100-km Variations in Ionospheric-Thermospheric Response to Geomagnetic Storms with Data Assimilation

Extreme space weather, i.e., a geomagnetic storm due to a solar coronal mass ejection, has significant impact on technological systems. Global Navigation Satellite Systems (GNSS) rely on trans-ionospheric signal ranging; the ranging error due to the ionosphere is proportional to the quantity of plasma along the signal path. Typical ionospheric errors can be estimated for navigation users effectively in real-time, for improved accuracy and safety for applications such as aircraft landing aids. However, extreme disturbances due to storms cause mid-latitude continent-scale ionospheric plasma storm-enhanced densities (SEDs), as plasma is redistributed between low, mid and high latitudes during a period of one or more days.

At the edges of the SED or its associated plume, large variations in electron density can occur over distances of only a few hundred kilometers or less. The density variation of an extreme storm poses challenges to navigation applications for which real-time operational safety assurance through error-bounding is required. Some of these storms have been shown to produce significant plasma density enhancement localized to only a few hundred km scale size in the mid-latitude nightside ionosphere. This can challenge safety-critical navigation applications if the enhancement is dense but compact enough at 100 km horizontally to be undetected in real-time. While global and sector-scale changes occur, density variations at the 100 km scale are of greater concern operationally.

To begin to mitigate the space weather effects at 100 km horizontal scales requires a better understanding of the dominant physical processes – production, loss, neutral winds, electric fields -- in the ionosphere and thermosphere and their relationship to the plasma distribution at those scales. Data assimilation represents an effective way to blend physics-based modeling with updated in situ and remotely sensed measurements. Data assimilation enables resolution of ionospheric features at degree or even sub-degree scales.

We estimate plasma density distribution and correlate these with data-assimilative estimates of the physical driving processes of the storm-time mid-latitude ionosphere. The case studied is October 25, 2011, a storm from the current solar cycle. Ionospheric Data Assimilation 4-Dimensional (IDA4D) is a 3D Variational method for ingesting ground- and space-based ionospheric density and total electron content data to routinely estimate plasma distribution. It is run in a global low resolution mode, and the results are bootstrapped as the background model for a regional high resolution mode that focuses on the mid-latitude American sector, for which many GNSS-based measurements are available for assimilation. The high-resolution run is performed at 1 degree geomagnetic latitude and longitude resolution.

We input the one-degree plasma density estimates to a physical driver assimilation tool known as Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). EMPIRE uses the mass spectrometer and incoherent scatter (MSIS) model, international reference ionosphere (IRI), horizontal wind model (HWM) and Weimer electric potential as background models for production, loss, gravity, neutral wind and electric fields. The models of these drivers are Kalman filtered with the plasma density estimates from IDA4D to produce time-varying estimates of the drivers at 1-degree resolution.

We compare nearby drift measurements from DMSP in situ, digisonde drifts, and the mid-latitude SuperDARN chain. Finally, we correlate electron density distribution and structuring from IDA4D with ionospheric drivers from EMPIRE, and with the geomagnetic activity measure Dst and the solar wind interplanetary magnetic field.