Intelligent Database of Solar Events and Active Regions (IDSEAR)

Viacheslav M Sadykov1, Alexander G Kosovichev2, Gelu M Nita3, Vincent Oria4 and Wei Wang4, (1)New Jersey Institute of Technology, Department of Physics, Edison, NJ, United States, (2)New Jersey Institute of Technology, Physics, Newark, NJ, United States, (3)New Jersey Institute of Technology, Center for Solar-Terrestrial Research, Newark, NJ, United States, (4)New Jersey Institute of Technology, Computer Science, Newark, NJ, United States
Abstract:
The growing needs for the accurate Space Weather Forecasts motivate the researchers to implement comprehensive prediction algorithms for solar transient events (flares, coronal mass ejections, filament eruptions). However, each prediction attempt will face the data preparation and processing phase, which usually takes a significant part of the research time. Besides some attempts (e.g. SDO SHARP archive), currently there are no databases containing processed descriptors of the Active Regions (AR) and related observations of flares and eruptive events. We develop an Intelligent Database of Solar Events and Active Regions (IDSEAR) which is the continuation of the Interactive Multi-Instrument Database of Solar Flares (IMIDSF, https://solarflare.njit.edu/) previously developed by our team. The IDSEAR will have full IMIDSF functionality (search of solar flares based on their physical descriptors) extended to the integration of Solar Events, ARs and related observations, which will allow users to make queries using descriptors of ARs and solar events linked to the ARs. In addition to the commonly-used AR descriptors, we plan to add new physical data products (NLFFF extrapolations and local helioseismology subsurface flow maps) and their descriptors, as well as operational data from SWPC NOAA (to include expert estimates in machine-learning procedures). The structure of the IDSEAR is scalable and allows addition of any descriptors and data products via the user contribution system (UCS). We envision that the developed database will allow the researchers to significantly speed up data processing and preparation for statistical analysis and physics-based prediction of solar events, as well as get access to and share high-quality scientific data products.