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Current computer simulations of the Earth's climate capture only a fraction of the many intricate processes that shape our climate. (GOES satellite image, courtesy NASA/Goddard Space Flight Center/GOES.)
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Recent
advances in supercomputing have brightened the future of climate modeling, but
they also bring to light complicated questions about the fundamental workings
of our planet and our atmosphere.
Until recently,
atmospheric scientists could generate only a blurry picture of the interplay of
the mechanisms that determine how the Earth’s climate evolves. Even advanced
computers capable of doing hundreds of trillions of calculations per second—like
Intrepid, Argonne's IBM Blue Gene/P
supercomputer—represented the complexity of nature in simplified ways.
“There are
just so many different levels of interrelated physical, biological, and
chemical processes in nature that we’re only just now beginning to get a handle
on exactly how they all interact at a level as broad as the planet’s climate,”
said Rick Stevens, who leads Argonne’s work in computing, the environment and
life sciences. “When you add in the anthropogenic mechanisms—the ways in which
people are causing climate change—the challenge becomes even harder.”
The development
of even more advanced petascale and exascale supercomputers, capable of doing
quadrillions and eventually quintillions of calculations per second, has begun
to change the game of climate science and modeling. The best verifiable climate
models currently operate with data points that represent areas hundreds to thousands
of square miles across. In these models, an area the size of Lake Michigan would be represented by one or maybe two
data points; that’s it.
Because
new computers are capable of digesting and processing such vast quantities of
data, scientists at Argonne and at other
institutions around the world believe for the first time that they can generate
models with resolutions down to possibly a single square kilometer, or about a
third of a square mile.
“With most
of the old models, you can’t see clouds, you can’t see the effects of cities
and you can only handle a small range of terrain and vegetation types,” said
Stevens. “The move to petascale and exascale computing presents us with both an
opportunity and a challenge, which is finding a way to include the real
nitty-gritty physics and biology that for a long time our technology had forced
us to simplify.
“The
potential of these computers to improve our understanding of climate and
humanity’s role in shaping it is virtually unlimited,” Stevens added.
According
to Stevens, the next generation of climate models will be able to more
effectively integrate small-scale differences between soil types, vegetation
profiles, cloud cover, and even the environmental impacts of bacteria. The
development of a new generation of models with greater accuracy and fewer
assumptions depends on discovering the principles that regulate how these
phenomena interact and feed into one another, he said.
“Argonne’s
major strength comes from the fact that it employs researchers with expertise
on every level from the gene to the entire atmosphere,” said Anthony Dvorak,
director of Argonne’s Environmental Science
Division. “If you really want to understand climate, you have to be able to
connect all the dots.”
Argonne has also teamed with the University of Chicago to explore the possibility of
creating an institute that would house interdisciplinary teams that would work
on important problems in climate and other areas of environmental research. The
institute would host computer scientists, hydrophysicists, ecologists,
environmental scientists, microbiologists, chemists, and other experts who
would collaboratively tackle these problems.
"We’re
faced with a plethora of questions from a multitude of different disciplines,”
Stevens said. “Are we getting the ecosystems right? Are we getting the soil
chemistry right? Are we getting the reflectivity of the surface right? Each of
these factors plays a role in determining the others, and we need to find ways
to tie them all together.”
In
addition to improving the spatial resolution of climate models, petascale and
exascale supercomputers would also allow modelers to find ways to extend the
runs of their simulations. Because studying changes in climatic patterns
requires examining global trends over many years, model developers need to find
ways of dealing with the accumulation of uncertainties, according to Stevens.
“The climate is in a perpetual state of disequilibrium for which both
biological and physical processes are responsible,” he said. “By uniting these
processes through all the different levels in time and space, we can gain a
much better understanding of how Earth’s climate evolves.”
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