(Bloomberg) — In a week when heavy rains in Louisiana led to eight deaths and forced more than 20,000 people from their homes, the U.S. said it can now tap a supercomputer to better forecast flood events across all of the nation’s waterways.
The new tool will let forecasters target potentially life and property threatening downpours street by street, giving people more time to get out of harm’s way or prepare for the worst if they can’t, said Thomas Graziano, director of NOAA’s Office of Water Prediction.
“It’s NOAA’s first foray into high-performance computing for water prediction,” Graziano said in a telephone interview. “It’s going to provide information in all kinds of areas where we have none today. It’s a quantum leap forward.”
The new computer model will draw data from more than 8,000 U.S. Geological Survey sites to simulate 2.7 million locations in the 48 contiguous states, generating hourly river and stream forecasts, the National Oceanic and Atmospheric Administration said in a statement Tuesday. Earlier computer models only used 4,000 sites every few hours.
With the new system, forecasters can pinpoint floods as much as three days in advance, Graziano said. The model, when used with other forecasting systems, should be able to look out 10 to 30 days for potential storms that could cause flooding.
Hydro Blind
Since Aug. 8, 20.13 inches (51 centimeters) of rain has fallen on Baton Rouge, according to the National Weather Service, pushing rivers, streams and bayous to major flood levels. More than 20,000 people have been forced from their homes by the rains, which come on the heals of severe floods in Texas and West Virginia earlier this year.
“There are many parts of this country where we are hydro blind,” Graziano said.
The goal is to be able to predict potential floods days in advance. The model was developed along with the National Centers for Atmospheric Research, the Consortium of Universities for the Advancement of Hydrologic Sciences and the National Science Foundation, among others.
Bloomberg News by Brian K. Sullivan
