Recent changes in spring snowmelt timing in the Yukon River basin detected by passive microwave satellite data
Bibliographic record
Abstract
Abstract. Spring melt is a significant feature of high latitude snowmelt dominated drainage basins influencing hydrological and ecological processes such as snowmelt runoff and green-up. Melt duration, defined as the transition period from snowmelt onset until the end of the melt refreeze, is characterized by high diurnal amplitude variations (DAV) where the snowpack is melting during the day and refreezing at night, after which the snowpack melts constantly until depletion. Determining trends for this critical period is necessary for understanding how the Arctic is changing with rising temperatures and provides a baseline from which to assess future change. To study this dynamic period, brightness temperature (Tb) data from the Special Sensor Microwave Imager (SSM/I) 37 V-GHz frequency from 1988 to 2010 were used to assess snowmelt timing trends for the Yukon River basin, Alaska/Canada. Annual Tb and DAV for 1434 Equal-Area Scalable Earth (EASE)-Grid pixels (25 km resolution) were processed to determine melt onset and melt refreeze dates from Tb and DAV thresholds previously established in the region. Temporal and spatial trends in the timing of melt onset and melt refreeze, and the duration of melt were analyzed for the 13 sub-basins of the Yukon River basin with three different time interval approaches. Results show a lengthening of the melt period for the majority of the sub-basins with a significant trend toward later end of melt refreeze after which the snowpack melts day and night leading to snow clearance, peak discharge, and green-up. Earlier melt onset trends were also found in the higher elevations and northernmost sub-basins (Porcupine, Chandalar, and Koyukuk rivers). Latitude and elevation displayed the dominant controls on melt timing variability and spring solar flux was highly correlated with melt timing in middle (∼600–1600 m) elevations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".