Mesosphere-to-stratosphere descent of odd nitrogen in February–March 2009 after sudden stratospheric warming
Bibliographic record
Abstract
Abstract. We use the 3-D FinROSE chemistry transport model (CTM) and ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations to study the connection between atmospheric dynamics and NOx descent during early 2009 in the northern polar region. We force the model NOx at 80 km poleward of 60° N with ACE-FTS observations and then compare the model results with observations at lower altitudes. Low geomagnetic indices indicate absence of local NOx production in early 2009, which gives a good opportunity to study the effects of atmospheric transport on polar NOx. No in-situ production of NOx by energetic particle precipitation is therefore included. This is the first model study using ECMWF (The European Centre for Medium-Range Weather Forecasts) data up to 80 km and simulating the exceptional winter of 2009 with one of the strongest major sudden stratospheric warmings (SSW). The model results show a strong NOx descent in February–March 2009 from the upper mesosphere to the stratosphere after the major SSW. Both observations and model results suggest an increase of NOx to 150–200 ppb (i.e. by factor of 50) at 65 km due to the descent following the SSW. The model, however, underestimates the amount of NOx around 55 km by 40–60 ppb. The results also show that the chemical loss of NOx was insignificant i.e. NOx was mainly controlled by the dynamics. Both ACE-FTS observations and FinROSE show a decrease of ozone of 20–30% at 30–50 km after mid-February to mid-March. However, these changes are not related to the NOx descent, but are due to activation of the halogen chemistry.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".