Impact of model errors in convective transport on CO source estimates inferred from MOPITT CO retrievals
Bibliographic record
Abstract
Estimates of surface fluxes of carbon monoxide (CO) inferred from remote sensing observations or free tropospheric trace gas measurements using global chemical transport models can have significant uncertainties because of discrepancies in the vertical transport in the models, which make it challenging to unequivocally relate the observations back to the surface fluxes in the models. The new Measurement of Pollution in the Troposphere (MOPITT) version 5 retrievals provide greater sensitivity to lower tropospheric CO over land relative to the previous versions and are, therefore, useful for evaluating vertical transport in models. We have assimilated the new MOPITT CO retrievals, using the Goddard Earth Observing System (GEOS)‐Chem model, to study the influence of vertical transport errors on inferred CO sources. We compared the source estimates obtained by assimilating the CO profiles, the column amounts, and the surface level retrievals for June–August 2006. The three different inversions produced large differences in the source estimates in regions of convection and strong CO emissions. The inversion using the CO profiles suggested an 85% increase in emissions in India/Southeast Asia, which exacerbated the model bias in the lower and middle troposphere, whereas using the surface level retrievals produced a 37% decrease in Indian/Southeast Asian emissions, which exacerbated the underestimate of CO in the upper troposphere. Globally, the inversion with the surface retrievals suggested a 22% reduction in emissions from the a priori estimate of 161 Tg CO/month (from combustion and the oxidation of biogenic volatile organic compounds), averaged in June–August 2006. The analysis results were validated with independent surface CO measurements from NOAA Global Monitoring Division (GMD) network and upper troposphere CO measurements from the Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrumented Container (CARIBIC). We found that the inversion with the surface retrievals agreed best with surface CO data but produced the largest discrepancy with the CARIBIC aircraft data in the upper troposphere, suggesting the influence of vertical transport errors in the model. Our results show that the comparison of the a posteriori CO distributions obtained from the inversions using the surface and profile retrievals provides a means of characterizing the potential impact of the vertical transport biases on the source estimates and the CO distribution.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".