The Global Space-based Stratospheric Aerosol Climatology (version 2.0): 1979–2018
Bibliographic record
Abstract
Abstract. A robust stratospheric aerosol climate data record enables the depiction of the radiative forcing of this highly variable component of climate. In addition to the radiative forcing, stratospheric aerosol also plays a key role in the chemical processes leading to ozone depletion. Therefore, stratospheric aerosol is one of the crucial parameters in understanding climate change in the past and potential changes in the future. As a part of Stratospheric-tropospheric Processes and their Role in Climate (SPARC) Stratospheric Sulfur and its Role in Climate (SSiRC) activity, the Global Space-based Stratospheric Aerosol Climatology (GloSSAC) was created (Thomason et al., 2018) to support the World Climate Research Programme's (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al., 2016). This data set is a follow-on to one created as a part of SPARC's Assessment of Stratospheric Aerosol Properties (ASAP) activity (SPARC, 2006) and a data created for the Chemistry-Climate Model Initiative (CCMI) in 2012 (Eyring and Lamarque, 2012). Herein, we discuss changes to the original release version including those as a part of v1.1 that was released in September 2018 that primarily corrects an error in the conversion of Cryogenic Limb Array Etalon Spectrometer (CLAES) data to Stratospheric Aerosol and Gas Experiment (SAGE) II wavelengths, as well as the new release, v2.0. Version 2.0 is focused on improving the post-SAGE II era (after 2005) with the goal of mitigating elevated aerosol extinction in the lower stratosphere at mid- and high latitudes noted in v1.0 as noted in Thomason et al. (2018). Changes include the use of version 7.0 of the Optical Spectrograph and InfraRed Imaging System (OSIRIS), the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar Level 3 stratospheric aerosol profile monthly product and the new addition of SAGE III/ISS. Here, we use an observed relationship between (i) OSIRIS extinction at 750 nm and (ii) SAGE II and SAGE III/ISS extinction at 525 nm to derive an altitude–latitude-based monthly climatology of Ångström exponent to compute OSIRIS extinction at 525 nm, resulting in a better agreement between OSIRIS and SAGE measurements. We employ a similar approach to convert OSIRIS 750 nm extinction to 1020 nm extinction for the post-SAGE II period. Additionally, we incorporate the recently released standard CALIPSO stratospheric aerosol profile monthly product into GloSSAC with an improved conversion technique of the 532 nm backscatter coefficient to extinction using an observed relationship between OSIRIS 525 nm extinction and CALIPSO 532 nm backscatter. SAGE III/ISS data are also incorporated in GloSSAC to extend the climatology to the present and to test the approach used to correct OSIRIS/CALIPSO data. The GloSSAC v2.0 netCDF file is accessible at https://doi.org/10.5067/glossac-l3-v2.0 (Thomason, 2020).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".