Accounting for Several Infrared Radiation Processes in Climate Models
Bibliographic record
Abstract
Abstract Three aspects of longwave (LW) radiation processes are investigated using numerical experiments with the Canadian Atmospheric Global Climate Model version 4.3 (CanAM4.3). These are the overlapping LW and shortwave (SW) radiation, scattering by clouds, and specification of ocean emissivity. For the overlapping of solar and infrared spectra, using a single band scheme was compared against a method directly inputting solar energy. Offline calculations show that for high clouds using the single band can cause an overestimate of the downward LW flux, whereas a method that accounts for input solar energy in the LW yields results that are more accurate. Longwave scattering by clouds traps more infrared energy in the atmosphere and reduces the outgoing radiation to space. Simulations with CanAM4.3 show that cloud LW scattering can enhance the LW cooling rate above the tropopause and reduce it inside the troposphere, resulting in warmer temperatures, especially in the tropics and low latitudes. This implies a larger temperature gradient toward the polar region, which causes a strengthening of the Hadley circulation and shifting of the intertropical convergence zone (ITCZ). The increase in lower tropospheric temperature also affects the lower troposphere water vapor and precipitation. Sensitivity to the specification of ocean emissivity is examined by comparing a broadband scheme dependent on the surface wind and solar zenith angle against one that resolves the wavelength dependence. Experiments with CanAM4.3 show that the two oceanic emissivity schemes can produce over 1 W m−2 seasonal mean difference of the upward flux at the surface.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".