MJO Diagnostic Tools v1.1: Reassessment and implementation of standard MJO diagnostic tools in Python

Abstract. The Madden–Julian Oscillation (MJO) remains difficult to simulate realistically in atmospheric and coupled models, with model performance being strongly dependent on physical parameterizations and model configurations. A standardized and reproducible diagnostic framework of the MJO is therefore essential for systematic evaluation and model development. A widely used set of MJO diagnostics was developed by the US CLIVAR MJO Working Group in 2009 (MJO-WG09), but its original implementation depends on software and workflows that are no longer readily accessible in modern computing environments.

In this study, we reimplement the MJO-WG09 diagnostics using Python-based analysis libraries. The diagnostics are reconstructed following the published methodology and, where necessary, by examining the original source code to resolve ambiguities. As a result of methodological reassessment, the new implementation differs from the original in aspects such as temporal filtering, statistical testing, and spectral analysis; these differences are documented and discussed. In addition, we introduce a new diagnostic to evaluate the Walker circulation associated with the MJO. The open-source package provides a reproducible foundation for consistent evaluation of MJO simulations across models.