PREDSTORM is our real time solar wind forecast. For details, see https://helioforecast.space/solarwind.



The real-time predictions on this site are intended for researchers or research purposes only. Please visit the NOAA Space Weather Prediction Center or the UK Met Office for official government space weather forecasts.

We take no responsibility or liability for the frequency of provision or accuracy of our forecasts, and we will not be liable for any losses and damages in connection with using the provided information.

Our research program currently covers these topics:

Magnetic structure of Coronal Mass Ejections (CMEs)

We are developing 3DCORE, a hyperfast semi-empirical model for flux ropes in coronal mass ejections that can be used for both fitting and forward modeling of multipoint in situ signatures of CME flux ropes. We also work on synthetic model images for comparison to data returned by coronagraphs and heliospheric imagers. [Möstl+ 2020] [Weiss+ 2021a] [Davies+ 2021] [Weiss+ 2021b] [Forstner+ 2021] [Palmerio+ 2021] [Möstl+ 2022] [Weiss+ 2022]

Missions: Wind, DSCOVR, STEREO, BepiColombo, Parker Solar Probe, Solar Orbiter, Venus Express, MESSENGER, MAVEN. Future: PUNCH, SWFO-L1, Vigil, interplanetary CubeSats.

Heliospheric Imaging

We advance innovative methods to use imaging of the solar wind to better predict the arrival time and speed of CMEs at Earth and other planets. Our ELEvoHI model is the state of the art method in fitting time-elongation tracks of CMEs to model their interplanetary evolution. [Amerstorfer+ 2018] [Barnes+ 2020] [Amerstorfer+ 2021] [Hinterreiter+ 2021a] [Bauer+ 2021] [Hinterreiter+ 2021b] [Barnard+ 2022]

Missions: STEREO (SECCHI). Soon: Solar Orbiter (SolOHI), Parker Solar Probe (WISPR). Future: PUNCH, Vigil.

Solar wind modeling

Another hyperfast modeling approach, the Wang-Sheeley-Arge (WSA) / Tunable Heliospheric Upwind eXtrapolation (THUX) model is developed in order to provide ambient solar wind solutions. We employ WSA/THUX for modeling corotating interaction regions (CIRs) and as the ambient wind feeding into our CME evolution models. With WSA/THUX we investigate open physics questions, for example how coronal holes are connected to CIR properties, or the propagation of uncertainties in the solar initial conditions to 1 AU. [Reiss+ 2019] [Reiss+ 2020] [Reiss+ 2021a] [Reiss+ 2022]

Missions: Wind, DSCOVR, STEREO, Parker Solar Probe, Solar Orbiter. Future: SWFO-L1, Vigil, interplanetary CubeSats.

Real time solar wind prediction

A major unsolved problem in space weather forecasting concerns the prediction of the southward pointing magnetic fields in CMEs and CIRs that lead to geomagnetic storms, known as the Bz problem. We conduct research into how solar wind data provided by spacecraft at the Sun-Earth L1 point can be used for permanently updating the solar wind models to provide a feasible solution to the Bz problem. We additionally provide forecasts of Dst, GIC, Newell coupling and aurora based on those solar wind predictions, to understand how the errors in the solar wind forecasts propagate into geospace. We also use advanced verification methods and machine learning to optimize the physical modeling. [Bailey+ 2020] [Bailey+ 2021] [Reiss+ 2021b]

Missions: DSCOVR, Wind, STEREO. Future: SWFO-L1, SMILE, Vigil, interplanetary CubeSats.

Geomagnetically induced currents (GICs)

In collaboration with the Austrian meteorological institute ZAMG and the Technical University Graz we work on the prediction of GICs in the Austrian power grid. GICs have long been known to affect power grids, transformers and any earthed conductive networks spanning large distances. We use machine learning approaches to map L1 solar wind nowcasts and forecasts to GICs. [Bailey+ 2018] [Bailey+ 2022]

Missions: DSCOVR, Wind, STEREO. Future: SWFO-L1, Vigil.

Exoplanetary space weather

The Solar System is the only stellar and planetary environment in which we can study how stellar eruptions influence various types of planetary atmospheres in great detail. These results can be used as proxies for other stars and their exoplanets. We have provided general parameters of solar eruptions for atmospheric loss modeling of Hot Jupiters. [Bisikalo+ 2018a] [Bisikalo+ 2018b] [Cherenkov+ 2019]

Please see the publications page for all team publications since 2018.

We are collaborating with many international teams, among them the Rutherford Appleton Laboratory (UK), the University of New Hampshire, the NASA Goddard Space Flight Center, the University of California in Berkeley, Predictive Science San Diego, and the University of Reading (UK).

Our research is covered frequently by national and international media. [AGU Eos: 11 Discoveries Awaiting Us at Solar Max] [ESA: The Sun as you’ve never seen it before - tracking space weather] [Warum gibt es gerade so viele Sonnenstürme?] [Using AI to Predict the Danger of Solar Storms for Earth] [Sonnenstürme: EU-Förderung für Grazer Forscher] [2 Millionen Euro gehen an Grazer für Erforschung von Sonnenstürmen] [ERC-Grants gehen an zehn in Österreich tätige Forschende] [Podcast: Science Call: Wie Sonnenstürme Satelliten zerstören können] [Wie gefährliche Sonnenstürme frühzeitig erkannt werden können] [Künstliche Intelligenz prognostiziert die Gefahr von Sonnenstürmen für die Erde] [How a rather mundane space storm knocked out 40 SpaceX satellites] [Der Sonnensturm, der 40 Satelliten vom Himmel holte] [Wie man die Intensität des Sonnenwindes misst] [Grazer Frühwarnsystem für Sonnenstürme] [Sonnenstürme: Künstliche Intelligenz soll Prognose verbessern] [Weltraumwetter gibt Rätsel auf] [Die Geheimnisse der Sonne] [Forscher rechnen mit mehr Sonnenstürmen] [Wie sich ein katastrophaler Asteroideneinschlag abwenden ließe] [Planetenkiller: warum Asteroiden hauptsächlich im Film einschlagen] [Prognose: Bis zu fünf Sonnenstürme könnten pro Monat die Erde treffen] [Wie man in den nächsten Jahren auf außerirdisches Leben stoßen könnte] [Wenn die Sonne den Strom abdreht]

With Helio4Cast we strive to bridge the gap between basic research and real-time space weather forecasts. We work on a better physical understanding and modeling of the evolution of solar storms and high-speed solar wind streams, and how these fundamental results may enhance real-time space weather forecasts.

We focus on a combination of numerical and empirical techniques, leading to hyperfast models, which are further optimized with parallel computation. The advantage of this approach is that in physical modeling, we can apply ensemble simulations to cover the full parameter space. In real-time modeling, the same simulations are fast enough to be actually applicable in real-time.

In this way we are also able to couple our models from the coronal magnetic field to the solar wind including CMEs with effects at Earth, such as the aurora and geomagnetically induced currents.