Researchers at Pennsylvania State University (PSU) and the U.S. National Oceanic and Atmospheric Administration (NOAA) have developed a hurricane forecasting system that improves on current methods.
The system uses a computer model that can more explicitly resolve a hurricane's inner-core dynamics and structure. It also analyzes Doppler radar data taken by planes flying through the hurricane. In addition, a data assimilation method using an ensemble Kalman filter has improved how the system processes Doppler radar data.
"By combining the forecast and the observations in a new optimal way, we greatly improved the model initial fields over the existing methods used by the NOAA operational hurricane models," says PSU professor Fuqing Zhang.
The researchers used the Ranger supercomputer at the Texas Advanced Computing Center to forecast the track and intensity of every major storm in the Atlantic during the 2011 hurricane season.
Zhang’s forecasts improved intensity predictions by an average of 20 percent to 40 percent over the official forecasts for 2008-2011 storms that have the airborne Doppler radar data. The forecasts require the hurricane simulations to simultaneously run dozens of times, which requires thousands of computer processors working in parallel, and is only possible on a few dozen existing supercomputing systems.
From Texas Advanced Computing Center
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