Tim Duckenfield & Lauren Orr (CFSA, Warwick)
Tim Duckenfield: "Detection of the second harmonic of decay-less kink oscillations in coronal loops"
Abstract: Kink oscillations of solar coronal loops have been intensively studied for many years, and allow for the seismological estimation of the (local) magnetic field, which is often difficult to determine directly. Observations show there exist two regimes of kink oscillation; a large amplitude, rapidly decaying regime, and the other involving omnipresent so-called ``decay-less oscillations'' of far lower amplitude that persist for far longer. A datacube of a well-contrasted loop, imaged in EUV with the SDO/AIA telescope, has been processed by a motion magnification routine that enhances transverse motions, in order to better resolve these decay-less oscillations. Spectral analysis show two strong periods of decay-less oscillation are present within the loop; one at 10.3(+1.5,-1.7) minutes, and another at 7.4(+1.1,-1.3) minutes. The spatial distribution of the periods through the loop, as well as the measured period values, are consistent with the oscillations being the fundamental and second harmonic standing kink modes. The existence of higher harmonics within the decay-less regime has implications for understanding their driving and damping mechanisms. Further, the ubiquity of decay-less oscillations in the solar corona suggests seismological techniques based upon the ratio of periods could be used on potentially all coronal loops.
Lauren Orr: Dynamical Networks Characterization of Space Weather Events
Abstract: Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth’s magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation, as correlated disturbances across the magnetometers capture transient currents. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series, this threshold needs to be both station specific as it varies with (non-linear) individual station sensitivity and location, and vary with season which affects ground conductivity. We present new methodology which addresses these problems and in particular performs a dynamic normalization of the physical time series in order to form the network. By calculating the canonical cross correlation for lags of 1-15 minutes, and taking the maximum we produce a directed network that can determine the timings and direction of information propagation which corresponds to plasma dynamics.