Polar amplification: what does the temperature feedback have to do with it?
Bibliographic record
Abstract
Polar amplification is a robust feature of both climate models and observations, yet its causes are still under debate. A surface temperature change attribution method based on top-of-atmosphere energy budget changes shows that the temperature feedback is about as important as the surface albedo feedback in promoting polar amplification. This thesis further examines the role of the temperature feedback --- which can be decomposed into the Planck and lapse rate feedbacks --- in polar amplification using idealized climate models.The Planck feedback is less stabilizing at high latitudes because the temperature dependence of blackbody radiation, given by the Stefan-Boltzmann law, is nonlinear. Hence a cold body needs a larger increase in temperature to reach a given increase in radiation than a warm body. In Chapter 2, I test the role of the Planck feedback by linearizing the Stefan-Boltzmann law in a grey radiation model which makes the Planck feedback latitudinally constant. I find that it does not change the pattern of surface temperature change as the lapse rate feedback, the structure of the forcing, and the convergence of atmospheric energy transport also change. I do, however, show that the nonlinearity of the Stefan-Boltzmann law affects the vertical structure of temperature change through the cold-altitudes-warm-more mechanism.In Chapter 3, I decompose the drivers of polar amplification in an idealized climate model using a single column model and reach a better understanding of what causes the lapse rate change in high latitudes. My surface temperature change attribution method based on a single column model attributes most of the polar surface warming to an increase in longwave absorbers (CO2 and water vapor) in the absence of a polar surface forcing, whereas the atmospheric energy transport convergence preferentially warms the mid-troposphere. The addition of a polar surface forcing increases the total polar warming and reduces the dry component of atmospheric energy transport convergence.In Chapter 4, I investigate the role of the forcing dependence of the high latitude lapse rate feedback on the residual polar warming in solar radiation management scenarios. The high latitude surface temperature change is large given the relatively small input of energy from the CO2 forcing, solar forcing reduction, and reduction in atmospheric energy transport convergence. This is explained by a large lapse rate change: the warming from CO2 is very bottom-heavy, whereas the cooling from insolation and atmospheric energy transport convergence reduction is more vertically uniform.It was previously accepted that the Planck and lapse rate feedback are major contributors to polar amplification. In this thesis, I use a mechanism denial experiment to find that a latitudinally constant Planck feedback does not affect the amount of polar amplification. And, I use a single column model to better understand what shapes the vertical structure of temperature change at high latitudes
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".