Forecasting of Localized Geomagnetic Disturbances in Global Models:
Physics and Numerics
Abstract
One of the prominent effects of space weather is the variation of
electric currents in the magnetosphere and ionosphere, which can cause
localized, high amplitude Geomagnetic Disturbances (GMDs) that disrupt
ground conducting systems. Because the source of localized GMDs is
unresolved, we are prompted to model these effects, identify the
physical drivers through examination of the model we use, and improve
our prediction of these phenomena. We run a high-resolution
configuration of the Space Weather Modeling Framework (SWMF) to model
the September 7, 2017 event, combining three physical models: Block
Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US), an ideal
magnetohydrodynamic model of the magnetosphere; the Ridley Ionosphere
Model (RIM), a shell ionosphere calculated by solving 2-D Ohm’s Law; and
the Rice Convection Model (RCM), a kinetic drift model of the inner
magnetosphere. The configuration mirrors that which is used in Space
Weather Prediction Center (SWPC) operations; however, the higher grid
resolution can reproduce mesoscale structure in the tail and ionosphere.
We use two metrics to quantify the success of the model against
observation. Regional Station Difference (RSD) is a metric that uses
dB/dt or geoelectric field to pinpoint when a single magnetometer
station records a significantly different value than others within a
given radius, indicating a localized GMD. Regional Tail Difference (RTD)
performs the same calculation using relevant variables in the
magnetosphere at points that map down along field lines to the
magnetometer station locations on the ground. We theorize two distinct
causes of RSD, the first being small-scale structure in the tail and the
second being station field lines mapping to spatially separated
locations in the tail. We examine the differences between RSD spikes
that we can reproduce in the model and those that we cannot. We
categorize spikes by cause of localized GMDs to examine model capability
for each theorized cause. We investigate the improvements in our model
when we switch from empirical specification of ionosphere conductance to
a physics-based one, MAGNetosphere-Ionosphere-Thermosphere (MAGNIT)
Auroral Conductance Model. For small-scale effects we cannot reproduce,
we explore the deficiencies in our model.