Anomaly patterns about strong convective events in the tropics and midlatitudes: Observations from radiosondes and surface weather stations
Bibliographic record
Abstract
Abstract We use 13 years (1998–2010) of rainfall estimates from the Tropical Rainfall Measuring Mission to identify high rain events located close to radiosondes. This is done in four regions: the Western Tropical Pacific, Tropical Brazil, Southeast China, and Southeast U.S. We then construct composite anomaly patterns of temperature, relative humidity, surface pressure, convective available potential energy (CAPE), geopotential height, mass divergence, relative vorticity, and potential vorticity about these high rain events. One motivation of this analysis is to identify regional differences in the interaction between strong convective events and the background atmosphere. We find, overall, that the changes in meteorological variables which occur during the evolution of strong convective events in midlatitudes are similar to the changes that occur in the tropics. In midlatitudes, however, strong convective events are associated with stronger anomalies in surface pressure and geopotential height and exhibit a warm anomaly in the lower troposphere prior to peak rainfall. In the Southeast U.S., the near‐surface layer of positive CAPE that occurs prior to high rain events is thicker than in the Western Tropical Pacific. In the two midlatitude regions, the midlevel potential vorticity maximum that develops during the growth stage of high rain events acquires a downward tilt toward the surface during the decay stage, suggesting downward transport toward the surface. A conceptual model previously used to interpret the anomaly patterns of the 2 day equatorial wave is used to interpret the anomaly patterns associated with more general types of high rain events in the tropics.
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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 | 0.001 | 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".