Stratospheric Injection Lifetimes
Bibliographic record
Abstract
not-yet-known not-yet-known not-yet-known unknown Material injected to the stratosphere by volcanoes and pyrocumulonimbus clouds (pyroCBs) is observed to have different lifetimes depending on the altitude, latitude, season of the injection and removal processes. We adopt a framework that describes the stratospheric lifetime of injected material as the sum of lag and decay timescales and compute these quantities in tracer simulations by injecting hundreds of thousands of trajectory parcels and tracking them over 8 years. We simulate the evolution of the Hunga water vapor plume from the January 2022 Hunga eruption. The simulation suggests the lag time would be 1.4 years and the decay time ~ 2.3 years, producing a stratospheric lifetime of ~3.7 years. From Microwave Limb Sounder observations, we estimate the Hunga lifetime to be 3.7±0.36 years which is in good agreement. Overall, we find that passive tracer lifetimes increase with altitude and decrease with the latitude. If polar stratospheric cloud formation is a tracer loss process, the lifetime is shortened. Aerosol gravitational settling also shortens the lifetime and should be included especially for aerosols with < 0.5 µm radius. With the decay of Hunga aerosol plume, we use the lifetime and gravitational settling rate to estimate a particle median radius of ~0.3µm in agreement with other estimates. Our calculations explain the different observed lifetimes for historic stratospheric injections and the changes in total stratospheric aerosols and water observed after the Hunga eruption. Our calculations are also relevant to geoengineering plans for modifying the stratospheric albedo where sustained stratospheric aerosol concentrations are envisioned.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".