Forecast in Space Weather modeling mostly ignore the fact everything is driven by the sun, that is basically unpredictable. Propagating observed solar dynamics to Earth is questionable, it depends on models whose boundary conditions we are incapable of constraining. We are limited to data at L1, giving a one hour lead time and neural net type forecasts of controlling parameters ( e.g. Kp) that govern the physics of our best models. Nowcasts are better: advanced data assimilation techniques with physics based models show great fidelity in reproducing the real radiation belt (RB) environment. Operational use of such Nowcasts is limited by lack of high quality real-time data beyond GEOS. The FARBES project is different: it limits its ambition to simple, achievable prediction goals that are of utility to satellite operators, while avoiding the pitfalls of past projects. We hold that while it may be impossible to accurately predict the break of a space weather event, once an event has started we have the tools to predict subsequent behavior and to update our predictions during the event. While we may not be able to globally predict in detail the subsequent dynamic behavior, we can provide actionable forecasts for satellite operators on a few key event characteristics: a. Time to most severe environment b. Most severe Flux reached c. Time to the end of event These characteristics were deemed most useful by spacecraft operator representatives at ESWW16 [http://www.stce.be/esww13/contributions/public/S5-O1/S5-O1-03-PitchfordDave/FORECASTINGTHEPERFECTSTORM.ppt]. We overcome the data-assimilation nowcast limitations by using physics based models driven by simple, affordable and reliable ground-based real-time inputs only, we overcome our inability to accurately forecast magnetospheric drivers by using a scenario-driven forecast approach for RB dynamics starting with nowcast and is constantly refined during an event by the ongoing availability of real-time model inputs

The PAGER project will provide space weather predictions that will be initiated from observations on the Sun and will predict radiation in space and its effects on satellite infrastructure. Real-time predictions and a historical record of the dynamics of the cold plasma density and ring current will allow for evaluation of surface charging, and predictions of the relativistic electron fluxes will allow for the evaluation of deep dielectric charging. We will provide a 1-2 day probabilistic forecast of ring current and radiation belt environments, which will allow satellite operators to respond to predictions that present a significant threat. As a backbone of the project, we will use the most advanced codes that currently exist. Codes outside of Europe will be transferred to operation in Europe, such as components of the state-of-the-art Space Weather Modelling Framework (SWMF). We will adapt existing codes to perform ensemble simulations and will perform uncertainty quantifications. The project will include a number of innovative tools including data assimilation and uncertainty quantification, new models of near-Earth electromagnetic wave environment, ensemble predictions of solar wind parameters at L1, and data-driven forecast of the geomangetic Kp index and plasma density. The developed codes may be used in the future for realistic modelling of extreme space weather events. Consultations with stakeholders will be central for the project. We will reach out to scientific, industry and government stakeholders and will tailor our products for the stakeholder’s needs and requirements. Dissemination of the results will play a central role in the project. Our team includes leading academic and industry experts in space weather research, space physics, empirical data modelling, and space environment effects on spacecraft from Europe and the US.

The SafeSpace project aims at advancing space weather nowcasting and forecasting capabilities and, consequently, at contributing to the safety of space assets through the transition of powerful tools from research to operations (R2O). This will be achieved through the synergy of five well-established space weather models (CNRS/CDPP solar disturbance propagation tool, KULeuven EUHFORIA CME evolution model, ONERA Neural Network tool, IASB plasmasphere model and ONERA Salammbô radiation belts code), which cover the whole Sun – interplanetary space – Earth’s magnetosphere chain. The combined use of these models will enable the delivery of a sophisticated model of the Van Allen electron belt and of a prototype space weather service of tailored particle radiation indicators. Moreover, it will enable forecast capabilities with a target lead time of 2 to 4 days, which is a tremendous advance from current forecasts, which are limited to lead times of a few hours. SafeSpace will improve radiation belt modelling through the incorporation into the Salammbô model of magnetospheric processes and parameters of critical importance to radiation belt dynamics. Furthermore, solar and interplanetary conditions will be used as initial conditions to drive the advanced radiation belt model and to provide the link to the solar origin and the interplanetary drivers of space weather. This approach will culminate in a prototype early warning system for detrimental space weather events, integrating information all the way from the Sun to the inner magnetosphere. With a major European space company, Thales Alenia Space (TAS-E), as a Partner in SafeSpace, we will define indicators of particle radiation of use to space industry and spacecraft operators. Indicator values will be generated by the advanced radiation belt model and the performance of the prototype service will be evaluated by TAS-E and by other stakeholders, who will be selected in collaboration with the External Advisory Panel.