A Physics-Based Kalman Filter Electrodynamics Model for the High-Latitude Ionosphere

Details A Physics-Based Kalman Filter Electrodynamics Model for the High-Latitude Ionosphere A Physics-Based Kalman Filter Electrodynamics Model for the High-Latitude Ionosphere

Dec 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsa41b1421z&link_type=abstract

American Geophysical Union, Fall Meeting 2006, abstract #SA41B-1421

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2407 Auroral Ionosphere (2704), 2409 Current Systems (2721), 2431 Ionosphere/Magnetosphere Interactions (2736), 2437 Ionospheric Dynamics, 2447 Modeling And Forecasting

Scientific paper

To have accurate specifications and forecasts for the high-latitude electrodynamics parameters, a physics- based Kalman filter electrodynamics model has been recently developed. This data assimilation model is constructed by combining our high-resolution, time-dependent, physics-based Ionosphere Dynamics and Electrodynamics Model (IDED), which consists of a global ionosphere model, an M-I electrodynamics model, and a 3-D magnetic inversion model, with real-time measurements and an ensemble Kalman filter assimilation scheme. The assimilation model can ingest a wide range of real-time ground-based and in situ measurements and the output of the model is a full set of self-consistent, time-dependent electrodynamics and plasma parameters for the high-latitude ionosphere. These include the electric potential, electric field, field-aligned and horizontal currents, Hall and Pedersen conductances, Joule heating rates, 3-D distributions of Ne, Ni, Te, and Ti, as well as other ionospheric plasma parameters. A unique feature of the model is its ability to capture sharp electrodynamic boundaries and small-scale structures, which are crucial for space weather applications and the M-I couplings where the ionosphere plays an active role. To date, we have used our Kalman filter electrodynamics model to successfully assimilate the magnetometer data from 92 ground stations, the in situ cross-track velocity measurements from the DMSP F13 and F14 satellites, and the line-of-sight velocity measurements from the SuperDARN radars. In addition to the model description, sample results from the assimilation runs will also be presented.

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