The objective of this activity is to advance the technology development of a Solar Particle Radiation Advanced Warning System (SAWS) which can collate and combine outputs from modules providing forecasts of solar phenomena, solar proton event occurrence and solar proton flux and duration characteristics which can be tailored to the needs of different spacecraft and launch operators.

Increased radiation levels, as a result of space weather, has been recognised as an important risk for spacecraft and launcher operations. Recently threshold levels of solar energetic particle (SEP) flux and solar activity have been considered as a baseline criteria for launches. After the launch of Gaia in 2013, the transfer included manoeuvres reliant upon the AOCS star trackers, operating in interplanetary space and whose reliability could be seriously impacted by radiation storms known as Solar Particle Events (SPEs). As a result, launch criteria include radiation levels provided by nowcasting and forecasting of the environment. Pre-cursor systems have been developed with three forecasting modules which contain one or more models: solar flare prediction, SEP occurrence prediction and SEP characteristic prediction. The three modules shall be evolved further to include: 1/ Extension of the timeframe for the solar flare forecast to cover forecast horizons from 6 to 72 hours and shall cover the whole Earth-facing solar disk making use of previous forecasts where necessary to resolve issues of data quality at the Western limb of the solar disk. 2/ Inclusion of additional data including CME data and high energy solar electron data to improve the accuracy of SEP occurrence prediction tools. 3/ Combination of data-driven statistical analysis, in-situ data and shock-arrival time predictions to improve forecasts of the SEP peak flux and duration characteristics. A detailed validation of all modules shall be performed and the outputs shall be used to develop the Solar Particle Radiation Advanced Warning System (SAWS) - a system combining outputs from different models in a way justified by an analysis of their performance in different scenarios to provide forecasts evolving with time. The central component of SAWS shall include standardised interfaces for each of the three module classes in order to allow for easy comparison and easy incorporation of future model developments. This approach shall also allow for the de-coupling of the processing and provision of data required by forecasting modules to take advantage of the highest quality data. The central system shall also perform combinations of forecasts on a module level and the provision of consolidated results to the user through a single web portal.