Simulated effects of internal mixing of anthropogenic aerosols on the aerosol–radiation interaction and global temperature
Bibliographic record
Abstract
ABSTRACT A partial internal mixing (PIM) treatment of black carbon (BC), organic carbon (OC), and sulphate was examined, and the core‐shell model was used to represent the internally mixed aerosols with BC as the core and sulphate or OC as the shell. The influences of PIM treatment on the effective radiative forcing due to aerosol–radiative interaction (ERFari) and global temperature were examined and compared to those of external mixing (EM) treatment using an aerosol‐climate online coupled model of BCC_AGCM2.0_CUACE/Aero. Radiative forcing due to aerosol–radiation interaction (RFari) of the anthropogenic aerosols since the preindustrial era was −0.34 W m−2 for EM and −0.23 W m−2 for PIM, respectively. The global annual mean ERFari of anthropogenic aerosols since the preindustrial era was −0.42 W m−2 for EM and −0.34 W m−2 for PIM, respectively. The change in global annual mean surface temperature increased accordingly from −0.18 K in the EM case to −0.125 K in the PIM case. Well geographic consistence between the change in low‐level cloud amount and the change in temperature can be found. The atmospheric temperature in the troposphere was markedly less reduced in the PIM case than in the EM case. The RFari/ERFari for 50% and 100% were −0.11/–0.07 and 0.13/0.14 W m−2, respectively. RFari, ERFari, and surface temperature changed approximately linearly with the internal mixing proportion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".