Numerical Simulations of Three Nor'easters with a Warm Atlantic Ocean
Bibliographic record
Abstract
Analyses and numerical simulations were conducted on three recent nor’easters which formed on the East Coast of the United States to explore the effects of warmer-than-normal sea-surface temperatures on their wind and precipitation fields. The purpose of the study was to determine how warmer sea-surface temperatures in the Atlantic Ocean following the Genesis Flood would have enhanced nor’easters. Wind and precipitation fields for the actual storms were compared with simulated storms using the NCAR WRF model to insure that the model was accurately replicating the storms. The sea-surface was then increased by about 10°C (18°F) and the models rerun for the three storms. The wind fields and precipitation patterns were compared to the simulated actual storms to find how much the storms had been enhanced and the precipitation footprint changed. The WRF model accurately replicated the actual storms and the warmer sea-surface temperatures dramatically increased the wind speeds and precipitation. The enhanced storms moved more quickly off the Eastern seaboard than the actual storms and formed a larger and heavier snow shield over the northeastern United States and southeastern Canada. The additional accumulation of snow from the larger snow shields likely contributed to the Laurentide Ice Sheet following the Genesis Flood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".