Methods
The ESA Swarm mission, launched in late 2013, comprises three identical
spacecraft equipped for making simultaneous, high accuracy and high
cadence magnetic and electric field measurements. This study uses data
from the Swarm A satellite, in a ~450 km polar orbit,
equipped with the fluxgate magnetometer instrument [14] measuring
magnetic field vectors at 50 samples/sec and the Electric Field
Instrument [30] measuring ion velocity vectors at 16 samples/sec
based on observed ion distributions from two sensors, which are
converted into a 2 Hz E-field data product. Under the assumption of
frozen flux of the observed ions based on ideal Ohm’s Law where E = -v x
B the inferred velocity vectors can be converted into electric field
vectors in the plane perpendicular to the magnetic field.
The automatic event identification algorithm used here has been designed
to extract useful scientific data from synchronous magnetic and electric
field measurements while addressing known caveats in the electric field
data (e.g. uncertainties regarding offsets and magnitudes of the
electric field instrument data [31], [32]). It is based on the
methodology employed by [33]. Only magnetic latitudes of between +-
60 and +- 80 degrees magnetic latitude (MLAT) are considered for the
analysis. This avoids low-latitude phenomena such as plasma bubbles
[34] and localised extreme high latitude phenomena such as polar cap
traversals [35]. The magnetic and electric field data is rotated
into the mean-field aligned (MFA) frame, where z points along the
direction of the mean magnetic field, x points towards the geomagnetic
North Pole, and y completes the triad facing eastwards. A sliding
3-minute window is used for mean field calculation.
For event detection and selection, the Poynting flux is calculated by
crossing the E- and B-field time series after applying a
2nd order Savitzky-Golay filter with window size 60.5
seconds, to remove any residual mean field influences or large-scale
electric fields, as well as any uncertainties with the E-field baselines
which are a known artefact in the electric field data. The modulus of
this Poynting flux is then low-pass filtered with a 120.5 sec moving
average filter to obtain its magnitude envelope. Where the magnitude of
this Poynting flux envelope exceeds an empirically determined threshold,
the event is flagged and event duration defined both backwards and
forwards in time until the magnitude of the Poynting flux envelope drops
below a second, lower, empirically determined threshold. For the
analysis presented here, the thresholds are 25 and 8.75, respectively.
This time window then defines a single event. Only E-field data sets
flagged with the quality flags 1 (“use in consultation with EFI TII
team at University of Calgary”) [36] is used in the analysis.
The 2 Hz E-field estimates are provided for both the horizontal and the
vertical sensors. Based on the caveats described in [36] the outputs
from both TII sensors are averaged. Since the analysis in this study
used high-pass filtering to focus on relatively small scales, it is
deemed acceptable to use the full 3-D vector for Poynting flux
calculations. A separate test performed using only the along-track
component of the E-field, which is identical in both sensors, to
calculate the Poynting flux, also reproduced the observed northern
preference.
The selected events must all occur at locations between 60 and 80
degrees magnetic latitude (MLAT) and event length must be at least 150
seconds long. The time series are extended with zeros for 30 seconds at
the beginning and the end, which serves as padding to allow all filter
sizes to fully capture the energy content in each event without
edge-effect distortion. For the selected events, the electric and
magnetic field data are then passed through a Savitzky-Golay filter of
2nd order and of various window sizes, from 1 (no
effective high-pass filter) to 60.5 seconds, at 0.5-second intervals.
The cross product of the two band-passed signals gives the Poynting flux
in that frequency band. The Poynting flux is integrated over time along
the spacecraft trajectory to obtain the integrated apparent energy flow
through the satellite world-line as it crosses the event region. This is
repeated for the entire range of low pass filter window sizes for each
event. Average Poynting fluxes for each event are obtained by dividing
the integrated Poynting flux values by the event duration. The median
and quartiles are obtained for these three quantities from all of the
events flagged by the algorithm.
A representative example of the analysis is shown in Figure 4 for an
auroral zone Swarm A crossing event from 05:11:30 to 05:15:00 UT on 17
Nov 2016, flagged by the algorithm. It can be seen that there is good
correspondence between B-field (panel (a)) and E-field (panel (b)) data,
suggesting mostly positive (downwards) Poynting flux throughout. This is
evidenced in panels (c) and (d) where the (parallel) Poynting flux
remains largely positive. The Poynting flux shown in panel (c) is
plotted for three Savitsky-Golay filter windows – 9 sec (blue) for
small-scale phenomena, 27 sec (red) for mesoscales, and 47 sec (black)
for perturbations associated with larger-scales. It can be seen that the
Poynting flux reduces as progressively more low-pass filtering is
applied to the constituent E-field and B-field time series. Panel (d)
shows the time integrals of the fluxes in panel (c) demonstrating the
accumulation of Poynting flux on the satellite’s world line as it
crosses the perturbation region. It can be seen that the cumulative
Poynting flux passing through the satellite during the event is
approximately half the value for large scales as for meso- and
small-scales, suggesting that large-scale perturbations associated with
global field aligned current systems carry only half of the
electromagnetic energy into the ionosphere during this particular event.