Ice-nucleating particles are emitted by raindrop impact
Bibliographic record
Abstract
Ice-nucleating particles (INPs) play a key role in ice formation and cloud microphysics and thus significantly impact the water cycle and the climate. However, our understanding of atmospheric INPs, particularly their sources, emissions, and spatiotemporal variability, is incomplete. While the enhancement of atmospheric INP concentrations with rainfall has been previously shown, a mechanistic understanding of the process is lacking. Here, we link detailed precipitation observations with near-surface atmospheric INP concentrations at a semi-arid grassland site in Colorado. Considering the during-precipitation air samples, INP concentrations positively correlate with cumulative rainfall kinetic energy and amount, suggesting that INP aerosolization is induced by raindrop and hailstone impact. By additionally analyzing the INP content of precipitation water, terrestrial source samples, and heat-treated samples, we demonstrate that local plants are the most important source of precipitation-induced INPs. Should INPs aerosolized by precipitation rise to cloud height, they could influence cloud ice fraction and initiate precipitation resulting in an aerosol-cloud-precipitation feedback.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".