A Low-Level Circulation in the Tropics
Bibliographic record
Abstract
Abstract Deep convective tropical systems are strongly convergent in the midtroposphere. Horizontal wind measurements from a variety of rawinsonde arrays in the equatorial Pacific and Caribbean are used to calculate the mean dynamical divergence profiles of large-scale arrays (≥1000 km in diameter) in actively convecting regions. Somewhat surprisingly, the magnitude of the midtropospheric divergence calculated from these arrays is usually small. In principle, the midlevel convergence of deep convective systems could be balanced on larger scales either by a vertical variation in the radiative mass flux of the background clear sky atmosphere, or by a divergence from shallow cumuli. The vertical variation of the clear sky mass flux in the midtroposphere is small, however, so that the offsetting divergence must be supplied by shallow cumuli. On spatial scales of ∼1000 km, the midlevel convergent inflow toward deep convection appears to be internally compensated, or “screened,” by a divergent outflow from surrounding precipitating shallow convection. Deep convective systems do not induce a large-scale inflow of midlevel air toward actively convecting regions from the rest of the tropics, but instead help generate a secondary low-level circulation, in which the net downward mass flux from mesoscale and convective-scale downdrafts is balanced by a net upward mass flux from precipitating shallow cumuli. The existence of this circulation is consistent with observational evidence showing that deep and shallow convection are spatiotemporally coupled on a wide range of both spatial and temporal scales. One of the mechanisms proposed for coupling shallow convection to deep convection is the tendency for deep convection to cool the lower troposphere. The authors use radiosonde temperature profiles and the Tropical Rainfall Measuring Mission (TRMM) 3B42 gridded rainfall product to argue that the distance over which deep convection cools the lower troposphere is approximately 1000 km.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".