CarbonTracker-CH <sub>4</sub> : an assimilation system for estimating emissions of atmospheric methane
Bibliographic record
Abstract
Abstract. We describe an assimilation system for atmospheric methane (CH4), CarbonTracker-CH4, and demonstrate the diagnostic value of global or zonally averaged CH4 abundances for evaluating the results. We show that CarbonTracker-CH4 is able to simulate the observed zonal average mole fractions and capture inter-annual variability in emissions quite well at high northern latitudes (53–90° N). CarbonTracker-CH4 estimates of total fluxes at high northern latitudes are about 81 Tg CH4 yr−1, about 12 Tg CH4 yr−1 (13%) lower than prior estimates, a result that is consistent with other atmospheric inversions. Emissions from European wetlands are decreased by 30%, a result consistent with previous; however, emissions from wetlands in Boreal Eurasia are increased relative to the prior estimate. Although CarbonTracker-CH4 does not estimate increases in emissions from high northern latitudes for 2000 through 2010, significant inter-annual variability in high northern latitude fluxes is recovered. During the exceptionally warm Arctic summer of 2007, estimated emissions were greater than the decadal average by 4.4 Tg CH4 yr−1. In 2008, temperatures returned to more normal values over Arctic North America while they stayed above normal over Arctic Eurasia. CarbonTracker-CH4 estimates were 2.4 Tg CH4 yr−1 higher than the decadal average, and the anomalous emissions occurred over Arctic Eurasia, suggesting that the data allow discrimination between these two source regions. Also, the emission estimates respond to climate variability without having the system constrained by climate parameters. CarbonTracker-CH4 estimates for temperate latitudes are only slightly increased over prior estimates, but about 10 Tg CH4 yr−1 is redistributed from Asia to North America. We used time invariant prior flux estimates, so for the period from 2000 to 2006, when the growth rate of global atmospheric CH4 was very small, the assimilation does not produce increases in natural or anthropogenic emissions in contrast to bottom-up emission datasets. After 2006, when atmospheric CH4 began its recent increases, CarbonTracker-CH4 allocates some of the increases to anthropogenic emissions at temperate latitudes, and some to tropical wetland emissions. For temperate North America the prior flux increases by about 4 Tg CH4 yr−1 during winter when biogenic emissions are small. Examination of the residuals at some North American observation sites suggests that increased gas and oil exploration may play a role since sites near fossil fuel production are particularly hard for the inversion to fit. The tropics are not currently well resolved by CarbonTracker-CH4 due to sparse observational coverage and a short assimilation window. However, there is a small uncertainty reduction and posterior emissions are about 18% higher than prior estimates. Most of this increase is allocated to tropical South America rather than being distributed among the global tropics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".