A New Volcanic Stratospheric Sulfate Aerosol Forcing Emulator (EVA_H): Comparison With Interactive Stratospheric Aerosol Models
Bibliographic record
Abstract
Abstract Idealized models or emulators of volcanic aerosol forcing have been widely used to reconstruct the spatiotemporal evolution of past volcanic forcing. However, existing models, including the most recently developed Easy Volcanic Aerosol (EVA; Toohey et al., doi: 10.5194/gmd‐2016‐83), (i) do not account for the height of injection of volcanic SO ; (ii) prescribe a vertical structure for the forcing; and (iii) are often calibrated against a single eruption. We present a new idealized model, EVA_H, that addresses these limitations. Compared to EVA, EVA_H makes predictions of the global mean stratospheric aerosol optical depth that are (i) similar for the 1979–1998 period characterized by the large and high‐altitude tropical SO injections of El Chichón (1982) and Mount Pinatubo (1991); (ii) significantly improved for the 1998–2015 period characterized by smaller eruptions with a large variety of injection latitudes and heights. Compared to EVA, the sensitivity of volcanic forcing to injection latitude and height in EVA_H is much more consistent with results from climate models that include interactive aerosol chemistry and microphysics, even though EVA_H remains less sensitive to eruption latitude than the latter models. We apply EVA_H to investigate potential biases and uncertainties in EVA‐based volcanic forcing data sets from phase 6 of the Coupled Model Intercomparison Project (CMIP6). EVA and EVA_H forcing reconstructions do not significantly differ for tropical high‐altitude volcanic injections. However, for high‐latitude or low‐altitude injections, our reconstructed forcing is significantly lower. This suggests that volcanic forcing in CMIP6 last millenium experiments may be overestimated for such eruptions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".