Global Positioning System interferometric reflectometry (GPS-IR) measurements of ground surface elevation changes in permafrost areas in northern Canada
Bibliographic record
Abstract
Abstract. Global Positioning System interferometric reflectometry (GPS-IR) is a relatively new technique which uses reflected GPS signals to measure surface elevation changes to study frozen-ground dynamics. At present, more than 200 GPS stations are operating continuously in the Northern Hemisphere permafrost areas, which were originally designed and maintained for tectonic and ionospheric studies. However, only one site in Utqiaġvik, Alaska (formerly Barrow), was assessed to be usable for studying permafrost by GPS-IR. Moreover, GPS-IR has high requirements on the ground surface condition, which needs to be open, flat, and homogeneous. In this study, we screen three major GPS networks in Canada and identify 12 out of 38 stations located in permafrost areas as useful ones where reliable GPS-IR measurements can be obtained. We focus on the five Canadian Active Control System stations and obtain their daily GPS-IR surface elevation changes. We find that the ground surface subsided in Alert, Resolute Bay, and Repulse Bay respectively by 0.61±0.04 cm yr−1 (2012–2018), 0.70±0.02 cm yr−1 (2003–2014), and 0.26±0.05 cm yr−1 (2014–2019). At the other two sites of Baker Lake and Iqaluit, the trends are not statistically significant. The linear trends of deformation were negatively correlated with those of thaw indices in Alert, Resolute Bay, and Repulse Bay. Furthermore, in Resolute Bay, we also find that the end-of-thaw elevations during 2003–2012 were highly negatively correlated with the square root of thaw indices. This study is the first one using multiple GPS stations to study permafrost by GPS-IR. It highlights the multiple useful GPS stations in northern Canada, offering multi-year, continuous, and daily GPS-IR surface deformation, which provides new insights into frozen-ground dynamics at various temporal scales and across a broad region.
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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 | 0.002 |
| 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 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".