height change measurements in this area by using data from the late-summer to early-fall when surface returns dominate the altimeter signal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".