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This report presents final results of a 2-year AFRL-sponsored project whose objective was to develop advanced modeling and data assimilation capabilities for the ionosphere and upper atmosphere. In the course of this project Fusion Numerics developed a new global three-dimensional numerical model of the ionosphere, novel ionospheric data assimilation software and methodology, and an infrastructure for obtaining and managing IGS reference station data for the system., The original document contains color images.

Report developed under SBIR Contract AF Topic AF02-038. This interim report describes progress in developing a new numerical model of the ionosphere and related tangent-linear and adjoint models necessary for developing ionospheric data assimilation capabilities., The original document contains color images. All DTIC reproductions will be in black and white.

The application of data assimilation methodology to terrestrial problems in meteorology, atmospheric physics and physical oceanography has already been described extensively within this book. Data assimilation, the combination of observations and numerical models which provide physical constraints, organize and propagate the observational information which is introduced, also offers significant potential advantages for the analysis of atmospheric data from other planets. The Solar System provides seven examples of thick neutral atmospheres in addition to that of the Earth: Mars, Venus and Saturn's moon Titan, which all have relatively large rocky cores surrounded by thinner atmospheres, like the Earth, and four largely gaseous Giant Planets, Jupiter, Saturn, Uranus and Neptune. In recent years satellites have been placed in orbit about Mars in particular, but also Venus, Jupiter and Saturn, in contrast to the relatively rapid fly-by missions in the initial stages of the exploration of the Solar System. These spacecraft provide the potential for long sequences of atmospheric observations. Together with the necessary advances in numerical modelling of planetary atmospheres, these new missions have provided an opportunity for the application of data assimilation techniques for the analysis of planetary observations. As described in this chapter, data assimilation has now been employed with some success in the context of the atmosphere of Mars and more ambitious studies are planned for the future. Assimilation in these unfamiliar and, compared to Earth, data-poor environments also provides valuable lessons for the development of terrestrial assimilation, especially in situations where it is vital to extract the maximum information from a limited observational record.

The application of data assimilation methodology to terrestrial problems in meteorology, atmospheric physics and physical oceanography has already been described extensively within this book. Data assimilation, the combination of observations and numerical models which provide physical constraints, organize and propagate the observational information which is introduced, also offers significant potential advantages for the analysis of atmospheric data from other planets. The Solar System provides seven examples of thick neutral atmospheres in addition to that of the Earth: Mars, Venus and Saturn's moon Titan, which all have relatively large rocky cores surrounded by thinner atmospheres, like the Earth, and four largely gaseous Giant Planets, Jupiter, Saturn, Uranus and Neptune. In recent years satellites have been placed in orbit about Mars in particular, but also Venus, Jupiter and Saturn, in contrast to the relatively rapid fly-by missions in the initial stages of the exploration of the Solar System. These spacecraft provide the potential for long sequences of atmospheric observations. Together with the necessary advances in numerical modelling of planetary atmospheres, these new missions have provided an opportunity for the application of data assimilation techniques for the analysis of planetary observations. As described in this chapter, data assimilation has now been employed with some success in the context of the atmosphere of Mars and more ambitious studies are planned for the future. Assimilation in these unfamiliar and, compared to Earth, data-poor environments also provides valuable lessons for the development of terrestrial assimilation, especially in situations where it is vital to extract the maximum information from a limited observational record.