Disentangling fast and slow responses of the East Asian summer monsoon to reflecting and absorbing aerosol forcings
Bibliographic record
Abstract
Abstract. We examine the roles of fast and slow responses in shaping the total equilibrium response of the East Asian summer monsoon (EASM) to reflecting (sulfate, SO4) and absorbing (black carbon, BC) aerosol forcings over the industrial era using the Community Earth System Model version 1 (CESM1). Our results show that there is a clear distinction between fast and slow responses of the EASM to aerosol forcings and the slow climate response due to aerosol-induced change in sea surface temperature (SST) plays an important role in the impacts of aerosols on the EASM. The EASM is weakened by a decrease in land–sea surface thermal contrast in the fast response (FR) component to SO4 forcing, whereas the weakening is more intensive due to the changes in tropospheric thermodynamic and dynamic structures in the slow response (SR) component to SO4. The total climate adjustment caused by SO4 is a significant weakening of the EASM and a decrease in precipitation. The BC-induced fast adjustment strengthens the EASM both by increasing the local land–sea surface thermal contrast and shifting the East Asian subtropical jet (EASJ) northwards. The BC-induced slow climate adjustment, however, weakens the EASM through altering the atmospheric temperature and circulation. Consequently, the EASM is slightly enhanced, especially north of 30° N, in the total response (TR) to BC. The spatial patterns of precipitation change over East Asia due to BC are similar in the total response and slow response. This study highlights the importance of ocean response to aerosol forcings in driving the changes of the EASM.
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 | 0.001 | 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 | 0.000 | 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".