Today DDN announced that an increasing number of weather and climate research facilities around the globe use the company’s storage solutions to meet the needs for accuracy and timeliness of their forecasts and predictions. Weather and climate modeling centers 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 organizations 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 organizations the infrastructure they need for rapid, high-fidelity modeling,” said Laura Shepard, senior director of product marketing, DDN. “These capabilities are essential to DDN’s growing base of weather and climate organizations, 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 modeling centers 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 world’s 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. Examples include:
NCAR utilizes DDN’s SFA14K high-performance hyper-converged storage platform to drive the performance and deliver the capacity needed for scientific breakthroughs in climate, weather and atmospheric-related science to power its “Cheyenne” supercomputer. Sponsored by the National Science Foundation, NCAR brings together researchers from more than 100 colleges and universities and thousands of scientists from across the globe to identify the risks and opportunities associated with changes in the Earth’s atmosphere – from protecting aircraft from wind shear, to investigating changes in the earth’s ozone layer, to linking weather to factors that shape epidemics.
DDN Storage enables us to keep pace with the increased number of people trying to do very large data assimilation problems,” said 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.”
UK Met Office, the United Kingdom’s national weather service, conducts weather forecasting and climate prediction research designed to protect lives and increase prosperity. The institution’s 500 scientists conduct research using data-intensive, high-resolution models to increase forecast accuracy and provide a deeper understanding of climate change. DDN Storage supports UK Met’s Managed Archive Storage System (MASS), which is predicted to grow to about 300 petabytes of weather and climate research data by 2020.
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,” said 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 of Meteorology, Australia’s national weather, climate and water agency, relies on DDN’s GRIDScaler Enterprise NAS storage appliance to handle its massive volumes of research data to deliver reliable forecasts, warnings, monitoring and advice spanning the Australian region and Antarctic territory.
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,” said Tim Pugh, supercomputer program 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 organizations 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 center, 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.
