Dynamics of diabatically forced anticyclonic plumes in the stratosphere
Bibliographic record
Abstract
Abstract A new class of vortices has been observed in the stratosphere following extreme wildfires (Canada 2017, Australia 2020) and volcanic eruptions (Raikoke 2019). These vortices are long‐lived mesoscale anticyclones (hundreds to 1,000 km in diameter) trapping plumes of aerosols and combustion/volcanic compounds. Owing to their unusual composition, these anticyclonically trapped plumes (ATPs) are associated with a significant radiative heating, which fuels their ascent through the stratosphere. This article investigates the dynamics of ATPs using two complementary approaches: analytically, in a potential vorticity (PV) perspective, and through idealised numerical simulations with the Weather Research and Forecasting (WRF) model. In both cases, we consider the vortical flow forced by a heating Lagrangian tracer. By reformulating the problem in the potential radius–potential temperature coordinate system introduced for tropical cyclones, we first clarify that ATP formation is concomitant with the injection of air into the stratosphere at extratropical latitudes. Then, we derive a set of simplified one‐dimensional equations describing the subsequent evolution of the flow after the injection. The equation obtained for the tracer is a variant of the classical Burgers' equation. In qualitative agreement with the three‐dimensional WRF simulations, this theoretical model predicts that ATPs develop an upper tracer front associated with sustained near‐zero anticyclonic PV, followed by a smooth tracer tail of cyclonic PV. Radiative relaxation of the temperature perturbations induced by the anticyclone and the presence of an initial PV anomaly tend to stabilise ATPs during their ascent. Finally, we note that the theory predicts a similar relationship between the plume and anticyclonic PV for cooled ATPs, which is supported by three‐dimensional simulations and may apply to the 2022 Hunga volcanic plume.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".