Quantifying space weather: networks, extreme events and dynamics in pattern and in distribution
There is an extensive toolkit of data analysis methods that are well understood when conditions are ideal. This talk will describe recent work in applying these methodologies to observations of real, physical systems. Real world observations are not uniform in space or time, they can be time-correlated and sample sizes are restricted. Here we will focus on observations of space weather and space climate. The earth is shielded to some extent by its intrinsic magnetic field from the sun’s expanding atmosphere. This shield is not perfect however, and space weather impacts on the earth range from the northern lights to radiation damage to satellites in orbit, to current inducing magnetic field perturbations on the ground.
Observations of space weather are made by several hundred magnetometers on the earth’s surface, and by satellites located ‘upstream’ between the earth and sun. These provide a comprehensive data set of activity, spanning several solar cycles. Sensitivity and accuracy is not uniform across these instruments and has also improved significantly over time. This is a challenge when combining these observations to characterize how space weather events evolve, and how their statistics (space climate) depends on solar activity which varies with the solar cycle.
This talk will describe recent work  the first analysis of the full available set of ground based magnetometer observations of space weather events using dynamical networks, and  robust features in the statistics of the most extreme events and how they vary with the solar cycle.
 Dods, J., S. C. Chapman, and J. W. Gjerloev (2015), Network analysis of geomagnetic substorms using the SuperMAG database of ground-based magnetometer stations, J. Geophys. Res. Space Physics, 120, 7774, doi:10.1002/2015JA021456
 Hush, P., S. C. Chapman, M. W. Dunlop, and N. W. Watkins (2015), Robust statistical properties of the size of large burst events in AE, Geophys. Res. Lett., 42 doi:10.1002/2015GL066277