Historical stratospheric aerosol optical properties and volcanic sulfur emissions for CMIP7 Fast Track
Bibliographic record
Abstract
Stratospheric aerosols, most of which originate from explosive volcanic sulfur emissions into the stratosphere, are a key natural driver of climate variability. They are thus one of the forcings provided by the Coupled Model Intercomparison Project (CMIP) Climate Forcings Task Team for the CMIP7 Fast Track, a set of climate model experiments designed to deliver the Intergovernmental Panel on Climate Change (IPCC) 7th assessment cycle. In this work, we document the final version of the stratospheric aerosol forcing datasets delivered to modelling groups for CMIP7 Fast Track. Our datasets cover the 1750-2023 period to meet to the need of modelling groups who might run extended historical simulations starting in 1750 instead of 1850. We produced one volcanic stratospheric sulfur emission dataset catering for the needs of models which have a prognostic interactive stratospheric aerosol scheme, as well as a stratospheric sulfate aerosol optical property dataset required by models that cannot interactively simulate stratospheric sufate aerosols. For the satellite era (from 1979 onwards), sulfur emissions and sufate aerosol optical properties are based on the MSVOLSO2L4 and GloSSAC datasets, respectively. For the pre-satellite era (1750-1978), the emission dataset is based on ice-core datasets complemented by the geological record for small-moderate magnitude eruptions not captured in ice-core records. Although inferring emissions of these eruptions from the geological record is highly uncertain, our approach minimizes an important bias in the pre-satellite era forcing, both in terms of mean and variability. The pre-satellite aerosol optical property dataset is directly derived from emissions using an updated version of EVA_H, a reduced-complexity volcanic aerosol model. This ensures methodological consistency between our emission and optical property datasets, and maximizes consistency with methodologies used in the paleoclimate (PMIP) and volcanic forcing (VolMIP) model intercomparison projects in CMIP6. We will present extensive comparison between our CMIP7 Fast Track dataset and the CMIP6 dataset. Last, we will discuss the main challenges to improve stratospheric aerosol datasets in the future and to move to high frequency (yearly or less) extension and update instead of an ad-hoc production for each CMIP phase.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".