Estimating Density Gradients and Drivers from 3D Ionospheric Imaging

Details Estimating Density Gradients and Drivers from 3D Ionospheric Imaging Estimating Density Gradients and Drivers from 3D Ionospheric Imaging

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsa22b..03d&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SA22B-03

Physics

[2437] Ionosphere / Ionospheric Dynamics, [2441] Ionosphere / Ionospheric Storms, [2447] Ionosphere / Modeling And Forecasting

Scientific paper

The transition regions at the edges of the ionospheric storm-enhanced density (SED) are important for a detailed understanding of the mid-latitude physical processes occurring during major magnetic storms. At the boundary, the density gradients are evidence of the drivers that link the larger processes of the SED, with its connection to the plasmasphere and prompt-penetration electric fields, to the smaller irregularities that result in scintillations. For this reason, we present our estimates of both the plasma variation with horizontal and vertical spatial scale of 10 - 100 km and the plasma motion within and along the edges of the SED. To estimate the density gradients, we use Ionospheric Data Assimilation Four-Dimensional (IDA4D), a mature data assimilation algorithm that has been developed over several years and applied to investigations of polar cap patches and space weather storms [Bust and Crowley, 2007; Bust et al., 2007]. We use the density specification produced by IDA4D with a new tool for deducing ionospheric drivers from 3D time-evolving electron density maps, called Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). The EMPIRE technique has been tested on simulated data from TIMEGCM-ASPEN and on IDA4D-based density estimates with ongoing validation from Arecibo ISR measurements [Datta-Barua et al., 2009a; 2009b]. We investigate the SED that formed during the geomagnetic super storm of November 20, 2003. We run IDA4D at low-resolution continent-wide, and then re-run it at high (~10 km horizontal and ~5-20 km vertical) resolution locally along the boundary of the SED, where density gradients are expected to be highest. We input the high-resolution estimates of electron density to EMPIRE to estimate the ExB drifts and field-aligned plasma velocities along the boundaries of the SED. We expect that these drivers contribute to the density structuring observed along the SED during the storm. Bust, G. S. and G. Crowley (2007), Tracking of polar cap patches using data assimilation, J. Geophys. Res., 112, A05307, doi:10.1029/2005JA011597. Bust, G. S., G. Crowley, T. W. Garner, T. L. Gaussiran II, R. W. Meggs, C. N. Mitchell, P. S. J. Spencer, P. Yin, and B. Zapfe (2007) ,Four Dimensional GPS Imaging of Space-Weather Storms, Space Weather, 5, S02003, doi:10.1029/2006SW000237. Datta-Barua, S., G. S. Bust, G. Crowley, and N. Curtis (2009a), Neutral wind estimation from 4-D ionospheric electron density images, J. Geophys. Res., 114, A06317, doi:10.1029/2008JA014004. Datta-Barua, S., G. Bust, and G. Crowley (2009b), "Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE)," presented at CEDAR, Santa Fe, New Mexico, July 1.

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