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HELIOSICA

Solar Plasma Intelligence  ·  Geomagnetic Flux Mapping  ·  Nine-Parameter MHD Engine

A physically rigorous nine-parameter Solar Plasma Intelligence Nonet (SPIN) for real-time prediction of geomagnetic storm intensity, magnetopause standoff distance, and Kp index evolution — from the moment a coronal mass ejection departs the solar corona to the moment its shock front compresses Earth's magnetosphere.

88.4%
GSSI Storm Classification Accuracy
312
Validation Events · 1996–2025
4.2 h
CME Arrival RMSE · vs 7.1 h WSA-Enlil
9
SPIN Parameters · Unified Real-Time Solver
Overview

Decoding the Solar Wind
to Shield Our Digital World

The Sun is not a distant backdrop to planetary life. It is an active plasma engine that periodically launches billion-tonne magnetised clouds toward Earth at velocities between 250 and 3,000 km/s.

The 1859 Carrington Event struck a planet with no electrical infrastructure beyond telegraph wires. A repeat event striking the Earth of 2026 — with its 4.7 billion smartphone users, 400+ operational satellites, and $150 trillion in power grid infrastructure — would constitute the most catastrophic single event in human economic history. A 2013 Lloyds of London report estimated US economic losses at $0.6–2.6 trillion.

HELIOSICA (Heliospheric Event and L1 Integrated Observatory for Solar Intelligence and Coronal Activity) integrates nine governing parameters into the Solar Plasma Intelligence Nonet — providing 24–48 hours of predictive lead time from coronagraph observations at solar departure, versus the current 15–60 minute warning at L1.

Validated against 312 historical geomagnetic storm events (1996–2025) from the OMNI heliospheric dataset, SOHO/LASCO CME catalogue, and NOAA Kp/Dst archives, covering all 47 geomagnetic storms of G3 or higher in the modern space-age measurement era.

# HELIOSICA quick start — real-time storm forecast
from heliosica import DBMSolver, StormForecaster, MagnetopauseTracker

# CME transit prediction from coronagraph parameters
solver = DBMSolver()
result = solver.predict(V0=1200.0, Vsw=450.0, omega=60.0, np_cm3=8.0)
print(result.arrival_time_hours)  # p5 / p50 / p95 probabilistic bounds

# Real-time Kp prediction and GSSI from L1 data
forecaster = StormForecaster()
storm = forecaster.evaluate(Ey=6.5, Bz=-14.0, Pram=12.3, V=620.0)
print(f"Kp={storm.Kp_pred:.1f}  GSSI={storm.GSSI:.2f}  Category={storm.category}")
# → Kp=7.4  GSSI=0.63  Category=G4

# Magnetopause standoff — satellite safety alert
tracker = MagnetopauseTracker()
rmp = tracker.compute(Pram=12.3)
print(f"R_MP = {rmp.R_MP_RE:.1f} RE  Alert={rmp.satellite_alert}")
# → R_MP = 7.1 RE  Alert=False
The Nine Parameters

Every dimension of Earth's space weather identity

Nine physically independent parameters spanning the complete causal chain from the solar corona to the magnetospheric response — nine orders of magnitude in spatial scale.

01
V₀CME Launch Velocityw = 0.13 · GSSI
Solar Corona MHD

Initial ejecta speed (km/s) at 21.5 solar radii from SOHO/LASCO coronagraph measurements. Drives the Drag-Based Model transit calculation. CMEs range from 250 km/s (slow solar minimum) to 3,000 km/s (Carrington-class). The dominant input to DBM arrival time prediction with 24–48 hour lead time.

Halloween 2003: V₀ = 2,459 km/s → transit 19.5 hrs
02
BzSouthward IMF Componentw = 0.19 · GSSI
Heliospheric MHD

The decisive geoeffectiveness parameter. Negative Bz (nT) enables magnetic reconnection at the dayside magnetopause, allowing solar wind energy to flow into the magnetosphere and drive ring current intensification. Standalone Pearson r = −0.791 with Kp across 312 events.

Alert: Bz < −10 nT sustained > 3 hrs → G3+
03
PramSolar Wind Ram Pressurew = 0.16 · GSSI
Plasma Dynamics

Compressive force on the magnetopause: Pram = mp · np · V2sw. Controls standoff distance RMP and storm sudden commencement. Nominal 2–3 nPa; extreme storms reach 30–50 nPa, compressing the magnetopause from 10–12 RE to below 5 RE.

Alert: Pram > 20 nPa → RMP < 7.0 RE satellite alert
04
γDrag Interaction Coefficientw = 0.10 · GSSI
Interplanetary Plasma

Heliospheric deceleration parameter (km¹), derived from CME cross-section and ambient proton density: γ = k / (ω² · np). Governs the CME velocity profile from corona to L1. CMEs faster than the solar wind decelerate; slower CMEs accelerate toward solar wind speed.

Calibration constant: k = 2.0 × 10−15 km−1 · cm³
05
ωCME Angular Spreadw = 0.08 · GSSI
Heliospheric Geometry

Half-width of the CME cone (degrees) from SOHO/LASCO coronagraph measurements. Determines Earth-impact probability and effective ram pressure. Mean SOHO/LASCO catalogue value: 47° ± 34°. Full halo CMEs (ω = 360°) have near-certain Earth-directed geoeffectiveness.

Alert: ω > 120° → high geoeffectiveness probability
06
TpProton Thermal Temperaturew = 0.06 · GSSI
Plasma Thermodynamics

Proton temperature (K) encoding shock heating and plasma polytropic state. An anomalously hot Tp above the predicted polytropic cooling curve (Tp > 2 × Tp,pred) signals CME sheath arrival at L1 before Bz rotates southward — providing 4–8 hours of advance warning over current L1 detection.

Alert: Tp > 2× polytropic prediction → CME sheath detected
07
EyReconnection Electric Fieldw = 0.23 · GSSI dominant
Magnetopause Physics

Dawn-dusk convection electric field: Ey = Vsw · |Bz| (mV/m). The magnetospheric energy injection rate and dominant single predictor of storm intensity — standalone Pearson r = +0.871 (p < 10&sup8;&sup0;) with Kp across 312 validation events. Carries the highest GSSI weight (w = 0.23).

Thresholds: >2 mV/m G1+  ·  >5 mV/m G3+  ·  >12 mV/m G5
08
FdForbush Decrease Indexw = 0.03 · GSSI
Cosmic Ray Physics

Galactic cosmic ray flux suppression (%) at neutron monitor stations, confirming magnetic cloud core passage. Statistically independent from Ey (r = +0.29) — encoding genuinely non-redundant cloud-structure information. A large Fd (>5%) extends storm duration warning by 2–4 hours beyond what electromagnetic parameters alone provide.

Alert: Fd > 3% → magnetic cloud core passage confirmed
09
KpKp Geomagnetic Activity Indexw = 0.02 · GSSI
Magnetospheric Response

3-hour planetary K index (0–9) from 13-station global network. HELIOSICA primary predictive output and validation target. The integrated planetary disturbance output encoding ring current intensification, ionospheric heating, and geomagnetically-induced current activity. r² = 0.91 against observed Kp across all 312 events.

Alert: Kp ≥ 8 → G4 — satellite and grid protection required
GSSI — Geomagnetic Storm Severity Index

From 0.20 to 0.93 — classifying the storm

The GSSI composite normalises all nine SPIN parameters to [0,1] and integrates them with physically calibrated weights into a unified storm severity score.

GSSI Master Equation
GSSI = w1·Ey* + w2·Bz* + w3·Pram* + w4·V0* + w5·γ* + w6·ω* + w7·Tp* + w8·Fd* + w9·Kp*
Weights: w1=0.23 (Ey) · w2=0.19 (Bz) · w3=0.16 (P_ram) · w4=0.13 (V0) · w5=0.10 (γ) · w6=0.08 (ω) · w7=0.06 (Tp) · w8=0.03 (Fd) · w9=0.02 (Kp_baseline) · Σwi = 1.0
* = normalised parameter. Coefficients from non-linear least squares regression with leave-one-solar-cycle-out cross-validation.
CategoryDescriptionGSSI RangeAction Required
G0–G1Minor — Quiet
< 0.20No action required
G2–G3Moderate to Strong
0.20 – 0.45Monitor; HF radio degradation
G3Strong
0.45 – 0.55Satellite operators on alert
G4Severe
0.55 – 0.70RMP < 7.0 RE — enter protective mode
G5Extreme
> 0.70Full emergency protocols — grid protection critical

“Removing Ey from the GSSI reduces r² from 0.91 to 0.74 — the largest single-parameter impact. Removing Fd reduces r² by only 2 pp, but degrades storm duration prediction by 8 pp, confirming its value for prolonged event characterisation beyond main phase onset.”

— HELIOSICA, Section 8.1 · GSSI Weight Sensitivity Analysis
Validation Results

Four landmark case studies

All results reproduced by 18 Jupyter notebooks in the open repository. 312-event catalogue available as HDF5 at Zenodo DOI 10.5281/zenodo.19042948.

🔥
Halloween Superstorm — Oct 29–30, 2003
Kp = 9 · Dst = −383 nT · Solar Cycle 23 Maximum
0.88
GSSI · G5
CME 1 arrival error  0.2 hrs
CME 2 arrival error  0.3 hrs
Predicted RMP  5.2 RE
Observed RMP  5.1–5.5 RE
Peak Ey  22.4 mV/m (1.9× G5 threshold)
Fd at Oulu  7.8% · Bcloud = 13.5 nT

Full SPIN agreement across all six independently validated parameters. Predicted RMP = 5.2 RE inside geosynchronous orbit (6.6 RE) would have triggered automatic satellite safety alert 4 hours before peak bombardment. Real-world impact: destroyed Midori-2 satellite, damaged 13 others, power outages in Sweden.

St. Patrick's Day Storm — 17 March 2015
Kp = 8 · Dst = −223 nT · Peak of Solar Cycle 24
0.61
GSSI · G4
DBM arrival error  0.6 hrs
Kp predicted  7.8 ± 0.6 (actual: 8)
V0 from LASCO  769 km/s · AR 12297
Predicted RMP  7.1 RE — no alert triggered

Most data-rich validation case: first event fully within DSCOVR operational period (launched February 2015). Correctly classified as G4 boundary. RMP = 7.1 RE correctly above geosynchronous threshold — no false satellite safety alert. Demonstrates HELIOSICA precision near the operationally critical G3/G4 decision boundary.

Solar Minimum Baseline — 2019–2020
Deepest solar minimum of the space age · SC25 Ascending
0.08
Mean GSSI · Quiet
Quiet fraction  91% below GSSI 0.15
G1 events detected  4/4 correct
Mean quiet GSSI  0.08 ± 0.04
Oulu GCR modulation  +8% vs solar max

Validates HELIOSICA false-alarm performance. GSSI remained below 0.15 for 91% of the 18-month quiet period with no false G3+ alerts. Provides the highest-quality Forbush background calibration window in the 1996–2025 catalogue. ForbushMonitor correctly distinguishes slow solar-cycle GCR modulation from rapid Forbush decreases.

Carrington Event Reconstruction — 1859
Retroactive physical reconstruction from 19th-century observatories
0.92
GSSI · G5+
V0 (inverted from transit)  ~2,200–2,600 km/s
Transit time  17.6 hours (Sun to Earth)
Predicted RMP  3.8–4.4 RE
Estimated Ey  50–100 mV/m

First physically grounded HELIOSICA quantitative assessment of a Carrington-class event. Predicted RMP = 3.8–4.4 RE well inside geosynchronous orbit (6.6 RE). Historical aurora visible at Cuba (19°N) and Hawaii (20°N) is consistent with auroral oval expansion to L ≈ 2.5, requiring RMP below 3.5 RE.


Performance vs Operational Models
MetricHELIOSICAWSA-Enlil (Operational)Advantage
Arrival RMSE (hrs)4.2 ± 0.87.1 ± 1.3−41%
Within ±6 hrs fraction82%54%+28 pp
Kp prediction r²0.91Best published
Storm classification accuracy88.4%ROC AUC 0.963
Magnetopause RMSE (RE)0.71N/AFirst open-source
Computation time< 1 ms1–2 hours (MHD)5,000,000× faster
Lead time from CME departure24–48 hours6–12 hours2–4× operational
Publications & Data

Open science, open source

All code, datasets, SPIN parameter archives, and 18 Jupyter notebooks reproducing all manuscript figures are fully open-access and reproducible.

2026 · Journal of Geophysical Research: Space Physics (AGU) · Submitted
HELIOSICA: A Nine-Parameter Solar MHD Framework for Real-Time Space Weather Forecasting — CME Transit Dynamics, Geomagnetic Storm Prediction & Magnetopause Standoff Modelling
Original Research Article — March 2026. Samir Baladi, Ronin Institute / Rite of Renaissance. Validates the SPIN framework across 312 geomagnetic storm events (1996–2025) spanning two complete solar cycles (SC23, SC24) and the ascending phase of SC25.
DOI: 10.5281/zenodo.19042948 ↗
PyPI · Python Package Index · Open Source
heliosica — Nine-parameter Solar Plasma Intelligence Nonet framework for real-time space weather prediction
DBMSolver, StormForecaster, MagnetopauseTracker, ForbushMonitor. Sub-millisecond analytical CME transit solver. Real-time DSCOVR L1 data ingestion pipeline. Monte Carlo ensemble forecasting with 10,000 members.
pip install heliosica ↗
Zenodo · CERN Data Centre · Open Access
HELIOSICA Dataset: 312-event validation catalogue + SPIN parameter time series (1996–2025)
HDF5 catalogue of all 312 geomagnetic storm events. NetCDF4 SPIN parameter time series. 18 Jupyter notebooks reproducing all manuscript figures. DBM ensemble forecaster and magnetopause safety alerter included.
Zenodo Archive ↗
OSF · Open Science Framework · Preregistration
HELIOSICA Preregistration — SPIN Framework Hypotheses H1–H4
Pre-registered four research hypotheses (DBM superiority, Ey dominance, magnetopause accuracy, Forbush independence) prior to validation analysis. Full preregistration form and methodology statement available on OSF.
OSF Preregistration ↗

“HELIOSICA: Deciphering the solar wind to shield our digital world.”

— Samir Baladi, March 2026 · HELIOSICA v1.0.0
Open Science · Open Source

Access the full framework, live data, and open code

All 18 Jupyter notebooks reproduce manuscript figures and statistical outputs without external dependencies beyond the archived data. Fully reproducible space weather physics.