Assessment of simulated water balance for continental‐scale river basins in an AMIP 2 simulation
Bibliographic record
Abstract
Streamflow, which integrates the response of the land surface to atmospheric forcing over large areas, is a useful diagnostic to assess the performance of land surface schemes over large spatial scales. This paper uses observed runoff and streamflow data to assess the performance of the Canadian land surface parameterization scheme (CLASS), when operated within the Canadian Centre for Climate modeling and analysis (CCCma) general circulation model (GCM) at 3.75° resolution, for three continental‐scale river basins. Estimates of evapotranspiration obtained using atmospheric water balance, and soil moisture obtained using the VIC‐2L model, are also used to assess the CLASS water balance simulations. Comparisons with observations of streamflow, and estimates of evapotranspiration and soil moisture, suggest that although CLASS simulates the annual cycle of evapotranspiration, streamflow, and soil moisture reasonably well, it overestimates evapotranspiration, underestimates runoff, and simulates slightly wetter soil moisture conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".