Remote sensing of drizzle onset and cloud microphysical properties in marine stratocumulus
Bibliographic record
Abstract
Low-level stratiform clouds remain one of the wildcards in future climate simulations. Despite their important role in the earth's radiation budget and the large number of dedicated field campaigns, several cloud-scale processes in marine stratocumulus clouds remain misrepresented. The 19-month-long deployment of the Atmospheric Radiation Measurement Program Mobile Facility in the Azores provided the longest and most comprehensive ground-based observational dataset of marine boundary layer clouds to date. The first objective of this project was the documentation of the frequency of occurrence of different cloud and precipitation systems in the Azores using a combination of passive and active measurements. The analysis indicates that, even though clouds were often observed (close to 80 % of the time), especially in the boundary layer (~50 %), a single-layer stratocumulus coverage rarely persisted more than a day. In fact, many stratocumulus clouds were observed to have cumulus clouds underneath them. This is linked to the nearly constant decoupled state of the boundary layer in the Azores, contrary to what has been observed in the Pacific decks. 35 cases of mostly single-layer persisting stratocumulus coverage were selected for further analysis. Results include similarities with other studies (e.g., maximum coverage at night, thicker clouds needed to drizzle, and importance of cloud-top radiative cooling at night), as well as differences (e.g., coherent structures account for a smaller fraction of the updraft mass flux). The second objective of this project was to revisit the detection of drizzle-size particles in stratocumulus clouds using radar observations. First, the cloud and drizzle size distributions are related theoretically to the radar measurements, including the effects of the dynamics. Then, a forward radar Doppler spectra model was developed to test the sensitivity of the radar measurements to modifications of the drizzle contribution. Finally, a simple 1-D steady-state model was exploited to simulate drizzle growth as it falls in a cloud, using the forward model to link the output back to the radar observations. Using that combination of models, some observed features of the drizzle evolution inside continental and maritime stratocumulus clouds were successfully investigated. Overall, it was found that the skewness of a radar Doppler spectrum is a good indicator of the presence of early drizzle droplets, while a reflectivity or Doppler velocity threshold indicates the change in dominance in the Doppler spectrum occurring when drizzle is well developed. The third and final objective of this project was to revisit another long-standing challenge: the retrieval of cloud microphysical properties using a combination of radar-radiometer measurements. A new technique was developed to retrieve the cloud particle size distribution in stratocumulus clouds, adding a microphysical condensational model under steady-state supersaturation conditions to a common retrieval method. The results appear reasonable in two nondrizzling marine stratocumulus clouds, and the derived cloud optical depth compares well with the one derived independently with another instrument. The errors of the retrievals were also estimated, demonstrating the added value of the new technique.
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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) | 0.000 | 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".