Understanding Hadley Cell Expansion versus Contraction: Insights from Simplified Models and Implications for Recent Observations
Bibliographic record
Abstract
Abstract This study seeks a deeper understanding of the causes of Hadley Cell (HC) expansion, as projected under global warming, and HC contraction, as observed under El Niño. Using an idealized general circulation model, the authors show that a thermal forcing applied to a narrow region around the equator produces “El Niño–like” HC contraction, while a forcing with wider meridional extent produces “global warming–like” HC expansion. These circulation responses are sensitive primarily to the thermal forcing’s meridional structure and are less sensitive to its vertical structure. If the thermal forcing is confined to the midlatitudes, the amount of HC expansion is more than three times that of a forcing of comparable amplitude that is spread over the tropics. This finding may be relevant to recently observed trends of rapid tropical widening. The shift of the HC edge is explained using a very simple model in which the transformed Eulerian mean (TEM) circulation acts to diffuse heat meridionally. In this context, the HC edge is defined as the downward maximum of residual vertical velocity in the upper troposphere ; this corresponds well with the conventional Eulerian definition of the HC edge. In response to a positive thermal forcing, there is anomalous diabatic cooling, and hence anomalous TEM descent, on the poleward flank of the thermal forcing. This causes the HC edge () to shift toward the descending anomaly, so that a narrow forcing causes HC contraction and a wide forcing causes HC expansion.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".