Skip to main content
NASA Advanced Supercomputing (NAS) Division World-class modeling, simulation, and supercomputing in support of the NASA mission

“All-Clear” Prediction of Solar Energetic Particle Events with Machine Learning

AMS Seminar Series

Speaker: Viacheslav M. Sadykov, Georgia State University

Presentation

Seminar Slide Deck (PDF-3.4MB)

Abstract

Robust prediction of Solar Energetic Particle (SEP) events is among the key priorities of the heliophysics and space weather communities. As hazardous radiation, SEPs may affect the health of astronauts in outer space and adversely impact current and future space exploration. Of special importance are so-called “all-clear” predictions, when one can say with certainty that no SEP events are expected within the considered time period. In this seminar, I will cover our contribution to the problem of SEP prediction by reporting progress on the project “Machine Learning Tools for Predicting Solar Energetic Particle Hazards,” supported by NASA’s Early Stage Innovation program. First, I will highlight the challenges related to the data collection and integration for SEP forecasting and our approach to developing an online-accessible database of SEP data, metadata, and products. Second, I will discuss the “all-clear” forecasting of Solar Proton Events (SPEs). Specifically, I will highlight (1) the primary outcomes of our study of the daily probabilistic prediction of > 10 MeV > 10 pfu proton events for the solar cycle 24 (2010-2020) and its comparison with the operational forecasts, (2) the approach to extend this study to the solar cycles 22-23 based on the statistical properties of soft X-ray and proton fluxes and the McIntosh and Hale classes of solar active regions, and (3) the development of flare-driven SPE forecasts based on the GOES soft X-ray measurements during the solar flares.

Biography

Photo of Viacheslav Sadykov
Viacheslav Sadykov obtained his Ph.D. degree from the New Jersey Institute of Technology in 2019 and worked as a Research Scientist at BAERI / NASA Ames Research Center from 2019 until 2021. In 2021, he joined the faculty of the Physics & Astronomy Department of Georgia State University as an Assistant Professor. Viacheslav has wide research interests, including the development and maintenance of databases of solar flares and flight radiation measurements, prediction of solar transient events using machine learning, machine learning-aided analysis of the spectroscopic observations of the Sun, modeling of solar spectral lines and EUV emission, and analysis of the realistic radiative MHD simulations of the quiet Sun. Viacheslav is one of the main developers of the Interactive Multi-Instrument Database of Solar Flares and the Radiation Data Portal (IMIDSF and RDP, deployed at https://data.nas.nasa.gov/helio/), and a PI and Co-I of several NASA and NSF research grants.