Relative contribution of transport/surface flux to the seasonal vertical synoptic CO<sub>2</sub> variability in the troposphere over Narita
Bibliographic record
Abstract
Frequent CO2 measurements obtained by commercial aircraft provide a unique, quasi-continuous record of free-tropospheric CO2 variability. Vertically-resolved synoptic-scale fluctuations of CO2 over Narita International Airport (lat 35.8°N, 140.4°E, 43 m above sea-level) were investigated from November 2005 to March 2009, and combined with analyses of results from a transport model simulation for the year 2007 to retrieve information on sources contributing to the observed variability. The synoptic-scale variability of the observed CO2 mixing ratio, represented by the standard deviation (SD) from the fitted curves, increased in the upper troposphere in the spring, with a noticeable increase at all altitudes in the summer. This seasonal/altitudinal change of the observed SD was shown to be statistically significant throughout the observation period, and the model result agreed with the observation except for the underestimation of the summertime SD. Tagged simulations were conducted to evaluate the relative contribution of the regional fluxes to the synoptic-scale variability over Narita. The results indicate that the major contribution to the free troposphere (FT) variability was made by the fluxes in East Asia, while the Japanese fluxes contributed mostly to the variability in the planetary boundary layer (PBL). A sensitivity analysis was performed to evaluate the relative influence of transport and of flux magnitude on the CO2 SD over Narita for 2007. It was found that a change in the surface flux magnitude could affect the altitudinal distribution of the annual SD over Narita as follows: 41 and 3% at 9 km, 61 and 4% at 5 km, 19 and 83% at 0.5 km when the fossil fuel flux from East Asia and Japan was doubled, respectively. These results are qualitative in nature (since SD is a non-linear function of concentration and flux), but do indicate that the CO2 SD over Narita is more sensitive to the fluctuation in the atmospheric transport (synoptic-scale meteorological variability) in the FT, while showing much more sensitivity to the magnitude of local fluxes in the PBL. The results also point to the fact that vertical profiles of atmospheric CO2 variability at the synoptic scale could potentially provide a useful additional constraint in the inversion analysis of regional CO2 fluxes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".