Datasetpublic

ddasilva/probabilistic-solar-wind

Probabilistic Forecasting of the Solar Wind by Data Mining Similar Scenarios (Supplemental Data) This dataset accompanies the paper Post-processing Probabilistic Forecasts of the Solar Wind by Data Mining Similar Scenarios, published in the AGU Journal Space Weather in 2026. It includes the full ADAPT-WSA outputs between 2010-2020 (inclusive) using four maps per day and driven by the GONG network, which is uploaded here because it is too large for Zenodo. Citing… See the full description on the dataset page: https://huggingface.co/datasets/ddasilva/probabilistic-solar-wind.

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face

0likes59downloads

Dataset Card

Probabilistic Forecasting of the Solar Wind by Data Mining Similar Scenarios (Supplemental Data)

This dataset accompanies the paper *Post-processing Probabilistic Forecasts of the Solar Wind by Data Mining Similar Scenarios*, published in the AGU Journal Space Weather in 2026.

It includes the full ADAPT-WSA outputs between 2010-2020 (inclusive) using four maps per day and driven by the GONG network, which is uploaded here because it is too large for Zenodo.

Citing

If you use this dataset, please cite the publication it came from:

@article{https://doi.org/10.1029/2025SW004859,
author = {da Silva, Daniel E. and Parlikar, Yash and Jones, Shaela I. and Arge, Charles N.},
title = {Post-Processing Probabilistic Forecasts of the Solar Wind by Data Mining Similar Scenarios},
journal = {Space Weather},
volume = {24},
number = {4},
pages = {e2025SW004859},
keywords = {solar wind, uncertainty quantification, space weather, potential field, probabilistic forecasting},
doi = {https://doi.org/10.1029/2025SW004859},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025SW004859},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025SW004859},
note = {e2025SW004859 2025SW004859},
year = {2026}
}

WSA FITS File Documentation

WSA FITS files are in the CORONA/ directory.

HDU #0: Arrays over the Sphere

Merged array of shape (10, 90, 180), representing 10 arrays over spherical coordinates. The arrays are:

Array Index	Description
0	Coronal field at outer boundary (nT)
1	Flux tube expansion factor eval. at the source surface
2	Colat. of open field footpoints at photosphere (rad)
3	Long. of open field footpoints (rad) (Take abs. value of Long and add carrLongitude HDU attribute to get correct value)
4	Photospheric Field (G)
5	Dist. from open field footpoint to nearest coronal bndry (deg)
6	Open (1,2,3) and closed (0) regions on the photosphere (1=in-to-out tracing; 2=out-to-in tracing; 3=both)
7	Dist. to current sheet at outer boundary
8	Coronal field at user defined radius (nT)
9	Squashing factor at outer boundary

HDU #1: Arrays over Subsatellite Track +/- 1 Grid Cell

Merged array of shape (8, 3, 180), representing data alond the L1 subsatellite track +/- one grid cell (dimension of 3).The dimension 8 arrays are:

Array Index	Description
0	Coronal field at outer boundary (nT)
1	Flux-tube expansion factor eval. at the source surface
2	Colat. of open field footpoints at photosphere (rad)
3	Long. of open field footpoints at photosphere (rad)
4	Photospheric field (G)
5	Dist. from open field footpoint to nearest coronal bndry (deg)
6	Dist. from subsatellite point to current sheet (deg)
7	Squashing factor eval. at outer boundary

HDU #2: More Arrays over Subsatellite Track

Merged array of shape (4, 180), representing data along the L1 subsatellite track. The dimension 4 arrays are:

Array Index	Description
0	co-lat. of subsatellite track (rad)
1	orbital radius of subsatellite track (AU)
2	julian date of subsatellite track
3	b angles correspond to values when central longs of pixels lie on CM

HDU #3: Coronal Potential Field Source Surface (PFSS) Spherical Harmonic Coefficients

Array of shape (2, 91, 91) representing the G and H spherical harmonic coefficients of the coronal PFSS solution, Schmidt normalized. Because the files were written in fortran, these are upper triangular matrices when read in C array order. We recommend the PySHTools library for working with spherical harmonics in python, including evaluating B vectors at arbitrary points.

HDU #4: Internal Records

This HDU holds internal records and can be ignored.

Contact

Daniel da Silva, daniel.e.dasilva@nasa.gov