Data for Exploring the Relative Contribution of the MJO and ENSO to Midlatitude Subseasonal Predictability

Here we explore the relative contribution of the Madden-Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO) to midlatitude subseasonal predictive skill of upper atmospheric circulation over the North Pacific, using an inherently interpretable neural network applied to pre-industrial control runs of the Community Earth System Model version 2. We find that this interpretable network generally favors the state of ENSO, rather than the MJO, to make correct predictions on a range of subseasonal lead times and predictand averaging windows. Moreover, the predictability of positive circulation anomalies over the North Pacific is comparatively lower than that of their negative counterparts, especially evident when the ENSO state is important. However, when ENSO is in a neutral state, our findings indicate that the MJO provides some predictive information, particularly for positive anomalies. We identify three distinct evolutions of these MJO states, offering fresh insights into opportune forecasting windows for MJO teleconnections.

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  • Will Chapman
    UCAR/NCAR - Climate and Global Dynamics Laboratory

Temporal Range

  • Begin:  0100
    End:  0400


Resource Type dataset
Temporal Range Begin 0100
Temporal Range End 0400
Temporal Resolution N/A
Bounding Box North Lat 90.0
Bounding Box South Lat -90.0
Bounding Box West Long -180.0
Bounding Box East Long 180.0
Spatial Representation N/A
Spatial Resolution 1.0 degree
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Github : Code Repository

Additional Information N/A
Resource Format application/x-netcdf
Standardized Resource Format NetCDF
Asset Size N/A
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Creative Commons Attribution 4.0 International License.

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Software Implementation Language N/A

Resource Support Name Will Chapman
Resource Support Email
Resource Support Organization UCAR/NCAR - Climate and Global Dynamics Laboratory
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Metadata Contact Name GDEX Curator
Metadata Contact Email
Metadata Contact Organization UCAR/NCAR - GDEX

Author Will Chapman
Kirsten Mayer
Publisher UCAR/NCAR - GDEX
Publication Date 2024-02-12
Digital Object Identifier (DOI)
Alternate Identifier N/A
Resource Version N/A
Topic Category N/A
Progress N/A
Metadata Date 2024-03-01T13:31:18-07:00
Metadata Record Identifier edu.ucar.gdex::e60e7fa2-964e-4d21-8e7f-a2964efd21f0
Metadata Language eng; USA
Suggested Citation Will Chapman, Kirsten Mayer. (2024). Data for Exploring the Relative Contribution of the MJO and ENSO to Midlatitude Subseasonal Predictability. UCAR/NCAR - GDEX. Accessed 15 April 2024.

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