Measurement of the Total Meltwater Amount in the Greenland Ice Sheet Using SMAP L-band Radiometry 
Bibliographic record
Abstract
With the growing concern of climate change, an accurate estimation of the total meltwater amounts (MWA) in the Greenland ice sheet (GIS) becomes crucial for understanding the physical processes of the GrIS and its mass balance, thereby enabling accurate prediction of its contribution to the global sea-level rise. Satellite microwave radiometers have been widely used for monitoring ice sheet melting for the last four decades; nevertheless, quantification of total MWA, especially the sub-surface MWA, remains a challenge.Here, we used the enhanced resolution L-band brightness temperature (TB) observations from the NASA Soil Moisture Active Passive (SMAP) mission to quantify the magnitude of the total MWA in GrIS for 2015-2023. Because of the larger penetration depth, L-band signals can track liquid water in deeper layers and provide a reliable estimate of surface-to-subsurface MWA, contrary to the higher frequency signals (18 or 37 GHz bands), which are limited to the top few centimeters of the surface snow. The algorithm uses vertically polarized (V-pol) TBs and an empirically derived adaptive thresholding technique to detect melt events. A simple microwave emission model, based on ice sheet radiative transfer, was used to simulate L-band TBs. The simulated TBs were then used in an inversion algorithm for MWA retrieval.Finally, the retrieval was compared with the corresponding MWA derived from an ice sheet energy and mass balance (EMB) model which was forced by hourly in situ observations from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station (AWS) network. The model was initialized and constrained by the relevant ice core density and sub-surface temperature profiles. The retrievals generally demonstrate a stronger agreement with the in situ observations in the percolation zone than in the ablation and upper elevation regions. The radiometric sensitivity, meltwater process, and their spatiotemporal variability were analyzed. The results demonstrate the potential for advancing our understanding of ice sheet physical processes to better project Greenland’s contribution to global sea level rise in response to the warming climate.
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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 | 0.000 | 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 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".