On the Predictability of Springtime Ozone Depletion Events using the ECCC Global Deterministic Prediction System
Bibliographic record
Abstract
Abstract Ozone depletion events are recurring phenomena in both polar regions, characterized by significant interannual variability. In this study, the Environment and Climate Change Canada (ECCC) Global Deterministic Prediction System is used to investigate the medium-range predictability of ozone and weather throughout the anomalous polar ozone depletion events of 2020. The system includes ozone assimilation and makes use of a prognostic ozone field for the computation of heating rates. The ozone scheme uses simplified photochemical modules to represent the impact of both gas-phase and heterogeneous reactions throughout polar ozone depletion events. The study shows that during the boreal and austral spring seasons, the predictability of the total ozone column exceeds 10 days and is comparable to the predictability of large-scale weather variables. It also demonstrates that over both polar regions, the inclusion of ozone radiative coupling has a significant impact on the temperature and wind distributions throughout the stratosphere. Over Antarctica, the ozone-coupled forecasts are systematically colder at all lead times, which helps eliminate a temperature bias present in the model using climatological ozone. The strength of the polar vortex also increases significantly throughout the lower stratosphere, in better agreement with zonal wind analyses. Over the Arctic, the use of an ozone-interactive model also produces significant changes in the temperature and wind forecasts, but the impact on the quality of the weather forecasts is generally neutral. The study shows the overall benefits of using ozone-coupled models in the highly perturbed springtime conditions of the polar regions. Significance Statement Ozone hole events which occur during springtime over polar regions can be predicted several days ahead using numerical weather prediction (NWP) systems. The ozone decrease associated with such events reduces the absorption of solar radiation, impacting the temperature and wind fields in the lower stratosphere at an altitude of about 15–20 km. This study shows that including this process within an NWP model can improve weather forecasts in the lower stratosphere. The impact of this process has been evaluated during the severe springtime ozone depletion events that took place in both polar regions in 2020. The study demonstrates that over Antarctica, using an ozone-coupled model produces a stronger and colder stratospheric polar vortex in better agreement with temperature and wind analyses. Overall, the study highlights the benefits of using ozone-coupled models in the highly perturbed springtime conditions of the polar regions.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".