Impact of land-water sensitivity contrast on MOPITT retrievals and trends over a coastal city
Bibliographic record
Abstract
Abstract. We compare MOPITT Version 7 (V7) Level 2 (L2) & Level 3 (L3) carbon monoxide (CO) products for the 1° x 1° L3 gridbox containing the coastal city of Halifax, Canada, for the seasons DJF and JJA, and highlight a limitation in the L3 products that has significant consequences for the temporal trends in near-surface CO identified using those data. Because this gridbox straddles the coastline, the MOPITT L3 products are created from the finer spatial resolution L2 products that are retrieved over both land and water, with a greater contribution from retrievals over water because more of the gridbox lies over water than land. We create alternative L3 products for this gridbox by separately averaging the bounded L2 retrievals over land (L3L) and water (L3W) and demonstrate that profile and total column CO (TCO) concentrations, retrieved at the same time, differ depending on whether the retrieval took place over land or water. These differences (ΔRET) are greatest, and most significant, in the lower troposphere (LT), with maximum mean differences of 11.4 % (14.9 ppbv, p = 0.116) at the 900 hPa level in DJF, and 10.8 % (12.4 ppbv, p = 0.005) at the surface profile level in JJA. Retrieved CO concentrations are more similar, on average, in the middle and upper troposphere (MT and UT), although large differences (in excess of 50 %) do infrequently occur. Significant (p
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".