Tomographic Retrievals of Hunga Tonga‐Hunga Ha'apai Volcanic Aerosol
Bibliographic record
Abstract
Abstract The 2022 eruption of the Hunga Tonga‐Hunga Ha'apai volcano caused substantial impacts on the atmosphere, including a massive injection of water vapor, and the largest increase in stratospheric aerosol for 30 years. The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler instrument has been critical in monitoring the amount and spread of the volcanic aerosol in the stratosphere. We show that the rapid imagery from the OMPS instrument enables a tomographic retrieval of the aerosol extinction that reduces a critical bias of up to a factor of two, and improves vertical structure and agreement with coincident lidar and occultation observations. Due to the vertically thin and heterogeneous nature of the volcanic aerosol, this impacts integrated values of aerosol across latitude, altitude, and time for several months. We also investigate the systematic impact of uncertainty in assumed particle size that result in an underestimation of the aerosol extinction at the peak of the volcanic aerosol layer.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".