Multi-scale analysis of the meteorological processes forcing African dust ablation and transport in the extreme mid-march 2022 case
Bibliographic record
Abstract
We examine the complex meteorological processes involved in the development of multiple dust storms in the middle of March 2022 over North Africa by means of multi-level high-resolution reanalysis datasets, and satellite and surface observations. These dust storms ultimately transported a remarkable amount of dust into Europe, and in particular to the Iberian Peninsula.The analyses show that baroclinic Rossby Wave Breaking (RWB) events over two regions: the eastern North Atlantic and the western Eurasian border, resulted in the creation of a downscale confluence of low-level jets that ablated dust in the Sahara Desert. One of these active baroclinic regions involved multiple wave-breaks over western Russia and the Middle East that transported unseasonably cold air southwestward into Egypt and Sudan. A second active baroclinic region occurred along the North African Atlantic Coast where rapid downstream dispersion of energy was focused in response to very intense cyclogenesis over Labrador. The cold pool which propagated into northwestern Africa and cold air over northeastern Africa effectively sandwiched hot Saharan air in between the Hoggar and Atlas Mountain Ranges. The fronts separating these air masses became juxtaposed with the two mountain ranges creating ideal conditions for blocking and multiple barrier jets’ genesis. These barrier jets each combined with larger scale semi-geostrophic low-level jet formation, resulted in the ablation of dust into two separate large plumes both of which were transported poleward out of North Africa into Europe around a upper-level cutoff-low near Iberia slowly displacing downstream.The blocked RWB forcing the penetration of cold air over eastern Africa constitutes a substantial difference with respect to other more frequent events where RW trains intensify, penetrate equatorward into North Africa and propagate eastward.Work funded by MCIN/AEI/ 10.13039/501100011033 under Grant PID2020-115153RB-I00 (rROSSETA Project).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".