Ship-borne radar observations of organized convection during the ORCESTRA/PICCOLO field campaign
Bibliographic record
Abstract
The ORganized Convection and Earthcare Studies over the TRopical Atlantic (ORCESTRA) field campaign occurred in the tropical Atlantic in August and September 2024. ORCESTRA is an international initiative that combined eight different sub-campaigns utilizing seven different ship, aircraft, ground-based, and satellite platforms. Here we focus on preliminary results from PICCOLO (Process Investigation of Clouds and Convective Organization over the atLantic Ocean), the NSF-funded sub-campaign that deployed the CSU SEA-POL radar on the RV Meteor in coordination with the BOWTIE ship campaign to study the nature, governing mechanisms, and impact of mesoscale convective organization within the Atlantic ITCZ. SEA-POL is a ship-stabilized scanning C-band radar that measures dual-polarization and provides advanced retrievals of precipitation and its spatial pattern. PICCOLO has four objectives: (1) evaluate process relationships between precipitation, humidity, and organization; (2) use advanced polarimetric radar retrievals to investigate microphysical, dynamical, and radiative characteristics of convection; (3) investigate the importance of radiative processes in driving mesoscale organization; and (4) use novel observational approaches to compute the entropy budget to advance understanding of the impacts of convection on climate. The 40-day cruise primarily sampled within the moist tropics and observed a wide variety of convective states. There was a significant longitudinal contrast, in which conditions east of 40W were rainier and moister with cooler sea surface temperatures, stronger surface winds, and stronger vertical wind shear than areas west of 40W. We use the SEA-POL retrievals to examine the variability of convective structures within the ITCZ including variability in the prevalence of congestus versus deep convection. We also present initial classifications of the spatial organization of convection, its variability, and its influence on precipitation amount and intensity.
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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".