Local and remote atmospheric response to tropical instability waves: A global view from space
Bibliographic record
Abstract
A La Niña took place in the equatorial Pacific in 1999, and strong tropical instability waves (TIWs) developed, causing large meanders of a sea surface temperature (SST) front between the equator and 3°N. High‐resolution satellite measurements are used to describe the variability of SST, surface wind velocity, column‐integrated water vapor, cloud liquid water, and precipitation associated with these strong TIWs in 1999. Coherent ocean‐atmosphere patterns emerge in both the Pacific and Atlantic, revealing rich regional characteristics. In the far eastern Pacific, southeasterly trades strengthen (weaken) over positive (negative) SST anomalies, apparently due to enhanced (reduced) mixing with high‐speed winds aloft. In the central Pacific we find evidence that SST‐induced sea level pressure changes also contribute substantially to wind fluctuations. Similar SST‐wind covariability also exists in the Southern Hemisphere along 2°S, but the wind variability induced by unit SST anomaly is much larger than that north of the equator. In the central Pacific where the equatorial front is broad, the northern SST pattern has a large meridional scale and reaches as far north as 6°N. Further to the north in the Intertropical Convergence Zone (ITCZ) where local SST anomalies are small, significant variability is found in clouds and precipitation, which is further correlated with surface wind convergence. In the Atlantic, TIW signals in SST are strongly trapped near the equator, but they induce significant remote response in the ITCZ, which takes a more southern position than its Pacific counterpart and thus more susceptible to TIW influence.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".