Solar Energetic Particles
Solar flares and coronal mass ejections result from sudden releases of magnetic energy built up in active regions that occur near sunspots. These spectacular eruptions can accelerate particles like electrons, protons and heavier ions to high energies.
The solar energetic particles escape into the interplanetary space following the magnetic field embedded in the solar wind. The sudden increases in the particle fluxes observed near Earth can last for several days or even weeks.
The Earth’s magnetic field deflects most of these particles and those that are able to penetrate are mostly absorbed in the atmosphere. There remains a concern for polar flight routes where particles can penetrate the magnetosphere more easily. They can cause damage to avionics, disturb communications and result in an increased absorbed radiation dose for aircrew and passengers. Satellites, spacecraft and astronauts are less protected by Earth’s natural shields and extra caution is required when such eruptions are predicted to happen.
The Advanced Solar Particle Events Casting System (ASPECS) is a tool developed under the ESA activity SEP Advanced Warning System (SAWS). The consortium, led by the National Observatory of Athens, developed two types of forecast modes to determine the expected proton flux time profiles for energies >10 MeV to > 300 MeV.
The forecast mode analyses the magnetic properties of all the active regions that are present on the solar disk and provides the probability for flares and proton events to occur up to 72 hours ahead in time. The nowcast mode provides shorter-term predictions following the observation of solar flares and coronal mass ejections. BIRA-IASB is responsible for the execution of an extensive validation in order to determine the accuracy of the forecasts.
The main goal of the ESA project DEeply uNderstanding Space weathER (DENSER), led by Space Applications Services, is to investigate how space weather forecasts can benefit from machine learning techniques and provide a guideline for future developments.
BIRA-IASB has coordinated an extensive literature review of more than 100 publications describing existing space weather forecast models based on machine learning algorithms. The Space Weather team has developed processing and cleaning techniques for solar X-ray and proton flux measurements that will serve as the input for a proton flux prediction model.