Synthetic aperture radar (SAR) backscatter response from methane ebullition bubbles trapped by thermokarst lake ice
Bibliographic record
Abstract
Thermokarst lakes, formed by permafrost thaw, are an important source of atmospheric methane (CH4), a powerful greenhouse gas. Ebullition (bubbling) is often the dominant mode of lake CH4 emission. Because extrapolating spatially limited field measurements of CH4 ebullition induces large uncertainties in regional emission estimates, there is a need for remote sensing based approaches to detect and quantify CH4 ebullition at larger spatial scales in lakes. We examined the relationship between spaceborne synthetic aperture radar (SAR) pixel values of lake ice and biogeochemical field measurements of CH4 ebullition on ten lakes on the northern Seward Peninsula. Among lakes, ebullition ranged from low to high. We found that both the area of ice-bound ebullition-bubble clusters and the bubbling rates that generated the clusters were correlated with L-band single-polarized (HH) SAR (R2 = 0.70, p = 0.002, n = 10) and with the “roughness” component of a Pauli decomposition of L-band quad-polarized SAR (R2 = 0.77, p = 0.001, n = 10). No relationship was found between ERS-2 C-band single-polarized (VV) SAR and ice-trapped CH4 bubbles. Results of this study indicate that analysis of L-band SAR backscatter intensity from winter lake ice could be a valuable new tool for constraining estimates of regional ebullition in lakes.
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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 | 0.000 | 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) | 0.010 | 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".