CO emission and export from Asia: an analysis combining complementary satellite measurements (MOPITT, SCIAMACHY and ACE-FTS) with global modeling
Bibliographic record
Abstract
Abstract. This study presents the complementary picture of the pollution outflow provided by several satellite observations of carbon monoxide (CO), based on different observation techniques. This is illustrated by an analysis of the Asian outflow during the spring of 2005, through comparisons with simulations by the LMDz-INCA global chemistry transport model. The CO observations from the MOPITT and SCIAMACHY nadir sounders, which provide vertically integrated information with excellent horizontal sampling, and from the ACE-FTS solar occultation instrument, which has limited spatial coverage but allows the retrieval of vertical profiles, are used. Combining observations from MOPITT (mainly sensitive to the free troposphere) and SCIAMACHY (sensitive to the full column) allows a qualitative evaluation of the boundary layer CO. The model tends to underestimate this residual compared to the observations, suggesting underestimated emissions, especially in eastern Asia. However, a better understanding of the consistency and possible biases between the MOPITT and SCIAMACHY CO is necessary for a quantitative evaluation. Underestimated emissions, and possibly too low lofting and underestimated chemical production in the model, lead to an underestimate of the export to the free troposphere, as highlighted by comparisons with MOPITT and ACE-FTS. Both instruments observe large trans-Pacific transport extending from ~20° N to ~60° N, with high upper tropospheric CO observed by ACE-FTS above the eastern Pacific (with values of up to 300 ppbv around 50° N at 500 hPa and up to ~200 ppbv around 30° N at 300 hPa). The low vertical and horizontal resolutions of the global model do not allow the simulation of the strong enhancements in the observed plumes. However, the transport patterns are well captured, and are mainly attributed to export from eastern Asia, with increasing contributions from South Asia and Indonesia towards the tropics. Additional measurements of C2H2, C2H6 and HCN by ACE-FTS provide further information on the plume history. C2H2 and C2H6 enhancements are well correlated with the CO plumes, indicating common sources and rapid trans-Pacific transport. HCN observations show that the biomass burning contributes mainly at latitudes lower than ~40° N. This study provides a first step towards a full combination of complementary observations, but also highlights the need for a better evaluation of consistency between the datasets in order to allow precise quantitative analyses.
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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 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".