Space Weather Analysis Tools

NASA and IBM just released **Surya**, the first open-source heliophysics foundation model—trained on nine years of Solar Dynamics Observatory data (≈218 TB). Why it matters: space weather is not abstract. Solar flares disrupt GPS, aviation, satellites, even power grids. Forecasting them hours ahead can mean billions saved in downtime and risk. What Surya delivers: - Transformer model (366M parameters) built on multi-channel solar imagery - Predicts flares, solar winds, spectral activity, and active region maps - Up to 16% higher accuracy in flare prediction - Two-hour early warnings—an AI radar for the Sun Strategic takeaway: by open-sourcing Surya on Hugging Face and GitHub, NASA and IBM are shifting heliophysics AI from closed science to collaborative infrastructure. It’s not just about astronomy—it’s about **resilience for global tech ecosystems**. AI is often hyped as futuristic. This is present tense: foundation models already protecting the backbone of digital society.

NOW: 𝐇𝐨𝐥𝐞𝐬 𝐢𝐧 𝐒𝐮𝐧'𝐬 𝐂𝐨𝐫𝐨𝐧𝐚. Solar Wind Acceleration. Home telescope sees nothing. Behold in UV light, from satellite, 36K km high—huge dark holes appear. Gusty solar winds. Few days to reach the Earth. Explore: Right now, massive dark holes in the Sun’s corona are accelerating solar wind toward Earth. These winds will take a few days to reach Earth, affecting space weather. The dark holes are not visible in normal light but appear in ultraviolet (EUV) images taken by NASA’s Solar Dynamics Observatory (SDO), a satellite orbiting 36,000 km above Earth. Jeff Bryant uses Wolfram tools to pull real-time data from SDO and process them: 🔴 Wolfram CODE & ARTICLE: https://lnkd.in/enyCbU2D Specifically, Wolfram’s SolarImage function to combine three EUV wavelengths—335, 211, and 193 Å—into a false-color composite that makes coronal holes visible, each wavelength mapped on an RGB channel. I adjusted the color mapping to enhance different details. False color isn’t fake; it reveals structures invisible to the human eye. Also Wolfram SpaceWeatherData can track solar wind speed to monitor changes.

Much like the daily weather forecasts we use to help us arrange our plans, space weather forecasts rely on cutting-edge models for accurate predictions. These physics-based models have been developed to simulate parts of the Sun-to-Earth system, which consist of plasma, magnetic fields and energetic charged particles. “Space weather, akin to Earth's weather, is governed by dynamic phenomena with storms becoming more frequent and severe when the Sun is more active. Solar activity is currently approaching the peak of its approximately 11-year cycle. However, unlike traditional weather, space weather processes are governed by charged particles and induced magnetic fields instead of viscosity and aerodynamic turbulence,” explains Piers Jiggens, the Technical Officer for the activity and part of ESA’s Space Environment and Effects section. A recent advancement funded by GSTP and led by KU Leuven, Belgium, on heliospheric modelling techniques is paving the way for a new system of coupled models for forecasting space weather in more timely and accurate ways, improving our understanding of how storms evolve and preparation for the unpredictable events occurring between the sun and Earth. Initially models are developed in the form of scientific codes but require additional technical development before they can transition for use in operations. As part of the activity three key modelling assets have been matured and refined for operational use, focusing on the region between the Sun and Earth's magnetosphere. The first, named COCONUT, is a cutting-edge magnetohydrodynamic (MHD) model, providing a more advanced and reliable solution for the solar corona. The second model, Icarus, takes the simulation from the solar corona to Earth, using Adaptive Mesh Refinement (AMR) to automatically focus processing power on areas of interest, such as eruptions called Coronal Mass Ejections (CMEs) and the shocks the induce, crucial for real-time forecasting. The third model, PARADISE, simulates high-energy particles accelerated by these coronal mass ejections, enabling the prediction of space storms. One of the challenges the project addressed is the acceleration of particles by CMEs, with a focus on predicting the most energetic particles arriving in radiation storms as these pose the most significant hazard. Coronal mass ejections in extreme cases may propagate to the Earth in less than 24 hours, whilst accelerated particles may arrive in 30 minutes from the time of the solar eruption. The ability to simulate these events quickly is crucial for timely predictions. #ESA #VSWMC #SpaceWeather