Immersion Freezing of Supermicron Mineral Dust Particles: Freezing Results, Testing Different Schemes for Describing Ice Nucleation, and Ice Nucleation Active Site Densities
Bibliographic record
Abstract
Ice nucleation on mineral dust particles is known to be an important process in the atmosphere. To accurately implement ice nucleation on mineral dust particles in atmospheric simulations, a suitable theory or scheme is desirable to describe laboratory freezing data in atmospheric models. In the following, we investigated ice nucleation by supermicron mineral dust particles [kaolinite and Arizona Test Dust (ATD)] in the immersion mode. The median freezing temperature for ATD was measured to be approximately -30 °C compared with approximately -36 °C for kaolinite. The freezing results were then used to test four different schemes previously used to describe ice nucleation in atmospheric models. In terms of ability to fit the data (quantified by calculating the reduced chi-squared values), the following order was found for ATD (from best to worst): active site, pdf-α, deterministic, single-α. For kaolinite, the following order was found (from best to worst): active site, deterministic, pdf-α, single-α. The variation in the predicted median freezing temperature per decade change in the cooling rate for each of the schemes was also compared with experimental results from other studies. The deterministic model predicts the median freezing temperature to be independent of cooling rate, while experimental results show a weak dependence on cooling rate. The single-α, pdf-α, and active site schemes all agree with the experimental results within roughly a factor of 2. On the basis of our results and previous results where different schemes were tested, the active site scheme is recommended for describing the freezing of ATD and kaolinite particles. We also used our ice nucleation results to determine the ice nucleation active site (INAS) density for the supermicron dust particles tested. Using the data, we show that the INAS densities of supermicron kaolinite and ATD particles studied here are smaller than the INAS densities of submicron kaolinite and ATD particles previously reported in the literature.
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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) | 0.000 | 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".