Data assimilation method offers improved hurricane forecasting

Using a technique developed at Penn State, researchers were better able to predict models for forecasting Hurricane Harvey. This approach uses all-sky radiance, which uses infrared technology to capture data in all-weather conditions.

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Operational models for severe weather forecasting predicted Hurricane Harvey would become a Category 1 hurricane in 2017, according to the University Corporation for Atmospheric Research. Instead, it became a massive Category 4 just before it made landfall, tying Hurricane Katrina for the costliest hurricane on record.

Now a new approach developed at Penn State's Center for Advanced Data Assimilation and Predictability Techniques can forecast the intensity and trajectory of Hurricane Harvey, according to researchers at Penn State and the National Oceanographic and Atmospheric Administration.

The approach used data from the GOES-16 satellite, coupled with Penn State's all-sky radiance method, which more accurately modeled Hurricane Harvey. The data is called "all-sky" because it captures data in all weather conditions, including clouds and rain.

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