Key points
AMPERE field-aligned currents have been combined with the SAMI3 model to
estimate the high-latitude potential
Independent validation of the new technique using satellite drifts and
ground-based TEC indicates good agreement overall
The SAMI3 model performs better in this case when using AMPERE-derived
potentials than when using the empirical Weimer potential
1. Introduction
Over the past several decades, great progress has been made in
specifying the ionosphere through first-principles modeling and data
assimilation. Ionospheric specification at high latitudes remains
challenging because of the influence of the solar wind and magnetosphere
on the ionosphere, especially in terms of plasma convection (e.g.
Spencer and Mitchell, 2007; Bust et al., 2007; Chartier et al., 2019),
as well as the relatively poor data coverage compared to other regions.
The northern high latitudes are becoming increasingly relevant in terms
of space weather due to the opening of the Arctic to shipping and
mineral exploration. This is reflected in a focus on the region from
several U.S. government agencies, notably the Department of the Air
Force in its Arctic Strategy (Barrett et al., 2020) and the National
Science Foundation’s Big Idea: Navigating the New Arctic. The lack of
ground networks in this area results in increased reliance on wireless
signals, which are susceptible to ionospheric disturbances.
Data from the Active Magnetosphere and Planetary Electrodynamics
Response Experiment (AMPERE, Anderson et al., 2000; 2002, Waters et al.,
2001; 2020) provide the most reliable and ubiquitous means of specifying
high-latitude ionospheric electrodynamics, with field-aligned current
measurements available from over 70 satellites in six polar low-Earth
orbits, yielding global measurement coverage at all latitudes every 10
minutes. The AMPERE dataset allows for the resolution of the full Region
1 and Region 2 current system in near real time and across both northern
and southern polar caps (e.g. Anderson et al., 2008). Understandably,
this dataset has featured prominently in many recent efforts to specify
the high-latitude electrodynamics, such as Assimilative Mapping of
Ionospheric Electrodynamics (Cousins et al., 2015) and Assimilative
Mapping of Geospace Observations (Matsuo et al., 2019).
To determine the high-latitude potential from the field-aligned current
distribution, it is necessary to know the ionospheric perpendicular
conductances (Pedersen and Hall). The most important determining factors
of the conductances are the solar EUV flux, the average energy and
energy flux of energetic particles and the neutral upper atmospheric
density and composition. Several approaches exist to address this
problem. The simplest is the assumption of constant conductance (used by
Merkin and Lyon, 2010), while others use empirical relations and
modeling to estimate conductance from other parameters (e.g. Robinson
and Vondrak, 1984; Robinson et al., 1987; Zhang et al., 2015;
McGranaghan et al., 2016). First-principles models of the
ionosphere/upper atmosphere (e.g. Quegan et al., 1982; Roble et al.,
1988; Huba et al., 2000; 2008) also contain all the parameters needed to
calculate the conductance (altitudinal profiles of electron density and
neutral atmospheric density).
A major obstacle to the development of reliable high-latitude
electrodynamic solutions has been the challenge of validation. The
high-latitude electric potential is not directly observable, and even
its derivative, the high-latitude electric field, is observed only
through its effect on ions via the E xB drift. As a
result of this lack of direct comparison data, many recent developments
in E xB drift solutions have been published without
validation (e.g. Bristow et al., 2016; Gjerloev et al., 2018). In order
to validate convection maps, some authors have used ionospheric F-region
electron density structures as a tracer of the ExB drift. Wang et al.
(2018) and Ramirez et al. (2019) have used the observed motion of
high-latitude electron density structures to assess the accuracy of
Weimer’s (2005) empirical model and Ruohoniemi and Baker’s (1998)
SuperDARN-driven high-latitude potentials.
2. Method
In this investigation, we aim to specify the high-latitude
electrodynamics in order to predict the generation and development of
ionospheric electron density structures (e.g. the tongue of ionization,
polar cap patches). We then test our predictions against independent
GPS-based TEC data showing those structures, and against satellite ion
drift data. The approach is as follows:
a) determine the Pedersen (\(\Sigma_{P}\)) and Hall (\(\Sigma_{H}\))
conductances from SAMI3,
b) calculate the high-latitude potential (Ψ) using \(\Sigma_{P}\),\(\Sigma_{H}\) and AMPERE-observed field-aligned currents
(J ),
c) use Ψ to calculate E xB plasma drifts in SAMI3
d) compare simulation results to data
The potential is calculated at a 10-minute cadence, matching the
latitude re-sampling cadence of the Iridium satellites used for AMPERE.
The outputs are the full set of electrodynamic parameters
(\(\Sigma_{P}\), \(\Sigma_{H}\), \(\Sigma_{||}\), Ψ, J )
as well as the ionospheric electron density distribution, which can be
vertically integrated to produce Total Electron Content (TEC). The
electric potentials are compared against Defense Meteorological
Satellite Program (DMSP) horizontal ion drift data (e.g. Hairston and
Heelis, 1993) during the period of interest. The TEC output is compared
against images from the University of Bath’s Multi-Instrument Data
Analysis Software (Mitchell and Spencer, 2003; Spencer and
Mitchell, 2007), which uses ground-based GPS data. The MIDAS algorithm’s
ability to image the tongue of ionization and patches has previously
been validated by Wang et al., 2018, Spencer and Mitchell, 2007, and
others.
For this demonstration, we have applied the technique to a magnetically
active period in the most recent solar maximum: 21-25 May 2014. This
period contains relatively strong field-aligned currents, both because
of the elevated magnetic activity and because the northern polar cap is
in sunlight. Figure 1 shows the IMF Bz component and the Kyoto
Disturbance Storm Time (Dst) and Auroral Electrojet (AE) indices for
this period. On 23 May 2014, Bz reached a minimum of -7.5 nT at 19 UT,
Dst reached a minimum of -36 nT at 21 UT, while the maximum AE of 909 nT
occurred earlier, at 17 UT. The case could be summarized as a weak
geomagnetic storm with substantial substorm activity.