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JASMIN Science Case (2016)

Lawrence, Bryan N.; Townsend, Poppy. 2016 JASMIN Science Case (2016). Didcot, Centre for Environmental Data Analysis, 35pp.

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Abstract/Summary

JASMIN exists to provide the UK environmental sciences the compute facility they need to deliver cost-effective world class science and impact from the exploitation of data. A £17M investment is needed for the next generation of JASMIN, to maintain the UK’s scientific and competitive edge, facilitating the exploitation of world-class environmental science to meet the global societal challenges of the future. Such an investment would build on international leadership and would support: • The merging of extremely large environmental data sets with the latest earth system models: building downstream growth in space-based environmental services; and underpinning international collaborations. • The transformation of data into information products and services; JASMIN provides the foundation for the UK environmental information ecosystem: investment will provide greater access to knowledge for a range of users. • Enabling researchers to better support government usage of environmental hazard data resulting in large-scale societal benefit e.g. development of earthquake monitoring systems. • The next generation of earth observation and environmental simulation, including for the next phase of the World Climate Research Programme (WCRP) global model intercomparison project (CMIP6). The updated JASMIN will deliver cost-effective, world-class environmental science, exploiting data for societal benefit. It will be a cutting-edge novel computational environment, ensuring highly-skilled people are retained in the UK from systems engineers to environmental data users, from data scientists and analysts to mathematicians.

Item Type: Publication - Report (Other)
UKCEH and CEH Sections/Science Areas: Unaffiliated
Funders/Sponsors: NERC
NORA Subject Terms: Earth Sciences
Ecology and Environment
Atmospheric Sciences
Computer Science
Related URLs:
Date made live: 20 Oct 2022 15:19 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/533309

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