Precipitation Distribution Associated with Landfalling Tropical Cyclones over the Eastern United States
Bibliographic record
Abstract
Abstract Tropical cyclones (TCs) making landfall over the United States are examined by separating those associated with precipitation predominantly left of their tracks from those with the same to the right of their tracks. Composites of atmospheric variables for these two TC categories are performed and analyzed using potential vorticity (PV) and quasigeostrophic (QG) frameworks. Dynamical signatures are retrieved from these composites to help understand the evolution of precipitation in these storms. Results indicate that a left of track precipitation distribution (e.g., Floyd 1999) is characteristic of TCs undergoing extratropical transition (ET). In these cases, a positively tilted midlatitude trough approaches the TC from the northwest, shifting precipitation to the north-northwest of the TC. Potential vorticity redistribution through diabatic heating leads to enhanced ridging over and downstream of the TC, resulting in an increase in the cyclonic advection of vorticity by the thermal wind over the transitioning TC. A right of track precipitation distribution is characteristic of TCs interacting with a downstream ridge (e.g., David 1979). When the downstream ridge amplifies in response to TC-induced diabatic heating ahead of a weak midlatitude trough, the PV gradient between the TC and the downstream ridge is accentuated, producing a region of enhanced positive PV advection (and cyclonic vorticity advection by the thermal wind) over the TC. The diabatic enhancement of the downstream ridge is instrumental in the redistribution of precipitation about the transitioning TCs in both cases and poses a significant forecast challenge.
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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 | 0.000 | 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) | 0.001 | 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".