juliensimon/solar-wind

Real-Time Solar Wind (DSCOVR/ACE)

Credit: NASA

Part of a dataset collection on Hugging Face.

Dataset description

Real-time solar wind plasma and magnetic field measurements from the DSCOVR and ACE spacecraft at the L1 Lagrange point, via NOAA SWPC. Updated daily.

The solar wind is a continuous stream of charged particles flowing from the Sun. Its speed, density, and magnetic field orientation (especially Bz) are the primary drivers of geomagnetic storms. When Bz turns strongly southward (negative), it couples with Earth's magnetosphere and can trigger storms that affect satellites, power grids, and GPS.

This dataset is the missing link in the Sun-to-Earth causal chain: solar flare -> CME -> solar wind -> Dst/Kp storm -> orbital drag.

The measurements come from the DSCOVR (Deep Space Climate Observatory) and ACE (Advanced Composition Explorer) spacecraft orbiting the Sun-Earth L1 Lagrange point, approximately 1.5 million km upstream of Earth. At this vantage point, the instruments sample the solar wind roughly 15-60 minutes before it reaches the magnetopause, providing a critical lead time for geomagnetic storm prediction. DSCOVR's Faraday Cup measures the bulk plasma properties (proton density, speed, and temperature), while its fluxgate magnetometer measures the interplanetary magnetic field (IMF) vector in Geocentric Solar Magnetospheric (GSM) coordinates.

The Bz component of the IMF in GSM coordinates is the single most important parameter for geomagnetic coupling. When Bz is strongly southward (negative), the IMF opposes Earth's northward magnetic field at the dayside magnetopause, enabling magnetic reconnection that transfers solar wind energy into the magnetosphere. Sustained Bz below -10 nT typically produces moderate geomagnetic storms (Kp 6-7, Dst below -100 nT), while extreme events with Bz below -30 nT can trigger severe storms affecting power grids and satellite operations.

Typical quiet-time solar wind conditions show speeds of 300-450 km/s and densities of 3-10 protons/cm^3. Coronal hole high-speed streams elevate speeds to 600-800 km/s, while interplanetary CMEs can drive transient speeds above 1,000 km/s with enhanced magnetic fields.

This dataset is suitable for time-series forecasting, tabular regression tasks.

Schema

Column	Type	Description	Sample	Null %
time_tag	datetime64[ns]	Measurement timestamp from DSCOVR/ACE at the L1 Lagrange point (UTC, ~1-minute cadence)	2026-03-17 08:31:00	0.0%
density	float64	Solar wind proton number density in protons/cm3; typical quiet-time range 3-10 p/cm3; high density combined with high speed increases dynamic pressure, compressing the magnetosphere	0.38	2.9%
speed	float64	Solar wind bulk velocity in km/s; typical 350-800 km/s; coronal hole streams reach 600-800 km/s; CME-driven shocks can exceed 1500 km/s	467.8	3.4%
temperature	float64	Solar wind proton temperature in Kelvin; typical 10^5 K; abnormally low values (10^4 K) suggest passage of a magnetic cloud	57895.0	3.5%
bt	float64	Total IMF magnitude in nT — sqrt(Bx^2 + By^2 + Bz^2); typical 2-10 nT; elevated during CME passage	4.49	1.9%
bx_gsm	float64	IMF Bx component in Geocentric Solar Magnetospheric (GSM) coordinates in nT; typical range +/-20 nT; sun-Earth direction component	-3.47	1.9%
by_gsm	float64	IMF By component in GSM coordinates in nT; typical range +/-20 nT; controls asymmetric magnetospheric convection and field-aligned currents	2.74	1.9%
bz_gsm	float64	IMF Bz component in GSM coordinates in nT — the primary geomagnetic storm driver; sustained southward (negative) Bz enables dayside magnetic reconnection; < -10 nT drives moderate storms, < -30 nT drives severe storms; typical range +/-20 nT	-0.79	1.9%

Quick stats

• 74,870 readings (2026-03-17 to 2026-05-08)
• Average speed: 453 km/s, max: 858 km/s
• Minimum Bz: -27.9 nT (36,022 southward readings)

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/solar-wind", split="train")
df = ds.to_pandas()

from datasets import load_dataset

ds = load_dataset("juliensimon/solar-wind", split="train")
df = ds.to_pandas()

# Solar wind speed time series
import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6), sharex=True)
ax1.plot(df["time_tag"], df["speed"], linewidth=0.5)
ax1.set_ylabel("Speed (km/s)")
ax1.set_title("Solar Wind Speed")

ax2.plot(df["time_tag"], df["bz_gsm"], linewidth=0.5, color="red")
ax2.axhline(0, color="gray", linestyle="--", alpha=0.5)
ax2.set_ylabel("Bz GSM (nT)")
ax2.set_title("IMF Bz (southward = storm driver)")
plt.tight_layout()
plt.show()

# Bz southward events (storm drivers)
southward = df[df["bz_gsm"] < -5]
print(f"{len(southward)} readings with Bz < -5 nT")

Data source

https://www.swpc.noaa.gov/products/real-time-solar-wind

Update schedule

Daily at 15:00 UTC

Related datasets

• juliensimon/dst-index

• juliensimon/donki-space-weather-events

• juliensimon/solar-flare-events

• juliensimon/space-weather-indices

• juliensimon/ae-index

• juliensimon/celestrak-sw

• juliensimon/donki

If you find this dataset useful, please consider giving it a like on Hugging Face. It helps others discover it.

About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

@dataset{solar_wind,
  title = {Real-Time Solar Wind (DSCOVR/ACE)},
  author = {juliensimon},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/solar-wind},
  publisher = {Hugging Face}
}

License

CC-BY-4.0