Changes in North American snowpacks for 1979–2007 detected from the snow water equivalent data of SMMR and SSM/I passive microwave and related climatic factors
Bibliographic record
Abstract
Changes to the North American snowpacks for 1979–2007 were detected from snow water equivalent (SWE) retrieved empirically from horizontally polarized brightness temperature ( T B ) of a scanning multichannel microwave radiometer (18 and 37 GHz) and special sensor microwave imager (19 and 37 GHz) passive microwave data using the nonparametric Kendall's test. The predominant SWE trends detected agree with negative anomalies in snow cover observed in Northern Hemisphere since the 1980s, and both the SWE and snow cover results should be related to the significant increase in the surface temperature of North America (NA) observed since the 1970s. About 30% of detected decreasing trends of SWE for 1979–2007 are statistically significant, which is three times more than the significant increasing trends of SWE detected in NA. Significant decreasing SWE trends are more extensive in Canada than in the United States. The mean trend magnitudes detected for December–April are −0.4 to −0.5 mm/yr, which means an overall reduction of snow depth of about 5–8 cm in 29 years (assuming a snowpack density between 200 and 250 kg/m 3 ), which can impact regions relying on spring snowmelt for water supply. From detected increasing (decreasing) trends of gridded temperature (precipitation) based on the North American Regional Reanalysis data set and the University of Delaware data set for NA, their respective correlations with SWE data and other findings, such as global scale decline of snow cover, longer rainfall seasons, etc., it seems the extensive decreasing trends in SWE detected mainly in Canada are more caused by increasing temperatures than by decreasing precipitation. However, climate anomalies could also contribute to the detected trends, such as PC1 of NA's SWE, which is found to be correlated to the Pacific Decadal Oscillation index and marginally correlated to the Pacific North American pattern.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".