Modelling Lake Ice Phenology with an Examination of Satellite-Detected Subgrid Cell Variability
Bibliographic record
Abstract
Lake ice was simulated for the province of Quebec, Canada, for both contemporary and future climate conditions using a one-dimensional thermodynamic ice model. The model was forced with NARR data (32 km) and both the daily IMS product (4 km) and the MODIS snow product (500 m) were assessed for their utility at determining lake ice phenology at the subgrid cell level (based on the 32 km NARR grid). Both products were useful for detecting ice-off; however, the MODIS product was advantageous for detecting ice-on, mainly due to the finer resolution and resulting spatial detail. The subgrid cell variability in ice-on/off dates was typically less than 2% of the mean, although it ranged up to 10% for some grid cells. The simulations were found to be within the satellite-detected subgrid cell variability: 62% of the time for ice-off and 80% of the time for ice-on. Forcing the model with future climate scenarios from the Canadian Regional Climate Model predicts the regional ice cover durations will decrease by up to 50 days from the current 1981–2010 means to the 2041–2070 means and decrease from 15 to nearly 100 days shorter from the current means to the 2071–2100 means.
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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 | 0.001 | 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 | 0.001 |
| 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".