Since the first attempt to numerically model the solar corona by Pneuman and Kopp (1971) considerable progress has been made and 3-D models for reconstructing the solar corona and solar wind are common nowadays. Moreover, the availability of detailed observations makes it possible to produce more realistic simulations by including observational data through the boundary conditions. The first 3-D coronal models which include measurements of the line-of-sight magnetic field as boundary conditions are in the meanwhile a decade old. When modelling the solar corona within the phyical constraints of magnetohydrodynamics, additional source terms have to be included in the equations in order to get a realistic description of the solar wind. Those source terms can include the contribution of Alfvén waves, thermal conduction, radiative losses, or/and more ad hoc source terms in order to reproduce the heating of the corona and acceleration of the solar wind. Since the solar magnetic field is playing an important role in the structure of the solar wind, the source terms are often made dependent on the magnetic field. Although the models can fit the in-situ data at 1AU in relative good agreement, they are often fine-tuned for a specific Carrington rotation and finding the appropriate model parameters is often non-trivial. In this presentation we will give an overview of the latest developments in the modelling of the solar wind in the MHD framework. We also discuss a new wind model based on a more general polytropic flow, in order to be physically more consistent. Polytropic models are still very popular because of their simplicity, but they do not reproduce the bimodal structure of the solar wind. Totten et al. (1995), who used Helios 1 data to obtain an average value for the polytropic index of the solar wind, concluded that the solar wind behaved fairly polytropic between 0.3 AU and 1 AU, with 1.46 as an average value for the polytropic index. It turned out that the polytropic index was rather independent of the solar wind type. The new wind model reproduces the solar wind characteristics at 1AU. The advantages and disadvantages of the new model are summarised.

Coronal mass ejections (CMEs) are one of the most violent manifestations in the solar system. They are ejections of a huge amount of plasma carying frozen-in magnetic field. Both the initiation and propagation of CMEs through the solar wind are not well understood. The Space Weather Modeling Framework (SWMF), developed at the University of Michigan, is a high performance simulation tool to model a wide variety physics domains ranging from solar corona and heliosphere to the magnetosphere, ionosphere and thermosphere of the Earth and can run these models in a coupled fashion. The SWMF is continuously improved to better model the space weather phenomena. For the CME initialization, we are currently modeling the emergence of flux ropes from the convective zone into the corona. Optically thin radiative losses in conjunction with an empirical heating model based on x-ray emission and the unsigned magnetic flux at the photosphere is used to obtain the convective cells. We will show that buoyant flux ropes with a strong poloidal magnetic field that rise through the photosphere into the corona can produce strong polarity inversion lines. Shear flows are produced by the Lorentz force during the flux emergence and the magnetic fields are anchored at the convective downdrafts during the eruption. A better understanding of the coronal heating is of vital importance for understanding of CME propagation. Turbulent Alfven waves have been suggested as a possible mechanism both to heat the corona and to accelerate the solar wind. Wave pressure gradient is an important contribution to the solar wind acceleration, while wave dissipation dominates the heating. Hence, a consistent model of the Alfven wave turbulence in the solar wind should be based on frequency-binned wave transport equations describing the momentum and energy exchange between the turbulent waves and the background plasma. We will present the latest results with this solar wind model that is implemented in the SWMF.

As the international space community turns to space exploration once again, and plans manned missions to the Moon and Mars, exposure of future astronauts and electronics to radiation in the hostile conditions of interplanetary space is of utmost concern. The Earth-Moon-Mars Radiation Environment Module (EMMREM) is a comprehensive numerical framework for characterizing and predicting the space radiation environment of the inner Heliosphere, developed at Boston University in cooperation with several other institutions. Current studies of energetic particle events with this system allow us not only to predict time-histories of high-energy particle fluxes at different locations in the heliosphere, but also to gain better understanding of the physical effects of the propagation of energetic particles, as well as how different types of Solar Energetic Particle (SEP) events and interplanetary conditions influence the radiation dose quantities. Thus, this numerical system is well fit for both research and for operational/applied purposes in the space weather field.

We present the EMMREM system, and its data products. We demonstrate its capabilities through a modeling study of a SEP event in which we simulate proton flux and radiation dose time-histories. We compare the model and its performance with in-situ particle flux data, and summarize the current direction of research and operations for the EMMREM team. We also present the online version of the system, on which users can run their own simulations and make flux and dose predictions. Ultimately, this system will be able to make near real-time predictions for particle radiation throughout the Heliosphere.

Solar energetic particle (SEP) events are a major hazard in the space environment. For reasons of rapid data availability, soft X-ray bursts play an important role in short term forecasting of SEP events. While there is an overall empirical correlation between the peak fluxes of soft X-ray bursts, notably from the western solar hemisphere, and SEP peak fluxes measured by the GOES spacecraft, a remarkable number of even very intense soft X-ray bursts (GOES class X) in the western hemisphere are not followed by SEP events. We give an overview of the association between intense soft X-ray bursts and SEP events and then discuss SEP-less X-class soft X-ray bursts in the western hemisphere. We show that many of these bursts belong to the category of 'confined' flares, where confined means that the energy release occurs near the centre of the flaring active region. While microwave emission demonstrates the vigorous acceleration of electrons to relativistic energies, these events have no radio counterpart at metre or longer waves. This suggests that the accelerated particles remained confined in closed coronal magnetic structures. Radio emission therefore provides important information on the geoeffectiveness, in terms of energetic particles, of large solar flares.

EGNOS is the European Space Based Augmentation System to GPS and GLONASS. EGNOS has been developed under a tripartite agreement between the European Space Agency (ESA), the European Commission (EC) and Eurocontrol. It was Europe?s first activity in the field of Global Navigation Satellite Systems (GNSS) infrastructure, paving the way to Galileo, the full global satellite navigation system under development in Europe.

The EGNOS system provides augmentation to GPS users in three main areas (1) providing accurate corrections to the broadcast GPS satellite ephemeris (2) providing a real time empirical model of the ionospheric delays in the region covered by the system and (3) providing integrity information to the previous information in the form of reliable estimates of the confidence of the ephemeris corrections and ionospheric delays.

In particular, the ionospheric information broadcast by EGNOS allows the single frequency GPS navigation users to accurately correct their measurements for ionospheric delay effects. Those ionospheric corrections are provided to the users as a set of vertical ionospheric delays in a set of grid points covering the EGNOS service area. And the estimates of the confidence of the ionospheric corrections are provided as grid ionospheric vertical error bounds. Vertical delays and error bounds are mapped to the actual line of sight of the user through a predetermined interpolation method and mapping function.

EGNOS entered its pre-operational phase in 2006 and it is progressively being brought into service. During 2008 several qualification reviews took place before the system is transferred to the European Commission. The certification of the system and the system operator, to enable a safety-of-life service to be provided for aviation, is planned to finish along 2010.

On top of the usage of EGNOS for Civil Aviation navigation services, the EGNOS broadcast information can be freely acquired and used (the so-called "EGNOS Open Service") by any user with a suitable receiver (available in low cost mass-market receivers) or through connection with the EGNOS Data Access Server (EDAS) or with the EGNOS Message Server (EMS).

Hence EGNOS real time estimates of the ionospheric delays and error bounds over the EGNOS Service Area (the European Civil Aviation Conference land masses) can be accessed as a permanent, reliable, accessible and real time source of ionospheric information for a variety of applications, among which we could include Space Weather monitoring.

This paper describes in detail the ionospheric information provided by EGNOS as well as the potential way to get access to these data.

In order to obtain the EGNOS ionospheric information, to be broadcast, the EGNOS Central Processing Facility incorporates precise state of the art algorithms for real time ionospheric monitoring and Hardware Bias estimation. The methods used within this processing facility to estimate the EGNOS ionospheric corrections will be also summarised within this paper, providing, additionally, sample examples of the ionospheric data obtained with EGNOS.

There is now substantial evidence showing that wave-particle interactions play a major role in the loss and acceleration of electrons in the outer radiation belt. Here we present a new dynamic global radiation belt model that includes radial diffusion, and electron acceleration and loss due to wave-particle interactions. We describe how wave-particle interactions are included in the model and show how the model is driven by a time series of geomagnetic indices and data from near geostationary orbit. The model outputs include the relativistic electron flux throughout the outer electron radiation belt. We run the model and compare results against electron flux measured by the CRRES satellite. We show that during quiet periods after a magnetic storm the model reproduces the formation of the slot region between the inner and outer radiation belts when wave-particle interactions due to plasmaspheric hiss are included. However, the results depend critically on the angular distribution of the waves. We show that during a storm driven by a coronal mass ejection electron acceleration by whistler mode chorus is required to reproduce the increase in the relativistic electron flux. For a storm driven by a fast solar wind stream the model is able to reproduce the increase in flux, but cannot reproduce the rapid flux drop out. The results emphasise the importance of including accurate models of wave-particle interactions with radial diffusion. Finally, we discuss how the model can be adapted for space weather applications to specify the radiation belt flux in near real time.

The Dynamic Radiation Environment Assimilation Model (DREAM) has recently been implemented for real-time space weather applications. Real-time applications impose some constraints on DREAM but the assimilation of data in physics-based models produces information that has significantly more spatial coverage, accuracy, and utility than either the data or model alone. The minimum data input for DREAM is real-time electron fluxes from a single satellite but data from multiple satellites can improve the model accuracy - particularly when different orbits are included. Data from different sources and different data latencies can also be assimilated asynchronously. Even data that is several days old can affect the real-time assimilated state so, when new data become available, DREAM reprocesses the intervening time period, updating both past and current forecasts. Unlike simple time series of particle fluxes or geomagnetic indices, assimilative models, like DREAM, produce multi-dimensional data products that require innovations in user interfaces. One example is output that specifies the space environment along a user-selected orbit and time interval. More sophisticated applications can determine the relationship of the current environment to known statistics and extremes in order to quickly flag environments that have known (or suspected) correlations with anomalies.

Radio remote sensing of the heliosphere using spacecraft radio signals has been used to study the near-sun plasma in and out of the ecliptic, close to the sun, and on spatial and temporal scales not accessible with other techniques. Studies of space-time variations in the inner solar wind are particularly timely because of the desire to understand and predict space weather, which can disturb satellites and systems at 1AU and affect human space exploration. Here we demonstrate proof-of-concept of a new radio science application for spacecraft radio science links. The differing transfer functions of plasma irregularities to spacecraft radio up- and downlinks can be exploited to localize plasma scattering along the line of sight. We demonstrate the utility of this idea using Cassini radio data taken in 2001-2002. Under favorable circumstances we demonstrate how this technique, unlike other remote sensing methods, can determine center-of-scattering position to within a few thousandths of an AU and thickness of scattering region to less than about 0.02 AU. This method, applied to large data sets and used in conjunction with other solar remote sensing data such as white light data, has space weather application in studies of inhomogeneity and nonstationarity in the near-sun solar wind.