On Constructing a Realistic Truth Model Using Ionosonde Data for
Observation System Simulation Experiments
Abstract
The ionosphere contains many small-scale electron density variations
that are under represented in smooth physics-based or climatological
models. This can negatively impact the results of Observation System
Simulation Experiments, which use a truth model to simulate data. This
paper addresses this problem by using ionosonde data to study
ionospheric variability and build a new truth model with
empirically-driven variations. The variations are studied for their
amplitude, horizontal and vertical size, and temporal extent. Results
are presented for different local times, seasons, and at two different
points in the solar cycle. We find that these departures from a smooth
background are often as large as 25\% and are most
prevalent near 250 km in altitude. They have horizontal spatial extents
that vary from a few hundred to a few thousand kilometers, and typically
have the largest horizontal extent at high altitudes. Their vertical
extents follow the same pattern of being larger at high altitudes, but
they only vary from 10s of km up to 200 km in vertical size. Temporally,
these variations can last for a few hours. The procedure for using these
spatial and temporal distributions to add empirically-driven variance to
a smooth truth model is outlined. This process is used to make a truth
model with representative variations, which is compared to ionosonde
data as well as GPS Total Electron Content (TEC) data that was not used
to inform the model. The new model resembles the data much better than
the smooth models traditionally used.