Predictive Science Inc. @predsci

Our POT3D code (buff.ly/QtRzBJc), which is part of SWiG, has been accepted and released as part of the new SPEC CPU 2026 Benchmark suite! More details here: buff.ly/6qmq6lS

While other effects (e.g., electron scattering) must also be accounted for when comparing simulations to in-situ data, these results underline the importance of including surface magnetic flux evolution when investigating magnetic connectivity of the corona and heliosphere.

Lionello et al. developed a method to identify folded field lines in the models, allowing for easy comparison with in-situ strahl statistics. The time-dependent runs agree well with ACE/WIND data, while the steady-state runs contain too little disconnected and folded flux.

🚨 New paper alert! 🚨 PSI's Roberto Lionello led a team (including U of Reading's Matt Owens) to investigate the magnetic connectivity of the corona/heliosphere system under busy (solar maximum) and quiet (solar minimum) conditions. Details below! buff.ly/lBbygiz

3/19 @ 11:20: "Understanding How Small-scale Photospheric Magnetic Fields Influence the Global Solar Corona and Solar Wind" (Cooper Downs, C.L. Evans, D. Schmit, J.A. Linker, V.S. Titov) buff.ly/qdoFp49

3/18 @ 09:45: "Global MHD Modelling of CME Evolution as Context for Multi-Spacecraft Observations" (Erika Palmerio, C. Downs, R.M. Caplan, P. Hess, R.C. Colaninno, A. Sahade, C. Mac Cormack) buff.ly/9o58HJn

Attending the Solar Orbiter workshop? Don't miss our talks! 3/17 @ 10:05: "Comparison of Predicted Solar Polar Fields with Solar Orbiter Observations" (Jon Linker, C. Downs, R. Caplan, J. Turtle, P. Riley, G. Valori, Solar Orbiter PHI Team) buff.ly/AJIjRMe

Key capabilities include: generating ensembles across model parameters; post-processing analysis; a user-friendly front-end wrapper script for space weather applications (oftswa.py); and high performance, with HipFT able to run on NVIDIA, Intel, and AMD GPUs!

OFT contains everything you need to acquire and process data from HMI (MagMAP), generate convective flow profiles (ConFlow), and run the flux transport model (HipFT).

Want to generate full-Sun magnetic maps with a surface flux transport model? Check out PSI's Open-source Flux Transport (OFT): github.com/predsci/oft Read on for details!

Using EUV and magnetic field observations and MHD modeling, the team found large areas around the holes likely contained both open & closed magnetic fields. This area's size could help explain the origin of 75% of the solar wind, & help solve the so-called "open flux problem."

🚨 New paper alert! 🚨 Yuan-Kuen Ko and co-authors (including PSI's Pete Riley and Roberto Lionello) deep dive into two coronal holes to present evidence for a surprisingly thick coronal hole boundary, and its implications for the "slow" solar wind. buff.ly/J7vBHYG

SWiG uses several of our tools (including POT3D and MapFL), to solve for the solar wind and allow field line tracing. The entire ecosystem is purely science-driven and, thanks to SWiG's GPU compatibility, you can get results (including summary plots) in about a minute!

This week, we're showcasing another component of our in-house -- but open source -- suite of modeling tools...the Solar Wind Generator (SWiG)! If you need to rapidly generate WSA-like solar wind outputs, SWiG is a must-have. buff.ly/27eESkx

@carolinevans04 Introducing spherical harmonics to analyze the dominant spatial scales of the magnetic field in each run allowed Caroline to quantify the structure and draw concrete, compelling correlations. This work is part of Caroline's PhD thesis work; more of her fascinating is coming soon!

@carolinevans04 The team also showed that a highly structured surface magnetic field meant that more heat was injected into the corona overall. This is related to the total unsigned flux, as well as changes in flux-tube expansion that attenuates the waves that reflect within coronal loops.

In @carolinevans04, Cooper Downs, and Don Schmit's new #ApJ paper, a series of simulations at increasing resolution uncover the correlation between magnetic complexity and coronal heating. The MAS model acted as a lab to probe difficult-to-observe scales. buff.ly/ls2p29Z

@AGUSpWx Pete and Michal found the #risk varies by a factor of >100 from the strongest to the weakest solar cycles observed over the past ~80 years. Punchline: If the strength of the cycle can be #forecast with accuracy, this variability can be predicted.

🚨📄 New paper alert! 📄🚨 In their new paper published in @AGUSpWx, PSI's Pete Riley and Michal Ben-Nun find that the chances of an extreme #spaceweather event depends strongly on the strength of the #solar cycle. What does this mean? Read on below! buff.ly/aAXGAg2