Studying the Space Weather Features of the High-Latitude Ionosphere by Using a Physics-Based Data Assimilation Model and Observational Data from Ground Magnetometer Arrays

Details Studying the Space Weather Features of the High-Latitude Ionosphere by Using a Physics-Based Data Assimilation Model and Observational Data from Ground Magnetometer Arrays Studying the Space Weather Features of the High-Latitude Ionosphere by Using a Physics-Based Data Assimilation Model and Observational Data from Ground Magnetometer Arrays

Dec 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufmsa51d1981z&link_type=abstract

American Geophysical Union, Fall Meeting 2011, abstract #SA51D-1981

Physics

[2409] Ionosphere / Current Systems, [2411] Ionosphere / Electric Fields, [2778] Magnetospheric Physics / Ring Current, [7959] Space Weather / Models

Scientific paper

The high-latitude ionosphere is a very dynamic region in the solar-terrestrial environment. Frequent disturbances in the region can adversely affect numerous military and civilian technologies. Accurate specifications and forecasts of the high-latitude electrodynamic and plasma structures have fundamental space weather importance for enabling mitigation of adverse effects. Presently, most of the space-weather models use limited observations and/or indices to define a set of empirical drivers for physical models to move forward in time. Since the empirical drivers have a "climatological" nature and there are significant physical inconsistencies among various empirical drivers due to independent statistical analysis of different observational data, the specifications of high-latitude space environment from these space weather models cannot truthfully reflect the weather features. In fact, unrealistic small- and large-scale structures could be produced in the specifications and forecasts from these models. We developed a data assimilation model for the high-latitude ionospheric plasma dynamics and electrodynamics to overcome these hurdles. With a set of physical models and an ensemble Kalman filter, the data assimilation model can determine the self-consistent structures of the high-latitude convection electric field, ionospheric conductivity, and the key drivers associated with these quantities by ingesting data from multiple observations. These ingested data include the magnetic perturbation from the ground-based magnetometers in the high-latitude regions, magnetic measurements of IRIDIUM satellites, SuperDARN line-of-sight velocity, and in-situ drift velocity measured by DMSP satellites. As a result, the assimilation model can capture the small- and large-scale plasma structures and sharp electrodynamic boundaries, thus, can provide a more accurate picture of the high-latitude space weather. In this presentation, we will first briefly describe the data-assimilation model of high-latitude electrodynamics and its strengths over the other space-weather models. Then we will present the space weather features produced by the model for quiet and storm periods constrained by the data from ground magnetometer arrays. This will demonstrate the dynamic variability of the high-latitude ionosphere. Finally, we will present high-resolution ionospheric modeling results of the time-evolution and spatial features of the high-latitude plasma structures to further demonstrate the model's capability in producing the space weather features in the high-latitude ionosphere. These results will illuminate the importance of real-time data availability and data assimilation models for accurate specification and forecasting of space weather.

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