Time‐Domain Reflectometry Measurements and Modeling of Firn Meltwater Infiltration at DYE‐2, Greenland
Bibliographic record
Abstract
Surface meltwater can be retained in an ice sheet if it infiltrates the firn and refreezes. This is an important mass balance process for the Greenland Ice Sheet, reducing meltwater runoff and associated sea-level rise. The processes of meltwater infiltration and refreezing are not fully understood, however, and remain difficult to monitor remotely. We deployed vertical arrays of thermistors and time-domain reflectometry (TDR) probes to 4-m depth in the firn to continuously monitor meltwater infiltration and refreezing processes at DYE-2, Greenland. The observations provide a detailed picture of the coupled thermal and hydrological evolution of the firn through the 2016 melt season, including estimates of firn water content. The thaw and wetting fronts reached a maximum depth of 1.8 m, with meltwater infiltration concentrated in four main pulses of melting and subsurface warming that reached progressively deeper into the firn. The observations were used to constrain a coupled model of firn thermodynamics and hydrology, which was then run over the period 1950-2020, driven by meteorological forcing from GC-Net station data and ERA5 climate reanalyses. Model results suggest that decadal-scale firn evolution at DYE-2 is strongly influenced by extreme melt seasons such as those of 1968, 2012, and 2019, when meltwater infiltration reached depths of 6-7 m. Extreme melt years drive increases in firn temperature, ice content, and density, reducing firn meltwater retention capacity. Such processes are likely to govern future meltwater retention as the percolation zone extends to higher elevations in Greenland in the coming decades.
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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 | 0.002 | 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 | 0.000 | 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) | 0.002 | 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".