Ice-nucleating particles over the Labrador Sea during the M-Phase campaigns
Bibliographic record
Abstract
As the Earth warms, it is important to understand how a change in the ice:water ratio in mixed-phase clouds influences the cloud-phase feedback; a cooling effect caused by the change in albedo of the cloud. Ice-nucleating particles (INPs), aerosols that can trigger the freezing of liquid cloud droplets via heterogeneous nucleation, may regulate this cooling process by maintaining the ice contents in clouds, hence it is necessary to identify the types, sources, and concentrations of INPs to determine their contribution and better represent this in models. We undertook ship and aircraft-based INP measurement campaign in the Labrador Sea region, which features clouds that are susceptible to the effect of INPs, in 2022: (i) a cruise on the RRS Discovery, as part of a joint SEANA/M-Phase project in May-June, and (ii) a flight campaign on the FAAM BAe-146 aircraft as part of the M-Phase project in October-November that focused on northwesterly cold air outbreak (CAO) cloud systems.During the SEANA/M-Phase ship cruise, real-time measurements of INP concentrations were taken using a Portable Ice Nucleation Experiment (PINE) expansion chamber alongside offline filter-based measurements and bulk seawater measurements. Preliminary results suggest that high INP concentrations correlated with air masses that had passed over the exposed (i.e. not snow- or ice-covered) coastline of Greenland, while lower concentrations correlated with air masses that had passed over the sea ice. These results suggest a high-latitude source of INPs not currently accounted for in models, the study of which could be crucial in understanding their influence on clouds in a changing climate.Offline filter-based INP measurements during the FAAM aircraft campaign showed highly reproducible INP concentrations during CAO events (0.05 INP L−1 at −15 °C), with both much higher and much lower concentrations during non-CAO days. Further analysis will include further processing of the campaign data, including aerosol size distributions together with real-time INP data taken from a new online continuous flow diffusion chamber (CFDC), the Met Office Ice Nuclei Counter (INC), aboard the aircraft, together with aerosol composition analysis via scanning electron microscopy of filters, which will allow the types and sources of INPs in the Labrador Sea region to be established.The M-Phase campaigns in the Labrador Sea have shed some light on INP properties in the region, and further processing of the data will allow determination of INP sources, activity, and relationship with aerosol size distributions. Better representation of INPs in models based on these findings will allow for reduced uncertainty in the cloud-phase feedback and its impact on climate predictions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".