Marsico et al. (2026) Modal Interference Drives Madden‐Julian Oscillation Evolution and Predictability

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Geophysical Research Letters
• Year: 2026
• Date: 2026-01-04
• Authors: David H. Marsico, John R. Albers, Matthew Newman, Maria Gehne, Juliana Dias, George N. Kiladis, Emerson LaJoie, Yan Wang
• DOI: 10.1029/2025gl118062

Research Groups

Not specified in abstract.

Short Summary

This study develops a data-driven dynamical filter to characterize Madden-Julian Oscillation (MJO) variability, identifying two intraseasonal atmospheric modes (MJO-fast with a 45-day period and MJO-slow with a 70-day period) whose interference explains MJO progression and extends forecast skill by approximately 7 days in the ECMWF operational model.

Objective

• To characterize Madden-Julian Oscillation (MJO) variability using a data-driven dynamical filter that represents tropical variability with nonorthogonal empirical-dynamical modes.

Study Configuration

• Spatial Scale: Tropical variability, Indian Ocean, Maritime Continent.
• Temporal Scale: Intraseasonal (45-day period for MJO-fast, 70-day period for MJO-slow); forecast skill extended by approximately 7 days.

Methodology and Data

• Models used: Data-driven dynamical filter, ECMWF operational forecast model.
• Data sources: Real-time Multivariate MJO (RMM) index-based variability (implying observational or reanalysis data).

Main Results

• A data-driven dynamical filter was developed to characterize MJO variability using nonorthogonal empirical-dynamical modes.
• Two intraseasonal atmospheric modes were identified: an "MJO-fast" mode with a 45-day period and a newly identified "MJO-slow" mode with a 70-day period.
• These two modes, alongside El Niño-Southern Oscillation modes, explain nearly all observed Real-time Multivariate MJO (RMM) index-based variability.
• The fastest growing and most predictable MJO events are initiated primarily by the MJO-fast mode over the Indian Ocean.
• Subsequent progression of these events across the Maritime Continent results from destructive and then constructive interference of the MJO-fast and MJO-slow modes.
• These identifiable events at forecast initialization time are "forecasts of opportunity" in the ECMWF operational forecast model, extending MJO skill by approximately 7 days compared to other forecasts.

Contributions

• Development of a novel data-driven dynamical filter for characterizing MJO variability.
• Identification of a new "MJO-slow" intraseasonal atmospheric mode with a 70-day period.
• Elucidation of the dynamic role of constructive and destructive interference between MJO-fast and MJO-slow modes in MJO progression.
• Demonstration of "forecasts of opportunity" that extend MJO forecast skill by approximately 7 days in an operational model.

Funding

Not specified in abstract.

Citation

@article{Marsico2026Modal,
  author = {Marsico, David H. and Albers, John R. and Newman, Matthew and Gehne, Maria and Dias, Juliana and Kiladis, George N. and LaJoie, Emerson and Wang, Yan},
  title = {Modal Interference Drives Madden‐Julian Oscillation Evolution and Predictability},
  journal = {Geophysical Research Letters},
  year = {2026},
  doi = {10.1029/2025gl118062},
  url = {https://doi.org/10.1029/2025gl118062}
}