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Record W4243059187 · doi:10.5194/essd-2020-56

A Global Space-based Stratospheric Aerosol Climatology (Version2.0): 1979–2018

2020· preprint· en· W4243059187 on OpenAlexafffund
Mahesh Kovilakam, L. W. Thomason, Nicholas Ernest, Landon Rieger, Adam Bourassa, Luis Millán

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Space AgencyScience Mission DirectorateNational Aeronautics and Space Administration
KeywordsStratosphereAerosolEnvironmental scienceAtmospheric sciencesClimatologyClimate modelTroposphereCoupled model intercomparison projectRadiative forcingOzone layerTotal Ozone Mapping SpectrometerAtmospheric chemistryClimate changeMeteorologyOzoneGeographyPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract. A robust stratospheric aerosol climate data record enables the depiction of the radiative forcing of this highly variable component of climate. Since stratospheric aerosol also plays a key role in the chemical processes leading to ozone depletion, stratosphere 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 (WCRP)’s Coupled Model Intercomparison Project Phase 6 (CMIP6) (Zanchettin et al., 2016). This data set is a follow-on to one created as a part of Stratosphere-Troposphere Process and their Role in Climate Project (SPARC)’s Assessment of Stratospheric Aerosol Properties (ASAP) activity(SPARC, 2006) and a data created for 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, and the new release, v2.0. Version 2.0 is focused on improving the post-SAGE II era (after 2005) with the goal to mitigate 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 Optical Spectrograph and InfraRed Imaging System(OSIRIS), the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Lidar Level 3 Stratospheric Aerosol profile monthly product, and the new addition of SAGE III/ISS. Although, the version 7.0 OSIRIS data is substantially improved at its native wavelength of 750 nm, conversion to 525 nm using a constant Angstrom exponent often results in disagreements with SAGEII/ SAGE III/ISS overlap measurements. We, therefore use an observed relationship between OSIRIS extinction at 750 nm and SAGEII/SAGE III/ISS extinction at 525 nm to derive Altitude-Latitude based monthly climatology of Angstrom exponent to compute 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-SAGEII period. Additionally, we incorporate the recently released standard CALIPSO stratospheric aerosol profile monthly product into GloSSAC with an improved conversion technique of 532 nm backscatter coefficient to extinction using an observed relationship between OSIRIS 525 nm extinction and CALIPSO 532 nm backscatter. We also investigate for any cloud contamination in OSIRIS/standard CALIPSO stratospheric aerosol product, which may have caused apparent enhancement in the aerosol extinction particularly in the lower stratosphere. SAGE III/ISS data is 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).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.003

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.

Opus teacher head0.022
GPT teacher head0.234
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2020
Admission routes2
Has abstractyes

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