Assimilation of GIRO data into a real‐time IRI

Abstract

[1] Increasingly accurate and detailed global 3-D specification of the Earth's space plasma environment is required to further understand its intricate organization and behavior. For a long time space physics and aeronomy research has been data starved due to the great variety of natural time scales involved in the plasma phenomenology. We have started developing a new approach to the global ionospheric specification called Real-Time Assimilative Mapping (RTAM). The IRI-RTAM will use data from the Global Ionospheric Radio Observatory (GIRO) to smoothly transform IRI's background empirical maps of the ionospheric characteristics to match the observations. Such empirical assimilative modeling will provide a high-resolution, global picture of the ionospheric response to various short-term events observed during periods of storm activity or the impact of gravity waves coupling the ionosphere to the lower atmosphere, including timelines of the vertical restructuring of the plasma distribution. It will also contribute to the challenging task of providing a rapid insight into the temporal and spatial space weather development using the real-time GIRO data streams. The new assimilation technique "updates" the IRI electron density distribution while preserving the overall integrity of IRI's typical ionospheric feature representations. The technique adjusts the coefficients of the spherical/diurnal expansions used by the CCIR and URSI-88 model to obtain the global subpeak electron density distribution. The set of global corrected coefficients can be generated as frequently as every 15 min and easily disseminated using a single real-time RTAM server operated by GIRO.

The International Reference Ionosphere 2012 – a model of international collaboration

“…Combing assimilation and updating techniques, Pezzopane et al (2011) first determine a ionospheric-effective sunspot number from comparing IRI to ionosonde F2 peak parameter (foF2, M(3000)F2) measurements and then after fully analyzing the ionograms applied a Kriging technique to assimilate the full electron density profile into IRI-2007. The IRI Real-Time Assimilative Mapping (IRTAM) of Galkin et al (2012) is based on plasma frequency (foF2) measurements by the worldwide network of Digisonde stations (the Global Ionospheric Radio Observatory -GIRO) and employs a linear optimization technique to obtain an improved global representation of foF2 for IRI every 15 min (http://giro.uml.edu/ RTAM). An example is shown in Figure 7.…”

Tomography of the ionospheric electron density with geostatistical inversion

“…We can identify methods modifying the coefficients of an empirical model (see Brunini et al, 2011;Galkin et al, 2012), methods updating the model towards the measurements without modification of its coefficients (seeods combining both (see Pezzopane et al, 2011) and approaches using physical background models and including the estimation of ionospheric drivers, such as neutral winds, in the state vector (see Schunk et al, 2004;Scherliess et al, 2009;Wang et al, 2004).…”

Simultaneous multiplicative column-normalized method (SMART) for 3-D ionosphere tomography in comparison to other algebraic methods

“…Several approaches have been developed and validated for ionospheric reconstruction by a combination of actual observations with an empirical or a physical background model. Galkin et al (2012) present a method to update the IRI coefficients, using vertical sounding observations of a 24 h sliding window. Bust et al (2004) use a variational data assimilation technique to update the background, combining the observations and the associated data error covariances.…”