Cray Signs $36 Million Contract to Upgrade Cray Systems at the European Centre for Medium-Range Weather Forecasts (ECMWF)

SEATTLE, WA--(Marketwired - Jan 25, 2016) -  Global supercomputer leader Cray Inc. (NASDAQ: CRAY) today announced the Company has signed a $36 million contract to upgrade and expand the Cray® XC™ supercomputers and Cray® Sonexion® storage system at the European Centre for Medium-Range Weather Forecasts (ECMWF). When the project is completed, the enhanced systems will allow the world-class numerical weather prediction and research center to continue to drive improvements in its highly-complex models to provide more accurate weather forecasts.

In June 2013, Cray announced it was awarded a contract to provide ECMWF with two Cray XC30™ supercomputers and a Cray Sonexion storage system. Under the terms of this new contract, Cray will expand and upgrade the supercomputers at ECMWF to Cray XC40™ systems, which will include next-generation Intel® Xeon® processors. ECMWF will also receive additional Cray Sonexion 2000 scale-out Lustre storage, and a 32-node Cray XC40-AC™ system with the next-generation of the Intel® Xeon Phi™ processor code-named "Knights Landing."

Located in Reading in the United Kingdom, ECMWF is focused on the development and operation of global models and data assimilation systems for the dynamics, thermodynamics and composition of the Earth's fluid envelope and interacting parts of the Earth system. An independent, intergovernmental organization supported by 34 nations, the center specializes in global numerical weather prediction up to a few weeks ahead. It also provides longer-range forecasts for up to a year ahead and runs the EU-funded Copernicus Atmosphere Monitoring and Climate Change Services.

"This upgrade will help us to improve the quality of the service we provide to our Member and Co-operating States," said ECMWF Director of Research Erland Källén. "It will enable us to develop high-resolution ensemble forecasts that improve the prediction of severe weather events in the medium range, up to about two weeks ahead. It will also make it possible to introduce improved data assimilation methods, allowing us to use more of the available Earth system observations, and to produce more detailed and better-quality atmospheric composition forecasts as well as high-quality climate datasets (re-analyses)."