Predicting the Emergence of Solar Active Regions Using Machine Learning

arXiv:2402.08890v1 Announce Type: cross
Abstract: To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic features in the evolution of acoustic power density to predict continuum intensity emergence. For our study, we have utilized Doppler shift and continuum intensity observations from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). The local tracking of 30.66 x 30.66-degree patches in the vicinity …

abstract arxiv astro-ph.sr capabilities cs.lg dataset emergence evolution features identify intensity machine machine learning power solar space study type weather