14 Mar 2017 Santa Clara - DataDirect Networks' (DDN) industry-leading data storage solutions for high performance computing (HPC) are driving an increasing number of weather and climate research facilities around the globe to meet the needs for accuracy and timeliness of their forecasts and predictions. Weather and climate modelling centres are ingesting and producing ever-increasing volumes of data and utilizing some of the most powerful supercomputers and innovative HPC technologies available to improve model accuracy and granularity. As a data storage leader in HPC, DDN supports dozens of weather and climate supercomputing organisations and has experienced more than 60 percent growth in this sector customer base in the past year.
"DDN's unique ability to handle tough application I/O profiles at speed and scale gives weather and climate organisations the infrastructure they need for rapid, high-fidelity modelling", stated Laura Shepard, senior director of product marketing, DDN. "These capabilities are essential to DDN's growing base of weather and climate organisations, which are at the forefront of scientific research and advancements - from whole climate atmospheric and oceanic modeling to hurricane and severe weather emergency preparedness to the use of revolutionary, new, high-resolution satellite imagery in weather forecasting."
New technologies are ushering in higher resolutions as modeling and digital data collection increase in scope. For example, NOAA/NASA recently launched the GOES-16 satellite, which has four times the spatial resolution of previous systems. Weather and climate modelling centres are amassing vast volumes of data as they strive to improve the accuracy and timeliness of their models via more diverse, higher-resolution input data, large data assimilation, multi-model ensemble forecasts and rapid forecast dissemination.
Per the Research Department Center at the European Centre for Medium-Range Weather Forecasts (ECMWF), a DDN customer, weather and climate prediction are HPC applications with significant societal and economic impact, ranging from disaster response and climate change adaptation strategies to agricultural production and energy policy. Forecasts are based on millions of observations made every day around the globe, which are then input to numerical models. The models represent complex processes that take place on scales from hundreds of meters to thousands of kilometers in the atmosphere, the ocean, the land surface, the cryosphere and the biosphere. Forecast production and dissemination to users is always time-critical, and output data volumes already reach petabytes per week.
More than two dozen of the worlds top supercomputing sites rely on DDN Storage to meet the demanding requirements for weather and climate modeling, including the National Center for Atmospheric Research (NCAR), UK Met Office, Bureau of Meteorology Australia, National Oceanic and Atmospheric Administration (NOAA), Meteorological Research Institute (MRI) Japan, Japan's National Institute for Environmental Studies (NIES) and the European Centre for Medium-Range Weather Forecasts (ECMWF), among others.
"DDN Storage enables us to keep pace with the increased number of people trying to do very large data assimilation problems", stated Rich Loft, director of technology development in the computational and information systems laboratory at NCAR. "Earth system research is very data-intensive. NCAR is now able to do more to help scientists go beyond just studying phenomena to making actual predictions through data-intensive simulations that require larger I/O bandwidth and storage performance."
"The development of high-resolution models is a key component of the Met Office forecast systems; however, it has created a major spike in the need to store and process large volumes of critical data", stated Alan Mackay, IT infrastructure manager, UK Met Office. "By 2020, we estimate our storage archive will grow to about 300PB. With DDN, we can meet our performance and capacity requirements and ensure our scientists and researchers can store data for later analysis and quickly retrieve it when needed."
"The Bureau intends to use DDN's GS14KX to support its new data-intensive computing applications with integrated workflows to the Cray XC40 HPC environment for weather forecasting. We will also consolidate workflows from multiple legacy systems into a high-performance, replicated storage system", stated Tim Pugh, supercomputer programme director at the Bureau of Meteorology Australia.
With DDN's leadership in parallel file systems at scale and its deep expertise in Lustre and IBM Spectrum Scale environments, DDN is well positioned to support weather and climate organisations as their unabated data growth continues and as they require acceleration technologies such as flash native caching to further speed simulations and hot data computations. For example, DDN's Infinite Memory Engine solution can accelerate performance speeds by 3x and make application completion times predictable.
Technologies such as DDN's flash-native storage cache - Infinite Memory Engine - are boosting weather code performance to process more data, faster. For example, researchers at Ireland's high-performance computing centre, ICHEC, realized a 3x performance boost of the popular Weather Research and Forecasting (WRF) model, with no code changes and with one-tenth the required infrastructure when using Infinite Memory Engine. With this type of accelerated performance, supercomputers can provide a quicker turn time for atmospheric and ocean simulations so that severe weather events can be predicted with sufficient time for preparedness. More performance also allows for better fidelity, with grid sizes reduced to 1 to 2 km on the more granular models. Improved fidelity translates to more accurate forecasts, so localized phenomenon such as tornadoes, hailstorms, and intense downpours can be predicted at more useful scales.