Local and Remote Forcing of the Ocean by the Madden-Julian Oscillation and its Predictability
Bibliographic record
Abstract
The Madden-Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the tropical atmosphere and provides global predictability on timescales that bridge the gap between weather and climate. The influence of the MJO on the ocean is explored with a combination of statistical analysis of observations using multivariate time series techniques, dynamical theory, and general circulation models with realistic forcing and bathymetry.\nThe MJO is shown to have a significant and predictable influence on global sea level. Three main regions of influence are identified: (i) the equatorial Pacific and the west coast of the Americas, (ii) the Gulf of of Carpentaria, and (iii) the northeastern Indian Ocean. In the equatorial Pacific, equatorially trapped Kelvin waves are forced by MJO-related surface winds in the western Pacific and propagate eastward. These remotely forced waves then transform into coastal trapped waves that propagate poleward along the west coast of the Americas (consistent with previous work). By way of contrast, in the Gulf of Carpentaria it is shown that the connection with the MJO is due to local wind forcing through simple set-up of sea level. In the northeastern Indian Ocean, a complex sea level pattern involving equatorially trapped Kelvin waves, coastal trapped waves along Sumatra, Java and the Bay of Bengal, and reflected Rossby waves along 5.5$^\\circ$N is shown to be caused by a combination of local and remote forcing by MJO-related surface winds.\n\nTo examine the predictability of the MJO, and the stability of MJO variability on multidecadal time scales, the MJO index is reconstructed over the last century. The reconstructed index is verified by comparing it with independently observed environmental variables. Three predictability time scales are proposed and estimated from the MJO index. A simple forced damped harmonic oscillator model is used to explain the complex relationship amongst the predictability time scales and also gain insight into the predictability of the MJO.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".