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Journal: NCAR Supercomputer ‘Up Against Complex Physics of Programming Thousands of Weather Variables’

Cheyenne supercomputer (credit: NCR)

The “Cheyenne” supercomputer, an Intel-powered SGI system installed in 2017 at the National Center for Atmospheric Research (NCAR) in Boulder, is at the heart of a major article on climate change appearing in yesterday’s Wall Street Journal. The article, based on extensive interviews with climate scientists at NCAR and other organizations, asserts that HPC simulations “are running up against the complex physics of programming thousands of weather variables such as the extensive impact of clouds.”

The result is conflicting and changing climate models that are “bedeviling policy” at national, regional and international governing bodies.

“As world leaders consider how to limit greenhouse gases,” wrote the Journal’s Robert Lee Holtz, “they depend heavily on what computer climate models predict. But as algorithms and the computer they run on become more powerful—able to crunch far more data and do better simulations—that very complexity has left climate scientists grappling with mismatches among competing computer models.”

The story focuses on the initial findings, released in 2018, of the Community Earth System Model 2 (CESM2) funded in large part by the U.S. National Science Foundation. For nearly five years, an international group of scientists rewrote more than 2 million lines of climate simulation code “adding more-intricate equations for clouds and hundreds of other improvements. They tested the equations, debugged them and tested again.”

But the 2018 findings significantly contradicted “decades of previous models had predicted, and future temperatures could be much higher than feared—perhaps even beyond hope of practical remedy.”

 Mesa Laboratory at NCAR

“We thought this was really strange,” Gokhan Danabasoglu, chief scientist for the climate-model project at the Mesa Laboratory at NCAR, told the Journal. “If that number was correct, that was really bad news.”

The scientists concluded the results of the new simulations had been thrown off track by faulty assumptions regarding the impact of clouds on climate as the world warms. “The old way is just wrong, we know that,” NCAR physicist Andrew Gettelman told the Journal. “I think our higher sensitivity is wrong too. It’s probably a consequence of other things we did by making clouds better and more realistic. You solve one problem and create another.”

So the scientists have continued to refine their CESM2 model, continued to develop their algorithms based on additional climate data. “They have abandoned their most extreme calculations of climate sensitivity, but their more recent projections of future global warming are still dire—and still in flux,” the Journal reported.

At the center of the story is the Cheyenne system, an SGI ICE XA cluster powered by 145,152 Intel Xeon processor cores in 4,032 dual-socket nodes (36 cores/node) and 313 TB of total memory. Data storage components provided by DataDirect Networks (DDN) give the GLADE system a total usable capacity of 38 PB. The DDN system transfers data at the rate of 200 GBps, more than twice as fast as the previous file system’s rate of 90 GBps.

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