The Effects of Marine Cloud Brightening on Seasonal Polar Temperatures and the Meridional Heat Flux
Bibliographic record
Abstract
Marine cloud brightening (MCB) is one of several proposed solar radiation management (SRM) geoengineering schemes designed to ameliorate some of the undesirable effects of climate change, for example polar ice loss and associated increased sea levels. Satellite measurements over the last 40 years show a general reduction in polar sea ice area and thickness which is attributed to climate change. In our studies, HadGEM1, a fully coupled climate model, is used to predict changes in surface temperatures and ice cover as a result of implementing MCB in a double carbon dioxide concentration atmosphere. The meridional heat flux (MHF) is the mechanism within the earth system for the transport of energy from tropical to polar regions. This poleward transport of heat in a double carbon dioxide atmosphere amplifies the effects in polar regions, where it has a significant impact on both temperatures and ice cover. The results from this work show that MCB is capable of roughly restoring control temperatures and ice cover (where control is defined as 440 ppm carbon dioxide, a predicted 2020 level) in a double carbon dioxide atmosphere scenario. This work presents the first results on the impact of MCB on the MHF and the ability of the MCB scheme to restore the MHF to a control level.
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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) | 0.001 | 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".