Total ozone loss during the 2019/20 Arctic winter and comparison to previous years
Bibliographic record
Abstract
The amplitude of ozone depletion in the Arctic is monitored every year since 1990 by comparison between total ozone measurements of SAOZ / NDACC UV-Vis spectrometers deployed in the Arctic and 3-D chemical transport model simulations in which ozone is considered as a passive tracer. When SAOZ measurements are missing for various reasons, lack of sunlight, station closed or instrument failure, they are replaced since 2017 by IASI/Metop overpasses above the station. These measurements in the thermal Infrared are available all year around, at all latitudes even in the polar night. IASI data have been compared to SAOZ and to 3-D CTM REPROBUS and the agreement is better than 3% at the latitude of the polar circle. The method allows determining the evolution of the daily rate of the ozone destruction and the amplitude of the cumulative loss at the end of the winter. The amplitude of the destruction varies between 0-10% in relatively warm and short vortex duration years up to 25-39% in colder and longer ones. Since a strong and large vortex centred at the North Pole, PSCs and activated chlorine are still present at all levels in the lower stratosphere on January 9, 2020, there is a good probability that a significant O3 loss may happen in 2020. But since, as shown by the unprecedented depletion of 39% in 2010/11, the loss depends on the vortex duration, strength and possible re-noxification, it is difficult to predict in advance the amplitude of the cumulative loss at the end of the winter. Shown in this presentation will be the evolution of ozone loss and re-noxification in the Arctic vortex during the winter 2019/20 compared to previous winters and REPROBUS and SLIMCAT CTM simulations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".