A Multi-Platform In Situ Kinematic and Microphysical Analysis of a Hybrid Parallel–Trailing Stratiform Mesoscale Convective System
Bibliographic record
Abstract
Abstract Parallel stratiform–type mesoscale convective systems (MCS) have been found to comprise less than 20% of the central U.S. MCSs, but parallel stratiform MCSs have been reviewed by few studies and only a handful have been sampled using airborne platforms. This study conducts a detailed review of the 11 May 2011 MCS that was observed during the Midlatitude Continental Convective Clouds Experiment. In situ data from the University of North Dakota Cessna Citation II Weather Research Aircraft and the Oklahoma Mesonet are used in conjunction with radar reflectivity data and a multiple-Doppler wind retrieval to present an in-depth analysis of the kinematic and microphysical processes within this hybrid parallel–trailing stratiform MCS. Results suggest the MCS started with parallel stratiform characteristics and then developed trailing stratiform features over the course of a couple of hours such as leading line convection and the presence of rear inflow, which is a feature not observed in previous studies of parallel stratiform MCSs. Based on surface observations and multi-Doppler wind field retrievals, the cold pool influenced the 11 May 2011 MCS and may have helped it to transition toward the trailing stratiform mode. Within the stratiform region, in situ measurements show hydrometeor aggregation and sublimation occurring above the melting layer via a faster rate of decline in total hydrometer concentration compared to the total water content, the presence of a bimodal droplet size spectra, and increasing dispersion and decreasing slope, with respect to increasing temperature in both the unimodal and bimodal gamma distributions. Significance Statement The purpose of this study is to investigate the wind pattern of a nontypical type of thunderstorm complex. The wind pattern is found to be a combination of features from both a common type of thunderstorm complex and another less common type. The behavior of snowflakes as they fall through this thunderstorm was also investigated. The snowflakes in this storm grew bigger by linking up with other snowflakes as they fell down, and then melted before they reached the ground. It is hoped that results from this study are useful to future work to improve weather prediction.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".