[1] We report on ionospheric optical emissions detected by the GUVI instrument on the TIMED satellite. As the satellite crosses the equatorial zone the bright Appleton Anomaly region is imaged. Often these bright zones are interrupted by regions slanted from west to east as the equator is approached forming a backwards 'C'-shape in the image. To explain this feature we use simultaneous ground-based observations looking equatorward from Hawaii using the 777.4-nm emission. We also compare these optical observations to inverted electron density maps, as well as to those made by radar and to numerical simulations of the Rayleigh-Taylor instability. The characteristic shape is a result of a shear in the eastward plasma flow velocity, which peaks near the F peak at the equator and decreases both above and below that height. The ability to detect these unstable and usually turbulent ionospheric regions from orbit provides a powerful global remote sensing capability for an important space weather process.
Space weather impacts on communications are often presented as a raison d'etre for studying space weather (e.g., Solar and Space Physics: A Science for a Technological Society, 2013). Here we consider a communications outage during Operation Anaconda in Afghanistan that may have been related to ionospheric disturbances. Early military operations occurred during the peak of solar cycle 23 when ionospheric variability was enhanced. During Operation Anaconda, the Battle of Takur Ghar occurred at the summit of a 3191 m Afghan mountaintop on 4 March 2002 when the ionosphere was disturbed and could have affected UHF Satellite Communications (SATCOM). In this paper, we consider UHF SATCOM outages that occurred during repeated attempts to notify a Quick Reaction Force (QRF) on board an MH-47H Chinook to avoid a "hot" landing zone at the top of Takur Ghar. During a subsequent analysis of Operation Anaconda, these outages were attributed to poor performance of the UHF radios on the helicopters and to blockage by terrain. However, it is also possible that ionospheric anomalies together with multipath effects could have combined to decrease the signal-to-noise ratio of the communication links used by the QRF. A forensics study of Takur Ghar with data from the Global Ultraviolet Imager on the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission showed the presence of ionospheric bubbles (regions of depleted electron density) along the line of sight between the Chinook and the UHF communications satellites in geostationary orbit that could have impacted communications. The events of 4 March 2002 motivated us to develop the Mesoscale Ionospheric Simulation Testbed model, which can be used to improve warnings of potential UHF outages during future military operations.
[1] A tomographic forward and inverse model is presented that enables the recovery of three-dimensional ionospheric structures from space-based optical observations. In this paper we apply the technique to the Global Ultraviolet Imager (GUVI) on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite. The forward model is based on GUVI observation geometry to simulate radiance observations of a model ionosphere. This model incorporates the physics of the 1356 Å emission and the pattern of line-of-sight measurements out of the plane of the orbit into a discrete matrix representation of the GUVI observation. The application of matrix inversion techniques to the discrete observation matrix allows a multidimensional electron density profile to be reconstructed from the GUVI brightness measurements. Appropriate regularization functionals are incorporated to constrain the reconstructed solution. A smoothness constraint with a nonconvex penalty function ensures smoothness while preserving edges in the reconstructed image, an attribute which is crucial for the reconstruction of sharp ionospheric gradients. Results using GUVI data are shown to demonstrate the applicability of this technique.
A comprehensive database of plasma bubble reconstructions is under development, with results reported here from more than 5 years of Global Ultraviolet Imager (GUVI) data. Climatological statistics of plasma bubble occurrence from this database are presented, including the effects of longitudinal, seasonal, geomagnetic, and solar cycle variations on plasma bubble occurrence. The relationship between the latitudinal separation and peak electron density values of the equatorial arcs and plasma bubble occurrence is also discussed. Since its launch on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite in December 2001, GUVI has more than 7 years of observations of the nightside equatorial ionosphere. GUVI is capable of detecting and imaging plasma bubbles within the northern and southern equatorial arcs. An automated algorithm was developed to locate the peaks of the equatorial arcs and detect the presence of equatorial plasma bubbles. This algorithm was integrated with a tomographic imaging model and a statistical inversion technique to reconstruct electron density and produce multidimensional images of plasma depletion structures.
[1] Recently the Global Ultraviolet Imager (GUVI) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite has detected far ultraviolet (FUV) images of plasma depletions in the low-latitude and equatorial ionosphere. A model of GUVI observation geometry was developed to simulate radiance observations of a model ionosphere. We report on results in reconstructing multi-dimensional electron density profiles from GUVI brightness measurements through the use of statistical inversion techniques. These results enable the global observation and characterization of the structure of plasma bubbles and provide a means to quantify the level of depletion in the structures. Results are compared with corresponding JULIA observations for validation. The ability to globally image and characterize equatorial plasma bubbles provides a powerful tool for understanding this elusive space weather phenomenon. Citation: Comberiate,
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