Dependence of Earth's Thermal Radiation on Five Most Abundant Greenhouse Gases
Bibliographic record
Abstract
The atmospheric temperatures and concentrations of Earth's five most important, greenhouse gases, H$_2$O, CO$_2$, O$_3$, N$_2$O and CH$_4$ control the cloud-free, thermal radiative flux from the Earth to outer space. Over 1/3 million lines having strengths as low as $10^{-27}$ cm of the HITRAN database were used to evaluate the dependence of the forcing on the gas concentrations. For a hypothetical, optically thin atmosphere, where there is negligible saturation of the absorption bands, or interference of one type of greenhouse gas with others, the per-molecule forcings are of order $10^{-22}$ W for H$_2$O, CO$_2$, O$_3$, N$_2$O and CH$_4$. For current atmospheric concentrations, the per-molecule forcings of the abundant greenhouse gases H$_2$O and CO$_2$ are suppressed by four orders of magnitude. The forcings of the less abundant greenhouse gases, O$_3$, N$_2$O and CH$_4$, are also suppressed, but much less so. For current concentrations, the per-molecule forcings are two to three orders of magnitude greater for O$_3$, N$_2$O and CH$_4$, than those of H$_2$O or CO$_2$. Doubling the current concentrations of CO$_2$, N$_2$O or CH$_4$ increases the forcings by a few per cent. These forcing results are close to previously published values even though the calculations did not utilize either a CO$_2$ or H$_2$O continuum. The change in surface temperature due to CO$_2$ doubling is estimated taking into account radiative-convective equilibrium of the atmosphere as well as water feedback for the cases of fixed absolute and relative humidities as well as the effect of using a pseudoadiabatic lapse rate to model the troposphere temperature. Satellite spectral measurements at various latitudes are in excellent quantitative agreement with modelled intensities.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".