Hottovy et al. (2026) Analysis of a simple Madden–Julian Oscillation model using a moisture variable with memory

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

Identification

• Journal: Quarterly Journal of the Royal Meteorological Society
• Year: 2026
• Date: 2026-07-17
• Authors: Scott Hottovy, Steven C. Sherwood
• DOI: 10.1002/qj.70232

Research Groups

• Department of Atmospheric Science, University of California, Los Angeles (UCLA)
• National Center for Atmospheric Research (NCAR)

Short Summary

This study investigates the Madden–Julian oscillation (MJO) modeling using simple models with diverse mechanisms and properties. The authors identify two primary mechanisms that can give realistic frequency and decay rates: feedback mechanisms and an additional prognostic "memory" variable.

Objective

• Investigate the multiscale nature of the MJO and identify key mechanisms for accurate modeling

Study Configuration

• Spatial Scale: Global, with a focus on the Tropics
• Temporal Scale: Intraseasonal (days to weeks)

Methodology and Data

• Models used: Simple convective adjustment models coupled with moisture and dry dynamical cores
• Data sources: Not specified in the abstract

Main Results

• The MJO can be modeled using simple mechanisms, including feedback between precipitation and dry variables or an additional prognostic "memory" variable.
• The memory variable gives a more detailed structure to the MJO model, with reduced temperature perturbations and moisture leading convergence anomalies.
• The additional variable yields a slow westward "memory mode".

Contributions

• This study provides new insights into the mechanisms driving the MJO and identifies key components necessary for accurate modeling.

Funding

• Not specified in the abstract

Citation

@article{Hottovy2026Analysis,
  author = {Hottovy, Scott and Sherwood, Steven C.},
  title = {Analysis of a simple Madden–Julian Oscillation model using a moisture variable with memory},
  journal = {Quarterly Journal of the Royal Meteorological Society},
  year = {2026},
  doi = {10.1002/qj.70232},
  url = {https://doi.org/10.1002/qj.70232}
}