![]() Forecasting previously relied on clear-sky observations, due to challenges in diagnosing the complex physical processes within clouds, the scientists said. The all-sky method, developed by Penn State’s Center for Advanced Data Assimilation and Predictability Techniques, can assimilate data from all weather conditions, including cloudy and rainy skies. Geostationary Operational Environmental Satellite, GOES-16, to predict severe thunderstorms through the all-sky radiance method. The researchers were previously the first to use data from the new U.S. “While these results need to be evaluated across a large spectrum of cases, they point to a path forward that could extend lead times for severe weather events, thereby providing improved information to the public when severe weather strikes.” “Our results suggest that each sensor provides unique information about the storm,” said David Stensrud, head of the Department of Meteorology and Atmospheric Science at Penn State. The best results came from combining infrared brightness temperature observations from satellites, and radial wind velocity observations from radar, the scientists reported in the American Meteorological Society journal Monthly Weather Review. The scientists assimilated satellite and radar data separately and simultaneously to see which combination could best recreate conditions during a large storm system that struck Wyoming and Nebraska in 2017. ![]() ![]() We found, for at least one severe weather event, assimilating satellite and radar simultaneously leads to the best forecasts.”ĭata assimilation is a statistical method used to paint the most accurate possible picture of current weather conditions, important because even small changes in the atmosphere can lead to large discrepancies in forecasts over time. “The question was whether these two types of observations would complement each other if combined together. “We know satellites have an advantage in producing forecasts earlier, and radar has more confidence in where clouds should be and where thunderstorms will be moving,” said Yunji Zhang, assistant research professor in meteorology and atmospheric sciences at Penn State. Combing data from cutting-edge geostationary satellites and traditional weather radar created a path toward earlier, more accurate warnings, according to Penn State researchers who studied supercell thuderstorms in the Midwest. Every minute counts when it comes to predicting severe weather.
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