Stratospheric Aerosol Characteristics from the 2017–2019 Volcanic Eruptions Using the SAGE III/ISS Observations
Bibliographic record
Abstract
In recent years (2017–2019), several moderate volcanic eruptions and wildfires have perturbed the stratospheric composition and concentration with distinct implications on radiative forcing and climate. The Stratospheric Aerosol and Gas Experiment III instruments onboard the International Space Station (SAGE III/ISS) have been providing aerosol extinction coefficient (EC) profiles at multiple wavelengths since June 2017. In this study, a method to invert the spectral stratospheric aerosol optical depth (sAOD) or EC values from SAGE III/ISS (to retrieve the number/volume size distributions and other microphysical properties) is presented, and the sensitivity of these retrievals is evaluated. It was found that the retrievals are strongly dependent on the choices of wavelengths, which in turn determine the shapes of the calculated curves. Further, we examine the changes in stratospheric aerosol spectral behavior, size distribution properties, time evolution (growth/decay) characteristics associated with subsequent moderate volcanic eruptions, namely, Ambae (15∘S, 167∘E; April and July 2018), Raikoke (48∘N, 153∘E; June 2019), and Ulawun (5∘S, 151∘E; June and August 2019), in different spatial regions. The observational period was classified with reference to Ambae eruptions into four phases (pre-Ambae, Ambae1, Ambae2, and post-Ambae). The pre-Ambae and post-Ambe periods comprise the 2017 Canadian fires and 2019 Raikoke/Ulawun eruptions, respectively. The spectral dependence of sAOD was comparable and lowest during the pre-Ambae and Ambae1 periods in all regions. The number concentration at the principal mode radius (between 0.07 and 0.2 μm) was observed to be higher during the Ambae2 period over the Northern Hemisphere (NH). The rate of change (growth/decay) in the sAOD on a global scale resembled the changes in the Southern Hemisphere (SH), unlike the time-lag-associated changes in the NH. These differences could be attributed to the prevailing horizontal and vertical dispersion mechanisms in the respective regions. Lastly, the radiative forcing estimates of Ambae and Raikoke/Ulawun eruptions, as reported in recent studies, was discussed by taking clues from other major and moderate eruptions to gain insight on their role in climate change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".