The government has confirmed it is ready to give a £60m boost in its funding to the European Space Agency (ESA) over the next two years.
The offer was revealed by chancellor George Osborne, speaking at the Royal Society, where he also highlighted the need for the UK to lead the world in big data and energy-efficient computing innovation.
Osborne said the additional funding was intended for “high value scientific and industrial programmes which will benefit the UK,”.
Currently, the UK funding is channelled to high-value areas such as “telecoms, earth observation and meteorological satellites”, the chancellor told the Royal Society.
This will take its funding from an average of £170m per year to £240m over the next two years.
While space programmes frequently conjure up images of moon landings, eye-catching planetary fly-bys and Martian rovers, the ESA has quietly gone about the business of delivering programmes focussed on more near-term benefits.
A good example is its space weather monitoring programme – one of those high-value areas the chancellor alighted on.
This week, scientists across Europe met to discuss future developments in the monitoring of space weather at an ESA-organised event.
There, ESA was showcasing the new near-real-time space weather service, which offers customers up-to-the-minute data on plasma, magnetic fields, radiation and particle flow. Such services should ultimately help businesses prepare for space weather disruption – an important consideration in today's super-connected world.
Back to earth, and the chancellor was also keen that the UK didn't miss out on the booming interest in big data and energy-efficient computing.
British involvement in projects at Cern, such as the Large Hadron Collider, had helped cement the UK's capabilities in the world of big data, Osborne said.
“The next generation of scientific discovery will be data-driven discovery, as previously unrecognised patterns are discovered by analysing massive data sets,” he said.
“We are good at the algorithms needed to handle these large data sets.”
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