Runoff modelling within the Canadian Regional Climate Model (CRCM): analysis over the Quebec/Labrador watersheds.
Bibliographic record
Abstract
This study focuses on evaluation of the hydrological performance of the Canadian Regional Climate Model (CRCM) coupled to the Canadian Land Surface Scheme (CLASS). The CRCM's ability to adequately simulate annual mean runoff over 21 small watersheds in the Quebec/Labrador peninsula is assessed over the period 1961―1999. Since runoff is a spatial and temporal integrator of weather events, it represents a very useful variable for climate model validation, especially in areas where conventional surface weather observations are scarce. In addition, the sensitivity of simulated runoff to domain size and lateral boundary conditions is investigated. Results of the analysis indicate that CRCM tends to systematically underestimate observed annual mean runoff over most of the investigated watersheds. It was found that choice of simulation domain has a considerable effect on the simulated hydrological regime at the watershed scale. Different re-analyses used as driving data have less influence than domain size. However it may be important (larger than CRCM's internal variability) when simulations are performed over a relatively small domain.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".