Response of the current climate to land-ocean contrasts in parameterized cumulus entrainment
Bibliographic record
Abstract
Cumulus entrainment substantially regulates the earth’s climate but remains poorly constrained in global climate models. Recent studies have shown that cumulus bulk entrainment (or dilution) is particularly sensitive to continentality, with the entrainment rate in simulated maritime cumuli nearly double that of continental cumuli. The present study examines the impacts of such land–ocean entrainment contrasts on the current climate using 21-year simulations with the Geophysical Fluid Dynamics Laboratory’s (GFDL) High-Resolution Atmospheric Model (HIRAM). In response to a 25% reduction in entrainment over land, precipitation over tropical land regions increases by up to 40%. Along with directly facilitating enhanced convective precipitation, this entrainment reduction induces a positive soil moisture–precipitation feedback that further enhances convective precipitation over land. A 25% entrainment reduction over the oceans leads to more widespread modifications of convection patterns, with the strongest signal in the tropical Pacific. Deep convection shifts upstream (eastward) there, inducing enhanced large-scale ascent over the central Pacific with compensating subsidence and reduced humidity and precipitation over the western Pacific. Land–ocean variations in entrainment project onto the Pacific Walker circulation, with the 25% land reduction strengthening it by 4% and the 25% ocean reduction weakening it by 14%. These changes are driven by variations in convective and large-scale stratiform heating over the Pacific. While reduced entrainment over land enhances diabatic heating in the Maritime Continent to strengthen the Walker circulation, reduced entrainment over the oceans decreases diabatic heating in the western Pacific to weaken the Walker circulation.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".