Editorial: Arctic amplification: Feedback process interactions and contributions
Bibliographic record
Abstract
Arctic amplification: Feedback process interactions and contributionsThe Arctic is a system in transition.In recent decades, we have witnessed rapid and unprecedented changes within the Arctic that represent an early warning sign of global climate change.Observed rapid Arctic climate change is considered indicative of a broader phenomenon called Arctic Amplification.Arctic Amplification is most clearly described as greater surface warming in the Arctic relative to the rest of the globe (roughly 2-4 times faster) in response to increased CO 2 and is accompanied by other changes to the Arctic system, most visibly reductions in the snow and ice cover.Despite the early awareness of this fundamental feature of the Arctic for more than 100 years (e.g., Arrhenius 1896), projections of the Arctic climate system response to increased CO 2 are more uncertain than in any other region.The evolution of the Arctic climate, and hence the uncertainty in its projected change, is of great societal relevance.The Arctic system affects the global climate through its influences on sea level, atmosphere and ocean circulation patterns, carbon storage and release, and extreme events.The societal relevance of the uncertainty in the Arctic warming rate is exemplified by considering the 2 ° C Paris Climate Agreement warming target.A 2 ° C global warming, considering present uncertainty levels, results in an Arctic warming range from + 3.5 to + 7.5 ° C. Substantially different degrees of land ice melt and permafrost thaw are expected for a +3.5 vs. a +7.5 ° C warming.Key to reducing this uncertainty in Arctic Amplification is improving our understanding of the processes driving Arctic Amplification.The aim of this Research Topic is to focus research efforts on how local and remote atmosphere, land, ocean, sea ice, and coupled physical processes drive Arctic Amplification.By bringing together current understanding from multiple perspectives in a manner that elucidates the influence of coupled processes, this Research Topic aims to accelerate advances in our understanding of Arctic Amplification and make progress towards reducing uncertainty in climate projections.This Research Topic contains original research and review articles that expand our knowledge of Arctic Amplification.Radiative climate feedback analysis is a key area discussed within this Research Topic as it is a critical tool for understanding Arctic Amplification.Sledd and L'Ecuyer present original research describing the interplay between the sea ice and clouds as it pertains to the ice-albedo feedback.Their findings indicate that not only do clouds influence the magnitude of the ice-albedo feedback, but they also change the ability to detect the emergence of the
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.033 | 0.023 |
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".