Symmetric and Antisymmetric Components of Polar-Amplified Warming
Bibliographic record
Abstract
Abstract CO2-forced surface warming in general circulation models (GCMs) is initially polar amplified in the Arctic but not in the Antarctic—a largely hemispherically antisymmetric signal. Nevertheless, we show in CESM1 and 11 LongRunMIP GCMs that the hemispherically symmetric component of global-mean-normalized, zonal-mean warming ( ) under 4 × CO2 changes weakly or becomes modestly more polar amplified from the first decade to near-equilibrium. Conversely, the antisymmetric warming component ( ) weakens with time in all models, modestly in some including FAMOUS, but effectively vanishing in others including CESM1. We explore mechanisms underlying the robust behavior with a diffusive moist energy balance model (MEBM), which given radiative feedback parameter (λ) and ocean heat uptake ( ) fields diagnosed from CESM1 adequately reproduces the CESM1 and fields. In further MEBM simulations perturbing λ and , is sensitive to their symmetric components only, and more to that of λ. A three-box, two-time-scale model fitted to FAMOUS and CESM1 reveals a curiously short Antarctic fast-response time scale in FAMOUS. In additional CESM1 simulations spanning a broader range of forcings, changes modestly across 2–16 × CO2, and in a Pliocene-like simulation is more polar amplified but likewise approximately time invariant. Determining the real-world relevance of these behaviors—which imply that a surprising amount of information about near-equilibrium polar amplification emerges within decades—merits further study.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".