Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation - PAGER
EU Horizon 2020
Overview
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.
Overview of the PAGER Workpackages
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 870452 (PAGER). |