A Python Package to Calculate the OLR-Based Index of the Madden- Julian-Oscillation (OMI) in Climate Science and Weather Forecasting

Christoph G Hoffmann,Christian Von Savigny,George N Kiladis,Maria Gehne

doi:10.5334/jors.331

Abstract

The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.

Highlights

The Madden-Julian Oscillation (MJO) is a prominent feature of the Earth’s atmosphere-ocean system with a high relevance for weather, climate and basic atmospheric research
The Madden-Julian Oscillation The MJO was described for the first time by [9] and is characterized by a strong tropical convective rainfall anomaly, which is perceptible as enhanced cloudiness and precipitation
The MJO is primarily observable in these tropical regions, its state has implications for many other locations in the atmosphere, which is still a subject of current research

Summary

Introduction

The Madden-Julian Oscillation (MJO) is a prominent feature of the Earth’s atmosphere-ocean system with a high relevance for weather, climate and basic atmospheric research. The PCA is executed 366 times (including leap days) resulting in 366 pairs of EOFs. The PCs for each particular date are calculated using the EOFs of the corresponding DOY [6].

Results

Conclusion