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Wednesday, February 27, 2013

IBM Big Data Technology Helps South Korea's Meteorological Administration Increase Accuracy of Weather Forecasting

IBM News Release:


IBM Big Data Technology Helps South Korea's Meteorological Administration Increase Accuracy of Weather Forecasting

South Korea’s most powerful data storage system helps tackle weather’s data deluge
Seoul, SOUTH KOREA - 27 Feb 2013: South Korea's Meteorological Administration (KMA) and IBM (NYSE: IBM) today announced a project to help KMA and its affiliate, the National Meteorological Satellite Center (NMSC), tackle Big Data for better, more accurate and predictive environmental forecasting.
IBM Deep Thunder for the New York City Metropolitian Area
IBM is helping organizations all over the world manage the Big Data deluge for better environmental forecasting. An IBM Deep Thunder visualization of weather in the New York City Metropolitan Area. (Credit: IBM)
As South Korea’s national meteorological organization, KMA’s mission is to protect citizens' lives and property from natural disasters and support economic activities sensitive to environmental conditions.
However, weather forecasting is the proverbial data deluge. Every day KMA gathers more than 1.6 terabytes of meteorological data, including temperature and barometric pressure readings, wind speeds, images as well as observations from satellites, balloons, ships and aircraft. One of the key sources of data is Korea’s first communication, ocean and meteorological satellite – dubbed Cheollian – managed by the National Meteorological Satellite Center.
To allow for the torrents of data to be stored and available for real-time analysis, IBM has provided KMA and NMSC with the latest IBM storage technologies capable of recording 20 gigabytes (equivalent to 400,000 web pages) of data per second. With a total storage capacity of 9.3 petabytes (1 million gigabytes) it is South Korea’s most powerful data storage system to date.
The new infrastructure enables KMA and NMSC to analyze data more quickly and accurately than previously possible. By incorporating maps and historical data, KMA is able to develop tailored weather forecasts for each of South Korea’s nine regions. Processing data in real time enables immediate updates on weather conditions. For example, meteorologists can predict more precisely the trajectory of a typhoon or the coverage of the ‘Hwangsa’ - the yellow sand storms originating in Mongolia and Northern China that cause environmental problems in Korea in the spring season.
The system is so powerful that it paves the way for localized weather forecasting services for clients in certain regions or cities, such as emergency service providers, hotels, golf courses and farms as well as related services such as weather insurance for outdoor events.
“IBM’s Smarter Storage system provides a powerful platform for Big Data analytics helping us to provide more accurate and timely weather forecasting services,” said Gyoung-Hyun Lee, Director of National Meteorological Supercomputing, KMA. 
IBM is partner to organizations around the world that are faced with effectively managing and drawing insight from the torrents of data produced by an increasingly instrumented, interconnected and intelligent world – an area often referred to as Big Data.
“The volume of meteorological and satellite data is so vast that it requires the most powerful technologies on earth” said Jung-Uk Tak, Systems & Technology Group Leader, IBM Korea. "IBM’s smarter computing system helps KMA and NMSC to take a proactive approach to changing weather conditions, supporting its mission of protecting and enhancing lives and business.”
The new system at KMA includes an IBM General Parallel File System (GPFS) - a high-performance enterprise file management platform. IBM has also provided a high-capacity data storage system to NMSC. Together, the systems provide consistent and secure access to a common set of data from multiple servers outperforming single file server solutions. IBM worked with local business partner Moasys to provide the solution.

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