Coupling between the North Atlantic subpolar gyre vigor and forest fire activity in northern Scandinavia
Bibliographic record
Abstract
Abstract. The circulation strength of the North Atlantic subpolar gyre varies on a range of timescales, it regulates the northwards oceanic heat transport and influences weather and climate over Scandinavia. We test the hypothesis that persistent atmospheric circulation anomalies favorable for extensive forest fire activity in the northern Scandinavian boreal region are predominantly associated with weaker subpolar gyre strength on subannual timescales. We included both winter and summer drought as important precursors for forest fire occurrence in the boreal region. Three ensemble members of climate model simulations covering the time period 850–2005 AD are considered. Years of widespread and severe drought in northern Scandinavia are identified using the monthly drought code as a summer-drought indicator, and winter drought is identified as the 5th percentile of coldest and driest winters. The statistical significance of anomalous ocean- and atmospheric circulation is tested for these years, both during and prior to the main fire season. Analysis of the ensemble of three simulations did not yield a generalized result, hence the hypothesis cannot be confirmed for subannual timescales. For the three simulations we find respectively that the fire-prone years are associated with subpolar gyre circulation that is on average stronger, weaker or insignificantly changed compared with the mean state. The 5th percentile of most extreme dry and cold winters has a strong relation to the winter North Atlantic oscillation (NAO), but not with the gyre circulation state. We find a number of extremely cold/dry winters occurring during the Little Ice Age (LIA, 16th–19th centuries AD), and infer that winter drought may have played a significant role in promoting forest fire activity at this time. Our results highlight the importance of resolving the past fire seasonality in the northern Scandinavian domain, and developing compound drought indicators for winter and spring.
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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) | 0.000 | 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 | 0.000 |
| 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".