Automatic Recognition of Solar Features for Developing Data Driven Prediction Models of Solar Activity and Space Weather
Abstract
Space weather is driven by solar activity and is an important component of U.S. Department of Defense (DoD) research. It affects both civilian and commercial assets in space and on the ground. Severe changes in space weather can damage or cause failure of communication and navigation systems of interest to the DoD, as well as civilian and commercial entities. Researchers in the solar community need a method of quickly characterizing solar activity to feed data-driven models that forecast eruptive events and space weather for the DoD ground and space systems. This work addresses this need by using several observational databases to develop and utilize algorithms to (a) automatically track and recognize features that precede eruptive solar events; (b) parametrize physical properties for each of these regions; and (c) create dynamic, data-driven models of solar activity that will capture the temporal evolution of these features and quantify their importance in the eruption of flares and coronal mass ejections.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 06, 2012
- Accession Number
- ADA563097
Entities
People
- Jason Jackiewicz
Organizations
- New Mexico State University