Stratospheric aerosol layer perturbation caused by the 2019 Raikoke and Ulawun eruptions and their radiative forcing
Bibliographic record
Abstract
Abstract. In June 2019 a stratospheric eruption occurred at Raikoke (48∘ N, 153∘ E). Satellite observations show the injection of ash and SO2 into the lower stratosphere and an early entrainment of the plume into a cyclone. Following the Raikoke eruption, stratospheric aerosol optical depth (sAOD) values increased in the whole Northern Hemisphere and tropics and remained enhanced for more than 1 year, with peak values at 0.040 (short-wavelength, high northern latitudes) to 0.025 (short-wavelength, Northern Hemisphere average). Discrepancies between observations and global model simulations indicate that ash may have influenced the extent and evolution of the sAOD. Top of the atmosphere radiative forcings are estimated at values between −0.3 and -0.4Wm-2 (clear-sky) and of −0.1 to -0.2Wm-2 (all-sky), comparable to what was estimated for the Sarychev eruption in 2009. Almost simultaneously two significantly smaller stratospheric eruptions occurred at Ulawun (5∘ S, 151∘ E) in June and August. Aerosol enhancements from the Ulawun eruptions mainly had an impact on the tropics and Southern Hemisphere. The Ulawun plume circled the Earth within 1 month in the tropics. Peak shorter-wavelength sAOD values at 0.01 are found in the tropics following the Ulawun eruptions and a radiative forcing not exceeding −0.15 (clear-sky) and −0.05 (all-sky). Compared to the Canadian fires (2017), Ambae eruption (2018), Ulawun (2019) and the Australian fires (2019/2020), the highest sAOD and radiative forcing values are found for the Raikoke eruption.
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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 | 0.000 |
| 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".