Overview and update of the SPARC Data Initiative: comparison of stratospheric composition measurements from satellite limb sounders
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NOy), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the “golden age” of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 it