Temporal Variability of the South Asian Monsoon through the Late Quaternary: Results from AGCM and AOGCM Simulations
Bibliographic record
Abstract
Abstract: The South Asian monsoon plays a fundamental role in determining the climatology of India and surrounding countries The Late Quaternary provides an ideal setting in which to study the monsoon’s response to the variety of forcing factors that were slowly changing throughout this time Understanding paleomonsoon variability is a critical step towards predicting how future monsoons will respond to climate change A sequence of atmospheric general circulation model (AGCM) simulations that spans most of the Holocene at 500-year intervals indicates a much stronger and wetter Early Holocene summer monsoon whose maximum jet core was displaced northward by nearly 3 degrees of latitude and which placed the eastern margin of the Thar Desert further west than today by nearly 5 degrees of longitude Simulated climate over India shifted towards drier and less humid conditions in the Mid-Holocene (7,000-6,000 years B P), although both the summer and winter monsoons remained stronger than today in all simulations The gradual decrease in summer monsoon strength from the Mid-Holocene to the present demonstrates the governing role of insolation during this time A second sequence of coupled atmosphere-ocean General Circulation Model simulations is also performed to examine how the monsoon responded at the Last Glacial Maximum (LGM) and during the Early- and Mid-Holocene (9,000 and 6,000 years B P respectively) when simulated ocean temperatures are allowed to change Changes in the coupled model are in accordance with those of the AGCM experiments with the addition that the LGM summer monsoon was much weaker than today Simulated moisture transport into the Himalaya results in a varying spatial pattern of snow accumulation that is in accordance with reconstructions of Himalayan glacier expansion at the LGM and during the Holocene
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".