August 22, 2015

The Future of Forecasting

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.

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