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Since January 1981, the Royal Observatory of Belgium (ROB) has operated the Sunspot Index Data Center (SIDC), the World Data Center for the Sunspot Index. From 2000, the SIDC obtained the status of Regional Warning Center (RWC) of the International Space Environment Service (ISES) and became the 'Solar Influences Data analysis Center'. As a data analysis service of the Federation of Astronomical and Geophysical data analysis Services (FAGS), the SIDC collects monthly observations from worldwide stations in order to calculate the International Sunspot Number, R i . The center broadcasts the daily, monthly, yearly sunspot numbers, with middle-range predictions (up to 12 months). Since August 1992, hemispheric sunspot numbers are also provided.

Aims This paper presents a H2020 project aimed at developing the world’s most advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and Coronal Mass Ejection (CME) evolution modelling with Solar Energetic Particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast Geomagnetically Induced Currents (GICs) and radiation on geospace. Methods We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely 1) data-driven flux-rope CME models, and 2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Uccle (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. Results The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.

This paper presents a review on the PECASUS service, which provides advisories on enhanced space weather activity for civil aviation. The advisories are tailored according to the Standards and Recommended Practices of the International Civil Aviation Organization (ICAO). Advisories are disseminated in three impact areas: radiation levels at flight altitudes, GNSS-based navigation and positioning, and HF communication. The review, which is based on the experiences of the authors from two years of running pilot ICAO services, describes empirical models behind PECASUS products and lists ground- and space-based sensors, providing inputs for the models and 24/7 manual monitoring activities. As a concrete example of PECASUS performance, its products for a post-storm ionospheric F2-layer depression event are analyzed in more detail. As PECASUS models are particularly tailored to describe F2-layer thinning, they reproduce observations more accurately than the International Reference Ionosphere model (IRI(STORM)), but, on the other hand, it is recognized that the service performance is much affected by the coverage of its input data. Therefore, more efforts will be directed toward systematic measuring of the availability, timeliness and quality of the data provision in the next steps of the service development.