Figure 1. The IFS
alternative dynamical core option: Left, an example of an unstructured
mesh for a
low-resolution model. Right, the domain decomposition used in IFS;
each patch
represents the grid area owned by an MPI task.
Leading weather agency turns to Titan to advance science of
prediction
Knowing how the weather will behave in the near future is
indispensable for countless human endeavors.
(August 22, 2015) According
to the National Oceanic and Atmospheric Administration (NOAA), extreme weather
events have caused more than $1 trillion in devastation since 1980 in the
United States alone. It’s a staggering figure, but not nearly as staggering as
the death toll associated with these events—approximately 10,000 lives.
The prediction of low-probability, high-impact events such
as hurricanes, droughts, and tornadoes, etc., has proven to have profound
economic and social impacts when it comes to limiting or preventing mass
property damages and saving human lives. But regardless of the aim, predicting
weather has always been a tricky business.
However, thanks to one of the world’s most powerful
computers, it’s becoming less tricky and more accurate. Researchers from the
European Centre for Medium-Range Weather Forecasts (ECMWF) have used the Titan
supercomputer, located at the US Department of Energy’s (DOE’s) Oak Ridge
National Laboratory, to refine their highly lauded weather prediction model,
the Integrated Forecasting System (IFS), in hopes of further understanding
their future computational needs for more localized weather forecasts.
ECMWF is both a research institute and a 24/7 operational
service, supported by 34 European countries. In the US, the IFS is perhaps best
known as the weather model that gave the earliest indication of Hurricane
Sandy’s path in 2012. Sandy is the second costliest hurricane in US history and
the most powerful of the 2012 season. “Our ensemble forecasting system
predicted the landfall of superstorm Sandy on the US East Coast more than 7
days in advance,” said Erland Källén, director of research at ECMWF.