On Constructing a Realistic Truth Model Using Ionosonde Data for Observation System Simulation Experiments. Issue 11 (25th November 2022) - Hughes, Joseph; Forsythe, Victoriya; Blay, Ryan; Azeem, Irfan; Crowley, Geoff; Wilson, Walter "Junk"; Dao, Eugene; Colman, Jonah; Parris, Richard
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 solar minimum and solar maximum. 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. A 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 Global Positioning System Total Electron Content data that was not used to inform the model. The new model resembles the data much better than the smooth models traditionally used. Plain Language Summary: The ionosphere is a region of space between 100 and 1, 000 km in altitude. It contains many small variations in electron density that are not well‐described in typical models used in Observation System Simulation Experiments. This paper uses ionosonde data to study the size and duration of these variabilities, and then develops a method to add them to one of these typical models. The new model with the variabilities added more closely replicates real ionospheric measurements. Key Points: The amplitude and spatio‐temporal extent of ionospheric variabilities are quantified across altitude, local time, season, and solar cycle A method to add these variations into a smooth model is demonstrated and replicates ionospheric data well This noisy truth model enables more accurate Observation System Simulation Experiments