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Phong V V Le1,2, Clément Guilloteau1, Antonios Mamalakis1,3

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Most climate models underestimate the Madden-Julian Oscillation (MJO), a key driver of weather patterns. This study evaluates 20 models, finding they poorly capture MJO

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Area of Science:

  • Climate Science
  • Atmospheric Dynamics
  • Meteorology

Background:

  • The Madden-Julian Oscillation (MJO) is the primary source of intra-seasonal climate variability.
  • MJO significantly influences weather and climate phenomena globally.
  • Accurate MJO representation in climate models is crucial for reliable climate projections.

Purpose of the Study:

  • To assess the skill of 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the MJO.
  • To evaluate models' ability to capture MJO's magnitude, dynamics, and associated precipitation variability.
  • To rank CMIP6 models based on their MJO simulation fidelity.

Main Methods:

  • Wavelet-based spectral Principal Component Analysis (wsPCA) was employed to analyze MJO characteristics.
  • wsPCA allows focusing on specific frequencies and isolating propagative modes.
  • Wasserstein distance was used to compare model-simulated MJO distributions with observational data.

Main Results:

  • Most CMIP6 models substantially underestimate the MJO's contribution to intra-seasonal climate variability.
  • Model simulations show reduced MJO magnitude and altered dynamics compared to observations.
  • Precipitation variability linked to MJO is underestimated in key regions like Amazonia, Southwest Africa, and the Maritime Continent.

Conclusions:

  • Significant deficiencies exist in CMIP6 models' representation of the MJO.
  • Underestimation of MJO's magnitude and precipitation impacts highlights areas for model improvement.
  • This study provides a framework for evaluating and ranking climate models based on MJO simulation skill.