Understanding Oxygen Photochemistry in CO2-dominated Atmospheres
Bibliographic record
Abstract
The motivation for this work is the weak level of confidence in forecasting the temperature profile for the Martian atmosphere over the aerobraking region. This limitation comes mainly because of a misrepresentation of the atomic oxygen distribution in atmospheric models, which is a result of lack of measurements. One effective way to observe atomic oxygen and temperature remotely in the 50 to 100 km altitude region is through airglow measurements.\n\nThe first part of the thesis involves the development of an airglow model to simulate four O2 emissions: the Herzberg I, Herzberg II, and Chamberlain band systems, as well as the Infrared Atmospheric emission at 1.27 um. The model predictions are compared with available observations from both the Mars and Venus atmospheres to exploit the consistency in the photochemistry of these two CO2-dominated atmospheres. Using composition from 3-D global circulation models of the Mars and Venus atmospheres, simulations are performed with realistic dynamical variations. Previous studies used 1-D photochemical models only. Hence, this novel approach allows in-depth investigation of the influence of dynamics and circulation on the airglow behaviour. A sensitivity study is conducted to understand the impact of the different photochemical parameters available in the literature and to recommend a set of parameters to be used in future model predictions. This approach also provides an understanding of the impact of atmospheric conditions, like temperature, dust load, water concentrations, etc., on the vertical structure of the emissions.\n\nA retrieval algorithm is also developed to perform a partial inversion of the recorded signal to extract the NO airglow emission in the Mars atmosphere from the SPICAM instrument. The method is tested with one year of stellar occultation measurements and validated with observations from SPICAM in a limb-viewing geometry and with airglow model predictions. This work identified and quantified, for the first time, localised variations in the NO nightglow, providing insights into the factors influencing the distribution of the oxygen species other than the general circulation and the photochemistry. The method proved to be a useful tool to build a climatology of the NO emission in the Mars atmosphere.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".