An energetic perspective on hydrological cycle changes in the Geoengineering Model Intercomparison Project
Bibliographic record
Abstract
Abstract Analysis of surface and atmospheric energy budget responses to CO 2 and solar forcings can be used to reveal mechanisms of change in the hydrological cycle. We apply this energetic perspective to output from 11 fully coupled atmosphere‐ocean general circulation models simulating experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP), which achieves top‐of‐atmosphere energy balance between an abrupt quadrupling of CO 2 from preindustrial levels ( abrupt4xCO2 ) and uniform solar irradiance reduction. We divide the climate system response into a rapid adjustment , in which climate response is due to adjustment of the atmosphere and land surface on short time scales, and a feedback response , in which the climate response is predominantly due to feedback related to global mean temperature changes. Global mean temperature change is small in G1 , so the feedback response is also small. G1 shows a smaller magnitude of land sensible heat flux rapid adjustment than in abrupt4xCO2 and a larger magnitude of latent heat flux adjustment, indicating a greater reduction of evaporation and less land temperature increase than abrupt4xCO2 . The sum of surface flux changes in G1 is small, indicating little ocean heat uptake. Using an energetic perspective to assess precipitation changes, abrupt4xCO2 shows decreased mean evaporative moisture flux and increased moisture convergence, particularly over land. However, most changes in precipitation in G1 are in mean evaporative flux, suggesting that changes in mean circulation are small.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".