Technologies developed at Reading to enable researchers from industry and academia to run simulations and calculations involving massive datasets have helped make the UK a world-leader in environmental data analytics.
Environmental scientists need mind-boggling volumes of data to do their work, gathered from satellites, radar, weather stations and aircraft all over the planet. These datasets are far too big for most institutions to be able to manage.
Research at Reading led by Professor Bryan Lawrence has developed technologies to handle millions of files and petabytes of data. Thanks in part to these advances, the UK’s large-scale environmental data analytics are the envy of the world.
One of the world’s largest online environmental data archives, CEDA (the Centre for Environmental Data Analysis) is underpinned by information systems incorporating Reading technology. CEDA is hosted on a unique computing facility called JASMIN which provides users with a processing power at the scale of petaflops (millions of times that of the average PC).
JASMIN can handle research that would previously have taken years in a matter of days and allows scientists to test as many ideas in a year as they would previously have managed over their whole careers.
For example, JASMIN has helped produce rainfall estimates and insurance products for over three million African farmers and a key government report on how biodiversity has changed over the past four decades, which involved crunching the numbers on 12,000 species using over 24 million records. The UK Met Office enlisted the help of Professor Lawrence to design their own mini version, SPICE, which supports Met Office research across both weather and climate.
Critical to important climate science, the Reading technology has also underpinned the research behind the Paris Agreement of the UN Framework for Climate Change and current and future assessments of the Intergovernmental Panel on Climate Change (IPCC).
Find out more
View the full impact case study on the REF 2021 website: New computer systems for exploiting big environmental data for worldwide usability, model and policy development