Synoptically forced hydroclimatology of major Arctic watersheds in general circulation models; Part 1: the Mackenzie River Basin
Bibliographic record
Abstract
Abstract The ability of 14 general circulation models (GCMs) to realistically simulate weather patterns and precipitation regimes affecting the Mackenzie River Basin has been assessed. Applying the method of self‐organizing maps to daily data from the model ensemble and the 40‐year reanalysis project of the ECWMF (ERA‐40), a regional synoptic climatology of sea level pressure was developed and used to analyse the model output. GCM performance, as compared with ERA‐40, varies significantly between models and seasons, but is generally best during the summer and winter. In‐depth examination of a five‐model subset reveals biases in the placement of the Pacific storm track, which may be related to misrepresentations of the Beaufort High. Biases in Mackenzie Basin precipitation are only weakly connected to these circulation errors, and are, instead, primarily the result of inaccurate representations of basin‐scale precipitation regimes. In particular, models allow excessive orographic precipitation along the west coast of North America to intrude into the Mackenzie Basin. These results suggest that projections of the Mackenzie's response to climate change could benefit from climate downscaling studies. Copyright © 2008 Royal Meteorological Society
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".