Common Ingredients and Orographic Rain Index (ORI) for Heavy Precipitation Associated with Tropical Cyclones Passing Over the Appalachian Mountains
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Bibliographic record
Abstract
Relative contributions of common ingredients to heavy orographic rainfall associated with the passage of Hurricanes Hugo (1989) and Isabel (2003) over the Appalachian Mountains are examined using a numerical weather prediction model. It is found that the key ingredients for producing local heavy orographic rainfall were: high precipitation efficiency, strong low-level flow, strong orographically forced upward motion associated with strong low-level flow over relatively gentle upslope, concave geometry providing local areas of convergence, high moist flow upstream, a relatively large convective system associated with both tropical cyclones (TCs), and relatively slower movement. In addition, neither conditional instability nor potential (convective) instability is found to play essential roles in producing strong upward motion leading to heavy orographic TC rain. A modified Orographic Rain Index (ORI) is proposed as a predictor for heavy orographic TC precipitation, which includes the upstream incoming horizontal wind speed normal to the local orography, the steepness of the mountain, the relative humidity, the TC moving speed, and the horizontal scale of the TC. It is found that the ORI estimated in regions of local maximum rainfall by using fine-resolution numerically simulated results correlate well with rainfall rates for both hurricanes, indicating that it may serve as a predictor for heavy orographic TC rainfall.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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