Retrieval of stratospheric NO<sub>2</sub>vertical profiles from ground‐based zenith‐sky DOAS measurements: Results for the MANTRA 1998 field campaign
Bibliographic record
Abstract
The importance of measurements of the vertical distribution of odd nitrogen in studies of ozone chemistry and climate change has long being recognized. In this paper, we use the optimal estimation method developed by Rodgers (1976, 1990) to retrieve NO2 vertical profiles from slant column observations made with a portable ultraviolet (UV)‐visible zenith‐sky spectrometer operated on the ground during the Middle Atmosphere Nitrogen TRend Assessment (MANTRA) balloon campaign carried out at Vanscoy, Saskatchewan, Canada (52°N, 107°W), from 18 to 25 August 1998. Late summer was chosen for the campaign because the stratospheric zonal wind velocity changes sign at that time. Under such conditions the stratospheric winds are at a minimum, leaving the stratosphere in a dynamically quiescent state and closer to photochemical control (Fahey et al., 2001; Fioletov and Shepherd, 2003). The NO2 profile retrieved from the ground‐based observations is compared with the co‐located and simultaneous NO2 profile measured by a balloon‐borne UV‐visible spectrometer during sunrise on 24 August. Good agreement is observed, giving us confidence in the retrieval technique adopted. The retrieved NO2 profiles are also compared with the output of the Model for Evaluating oZONe trends (MEZON) 3D stratospheric chemical transport model. It is observed that, for altitudes below the peak concentration, the model underestimates the NO2 amount, and at the altitude of peak concentration, the model values lie between the values measured from the balloon and those retrieved from the ground‐based measurements. Nevertheless, the model reproduces the general shape of the retrieved profiles, including the altitude of the NO2 maximum, for both sunrise and sunset conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".