Seasonal and Interannual Variabilities of the Central Indian Ocean Mode
Bibliographic record
Abstract
The central Indian Ocean (CIO) mode, an intrinsic coupled mode, plays an important role in the intraseasonal variabilities over the Indian monsoon region. Besides the intraseasonal variabilities, the CIO mode also has pronounced seasonal and interannual variabilities. The CIO mode is active during boreal summer but suppressed during boreal winter. The seasonality is mainly attributable to the barotropic instability, which is caused by the large meridional shear of zonal winds. By decomposing the temporal tendency of the meridional gradient of zonal winds, it is found that the zonal wind shear mainly follows the variation of the horizontal eddy flux, which indicates the importance of the multiscale interaction in tropical dynamics. The interannual variability of the CIO mode also depends on the energy transfer associated with the barotropic instability. The influences of El Niño or La Niña and Indian Ocean dipole–zonal mode (IODZM) on the CIO mode are analyzed. El Niño and La Niña have moderate impacts on the CIO mode. El Niño weakens the CIO mode and La Niña strengthens it via the changes in the low-level zonal wind shear. IODZM does not significantly change the amplitude of the CIO mode but can shift its latitudinal position by modifying the meridional shear of the zonal winds. The low-frequency variabilities of the CIO mode at seasonal and interannual time scales unveil the impacts of the background circulations at the intraseasonal variabilities during the Indian summer monsoon in a multiscale framework. While the low-frequency variabilities of this mode will clearly have an implication for monsoon variability and prediction, further studies are needed to quantify the impacts.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".