Utah State University Global Assimilation of Ionospheric Measurements Gauss‐Markov Kalman filter model of the ionosphere: Model description and validation

Abstract

[1] The Utah State University Gauss-Markov Kalman Filter (GMKF) was developed as part of the Global Assimilation of Ionospheric Measurements (GAIM) program. The GMKF uses a physics-based model of the ionosphere and a Gauss-Markov Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) observations. The physics-based model is the Ionospheric Forecast Model (IFM), which accounts for five ion species and covers the E region, F region, and the topside from 90 to 1400 km altitude. Within the GMKF, the IFM derived ionospheric densities constitute a background density field on which perturbations are superimposed based on the available data and their errors. In the current configuration, the GMKF assimilates slant total electron content (TEC) from a variable number of global positioning satellite (GPS) ground sites, bottomside electron density (N e ) profiles from a variable number of ionosondes, in situ N e from four Defense Meteorological Satellite Program (DMSP) satellites, and nighttime line-of-sight ultraviolet (UV) radiances measured by satellites. To test the GMKF for real-time operations and to validate its ionospheric density specifications, we have tested the model performance for a variety of geophysical conditions. During these model runs various combination of data types and data quantities were assimilated. To simulate real-time operations, the model ran continuously and automatically and produced three-dimensional global electron density distributions in 15 min increments. In this paper we will describe the Gauss-Markov Kalman filter model and present results of our validation study, with an emphasis on comparisons with independent observations.

Exploring Earth's atmosphere with radio occultation: contributions to weather, climate and space weather

“…The measurements of TEC and electron density profiles are potentially valuable for data assimilation into ionospheric models like the Jet Propulsion Laboratory/University of Southern California Global Assimilative Ionospheric Model (JPL/USC GAIM; Wang et al, 2004) and the Utah State University Global Assimilation of Ionospheric Measurements model (USU GAIM; Schunk et al, 2004, Scherliess et al, 2006. Many research groups running space weather models have assimilated TEC data.…”

Global Ionospheric Radio Observatory (GIRO)

“…The real-time data streams from these instruments were provided for assimilation into ICED/PRISM (Daniell et al, 1990(Daniell et al, , 1993) and later to GAIM (Schunk et al, 2004;Scherliess et al, 2006). Since then, other agencies have built similar networks: the Digital Atmospheric Server (DIAS) (Belehaki et al, 2005) became operational in 2004 with 6 contributing Digisondes located in Europe; and the Jindalee Operational Radar Network of the Australian government installed 11 Digisondes (Gardiner-Garden, 2006) to provide data to their real time ionospheric model RTIM (Wheadon et al, 1994;Barnes et al, 2000).…”

Thermospheric mass density specification using an ensemble Kalman filter

“…[3] Applications of the Kalman filter [Kalman, 1960;Kalman and Bucy, 1961] and its variants for assimilation of ionospheric observations to first principle ionospheric models have been shown to be effective [e.g., Schunk et al, 2004;Scherliess et al, 2006Scherliess et al, , 2009Hajj et al, 2004;Komjathy et al, 2010;Khattatov, 2010, and references therein]. On the other hand, thermospheric data assimilation applications have so far been limited largely by a lack of operational monitoring of thermospheric parameters.…”