  The overall morphology and dynamics of magnetospheric substorms is well
established in terms of the observed qualitative auroral features seen in
ground-based magnetometers. This paper focuses on the quantitative
characterization of substorm dynamics captured by ground-based magnetometer
stations. We present the first analysis of substorms using dynamical networks
obtained from the full available set of ground-based magnetometer observations
in the Northern Hemisphere. The stations are connected in the network when the
correlation between the vector magnetometer time series from pairs of stations
within a running time window exceeds a threshold. Dimensionless parameters can
then be obtained that characterize the network and by extension, the
spatiotemporal dynamics of the substorm under observation. We analyze four
isolated substorm test cases as well as a steady magnetic convection (SMC)
event and a day in which no substorms occur. These test case substorms are
found to give a consistent characteristic network response at onset in terms of
their spatial correlation. Such responses are differentiable from responses to
the SMC event and nonsubstorm times. We present a method to optimize network
parametrization with respect to the different individual station responses, the
spatial inhomogeneity of stations in the Northern Hemisphere, and the choice of
correlation window sizes. Our results suggest that dynamical network analysis
has potential to quantitatively categorize substorms.
