GPS phase scintillation associated with optical auroral emissions:first statistical results from the geographic South Pole

Ionospheric irregularities affect the propagation of Global Navigation Satellite System (GNSS) signals, causing radio scintillation. Particle precipitation from the magnetosphere into the ionosphere, following solar activity, is an important production mechanism for ionospheric irregularities. Particle precipitation also causes the aurorae. However, the correlation of aurorae and GNSS scintillation events is not well established in literature. This study examines optical auroral events during 2010-2011 and reports spatial and temporal correlations with Global Positioning System (GPS) L1 phase fluctuations using instrumentation located at South Pole Station. An all-sky imager provides a measure of optical emission intensities ([OI] 557.7nm and 630.0nm) at auroral latitudes during the winter months. A collocated GPS antenna and scintillation receiver facilitates superimposition of auroral images and GPS signal measurements. Correlation statistics are produced by tracking emission intensities and GPS L1 sigma indices at E and F-region heights. This is the first time that multi-wavelength auroral images have been compared with scintillation measurements in this way. Correlation levels of up to 74% are observed during 2-3hour periods of discrete arc structuring. Analysis revealed that higher values of emission intensity corresponded with elevated levels of sigma. The study has yielded the first statistical evidence supporting the previously assumed relationship between the aurorae and GPS signal propagation. The probability of scintillation-induced GPS outages is of interest for commercial and safety-critical operations at high latitudes. Results in this paper indicate that image databases of optical auroral emissions could be used to assess the likelihood of multiple satellite scintillation activity

CASES: A Smart, Compact GPS Software Receiver for Space Weather Monitoring

A real-time software-defined GPS receiver for the L1 C/A and L2C codes has been developed as a low-cost space weather instrument for monitoring ionospheric scintillation and total electron content. The so-called CASES receiver implements several novel processing techniques not previously published that make it well suited for space weather monitoring: (A) a differencing technique for eliminating local clock effects, (B) an advanced triggering mechanism for determining the onset of scintillation, (C) data buffering to permit observation of the prelude to scintillation, and (D) data-bit prediction and wipe-off for robust tracking. The receiver has been tested in a variety of benign and adverse signal conditions (e.g., severe ionospheric scintillation, both real and simulated); the results are presented here. The custom hardware platform on which the software runs is compact while remaining flexible and extensible. The CASES platform consists of a digital signal processor, an ARM microcontroller, and a custom-built narrow-band dualfrequency front end. Because the receiver is softwaredefined, it can be remotely reprogrammed via the internet or another communications link.Aerospace Engineering and Engineering Mechanic

Ionospheric data assimilation and forecasting during storms

Ionospheric storms can have important effects on radio communications and navigation systems. Storm time ionospheric predictions have the potential to form part of effective mitigation strategies to these problems. Ionospheric storms are caused by strong forcing from the solar wind. Electron density enhancements are driven by penetration electric fields, as well as by thermosphere-ionosphere behavior including Traveling Atmospheric Disturbances and Traveling Ionospheric Disturbances and changes to the neutral composition. This study assesses the effect on 1 h predictions of specifying initial ionospheric and thermospheric conditions using total electron content (TEC) observations under a fixed set of solar and high-latitude drivers. Prediction performance is assessed against TEC observations, incoherent scatter radar, and in situ electron density observations. Corotated TEC data provide a benchmark of forecast accuracy. The primary case study is the storm of 10 September 2005, while the anomalous storm of 21 January 2005 provides a secondary comparison. The study uses an ensemble Kalman filter constructed with the Data Assimilation Research Testbed and the Thermosphere Ionosphere Electrodynamics General Circulation Model. Maps of preprocessed, verticalized GPS TEC are assimilated, while high-latitude specifications from the Assimilative Mapping of Ionospheric Electrodynamics and solar flux observations from the Solar Extreme Ultraviolet Experiment are used to drive the model. The filter adjusts ionospheric and thermospheric parameters, making use of time-evolving covariance estimates. The approach is effective in correcting model biases but does not capture all the behavior of the storms. In particular, a ridge-like enhancement over the continental USA is not predicted, indicating the importance of predicting storm time electric field behavior to the problem of ionospheric forecasting.</p