Simulated Operational Testing of the Prototype Implementation of the SOFIE Model: The 2025 Space Weather Prediction Testbed Exercise

The CLEAR Space Weather Center of Excellence’s solar energetic particle (SEP) model, SOlar wind with FIeld lines and Energetic particles (SOFIE), was run and evaluated on-site during the Space Weather Prediction Testbed (SWPT) exercise at the National Oceanic and Atmospheric Administration’s Space Weather Prediction Center (NOAA/SWPC) in May 2025. As a physics-based SEP model, SOFIE simulates the acceleration and transport of energetic particles by the coronal mass ejection (CME)-driven shock in the solar corona and inner heliosphere, and has been validated against historical events. However, questions remain regarding whether a physics-based model, traditionally considered computationally expensive, could meet operational needs. The SWPT exercise offered a valuable opportunity to evaluate SOFIE under simulated operational conditions. On-site interactive feedback from SWPC forecasters, Space Radiation Analysis Group (SRAG) console operators, Community Coordinated Modeling Center (CCMC) personnel, and Moon-to-Mars Space Weather Analysis Office (M2M SWAO) analysts led to significant strategic improvements in the model configuration. The simulation grid was optimized by combining a coarser background grid with higher-resolution regions along the CME path and toward Earth, reducing computational cost without compromising accuracy. In this work, we present the simulated operational performance of SOFIE and its capability to predict SEP fluxes significantly faster than real time. During the SWPT exercise, SOFIE completed a 4-day SEP simulation within 5 hours using 1,000 central processing unit cores, although the earliest SEP forecast was obtained a few hours after CME onset. This marks a milestone in demonstrating SOFIE’s operational usefulness and robustness to support future human space exploration.

💡 Research Summary

The paper reports on the operational testing of the prototype implementation of the SOlar wind with FIeld lines and Energetic particles (SOFIE) model during the 2025 Space Weather Prediction Testbed (SWPT) exercise held at NOAA’s Space Weather Prediction Center (SWPC). SOFIE is a physics‑based solar energetic particle (SEP) model that couples a global solar‑wind background (AWSoM‑R), a coronal mass ejection (CME) generator (EEGGL), and a particle acceleration/transport solver (M‑FLAMP‑A). For the test, the authors selected two well‑documented historical SEP events—10 September 2017 and 4 November 2001—both of which produced strong proton enhancements at Earth.

In the preparatory phase, a steady‑state solar‑wind solution was generated using the GONG synoptic magnetogram, a Po​ynting‑flux parameter tuned to the solar cycle (0.55 MW m⁻² T⁻¹ for 2017, 0.20 MW m⁻² T⁻¹ for 2001), and 1 000 CPU cores on the NASA Pleiades supercomputer. This background run required roughly three hours, demonstrating the need to pre‑compute the ambient wind before an operational event.

During the live exercise, CME parameters (active‑region location, speed, and direction) were extracted from EUV, X‑ray, Hα images and coronagraph data (2650 km s⁻¹ for 2017, 1925 km s⁻¹ for 2001). EEGGL generated a Gibson‑Low flux‑rope CME that was injected into the AWSoM‑R MHD simulation. M‑FLAMP‑A then solved the Parker transport equation along magnetic field lines, using two key free parameters: a seed‑particle scaling factor (1.0 for 2017, 10.0 for 2001) and an upstream mean free path λ₀ = 0.1 au. By adjusting these parameters, the model reproduced the observed SEP peak intensities and timing.

A central operational innovation was the hybrid grid strategy. The authors combined a coarse, block‑adaptive spherical grid for the global solar‑wind background with high‑resolution, block‑adaptive Cartesian sub‑grids focused along the CME trajectory and toward 1 au. This mixed‑resolution approach reduced the total wall‑clock time for a four‑day SEP simulation to under five hours on 1 000 cores, while preserving the fidelity of CME shock arrival times, SEP onset, and peak fluxes.

Real‑time feedback from SWPC forecasters, SRAG console operators, CCMC modelers, and M2M SWAO analysts was incorporated throughout the exercise. Forecasters emphasized rapid provision of CME kinematics and active‑region coordinates; SRAG operators required timely alerts when >10 MeV proton flux exceeded 10 pfu or >100 MeV exceeded 1 pfu. CCMC staff helped standardize input/output formats and automate error logging, while M2M analysts validated the model’s radiation dose predictions for the simulated Artemis II Orion vehicle environment. This collaborative loop shortened data‑pre‑processing and parameter‑tuning cycles, making the model more responsive to operational timelines.

Validation against GOES observations showed that SOFIE captured the essential features of both events: the timing of shock arrival, the rise and decay of 10 MeV and 100 MeV proton fluxes, and the spectral shape of the SEP event. The model’s earliest forecast was produced a few hours after CME onset, which, although not instantaneous, represents a substantial improvement over traditional empirical tools that often lag behind real‑time measurements.

The authors conclude that, despite the historically high computational cost associated with physics‑based SEP modeling, strategic grid optimization, judicious parameter selection, and close integration with operational staff can render such models viable for real‑time space‑weather forecasting. SOFIE’s demonstrated ability to deliver multi‑day SEP forecasts faster than real time positions it as a promising component of the forecasting toolkit for upcoming human deep‑space missions such as Artemis II. Future work will focus on incorporating cross‑field diffusion, expanding the suite of observational inputs (e.g., heliospheric imagers), and deploying the model within a cloud‑based, automated pipeline to further reduce latency and increase robustness.