license: cc-by-4.0
pretty_name: Substorm Onset Events (SuperMAG)
language:
- en
description: >-
Magnetospheric substorm onset events from 5 detection algorithms via SuperMAG
(253,319 events, 1975-2024).
task_categories:
- tabular-classification
- time-series-forecasting
tags:
- space
- space-weather
- substorm
- magnetosphere
- aurora
- geomagnetic
- supermag
- open-data
- tabular-data
- parquet
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: data/substorm_onsets.parquet
default: true
Substorm Onset Events (SuperMAG)
Credit: NASA
Part of the Space Weather Datasets collection on Hugging Face.
A consolidated catalog of 253,319 magnetospheric substorm onset events spanning 1975--2024, combining five independent detection algorithms from the SuperMAG collaboration. This is the most comprehensive substorm event list available, enabling multi-algorithm comparison and consensus studies.
Dataset description
Magnetospheric substorms are fundamental space weather events driven by the solar wind's interaction with Earth's magnetic field. During a substorm, magnetic energy stored in the magnetotail is explosively released, accelerating charged particles that stream along field lines into the polar regions. This produces sudden auroral brightenings — the dramatic intensification of the Northern and Southern Lights — along with rapid changes in ground-level magnetic fields detected by magnetometer networks worldwide.
This dataset merges five complementary onset detection methods:
| Source | Events | Detection method |
|---|---|---|
forsyth |
120,069 | SML/SMU expansion-recovery (ground magnetometers) |
newell |
81,914 | SML index (ground magnetometers) |
ohtani |
44,606 | SML bay detection (ground magnetometers) |
frey |
4,191 | IMAGE/FUV auroral imaging (space-based) |
liou |
2,539 | Polar UVI auroral imaging (space-based) |
Ground-based methods (246,589 events) detect substorms through characteristic negative bays in the SML (SuperMAG Lower) index — a measure of the westward auroral electrojet current. Space-based methods (6,730 events) directly observe the initial auroral brightening using ultraviolet imagers aboard the IMAGE and Polar satellites.
Each algorithm has different sensitivity and false-positive rates, so researchers often require onset confirmation across multiple lists. The source column enables filtering by algorithm or finding consensus events where multiple methods agree within a time window.
Schema
| Column | Type | Description |
|---|---|---|
datetime_utc |
datetime | Substorm onset time (UTC) |
mlt_hours |
float64 | Magnetic Local Time of onset (hours, 0-24) |
magnetic_latitude_deg |
float64 | Magnetic latitude of onset (degrees) |
geographic_longitude_deg |
float64 | Geographic longitude of onset (degrees) |
geographic_latitude_deg |
float64 | Geographic latitude of onset (degrees) |
source |
string | Detection algorithm: newell, forsyth, ohtani, frey, liou |
method |
string | Detection method description |
Quick stats
- 253,319 total substorm onset events
- 1975--2024 temporal coverage
- 5 independent detection algorithms
- 246,589 ground magnetometer detections, 6,730 auroral imaging detections
Usage
from datasets import load_dataset
ds = load_dataset("juliensimon/substorm-onsets", split="train")
df = ds.to_pandas()
# Events per algorithm
print(df["source"].value_counts())
# Annual substorm rate by algorithm
import matplotlib.pyplot as plt
df["year"] = df["datetime_utc"].dt.year
df.groupby(["year", "source"]).size().unstack().plot(figsize=(12, 5))
plt.ylabel("Substorm onsets per year")
plt.title("Annual Substorm Rate by Detection Algorithm")
plt.show()
# MLT distribution — substorms peak near midnight
df["mlt_hours"].hist(bins=48, alpha=0.7)
plt.xlabel("Magnetic Local Time (hours)")
plt.ylabel("Count")
plt.title("Substorm Onset MLT Distribution")
plt.show()
# Find consensus events (multiple algorithms within 10 minutes)
from datetime import timedelta
newell = df[df["source"] == "newell"]["datetime_utc"]
ohtani = df[df["source"] == "ohtani"]["datetime_utc"]
Data source
SuperMAG substorm onset lists, provided by the Johns Hopkins University Applied Physics Laboratory:
- Newell & Gjerloev (2011), doi:10.1029/2010JA016141
- Forsyth et al. (2015), doi:10.1002/2015JA021343
- Ohtani & Gjerloev (2020), doi:10.1029/2019JA027680
- Frey et al. (2004), doi:10.1029/2003JA010300
- Liou (2010), doi:10.1016/j.jastp.2009.08.005
Related datasets
- Dst Index — Hourly geomagnetic storm index
- Kp Index — 3-hourly geomagnetic activity
- AE Index — Auroral electrojet indices
- DONKI Space Weather — CMEs, flares, and geomagnetic storms
Pipeline
Source code: juliensimon/space-datasets
Support
If you find this dataset useful, please give it a ❤️ on the dataset page and share feedback in the Community tab! Also consider giving a ⭐ to the space-datasets repo.
Citation
@dataset{substorm_onsets,
author = {Simon, Julien},
title = {Substorm Onset Events (SuperMAG)},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/substorm-onsets},
note = {Consolidated from SuperMAG: Newell, Forsyth, Ohtani, Frey, Liou lists}
}