Weather Regime Diversity, Transitions, and Trends using Hexagonal Self-Organizing Maps

This repository documents the dataset associated with the preprint:

Weather Regime Diversity, Transitions, and Trends using Hexagonal Self-Organizing Maps
Luke Wichrowski, Jhayron S. Pérez-Carrasquilla, and Maria J. Molina (July 25, 2025)

Preprint (ESS Open Archive): https://doi.org/10.22541/essoar.175346129.95426517/v1 Zenodo record: https://zenodo.org/records/18284214

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Overview

Persistent atmospheric circulation patterns (“weather regimes”) strongly modulate surface weather and extremes. This dataset supports the analyses in the accompanying preprint, which applies a hexagonal self-organizing map (SOM) framework to represent North American weather regimes using 500-hPa geopotential height (Z500) anomalies over 1940–2023.

The preprint introduces:

• A hexagonal SOM lattice designed to reduce geometric artifacts
• A transition-based metric to optimize the SOM for smoother regime-to-regime transitions

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Data source and preprocessing (from the preprint)

The underlying atmospheric data are derived from ERA5 and include daily averages of 500-hPa geopotential height (Z500). The preprint notes that ERA5 was used for its global coverage and long-term record.

Key preprocessing steps reported in the preprint include:

• Domain: North America (20°N–80°N, 180°W–30°W)
• Regridding: ERA5 regridded to a 1° × 1° latitude–longitude grid (nearest-neighbor interpolation)
• Seasonal cycle removal: 60-day centered running mean (by calendar day; 1940-01-01 to 2023-12-31)
• Low-pass filtering: 10-day Fourier low-pass filter to emphasize subseasonal and longer variability
• Detrending: subtract a 3rd-degree polynomial fit to the yearly time series of area-averaged anomalies
• Normalization: divide by a 60-day centered running mean of the standard deviation (area-averaged)

ERA5 access location (as cited in the preprint):
U.S. NSF NCAR Research Data Archive (RDA): https://doi.org/10.5065/D6X34W69

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What’s in this Zenodo record?

This section should reflect the actual files shown on Zenodo (recommended: copy/paste the filenames exactly from the Zenodo “Files” list).

Example structure (edit to match your record):

• Z500Anoms_ERA5.nc — (preprocessed ERA5 500-hPa GPH anomalies)
• Z500Anoms_JRA3Q.nc — (same but for JRA3Q)
• Z500Anoms_NCEP_NCAR.nc — (same but for NCEP/NCAR reanalysis)
• df_labels_nocorrfilt_ERA5.csv — (weather regime assignments)
• df_labels_nocorrfilt_JRA3Q.csv — (same but for JRA3Q)
• df_labels_nocorrfilt_NCEP_NCAR.csv — (same but for NCEP/NCAR reanalysis)
• SOM40.p — (pretrained SOM)

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Recommended citation

Cite the preprint

If you use this dataset, please cite the associated preprint:

Wichrowski, L., Pérez-Carrasquilla, J. S., & Molina, M. J. (2025). Weather Regime Diversity, Transitions, and Trends using Hexagonal Self-Organizing Maps (preprint). ESS Open Archive. https://doi.org/10.22541/essoar.175346129.95426517/v1

Cite the dataset

Please also cite the Zenodo dataset:

Zenodo record: https://zenodo.org/records/18284214
(DOI: https://doi.org/10.5281/zenodo.18284214)

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Software and reproducibility

For full methodological details (SOM configuration, transition metric definition, and regime interpretation), refer to the preprint.