Moisture transport to British Columbia’s upper Nechako Watershed associated with three atmospheric rivers
Bibliographic record
Abstract
Abstract Atmospheric rivers (ARs) that reach British Columbia’s (BC’s) Coast Mountains undergo orographic lifting, leading to intense precipitation that impacts the region’s hydroclimatology. To assess the impact of ARs on the upper Nechako Watershed, the Tahtsa Ranges Atmospheric River Experiment (TRARE) collected detailed hydrometeorological data in this region during September and October 2021. For three case studies, primary pathways of moisture transport, water vapor budgets, and constancy of moisture transport across the upper Nechako Watershed are identified and quantified using TRARE observational and ERA5 reanalysis datasets. ARs associated with Events 3 and 5 had a southwest-to-northeast path with minimal temporal moisture variability. In contrast, Event 10 primarily followed a southeasterly-to-northwesterly pathway exhibiting more variable moisture transport. Although Events 3 and 5 are associated with weak ARs and Event 10 is indirectly linked to bombogenesis, they all contributed similar amounts (~ 109 kg s−1) to the water vapor budget for the upper Nechako. Additionally, stronger winds and higher steadiness of moisture transport are associated with copious precipitation across the upper Nechako, particularly along the basin’s southern and western boundaries. ARs that impact the upper Nechako therefore play a crucial role in replenishing water resources that sustain ecological systems, aquatic habitat, hydropower generation, and domestic water consumption.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".