There is a growing appreciation that the environmental conditions that we call space weather impact the technological infrastructure that powers the coupled economies around the world. With that comes the need to better shield society against space weather by improving forecasts, environmental specifications, and infrastructure design. We recognize that much progress has been made and continues to be made with a powerful suite of research observatories on the ground and in space, forming the basis of a Sun-Earth system observatory. But the domain of space weather is vastextending from deep within the Sun to far outside the planetary orbits -and the physics complex -including couplings between various types of physical processes that link scales and domains from the microscopic to large parts of the solar system. Consequently, advanced understanding of space weather requires a coordinated international approach to effectively provide awareness of the processes within the Sun-Earth system through observation-driven models. This roadmap prioritizes the scientific focus areas and research infrastructure that are needed to significantly advance our understanding of space weather of all intensities and of its implications for society. Advancement of the existing system observatory through the addition of small to moderate state-of-the-art capabilities designed to fill observational gaps will enable significant advances. Such a strategy requires urgent action: key instrumentation needs to be sustained, and action needs to be taken before core capabilities are lost in the aging ensemble. We recommend advances through priority focus (1) on observation-based modeling throughout the Sun-Earth system, (2) on forecasts more than 12 hrs ahead of the magnetic structure of incoming coronal mass ejections, (3) on understanding the geospace response to variable solar-wind stresses that lead to intense geomagnetically-induced currents and ionospheric and radiation storms, and (4) on developing a comprehensive specification of space climate, including the characterization of extreme space storms to guide resilient and robust engineering of technological infrastructures. The roadmap clusters its implementation recommendations by formulating three action pathways, and outlines needed instrumentation and research programs and infrastructure for each of these. An executive summary provides an overview of all recommendations.

The operational data analysis of the GPS radio occultation experiment aboard the German CHAMP (CHAllenging Minisatellite Payload) satellite mission is described. Continuous Near-Real-Time processing with average time delay of @5 hours between measurement and provision of analysis results is demonstrated. A delay of less than 3 hours is reached for individual events. This is made possible by using an operationally operated ground infrastructure, consisting of a polar downlink station, a globally distributed fiducial GPS ground network, a precise orbit determination facility, an automated occultation processing system and an advanced data center (the Information System and Data Center at GFZ, ISDC). The infrastructure was installed within the CHAMP and the German GPS Atmosphere Sounding Project (GASP). More than 120,000 globally distributed occultation measurements were automatically analysed during 2001 and 2002. A set of @46,000 vertical profiles of refractivity, temperature and water vapor is validated with meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the global radiosonde network. The mean temperature bias in relation to the analyses is less then 0.4 K between 10 and 35 km, the mean deviation of the refractivity is <0.5%. A height dependent standard deviation of @1 K at 10 km and @2 K at 30 km is observed. This result is confirmed by comparing @6,000 CHAMP occultations with corresponding radiosonde measurements. A negative bias of the refractivity in relation to the analyses up to @5% in the Tropics is found in the lower troposphere. It corresponds to mean meridional dry biases of the specific humidity up to @30%. It is shown, that the application of a heuristic retrieval method, based on the Canonical Transform method and the sliding spectral approach, reduces the refractivity bias on average by a factor of @2. The corresponding bias in the specific humidity is reduced by a factor of @3. In mid-latitudes almost no more refractivity bias out of the planetary boundary layer is observed. This is shown by a comparison of

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The paper deals with initial analyzes of radio occultation measurements of the ionosphere carried out on board the CHAMP satellite since 11 April 2001. The accuracy of the operationally retrieved electron density profiles has been estimated by comparing with independent measurements. The derived ionospheric key parameters such as f0F2 and hmF2 agree with a standard deviation of 18 and 13%, respectively. It is shown that the CHAMP data products can essentially contribute to the establishment of operational data sets of the global electron density distribution for developing and improving global ionospheric models and to provide operational space weather information.

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[1] Precise navigation and positioning using GPS/GLONASS/Galileo require the ionospheric propagation errors to be accurately determined and corrected for. Current dual-frequency method of ionospheric correction ignores higher order ionospheric errors such as the second and third order ionospheric terms in the refractive index formula and errors due to bending of the signal. The total electron content (TEC) is assumed to be same at two GPS frequencies. All these assumptions lead to erroneous estimations and corrections of the ionospheric errors. In this paper a rigorous treatment of these problems is presented. Different approximation formulas have been proposed to correct errors due to excess path length in addition to the free space path length, TEC difference at two GNSS frequencies, and third-order ionospheric term. The GPS dual-frequency residual range errors can be corrected within millimeter level accuracy using the proposed correction formulas.

[1] Ground-based ionosphere sounding measurements alone are incapable of reliably modeling the topside electron density distribution above the F layer peak density height. Such information can be derived from Global Positioning System (GPS)-based total electron content (TEC) measurements. A novel technique is presented for retrieving the electron density height profile from three types of measurements: ionosonde ( f o F 2 , f o E, M 3000 F 2 , h m f 2 ), TEC (GPS-based), and O + -H + ion transition level. The method employs new formulae based on Chapman, sech-squared, and exponential ionosphere profilers to construct a system of equations, the solution of which system provides the unknown ion scale heights, sufficient to construct a unique electron density profile at the site of measurements. All formulae are based on the assumption of diffusive equilibrium with constant scale height for each ion species. The presented technique is most suitable for middle-and high-geomagnetic latitudes and possible applications include: development, evaluation, and improvement of theoretical and empirical ionospheric models, development of similar reconstruction methods utilizing low-earth-orbiting satellite measurements of TEC, operational reconstruction of the electron density on a real-time basis, etc.