Role of atmospheric circulation with respect to the interannual variability in the date of snow cover disappearance over northern latitudes between 1988 and 2003
Bibliographic record
Abstract
This paper analyzes the main spatial patterns in the dates of snow cover disappearance variability over northern latitudes between 1988 and 2003. The dates of snow cover disappearance were calculated using satellite passive microwave data from the Special Sensor Microwave/Imager. Spatial and temporal patterns were obtained using principal components analysis in the S mode. We identified eight components, each representing a large region characterized by homogeneous interannual variability in the dates of snow cover disappearance. We found that atmospheric circulation, summarized by means of teleconnection indices, had an important impact on the date of snow cover disappearance for most of these regions. A role is played by the Arctic Oscillation in western Siberia, the spring east Atlantic/west Russian pattern in central Siberia, and the Pacific North American pattern in southern Canada, while the El Niño–Southern Oscillation phenomenon and the west Pacific pattern are significantly related to variability in the date of snow cover disappearance in the northernmost areas of America. For the regions where we found no relationship between the interannual variability in the date of snow cover disappearance and the teleconnection indices, a direct relationship with some spatial patterns of sea level pressures, which are not well summarized by the teleconnection indices, was found.
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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 | 0.001 |
| 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".