Subkilometer Numerical Weather Prediction in an Urban Coastal Area: A Case Study over the Vancouver Metropolitan Area
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Numerical weather prediction is moving toward the representation of finescale processes such as the interactions between the sea-breeze flow and urban processes. This study investigates the ability and necessity of using kilometer- to subkilometer-scale numerical simulations with the Canadian urban modeling system over the complex urban coastal area of Vancouver, British Columbia, Canada, during a sea-breeze event. Observations over the densely urbanized areas, collected from the Environmental Prediction in Canadian Cities (EPiCC) network and from satellite imagery, are used to evaluate several aspects of the urban boundary layer features simulated in three model configurations with different grid spacings (2.5 km, 1 km, and 250 m). In agreement with the observations, results from the numerical experiments with 1-km and 250-m grid spacings suggest that two sea-breeze flows converge over the residential areas of Vancouver. The resulting convergence line oscillates around the hill ridge, depending on thermal contrast and flow strength. This propagation mode impacts the growing urban boundary layer, with the presence of subsidence and entrainment events. Urban-induced circulation is superimposed with the sea-breeze circulation and realistically slows down the propagation of the sea-breeze front to the south. A clear improvement is obtained for numerical experiments with 1-km instead of 2.5-km grid spacing. The use of subkilometer grid spacing provides a more detailed representation of the surface thermal forcing and of local circulations, with results more sensitive to the airflow variability and, thus, to the location of measurement sites. Joint analyses of kilometer- and subkilometer-scale numerical experiments are thus recommended for different environmental applications.
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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 | 0.000 |
| 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 it