This NSF award to UCLA funds U.S. researchers participating in a project competitively selected by the G8 Research Councils Initiative on Multilateral Research through the Interdisciplinary Program on Application Software towards Exascale Computing for Global Scale Issues. This is a pilot collaboration among the U.S. National Science Foundation, the Canadian National Sciences and Engineering Research Council (NSERC), the French Agence Nationale de la Recherche (ANR), the German Deutsche Forschungsgemeinschaft (DFG), the Japan Society for the Promotion of Science (JSPS), the Russian Foundation for Basic Research (RFBR),and the United Kingdom Research Councils (RC-UK), supporting collaborative research projects selected on a competitive basis that are comprised of researchers from at least three of the partner countries.
This international project targets the rapidly growing demands of climate science data management as models increase the precision with which they depict spatial structure and the completeness with which they describe a vast range of physical processes. The ExArch project is principally a framework for the scientific interpretation of multi-model ensembles at the peta-and exa-scale. It applies a strategy, a prototype infrastructure and demonstration usage examples in the context of the imminent CMIP5 archive, which will be the largest of its kind ever assembled in this domain. It will attach the ExArch framework to the CORDEX experiment, pushing beyond CMIP5 in resolution, albeit at regional scale.
This international project involving collaborating researchers in six countries will explore the challenges of developing a software management infrastructure which will scale to the multi-exabyte archives of climate data which are likely to be crucial to major policy decisions by the end of the decade. In the short term, strategies will be evaluated by applying them to existing data archives. The NSF funding to UCLA primarily supports the extension of the information model to earth observational data and the validation of regional climate models with observational data.