Comparison of microphysical modeling of polar stratospheric clouds against balloon‐borne and Improved Limb Atmospheric Spectrometer (ILAS) satellite observations
Bibliographic record
Abstract
A size‐segregated stratospheric aerosol model with detailed polar stratospheric cloud (PSC) microphysics has been developed to study the formation and evolution of PSCs. For comparison with satellite and balloon‐borne observations, one‐dimensional simulations have been performed in Esrange/Kiruna (67.93°N, 21.07°E), Sweden during the period of winter 1996/1997. The modeled proportions of PSCs are consistent with the observations of volume, number, size distributions, and extinction coefficients derived from the in situ balloon‐borne optical particle counter and the Improved Limb Atmospheric Spectrometer (ILAS) satellite sensor, demonstrating the capability of the model to capture PSC events. Model simulations successfully reproduce three major PSC events in the period from January to February 1997. The model is able to produce particle size distribution and number densities typical of the field observations in the Arctic stratosphere. Large HNO3‐containing particles with a median radius of 6 μm and number densities in the range of 10−5 to 10−3 cm−3 are predicted to occur over a broad range of altitudes. Model simulations suggest that the homogeneous nucleation mechanism of type Ia PSCs out of type Ib PSCs plays a critical role in the formation of large HNO3‐containing particles. The present model shows good potential for interpreting and validating the balloon‐borne and satellite observations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".