Analysis of IASI tropospheric O <sub>3</sub> data over the Arctic during POLARCAT campaigns in 2008
Bibliographic record
Abstract
Abstract. Ozone data retrieved in the Arctic region from infrared radiance spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp-A European satellite are presented. They are compared with in situ and lidar observations obtained during a series of aircraft measurement campaigns as part of the International Polar Year POLARCAT activities in spring and summer 2008. Different air masses were sampled during the campaigns including clean air, polluted plumes originating from anthropogenic sources, forest fire plumes from the three northern continents, and stratospheric-influenced air masses. The comparison between IASI O3 [0–8 km], [0–12 km] partial columns and profiles with collocated aircraft observations is achieved by taking into account the different sensitivity and geometry of the sounding instruments. A detailed analysis is provided and the agreement is discussed in terms of vertical sensitivity and surface properties at the location of the observations. Overall, IASI O3 profiles are found to be in relatively good agreement with smoothed in situ and lidar profiles in the free troposphere with differences of less than 40% (25% over sea for both seasons) and 10%, respectively. The correlation between IASI O3 retrieved partial columns and the smoothed aircraft partial columns is good with DC-8 in situ data in spring over North America (r = 0.68), and over Greenland with ATR-42 lidar measurements in summer (r = 0.67). Correlations with other data are less significant highlighting the difficulty of IASI to capture precisely the O3 variability in the Arctic upper troposphere and lower stratosphere (UTLS). This is particularly noted in comparison with the [0–12 km] partial columns. The IASI [0–8 km] partial columns display a low negative bias (by less than 26% over snow) compared to columns derived from in situ measurements. Despite the relatively high biases of the IASI retrievals in the Arctic UTLS, our analysis shows that IASI can be used to identify, using O3 / CO ratios, stratospheric intrusions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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 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".