Clouds, Precipitation, and Marine Boundary Layer Structure during the MAGIC Field Campaign
Bibliographic record
Abstract
Abstract The recent ship-based Marine ARM GCSS Pacific Cross-Section Intercomparison (GPCI) Investigation of Clouds (MAGIC) field campaign with the marine-capable Second ARM Mobile Facility (AMF2) deployed on the Horizon Lines cargo container M/V Spirit provided nearly 200 days of intraseasonal high-resolution observations of clouds, precipitation, and marine boundary layer (MBL) structure on multiple legs between Los Angeles, California, and Honolulu, Hawaii. During the deployment, MBL clouds exhibited a much higher frequency of occurrence than other cloud types and occurred more often in the warm season than in the cold season. MBL clouds demonstrated a propensity to produce precipitation, which often evaporated before reaching the ocean surface. The formation of stratocumulus is strongly correlated to a shallow MBL with a strong inversion and a weak transition, while cumulus formation is associated with a much weaker inversion and stronger transition. The estimated inversion strength is shown to depend seasonally on the potential temperature at 700 hPa. The location of the commencement of systematic MBL decoupling always occurred eastward of the locations of cloud breakup, and the systematic decoupling showed a strong moisture stratification. The entrainment of the dry warm air above the inversion appears to be the dominant factor triggering the systematic decoupling, while surface latent heat flux, precipitation, and diurnal circulation did not play major roles. MBL clouds broke up over a short spatial region due to the changes in the synoptic conditions, implying that in real atmospheric conditions the MBL clouds do not have enough time to evolve as in the idealized models.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".