On Risk of Rain on Snow Over High‐Latitude Coastal Areas in North America
Bibliographic record
Abstract
Abstract Extreme floods and landslides in high‐latitude watersheds have been associated with rain‐on‐snow (ROS) events. Yet, the risks of changing precipitation phases on a declining snowpack under a warming climate remain unclear. Normalizing the total annual duration of ROS with that of the seasonal snowpack, the ERA5 data (1941–2023) show that the frequency of high‐runoff ROS events is a characteristic feature of high‐latitude coastal zones, particularly over the coasts of south‐central Alaska and southern Newfoundland. Total rainfall accumulation per seasonal snowpack duration has increased across western mountain ranges, with the Olympic Mountains experiencing more than 40 mm of additional rainfall over the snowpack in the past eight decades, followed by the Sierra Nevada. These trends could drive an 8% increase in rainfall extremes (e.g., more than 10 mm for 6 hr storm with a 15‐year return period), highlighting the need for resilient flood control systems in high‐latitude coastal cities.
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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 | 0.001 |
| 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 | 0.001 | 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".