A multi-source dataset for solar energetic particle forecasting
Abstract
Solar energetic particle (SEP) event forecasting often involves integrating heterogeneous observations that differ in cadence, temporal coverage, format, and historical availability, posing challenges for reproducible analysis of data-driven approaches. This paper presents SEP-PRISM Data, a curated multi-source dataset designed for 24-hour-ahead forecasting of operational SEP events, defined as proton flux exceeding 10 pfu in the GOES > 10 MeV channel. SEP-PRISM Data integrates flare records, active-region magnetic field parameters, coronal mass ejection (CME) catalog data, GOES soft X-ray flux, and historical proton flux into a common window-based representation spanning 3 February 1986 to 10 September 2025. To improve temporal coverage and cross-source consistency, SHARP and SMARP magnetic products were aligned into a unified SMHARP archive, and CME records from DONKI and CDAW were aligned into a unified CDAWDONKI event set. Predictor variables were summarized over fixed non-overlapping 24-hour historical windows using minimum, mean, and maximum statistics and paired with targets defined over the subsequent 24-hour window, forming a supervised learning dataset. The resulting SEP-PRISM Data contains 14,464 labeled samples, including 650 positive operational SEP cases, and is intended to support reproducible benchmarking, model development, feature analysis, and future studies of space weather forecasting.
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BibTeX
@misc{yu2026multisource,
title = {{A multi-source dataset for solar energetic particle forecasting}},
author = {Yian Yu and Yang Chen and Lulu Zhao and Kathryn Whitman and Ward Manchester and Tamas Gombosi},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2607.16160},
eprint = {2607.16160},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2607.16160},
}
RIS
TY - UNPB
TI - A multi-source dataset for solar energetic particle forecasting
AU - Yian Yu
AU - Yang Chen
AU - Lulu Zhao
AU - Kathryn Whitman
AU - Ward Manchester
AU - Tamas Gombosi
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2607.16160
UR - https://arxiv.org/abs/2607.16160
AB - Solar energetic particle (SEP) event forecasting often involves integrating heterogeneous observations that differ in cadence, temporal coverage, format, and historical availability, posing challenges for reproducible analysis of data-driven approaches. This paper presents SEP-PRISM Data, a curated multi-source dataset designed for 24-hour-ahead forecasting of operational SEP events, defined as proton flux exceeding 10 pfu in the GOES > 10 MeV channel. SEP-PRISM Data integrates flare records, active-region magnetic field parameters, coronal mass ejection (CME) catalog data, GOES soft X-ray flux, and historical proton flux into a common window-based representation spanning 3 February 1986 to 10 September 2025. To improve temporal coverage and cross-source consistency, SHARP and SMARP magnetic products were aligned into a unified SMHARP archive, and CME records from DONKI and CDAW were aligned into a unified CDAWDONKI event set. Predictor variables were summarized over fixed non-overlapping 24-hour historical windows using minimum, mean, and maximum statistics and paired with targets defined over the subsequent 24-hour window, forming a supervised learning dataset. The resulting SEP-PRISM Data contains 14,464 labeled samples, including 650 positive operational SEP cases, and is intended to support reproducible benchmarking, model development, feature analysis, and future studies of space weather forecasting.
ER -