Changes in poleward atmospheric energy transport over a wide range of climates: Energetic and diffusive perspectives and a priori theories
Bibliographic record
Abstract
The midlatitude poleward atmospheric energy transport increases in radiatively forced simulations of warmed climates across a range of models from comprehensive coupled general circulation models (GCMs) to idealized aquaplanet moist GCMs to diffusive moist energy balance models. These increases have been rationalized from two perspectives. The energetic (or radiative) perspective takes the atmospheric energy budget and decomposes energy flux changes (radiative forcing, feedbacks, or surface fluxes) to determine the energy transport changes required by the budget. The diffusive perspective takes the net effect of atmospheric macroturbulence to be a diffusive energy transport down-gradient, so transport changes can arise from changes in mean energy gradients or turbulent diffusivity. Here, we compare these perspectives in idealized moist, gray-radiation GCM simulations over a wide range of climates. The energetic perspective has a dominant role for radiative forcing in this GCM, with cancellation between the temperature feedback components that account for the GCM'snon-monotonic energy transport changes in response to warming. Comprehensive CMIP5 simulations have similarities in the northern hemisphere to the idealized GCM, though a comprehensive GCM over several CO2 doublings has a distinctly different feedback evolution structure. The diffusive perspective requires a non-constant diffusivity to account for the idealized GCM-simulated changes, with important roles for the eddy velocity, dry static stability, and horizontal energy gradients. Beyond diagnostic analysis, GCM-independent a priori theories for components of the temperature feedback are presented that account for changes without knowledge of a perturbed climate state, suggesting that the energetic perspective is the more parsimonious one.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".