Limb–nadir matching using non-coincident NO <sub>2</sub> observations: proof ofconcept and the OMI-minus-OSIRIS prototype product
Bibliographic record
Abstract
Abstract. A variant of the limb–nadir matching technique for deriving tropospheric NO2 columns is presented in which the stratospheric component of the NO2 slant column density (SCD) measured by the Ozone Monitoring Instrument (OMI) is removed using non-coincident profiles from the Optical Spectrograph and InfraRed Imaging System (OSIRIS). In order to correct their mismatch in local time and the diurnal variation of stratospheric NO2, OSIRIS profiles, which were measured just after sunrise, were mapped to the local time of OMI observations using a photochemical box model. Following the profile time adjustment, OSIRIS NO2 stratospheric vertical column densities (VCDs) were calculated. For profiles that did not reach down to the tropopause, VCDs were adjusted using the photochemical model. Using air mass factors from the OMI Standard Product (SP), a new tropospheric NO2 VCD product – referred to as OMI-minus-OSIRIS (OmO) – was generated through limb–nadir matching. To accomplish this, the OMI total SCDs were scaled using correction factors derived from the next-generation SCDs that improve upon the spectral fitting used for the current operational products. One year, 2008, of OmO was generated for 60° S to 60° N and a cursory evaluation was performed. The OmO product was found to capture the main features of tropospheric NO2, including a background value of about 0.3 × 1015 molecules cm−2 over the tropical Pacific and values comparable to the OMI operational products over anthropogenic source areas. While additional study is required, these results suggest that a limb–nadir matching approach is feasible for the removal of stratospheric NO2 measured by a polar orbiter from a nadir-viewing instrument in a geostationary orbit such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) or Sentinel-4.
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 | 0.002 | 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 | 0.001 |
| 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".