A Python Package to Calculate the OLR-Based Index of the Madden-Julian-Oscillation (OMI) in Climate Science and Weather Forecasting. (14th May 2021)

• Record Type: Journal Article
• Authors: Hoffmann, Christoph G.; Kiladis, George N.; Gehne, Maria; von Savigny, Christian
• Is Part Of: Journal of open research software. Volume 9(2021)
• Publication Date: 2021-05-14
• Subjects: Madden-Julian Oscillation -- OLR-based MJO Index -- OMI -- atmosphere -- weather forecasting -- climate -- intraseasonal variation -- Python; Computer software -- Reusability -- Periodicals; Open source software -- Periodicals; 005
• DOI: 10.5334/jors.331
• Languages: English
• ISSNs: 2049-9647

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.