Satellite Could Provide Better Data for Hurricane Prediction

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Using data from GOES-13, the team completed a proof-of-concept experiment, analyzing data from Hurricane Karl in 2010. They used the Penn State real-time hurricane analysis and prediction system that Zhang and his team have been developing and refining for nearly a decade.

"Hurricane prediction models work by chunking individual blocks of the hurricane and this starts from the initial information that is fed into the model," said Zhang. "We then run an ensemble of possible outcomes for the hurricane using different variables to estimate uncertainty and this tells us how the hurricane might behave. If we are able to use a higher resolution for the initial state, this could allow us to vastly improve hurricane predictions in the future."

GOES-13 provides data at a resolution of 2.5 miles, and GOES-R will increase that to under 0.6 miles for some frequencies of brightness temperature. The increase in resolution is especially important because of the size of hurricanes. The eyewall, the layer of clouds surrounding the eye, varies in size but is roughly 6 miles thick. Using GOES-13 brightness temperatures with 2.5-mile resolution, the eyewall is often grouped together with other parts of the storm, with only one or two brightness temperature measurements from only the eyewall itself. A 0.6 mile resolution brightness temperature measurement would allow for up to 10 eyewall measurements to be fed into prediction models as separate chunks of information instead of grouped together with other parts of the storm.

This new data source could have implications on the longstanding challenge of predicting hurricane intensity, Zhang said. Researchers know that wind speed and other levels of activity near the eye of the hurricane are linked to future intensity, but actually collecting these data is difficult. Today, NOAA uses airborne reconnaissance to collect data, but this is only possible when the storm is within flying distance. Satellites that constantly monitor the oceans at high spatial and temporal resolution and with many frequencies of brightness temperature, like GOES-R, could remove that constraint.

 "Geostationary satellites are there all the time, which makes them ideal for capturing the initial and evolving states of hurricanes, including the crucial information in the cloudy region of the storm," said Zhang. "Using satellite data more effectively could potentially revolutionize hurricane monitoring and prediction for many years."

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