Evaluation of land-atmosphere processes of the Polar WRF in the summertime Arctic tundra
Bibliographic record
Abstract
Arctic tundra is changing rapidly under the influence of global warming and it is important to know its impact on local and regional climate. Polar Weather Research and Forecasting (PWRF) model is a regional climate model optimized for the polar region and it is a useful tool for studying the Arctic tundra in high resolution. In this study, we evaluate the performance of the PWRF model over the Arctic tundra on clear summer days, when the transition is taking place the most, based on the surface energy fluxes and PBL observations in Cambridge Bay, Nunavut, Canada. The PWRF simulates a drier and warmer environment in PBL than the observations. Our analysis shows that it is due to the surface energy imbalance in the model caused by the uncertainties in prescribed initial input data and physical parameters rather than structural flaws in the model physics. The performance of the PWRF model over the Arctic tundra is improved when those values are modified based on the observation data.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".