Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport
Bibliographic record
Abstract
Atmospheric methane (CH 4 ) concentrations are rising, which are expected to lead to a corresponding increase in the global seasonal cycle amplitude (SCA) – the difference between its seasonal maximum and minimum values. The reaction between CH 4 and its main sink, OH, is dependent on the amount of CH 4 and OH in the atmosphere. The concentration of OH varies seasonally, and due to the increasing burden of CH 4 in the atmosphere, it is expected that the SCA of CH 4 will increase due to the increased removal of CH 4 through a reaction with OH in the atmosphere. Spatially varying changes in the SCA could indicate long-term persistent variations in the seasonal sources and sinks, but such SCA changes have not been investigated. Here we use surface flask measurements and a 3D chemical transport model (TOMCAT) to diagnose changes in the SCA of atmospheric CH 4 between 1995–2020 and attribute the changes regionally to contributions from different sectors. We find that the observed SCA decreased by 4 ppb (7.6 %) in the northern high latitudes (NHLs; 60–90 ∘ N), while the SCA increased globally by 2.5 ppb (6.5 %) during this time period. TOMCAT reproduces the change in the SCA at observation sites across the globe. Therefore, we use it to attribute regions which are contributing to the changes in the NHL SCA, which shows an unexpected change in the SCA that differs from the rest of the world. We find that well-mixed background CH 4 , likely from emissions originating in, and transported from, more southerly latitudes has the largest impact on the decreasing SCA in the NHLs (56.5 % of total contribution to NHLs). In addition to the background CH 4 , recent emissions from Canada, the Middle East, and Europe contribute 16.9 %, 12.1 %, and 8.4 %, respectively, to the total change in the SCA in the NHLs. The remaining contributions are due to changes in emissions and transport from other regions. The three largest regional contributions are driven by increases in summer emissions from the Boreal Plains in Canada, decreases in winter emissions across Europe, and a combination of increases in summer emissions and decreases in winter emissions over the Arabian Peninsula and Caspian Sea in the Middle East. These results highlight that changes in the observed seasonal cycle can be an indicator of changing emission regimes in local and non-local regions, particularly in the NHL, where the change is counterintuitive.
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) | 0.001 | 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".