Methane Fluxes in the High Northern Latitudes for 2005 - 2013 Estimated Using a Bayesian Atmospheric Inversion
Bibliographic record
Abstract
We present methane (CH4) flux estimates for 2005 to 2013 from a Bayesian inversion focusing on the high northern latitudes (north of 50° N). Our inversion is based on atmospheric transport modelled by the Lagrangian particle dispersion model, FLEXPART, and CH4 observations from 17 in-situ and 5 discrete flask-sampling sites distributed over northern North America and Eurasia. CH4 fluxes are determined at monthly temporal resolution and on a variable grid with maximum resolution of 1° × 1°. Our inversion finds a CH4 source from the high northern latitudes of 82 to 84 Tg y−1, constituting ~15 % of the global total, compared to 64 to 68 Tg y−1 (~12 %) in the prior estimates. For northern North America, we estimate a mean source of 16.6 to 17.9 Tg y−1, which is dominated by fluxes in the Hudson Bay Lowlands (HBL) and western Canada, specifically, the province of Alberta. Our estimate for the HBL, of 2.7 to 3.4 Tg y−1, is close to the prior estimate (which includes wetland fluxes from the land surface model, LPX-Bern) and to other independent inversion estimates. However, our estimate for Alberta, of 5.0 to 5.8 Tg y−1 is significantly higher than the prior (which also includes anthropogenic sources from the EDGAR-4.2FT2010 inventory). Since the fluxes from this region persist throughout the winter, this may signify that the anthropogenic emissions are underestimated. For North Eurasia, we find a mean source of 52.2 to 55.5 Tg y−1, with a strong contribution from fluxes in the Western Siberian Lowlands (WSL) for which we estimate a source of 19.3 to 19.9 Tg y−1. Over the 9-year inversion period, we find significant year-to-year variations in the fluxes, which in North America and, specifically, in the HBL appear to be driven at least in part by soil temperature, while in the WSL, the variability is more dependent on soil moisture. Moreover, we find significant positive trends in the CH4 fluxes in North America of 0.38 to 0.57 Tg y−1 per year, and North Eurasia of 0.76 to 1.09 Tg y−1 per year. In North America, this could be due to an increase in soil temperature, while in North Eurasia, specifically, Russia, the trend is likely due, at least in part, to an increase in anthropogenic sources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".