The stochastic skeleton model for the Madden-Julian Oscillation with time-dependent observation-based forcing

TL;DR

This study extends the stochastic skeleton model for the Madden-Julian Oscillation by incorporating time-dependent, observation-based forcing functions, improving its ability to replicate key MJO features and analyze the impact of ENSO phases.

Contribution

The paper introduces a version of the stochastic skeleton model with realistic, time-dependent forcing functions, enhancing its realism and analytical capabilities.

Findings

Successfully reproduces MJO lifetime, extent, and amplitude.

Fails to capture MJO seasonality and spatial variations.

Does not reflect ENSO phase-related changes in MJO characteristics.

Abstract

We analyze solutions to the stochastic skeleton model, a minimal nonlinear oscillator model for the Madden-Julian Oscillation (MJO). This model has been recognized for its ability to reproduce several large-scale features of the MJO. In previous studies, the model's forcings were predominantly chosen to be mathematically simple and time-independent. Here, we present solutions to the model with time-dependent observation-based forcing functions. Our results show that the model, with these more realistic forcing functions, successfully replicates key characteristics of MJO events, such as their lifetime, extent, and amplitude, whose statistics agree well with observations. However, we find that the seasonality of MJO events and the spatial variations in the MJO properties are not well reproduced. Having implemented the model in the presence of time-dependent forcings, we can analyze the impact of temporal variability at different time scales. In particular, we study the model's ability to reflect changes in MJO characteristics under the different phases of ENSO. We find that it does not capture differences in studied characteristics of MJO events in response to differences in conditions during El Ni\~no, La Ni\~na, and neutral ENSO.