Trends in the boreal summer regional Hadley and Walker circulations as expressed in precipitation records from Asia and Africa during the latter half of the 20th century
Bibliographic record
Abstract
Abstract West African summer rainfall, north China summer rainfall and a new climate proxy, snow accumulation from the Dasuopu ice core in the southern Himalaya, have all experienced decreasing trends during the latter half of the 20th century. In this paper, we investigate the existence of a common mechanism that explains these geographically dispersed trends during the boreal summer. In particular, we explore the hypothesis that these trends are related to changes in the regional Hadley and Walker circulations. We show that the divergent circulation in the NCEP reanalysis indicates the existence of trends in these circulations that are consistent with the observed changes in the precipitation records. In addition, the regressions of the divergent circulation in the NCEP reanalysis against these precipitation records indicate that a similar globally coherent signal is associated with the time series and their linear trends while the regressions against the de‐trended residuals do not contain statistically significant large‐scale signals. These similarities lead us to conclude that the decreasing trends in the three precipitation time series during the latter half of the 20th century are consistent with large‐scale changes in the global overturning circulation during the boreal summer. Copyright © 2007 Royal Meteorological Society
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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) | 0.000 | 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 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".