A new satellite being launched this October could bring about keener, more expansive hurricane predictions - and fewer surprises for us all.
That's according to a new study led by researchers at Pennsylvania State University, including meteorologist Fuqing Zhang, regarding GOES-R, a geostationary satellite.
"For decades, geostationary satellites such as the GOES series have been the primary tool to monitor severe weather like storms and hurricanes in real time," noted Zhang. "They have helped people see what's going on in the present, but, until now, we as a community have not been able to tap into these resources to guide us to predict future severe weather."
Geostationary satellites are a type that remain in orbit above a fixed Earth location. They take images of meteorological information, including cloud formations. GOES stands for Geostationary Operational Environmental Satellites and the program is operated by the National Oceanic and Atmospheric Administration with NASA contributions.
In terms of predicting hurricanes, data types and amounts have been an existing challenge. It would be helpful to be able to gather more information regarding the intensity of a hurricane. This data would include wind speeds, surface pressure and water vapor under the cloud areas of the hurricane's eyewall (its area of most powerful winds). However, "brightness temperature" is part of the currently collected data, demonstrating radiation quantities emitted by Earth objects and existing in the atmosphere at different degrees of infrared.
"At some frequencies, water vapor absorbs moderate amounts of radiation passing through it, at other frequencies it absorbs most of that radiation, and at other frequencies it absorbs hardly any at all. Unlike water vapor, clouds strongly absorb radiation at all of these frequencies," noted Eugene Clothiaux, study co-author and a meteorologist at Penn State. "Comparing measurements at different frequencies leads to information about water vapor and clouds at different altitudes above the Earth. This begins to tell us about the physical structure of water vapor fields and clouds, including those in the area around a hurricane."
The team showed in their study that brightness data can reveal more than expected. They located correlations between brightness temperature measurements and storm information, such as sea level pressure and wind speed below the hurricane.
"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."
The research was published in the journal Geophysical Research Letters.
