The Importance of the Ice-Phase Microphysics Parameterization for Simulating the Effects of Changes to CCN Concentrations in Deep Convection
Bibliographic record
Abstract
Abstract Simulations of a well-observed squall line that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) were conducted using a mesoscale model with a horizontal grid spacing of 1 km to examine the importance of parameterized ice-phase processes to changes in concentrations of activated cloud condensation nuclei (CCN) in a detailed two-moment bulk microphysics scheme. Numerical experiments showed that the simulated squall-line structure was sensitive to changes in activated CCN concentration not only from the direct impacts on cloud droplet sizes and autoconversion rates, but also because of changes in the growth rates and spatial distribution of ice-phase condensate. A microphysical budget analysis highlighted the importance of graupel in rain production and the sensitivity of graupel growth rates on changes to CCN concentrations. Sensitivity tests on the level of detail in the representation of graupel, specifically the treatment of its bulk density and the number of prognostic moments, indicated that changes in the reflectivity and precipitation structure of the simulated storm due to changes in CCN were sensitive to the graupel parameterization. The results suggest that the proper representation of graupel and possibly other ice-phase categories in microphysics schemes may be crucial for correctly simulating the effects of changes to CCN concentrations for continental deep convective systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".