The COSMIC radio occultation mission represents a revolution in atmospheric sounding from space, with precise, accurate, and all-weather global observations useful for weather, climate, and space weather research and operations. GPS Signal GPS Satellite

The ionosphere is a highly dynamic medium that exhibits weather disturbances at all latitudes, longitudes, and altitudes, and these disturbances can have detrimental effects on both military and civilian systems. In an effort to mitigate the adverse effects, we are developing a physics‐based data assimilation model of the ionosphere and neutral atmosphere called the Global Assimilation of Ionospheric Measurements (GAIM). GAIM will use a physics‐based ionosphere‐plasmasphere model and a Kalman filter as a basis for assimilating a diverse set of real‐time (or near real‐time) measurements. Some of the data to be assimilated include in situ density measurements from satellites, ionosonde electron density profiles, occultation data, ground‐based GPS total electron contents (TECs), two‐dimensional ionospheric density distributions from tomography chains, and line‐of‐sight UV emissions from selected satellites. When completed, GAIM will provide specifications and forecasts on a spatial grid that can be global, regional, or local. The primary output of GAIM will be a continuous reconstruction of the three‐dimensional electron density distribution from 90 km to geosynchronous altitude (35,000 km). GAIM also outputs auxiliary parameters, including NmF2, hmF2, NmE, hmE, and slant and vertical TEC. Furthermore, GAIM provides global distributions for the ionospheric drivers (neutral winds and densities, magnetospheric and equatorial electric fields, and electron precipitation patterns). In its specification mode, GAIM yields quantitative estimates for the accuracy of the reconstructed ionospheric densities.

[1] Recently, nighttime ultraviolet (UV) observations obtained by IMAGE FUV and TIMED GUVI instruments have revealed a longitudinal wave number four pattern in the nighttime airglow intensity and in the position of the equatorial anomalies during equinox and high solar flux conditions. In the present study, we have extended this work and determined the longitudinal variability of the low-latitude total electron content (TEC) climatology during different geophysical conditions with a special emphasis on the longitudinal wave number four structure in the low-latitude ionosphere. We have used more than 5 million low-latitude TOPEX TEC observations covering the entire 13 years of TOPEX TEC data from August 1992 until October 2005. This data set was used to determine the local time, seasonal, solar cycle, and geomagnetic activity dependence of the longitudinal variability of TEC at equatorial and low latitudes, and in particular, to address the existence and evolution of the wave number four longitudinal pattern under these conditions. Our study shows that the wave number four pattern is created during the daytime hours at equinox and June solstice but is absent, or washed out by other processes, during December solstice. During equinox the wave number four pattern is created around noon with well-defined longitudinal enhancements in the low-latitude TEC. These enhancements, which are symmetric about the geomagnetic equator during this season, last for many hours and can be clearly seen past midnight. The longitudinal patterns are found to be nearly identical between the vernal (March/April) and autumnal (September/October) equinoxes and largely independent of the solar cycle conditions. The wave number four pattern is also observed during geomagnetically active conditions, indicating that the processes that create this pattern are also present during active times. The variations between the well-defined longitudinal maxima and minima are of the order of 20%. During June solstice, the wave number four pattern is also observed in the afternoon hours but, in contrast to the equinox cases, it exhibits a strong hemispheric asymmetry and is not observed during the night. The low-latitude TEC exhibits clear longitudinal variations during December solstice, with large daytime enhancements over the east Asian and Pacific regions and a third enhancement emerging in the afternoon over the Atlantic Ocean, but a clear wave number four pattern is not observed during this season. Although the equatorial and low-latitude TEC values exhibit clear longitudinal patterns during all seasons, a significant amount of scatter remains in the TEC data that is not accounted for by changes in the solar cycle, the season, or the local time or by the longitudinal variability. This remaining scatter is largest near the poleward edges of the anomalies and is of the order of 40%.

Our primary goal is to construct a real-time data assimilation model for the ionosphere-plasmasphere system that will provide reliable specifications and forecasts. A secondary goal is to validate the model for a wide range of geophysical conditions, including different solar cycle, seasonal, storm, and substorm conditions. OBJECTIVES We propose to develop a software program that will provide for a Global Assimilation of Ionospheric Measurements (GAIM). GAIM will use a physics-based ionosphere-plasmasphere model as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The program will provide specifications and forecasts on a specified spatial grid that can be global, regional, or local (50 km x 50 km). The specifications/forecasts will be in the form of 3-dimensional electron density distributions from 90 km to geosynchronous altitudes (35,000 km). Auxiliary plasma parameters will also be provided, such as N m F 2 , h m F 2 , N m E, h m E, and slant and vertical TEC. In its specification mode, GAIM will provide quantitative estimates for the accuracy of the reconstructed ionospheric densities. The measurements GAIM will assimilate include: (1) Slant path TECs between 80-90 ground receivers and the Global Positioning System (GPS) satellites; (2) Occultation data from a satellite constellation such as COSMIC; (3) TECs associated with the CIT network; (4) Bottomside N e profiles from digisondes associated with the Air Force DISS network; (5) In situ plasma parameters from the SSIES instrument package on the DMSP satellites; and (6) Line-of-sight UV emissions and deduced plasma parameters from the Naval Research Laboratory's SSUSI and SSULI instruments. GAIM will have a modular construction, so that new data types can be readily assimilated when they become available. APPROACH Our approach is to use a two-step process to obtain a 3-D ionospheric reconstruction. First, certain data sets will be assimilated so that the inputs (neutral parameters, electric fields, precipitation) to the physics-based ionosphere-plasmasphere model can be adjusted, within expected errors, to match observations, and then the physics-based model will be run in order to obtain a 3-D N e distribution that is consistent with the measured inputs. This first step should result in realistic ionospheric density features. Next, this simulated ionosphere-plasmasphere system will be used as a starting point for an electron density reconstruction using all of the different data types that pertain to N e and a Kalman filter assimilation technique. The use of a simulated ionosphere-plasmasphere system will provide

[1] The Utah State University Gauss-Markov Kalman Filter (GMKF) was developed as part of the Global Assimilation of Ionospheric Measurements (GAIM) program. The GMKF uses a physics-based model of the ionosphere and a Gauss-Markov Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) observations. The physics-based model is the Ionospheric Forecast Model (IFM), which accounts for five ion species and covers the E region, F region, and the topside from 90 to 1400 km altitude. Within the GMKF, the IFM derived ionospheric densities constitute a background density field on which perturbations are superimposed based on the available data and their errors. In the current configuration, the GMKF assimilates slant total electron content (TEC) from a variable number of global positioning satellite (GPS) ground sites, bottomside electron density (N e ) profiles from a variable number of ionosondes, in situ N e from four Defense Meteorological Satellite Program (DMSP) satellites, and nighttime line-of-sight ultraviolet (UV) radiances measured by satellites. To test the GMKF for real-time operations and to validate its ionospheric density specifications, we have tested the model performance for a variety of geophysical conditions. During these model runs various combination of data types and data quantities were assimilated. To simulate real-time operations, the model ran continuously and automatically and produced three-dimensional global electron density distributions in 15 min increments. In this paper we will describe the Gauss-Markov Kalman filter model and present results of our validation study, with an emphasis on comparisons with independent observations.