New high-tech weather satellites launched in the past two years aren't just providing meteorologist a better look at what's happening now, but could be a key to better severe weather predictions.
Penn State University researchers were able to take some of the enhanced weather data coming in via the new GOES-16 satellite, and incorporate it into new forecast models to try and better predict severe thunderstorms and tornado development in the Midwest.
Their experiments were done in reverse -- they ran model simulations on past events to see if the models would accurately predict how the storms eventually formed. And the results were promising: The model was indeed able to forecast supercell thunderstorms with atmospheric conditions that are very conducive to tornadoes, researchers said.
Forecasting tornadic thunderstorms is difficult, but important because these events are especially quick to form. Thunderstorms account for 40 percent of all severe weather events in the United States, causing 14 percent of damage and 17 percent of related deaths, according to the National Climate Data Center.
“For many storms in the United States, we have good radar data, however, it’s very hard using any of the existing technologies to capture the environmental and storm conditions before the storm totally develops,” said Fuqing Zhang, professor of meteorology and director of Penn State's center for Advanced Data Assimilation and Predictability Techniques. “We’re able to extend the warning time for these events because the satellite can look at the field even before the clouds form and our models can ingest that information to improve and advance forecasts."
Researchers say tornado lead time has increased from an average of 3 minutes to 14 minutes over the past 40 years, but they say they can do better.
"For many people, 14 minutes isn’t enough,” said David Stensrud, head of the Department of Meteorology and Atmospheric Science at Penn State. “If you have a big sports stadium or a hospital it takes more than 14 minutes to prepare for the weather threat. There is certainly a need for more advanced warnings. Our research indicates that by combining data assimilation and high-resolution models we can get lead times beyond 30 minutes. Doubling the lead time would have huge potential societal impacts.”
Better models and better data supplied by GOES-16 could also reduce false alarm rates, Stensrud said.
Researchers are now working with the National Weather Service and NOAA to ingest the satellite data for widespread use in forecasting severe weather.