Inputs from Underwater Gliders Used to Improve Accuracy of Forecast Models

In recent years, the models used by hurricane forecasters to predict the paths of storms have gained considerable accuracy. However, they are still not so exceptional at accurate prediction of the intensity of a storm.

Currently, underwater gliders, used by scientists from the University of Georgia Skidaway Institute of Oceanography, have become part of a national effort to enhance the accuracy of forecast models by including more data from the ocean with the help of marine robots.

Two storms from the 2018 hurricane season offer examples of how rapidly storm intensity can vary. It was predicted that Hurricane Florence would be a Category 5 storm. However, the storm weakened considerably before landfall in North Carolina as a Category 1 storm on September 14^th, 2018. By contrast, after a month, Hurricane Michael strengthened from a Category 1 to a Category 5 storm within two days and hit the Florida panhandle on October 10^th, 2018.

Hurricanes feed off heat from warm ocean waters such as those that found in the Caribbean, as well as in the Gulf Stream and shallow waters off the Southeast United States, called the South Atlantic Bight. This could be an enormous source of energy for emerging storms. While heat is conveyed between the ocean and atmosphere at the ocean’s surface, it is also crucial to gain insights into the amount of subsurface heat.

Collecting Valuable Information

Places where warm waters near the surface lie over cooler water near bottom, winds and other factors can mix up the water, cooling the surface and limiting the heat available to the atmosphere. Satellite data provides a nice picture of where the surface ocean is warm, but the subsurface temperature field remains hidden.

Catherine Edwards, Researcher, Skidaway Institute of Oceanography, University of Georgia

Autonomous underwater vehicles, also called gliders, can gather valuable information exactly in this sense. Gliders, which are torpedo-shaped crafts, can be loaded with sensors and commissioned on underwater missions to gather oceanographic data.

Apart from other parameters, the gliders measure salinity and temperature while profiling up and down in the water. The gliders are fitted with satellite phones and surface periodically to transfer the data recorded during missions lasting from weeks to even months.

“This regular communication with the surface allows us to adapt the mission on the fly, and also process and share the data only minutes to hours after it has been measured,” stated Edwards. “By using a network of data contributed by glider operators around the world, the U.S. Navy and other ocean modelers can incorporate these data into their predictions, injecting subsurface heat content information into the hurricane models from below.”

The 2018 hurricane season offered Edwards and her colleagues a fortuitous chance to show the value of glider data. Two gliders were deployed by Edwards in advance of the Hurricane Florence—one off the North Carolina coast and the other farther south, close to the South Carolina-Georgia state line.

The ocean temperature forecasts of the models were found by the gliders to be considerably off target. Edwards calls attention to charts with a comparison of the predictions from ocean models operated in the United States and Europe with the real temperatures two days before Florence made landfall.

On the storm path’s south side, the models estimated that the ocean had a slightly fresh, warm layer overtopping saltier, cooler water below. However, the glider unraveled that the water column was well-blended and, overall, fresher and warmer than estimated.

On the storm’s north side, warm, well-mixed water was predicted by the models. However, the glider found a sharp change in temperature below the surface, with a considerably cooler layer near-bottom. And the most fascinating part was just how stratified the water was.

More than a Unique View

There is almost a 14-degree Celsius (approximately 25 degrees Fahrenheit) error that the glider corrects in the model. The model and data agree near-surface, but the models that don’t use the glider data all miss the colder, saltier layer below. The model that incorporated glider data that day is the only one that captures that vertical pattern.

Catherine Edwards, Researcher, Skidaway Institute of Oceanography, University of Georgia

Besides offering a unique view of the ocean, the gliders fly on their own and report data regularly, before, during, and after a hurricane, thereby rendering them a robust tool for understanding the storms’ effects.

“The glider data is being used in real time,” Edwards added. “These real time observations can improve our hurricane forecasts right now, not just in a paper to be published a year from now.”

As part of a glider observatory run by Edwards for the Southeast Coastal Ocean Observing Regional Association, she and collaborator Chad Lembke, from the University of South Florida, launched a third glider in August in advance of Florence. It was recovered just a little more than a week before Florence’s landfall and helped define the Gulf Stream’s edge, which is a crucial ocean feature very difficult for models to get right.

Ready for the 2019 Hurricane Season

So it’s possible that the data from that glider already improved any tropical storm predictions that use ocean models and take that glider data into account, because the Gulf Stream is so important in our region.

Catherine Edwards, Researcher, Skidaway Institute of Oceanography, University of Georgia

Edwards collaborates with coworkers from other institutions through the association. Jointly, they are sketching plans for the 2019 hurricane season. With support from a $220,000 grant from the National Oceanic and Atmospheric Administration, they intend to pre-position several gliders in strategic locations to be ready for deployment before incoming storms.

“Gliders are like the weather balloons of the ocean,” stated Edwards. “Imagine how powerful a regular network of these kinds of glider observations could be for understanding the ocean and weather, and how they interact.”