[1] With the advent of the Global Positioning System (GPS) measurements (from both ground-based and satellite-based receivers), the number of available ionospheric measurements has dramatically increased. Total electron content (TEC) measurements from GPS instruments augment observations from more traditional ionospheric instruments like ionospheric sounders and Langmuir probes. This volume of data creates both an opportunity and a need for the observations to be collected into coherent synoptic scale maps. This paper describes the Ionospheric Data Assimilation Three-Dimensional (IDA3D), an ionospheric objective analysis algorithm. IDA3D uses a three-dimensional variational data assimilation technique (3DVAR), similar to those used in meteorology. IDA3D incorporates available data, the associated data error covariances, a reasonable background specification, and the expected background error covariance into a coherent specification on a global grid. It is capable of incorporating most electron density related measurements including GPS-TEC measurements, low-Earth-orbiting ''beacon'' TEC, and electron density measurements from radars and satellites. At present, the background specification is based upon empirical ionospheric models, but IDA3D is capable of using any global ionospheric specification as a background. In its basic form, IDA3D produces a spatial analysis of the electron density distribution at a specified time. A time series of these specifications can be created using past specifications to determine the background for the current analysis. IDA3D specifications are able to reproduce dynamic features of electron density, including the movement of the auroral boundary and the strength of the trough region.

With the current data availability from both ground‐ and space‐based sources, the network of ground‐based Global Positioning System (GPS) receivers, GPS occultation receivers, in situ electron density sensors, and dual‐frequency beacon transmitters, the time is right for a comprehensive review of the history, current state, and future directions of ionospheric imaging. A brief introduction and history of ionospheric imaging is presented, beginning with computerized ionospheric tomography. Then, a comprehensive review of the current state of ionospheric imaging is presented. The ability of imaging algorithms to ingest multiple types of data and use advanced inverse techniques borrowed from meteorological data assimilation to produce four‐dimensional images of electron density is discussed. Particular emphasis is given to the mathematical basis for the different methods. The science that ionospheric imaging addresses is discussed, and the scientific contributions that ionospheric imaging has made are described. Finally, future directions for this research area are outlined.

The Ionospheric Connection Explorer, or ICON, is a new NASA Explorer mission that will explore the boundary between Earth and space to understand the physical connection between our world and our space environment. This connection is made in the ionosphere, which has long been known to exhibit variability associated with the sun and solar wind. However, it has been recognized in the 21st century that equally significant changes in ionospheric conditions are apparently associated with energy and momentum The Ionospheric Connection Explorer (ICON) mission Edited by Doug Rowland and Thomas J. Immel B T.J. Immel

[1] There is great interest in understanding how the thermosphere-ionosphere system responds to geomagnetic storms. New insights are possible using the new generation of fully coupled three-dimensional models, together with extensive ionospheric databases. The period of postsolar maximum geomagnetic storms in October and November 2003 were some of the largest storms ever recorded. In this paper, we explore how the thermosphere-ionosphere system responded to the onset of the 20 November 2003 geomagnetic storm, using the NCAR TIMEGCM. The model simulates dramatic changes in the thermospheric equatorward winds, O/N 2 , and corresponding ionospheric electron densities. The model is used as a framework to interpret an increase in the observed ionospheric total electron content, and F region electron density, in the European and North African sector, in terms of changes in the neutral gas. Corresponding compositional effects observed by the GUVI instrument on the TIMED satellite lend credence to the model results. We describe some of the important physical processes that will affect planning for the utilization of measurements from the Geospace investigations in NASA's Living With a Star Program. The study illustrates the value of measuring both the neutral and ionized gases, of obtaining quasi-global views from imaging instruments, and the synergy between satellite data, ground-based measurements, and models.

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.

Ionospheric F‐region patches are 2–10 larger than background electron densities in the polar ionosphere. The EISCAT Svalbard incoherent radar (ESR) observed a sequence of patches between 2000–2200 UT on 12 December 2001. In this paper the source of these structures is investigated using several other data sets, together with a convection‐driven trajectory analysis. The data are assimilated into Ionospheric Data Assimilation Three Dimensional (IDA3D). The background model used is the National Center for Atmospheric Research‐Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (NCAR TIMEGCM). The trajectory analysis is based on maps of ionospheric convection obtained from the Assimilative Mapping of Ionospheric Electrodynamics (AMIE). In addition to patches, a tongue of ionization (TOI) is investigated. It is shown that patches formed part of the TOI. It is tempting to conclude the TOI and the patches originate at midlatitudes. However, the IDA3D and trajectory analysis suggest that they were transported toward noon from the morning and afternoon sectors near 62° geographic latitude. Thus for this case the TOI and patches did not originate at midlatitudes. This work represents advances in the field of patch research. A new capability to perform an analysis of patch origin and fate, using three‐dimensional (3‐D) ionospheric assimilation and 2‐D trajectory analysis codes, is demonstrated for a sequence of patches observed 12 December 2001. The current resolution of the technique is not able to identify detailed patch formation mechanisms. However, by it can track the plasma back in time to locations and times where patch formation mechanisms operate.

1] Recent developments in tomographic imaging allow the use of GPS satellite data to image the Earth's ionosphere. Ground-based GPS receivers monitor the Earth's ionosphere continuously, and a comprehensive database of ionospheric measurements suitable for tomographic processing now exists. The tomographic inversion of these GPS data in a three-dimensional time-dependent inversion algorithm can reveal the spatial and temporal distribution of ionospheric electron density. This new technique is unique for studying ionospheric physics because it gives a time-continuous near-global view of the ionosphere. The tomographic algorithms have been under continuous development for several years and are now yielding new geophysical results. Two fundamentally different algorithms (Multi-instrument Data Analysis System and Ionospheric Data Assimilation Three-Dimensional) are presented. They show the ionospheric impact of two major space weather events during the recent solar maximum. Results obtained from these two algorithms are similar, which provides additional confidence in the accuracy of the images.

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] 557.7 nm and 630.0 nm) 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 σφ 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 2–3 hour periods of discrete arc structuring. Analysis revealed that higher values of emission intensity corresponded with elevated levels of σφ. 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.