Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...
Nature

Application of explainable machine learning for estimating direct and diffuse components of solar irradiance

Solar energy applications indeed rely on precise solar irradiance data, including global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI). These ...
Nature

SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction

This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA’s Solar Dynamics Observatory (SDO), specifically designed to advance machine learning (ML) ...