No significant increase in long‐term CH<sub>4</sub> emissions on North Slope of Alaska despite significant increase in air temperature
Bibliographic record
Abstract
Abstract Continuous measurements of atmospheric methane (CH4) mole fractions measured by NOAA's Global Greenhouse Gas Reference Network in Barrow, AK (BRW), show strong enhancements above background values when winds come from the land sector from July to December from 1986 to 2015, indicating that emissions from arctic tundra continue through autumn and into early winter. Twenty‐nine years of measurements show little change in seasonal mean land sector CH4 enhancements, despite an increase in annual mean temperatures of 1.2 ± 0.8°C/decade (2σ). The record does reveal small increases in CH4 enhancements in November and December after 2010 due to increased late‐season emissions. The lack of significant long‐term trends suggests that more complex biogeochemical processes are counteracting the observed short‐term (monthly) temperature sensitivity of 5.0 ± 3.6 ppb CH4/°C. Our results suggest that even the observed short‐term temperature sensitivity from the Arctic will have little impact on the global atmospheric CH4 budget in the long term if future trajectories evolve with the same temperature sensitivity.
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 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 | 0.000 |
| 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) | 0.002 | 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 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".