Network analysis of Pc waves using the SuperMAG database of ground-based magnetometer stations

Abstract:

Pc waves are ubiquitous in the inner magnetosphere and have been extensively studied both to understand the underlying physical processes, and to quantify their relationship with geomagnetic substorms and storms. We present a comprehensive network analysis of Pc waves using 1-sec data obtained from SuperMAG. SuperMAG collates the observations from 100s of ground based magnetometers with a single calibration and timebase, providing an unprecedented opportunity to quantify spatially coherent pattern and propagation. This data can be used to construct dynamical networks which parameterize spatio-temporal correlation. Network-based analysis of 1 min cadence SuperMAG data has resolved the dynamics of substorm current systems (Dods et al. JGR 2015, Orr et al. GRL 2019) and the magnetospheric response to IMF turnings (Dods et al. JGR 2017). Now, with the availability of 1 sec data across the entire network of SuperMAG magnetometers we are able to apply network analysis to obtain new quantitative understanding of Pc waves. Prior to constructing the network, time series data is band-pass filter using Pc wave frequency intervals and cross-correlated ensuring the window is twice the Pc wave period of interest. To construct the network we use noise surrogates to establish a threshold to filters out insignificant cross-correlation values. Once a network is constructed, it can be characterized by a few network parameters. This may lead to the identification of new Pc indices that capture the spatial coherence and propagation of Pc activity. Quantifying the full spatio-temporal response of the magnetosphere across 100s of ground based magnetometers with a few parameters also forms the basis of statistical studies across many events. First results will be presented for the dynamical directed network for Pc wave intensity and coherence during intervals of enhanced geomagnetic activity.