A Python diagnostics package for evaluation of Madden–Julian Oscillation (MJO) teleconnections in subseasonal-to-seasonal (S2S) forecast systems

Stan, Cristiana; Kollapaneni, Saisri; Jenney, Andrea M.; Wang, Jiabao; Wu, Zheng; Zheng, Cheng; Kim, Hyemi; Garfinkel, Chaim I.; Singh, Ayush

doi:10.5194/gmd-18-7969-2025

i

A Python diagnostics package for evaluation of Madden–Julian Oscillation (MJO) teleconnections in subseasonal-to-seasonal (S2S) forecast systems

2025
By Stan, Cristiana ; Kollapaneni, Saisri ; Jenney, Andrea M. ; ...

[PDF - 12.77 MB ]

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Journal Title:

Geoscientific Model Development
Personal Author:

Stan, Cristiana ; Kollapaneni, Saisri ; Jenney, Andrea M. ; Wang, Jiabao ; Wu, Zheng ; Zheng, Cheng ; Kim, Hyemi ; Garfinkel, Chaim I. ; Singh, Ayush
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; WPO (Weather Program Office)
Description:

The Madden–Julian Oscillation (MJO) teleconnections diagnostics package is an open-source Python software package that provides process-level evaluation of MJO teleconnections predicted by subseasonal-to-seasonal (S2S) forecast systems. The package provides in-depth process level evaluation of both tropospheric and stratospheric pathways defining the atmospheric teleconnections from the tropics to the extratropics on S2S time scales. The analyses include the comparison of a forecast model with a default verification dataset or user-provided verification data. The package consists of a user-friendly graphical user interface (GUI), which allows the package to be applied to both operational and research models. This approach allows for efficient data management and the reproducibility of the analysis.
Keywords:

Madden-Julian Oscillation Python (Computer Program Language) Madden-Julian Oscillation Python (Computer Program Language) Forecast Models Subseasonal-to-seasonal (S2S)
Source:

Geosci. Model Dev., 18, 7969–7985
DOI:

https://doi.org/10.5194/gmd-18-7969-2025
Format:

PDF
Document Type:

Journal Article
Funding:

Grant no. NA22OAR4590216
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:1dd35cc3e68fa526fa3f4a084a47879aea90bf33effb732d1b21d8704373cda5f1f9244402e1fe7285b80bddd89f50ae5054aa28431fcba6c755153303264894
Download URL:

https://repository.library.noaa.gov/view/noaa/73461/noaa_73461_DS1.pdf
File Type:

[PDF - 12.77 MB ]

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