The potential influence of Asian and African mineral dust on ice, mixed-phase and liquid water clouds
Bibliographic record
Abstract
Abstract. This modelling study explores the availability of mineral dust particles as ice nuclei for interactions with ice, mixed-phase and liquid water clouds, also tracking the particles' history of cloud-processing. We performed 61 320 one-week forward trajectory calculations originating near the surface of major dust emitting regions in Africa and Asia using high-resolution meteorological analysis fields for the year 2007. Dust-bearing trajectories were assumed to be those coinciding with known dust emission seasons, without explicitly modelling dust emission and deposition processes. We found that dust emissions from Asian deserts lead to a higher potential for interactions with high ice clouds, despite being the climatologically much smaller dust emission source. This is due to Asian regions experiencing significantly more ascent than African regions, with strongest ascent in the Asian Taklimakan desert at ~25%, ~40% and 10% of trajectories ascending to 300 hPa in spring, summer and fall, respectively. The specific humidity at each trajectory's starting point was transported in a Lagrangian manner and relative humidities with respect to water and ice were calculated in 6-h steps downstream, allowing us to estimate the formation of liquid, mixed-phase and ice clouds. Downstream of the investigated dust sources, practically none of the simulated air parcels reached conditions of homogeneous ice nucleation (T≲−40 °C) along trajectories that have not experienced water saturation first. By far the largest fraction of cloud forming trajectories entered conditions of mixed-phase clouds, where mineral dust will potentially exert the biggest influence. The majority of trajectories also passed through atmospheric regions supersaturated with respect to ice but subsaturated with respect to water, where so-called "warm ice clouds" (T≳−40 °C) theoretically may form prior to supercooled water or mixed-phase clouds. The importance of "warm ice clouds" and the general influence of dust in the mixed-phase cloud region are highly uncertain due to both a considerable scatter in recent laboratory data from ice nucleation experiments, which we briefly review in this work, and due to uncertainties in sub-grid scale vertical transport processes unresolved by the present trajectory analysis. For "classical" cirrus-forming temperatures (T≲−40 °C), our results show that only mineral dust ice nuclei that underwent mixed-phase cloud-processing, most likely acquiring coatings of organic or inorganic material, are likely to be relevant. While the potential paucity of deposition ice nuclei shown in this work dimishes the possibility of deposition nucleation, the absence of liquid water droplets at T≲−40 °C makes the less explored contact freezing mechanism (involving droplet collisions with bare ice nuclei) highly inefficient. These factors together indicate the necessity of further systematic studies of immersion mode ice nucleation on mineral dust suspended in atmospherically relevant coatings.
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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 | 0.001 |
| 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".