Developing the Science of Networks to Quantify Pattern in Earth and Space-Based Observations of Space Weather
Abstract
We are now in a data rich era of space plasma physics observations which are unprecedented in their spatio-temporal coverage. The driver of space weather, the solar wind, is now monitored with time resolution from sub-second to decades, spanning multiple solar cycles. Historical data of geomagnetic activity at earth reaches back over 150 years. On earth, the data from 100+ ground-based magnetometers again spanning several decades is now readily available alongside multipoint satellite observations. This project brings new approaches to this wealth of data, harnessing the state of the art in trans-disciplinary approaches in time series analysis, statistical characterization, data analytics and the quantification of risk to provide quantitative insight on how the earths magnetosphere, a highly variable non-linear dynamical system, responds to the dynamical driving of the solar wind. Our results range from the first use of network science approaches to quantify the full spatio-temporal pattern of ground magnetic perturbations during space weather events, providing a benchmark for global space weather models, to quantifying the risk of extreme space weather events and how this risk varies with the solar cycle of activity.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 02, 2021
- Accession Number
- AD1157986
Entities
People
- Sandra Chapman
Organizations
- University of Warwick