University of Oklahoma SMART radar team heads to the East Coast before Hurricane Florence makes landfall

NORMAN, Okla. – The University of Oklahoma’s Shared Mobile and Atmospheric Research and Testing radar team left for the East Coast Sunday afternoon.

The team, led by Michael Biggerstaff, will be studying Hurricane Florence with scientists from the National Oceanic and Atmospheric Administration’s National Severe Storms Laboratory.

Hurricane Florence, a Category 4 storm, will make landfall later this week while the team is there.

The two costliest hurricanes to hit the United States were Category 3 hurricanes, Katrina in 2005 and Harvey in 2017.

“Florence will no doubt create significant storm surge and inland floods to go along with winds in excess of 110 miles per hour. We are interested in studying the inner core rain bands and eyewall convection,” said Biggerstaff, professor of meteorology, School of Meteorology, OU College of Atmospheric and Geographic Sciences. “As the hurricanes come ashore, the primary vortex circulation breaks down and creates deep waves in the atmosphere called Vortex Rossby Waves that generate rain bands that spin outward from the eyewall and contribute to inland flooding.”

Team members Biggerstaff; Gordon Carrie, research scientists; Addison Alford and Noah Brauer, OU doctoral students; and Sean Waugh, NSSL scientists; “deployed with a newly upgraded OU Cooperative Institute for Mesoscale Meteorological Studies’ C-band dual-polarimetric SR3 radar, four OU and Purdue University Portable Integrated Precipitation Sensors that carry a disdrometer to study the size distribution of raindrops in addition to standard weather station instruments, an experimental wind sensor and an NSSL mobile mesonet that serves as a weather balloon launch vehicle.”

The team plans to combine the SMART radar data with nearby National Weather Service radar data to produce the first ever near-real-time wind analyses during the landfall of a major hurricane.

If they are successful, maps of maximum wind speed and its time of occurrence will be generated.