Radiative forcings for 28 potential Archean greenhouse gases
Bibliographic record
Abstract
Abstract. Despite reduced insolation in the late Archean, evidence suggests a~warm climate which was likely sustained by a stronger greenhouse effect, the so-called faint young sun problem (FYSP). CO2 and CH4 are generally thought to be the mainstays of this enhanced greenhouse, though many other gases have been proposed. We present high accuracy radiative forcings for CO2, CH4, and 26 other gases, performing the radiative transfer calculations at line-by-line resolution and using HITRAN 2012 line data for background pressures of 0.5, 1, and 2 bar of atmospheric N2. For CO2 to resolve the FYSP alone at 2.8 Gyr BP (80% of present solar luminosity), 0.32 bar is needed with 0.5 bar of atmospheric N2, 0.20 bar with 1 bar of atmospheric N2, or 0.11 bar with 2 bar of atmospheric N2. For CH4, we find that near-infrared absorption is much stronger than previously thought, arising from updates to the HITRAN database. CH4 radiative forcing peaks at 10.3, 9, or 8.3 W m−2 for background pressures of 0.5, 1, or 2 bar, likely limiting the utility of CH4 for warming the Archean. For the other 26 HITRAN gases, radiative forcings of up to a few to 10 W m−2 are obtained from concentrations of 0.1–1 ppmv for many gases. For the 20 strongest gases, we calculate the reduction in radiative forcing due to overlap. We also tabulate the modern sources, sinks, concentrations, and lifetimes of these gases and summaries the literature on Archean sources and concentrations. We recommend the forcings provided here be used both as a first reference for which gases are likely good greenhouse gases, and as a standard set of calculations for validation of radiative forcing calculations for the Archean.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".