December 21, 2007
CHAPEL HILL, N.C., Dec. 19 -- Researchers at the Renaissance Computing Institute (RENCI) have compiled new data on ocean floor and coastal typography that will help, state and local emergency managers and scientists who model, predict, plan for and respond to floods and storms along the North Carolina coast.
The dataset, dubbed TopoBathy because it combines bathymetry (ocean floor topography) and coastline topography information, will be used to create more accurate storm surge model application, including storm surge forecasts and higher quality floodplain maps.
"The physical features of the earth's surface -- whether it is offshore and underwater or on land -- are very important in determining the response of the coastal ocean to strong storm events," said Rick Leuttich, director of the Institute for Marine Sciences, a University of North Carolina research center in Morehead City.
"Bathymetric and topographic features block waves and currents, dissipate energy, channel water movement and generally effect how easy it is for a strong storm to move water. Thus it is critical to create accurate databases of this information for use in modeling storm surge."
Leuttich, who collaborates with RENCI on coastal modeling, is one of the developers of the advanced circulation model (ADCIRC) storm surge model, and using the TopoBathy dataset as input for ADCIRC will allow the model to more accurately predict how deep and how far inland water will surge during a major coastal storm.
The TopoBathy dataset also will be used as input for new high-resolution coastal storm models, which RENCI is producing in order to create updated floodplain maps of coastal areas. That project, funded by the state's Division of Emergency Management in cooperation with the Federal Emergency Management Agency (FEMA) began last August with RENCI working to produce more than 1,000 tracks of possible coastal storms in order to create floodplain maps that take advantage of new high-resolution data and models and account for new coastal developments. With RENCI compiling the TopoBathy dataset this fall, RENCI's disaster research team decided to integrate this unique, multidimensional data into the floodplain models to further enhance them.
"As we began computing the models for the floodplain mapping project, it became apparent that this new dataset would greatly enhance our model result," said Ken Galluppi, RENCI's manager of emergency management and disaster research projects. "We are now running our floodplain models using the better datasets, and we will turn those models over to the state early next year for them to develop updated floodmaps for FEMA. Combining multiple terrestrial and marine data into a single dataset at this resolution is a major improvement over existing data and should improve the resulting floodplain maps."
The coastal topography data was derived from a Light Detection and Ranging (LIDAR) survey system through the state-funded North Carolina Floodplain Mapping Program. The LIDAR is mounted on an airplane and collects three-dimensional data points from light reflected off objects such as buildings, trees and the ground.
The National Geospatial Development Center, the U.S. Geological Survey, the Army Corp of Engineers, and the National Oceanic and Atmospheric Administration also provided TopoBathy data.
About RENCI
The Renaissance Computing Institute brings together computer and discipline scientists, artists, humanists, industry leaders, entrepreneurs, state leaders and educators for collaborations designed to reshape science, the economy, the state of North Carolina and the world. RENCI leverages its expertise and resources in leading edge computing, networking and data technologies to ignite innovation and find solutions to previously intractable problems. Founded in 2004 as a major collaborative venture of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the state of North Carolina, RENCI is a statewide virtual organization. For more, see www.renci.org.
-----
Source: RENCI
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
Read more...
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
Read more...
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Read more...
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
Read more...
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
Read more...
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
Read more...
May 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
Read more...
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.