Impacts of stratospheric dynamical variability on total inorganic fluorine from observations and models constrained by state-of-the-art reanalyses
Bibliographic record
Abstract
Man-made halogenated compounds emitted from the Earth’s surface ultimately reach the stratosphere where they undergo photolysis, leading to three main fluorine reservoirs: hydrogen fluoride (HF), carbonyl fluoride (COF2) and carbonyl chloride fluoride (COClF). This process is directly influenced by the strength of the mean meridional circulation of the stratosphere, the Brewer-Dobson Circulation (BDC). The BDC is projected to speed-up with the greenhouse gases induced global warming. However, studies have highlighted a multiyear variability in the strength of the BDC resulting in hemispheric asymmetries in observed and modelled trends of age of air and long-lived tracers. Total inorganic fluorine (Fy, the fluorine weighted sum of HF, COF2 and COClF) is used here as a tracer of the stratospheric circulation changes. We perform an analysis and interpretation of Fourier transform infrared (FTIR) multidecadal time-series of HF and COF2 from the Jungfraujoch (Switzerland, 46.55°N) and Lauder (New-Zealand, 45.03°S) stations and from the space-borne Atmospheric Chemistry Experiment - Fourier Transform Spectrometer (ACE-FTS). Indeed, the summation of HF and COF2 is a very good proxy of Fy as we determine, from ACE-FTS and the chemical-transport model (CTM) TOMCAT, that COClF is only accounting for less than 5% of the total Fy budget. The kinematic CTM BASCOE (Belgian assimilation system for chemical observations) is used here to assess the representation of the investigated circulation changes in four state-of-the-art meteorological reanalyses, i.e., ERA-Interim, JRA-55, MERRA and MERRA-2. We also investigate if WACCM4 (Whole Atmosphere Community Climate Model version 4) is able to reproduce these changes through a free-running simulation. The ground-based and satellite FTIR time-series of COF2 show contrasting results over their common time period (2004-2019), with a positive total column trend above the Jungfraujoch, and a non-significant (ground-based) or decreasing trend (ACE-FTS) above Lauder. We find large discrepancies between the BASCOE-CTM simulations, with MERRA-2 inducing overly large simulated Fy total columns which could confirm the weaker tropical upwelling highlighted in previous age of air studies.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".