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Research Spending & Results

Award Detail

Doing Business As Name:University of Oklahoma Norman Campus
  • Benjamin A Schenkel
  • (973) 202-3245
  • Nusrat Yussouf
Award Date:07/10/2020
Estimated Total Award Amount: $ 498,590
Funds Obligated to Date: $ 498,590
  • FY 2020=$498,590
Start Date:10/01/2020
End Date:09/30/2023
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.050
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:The Impact of Ambient Deep-Tropospheric Vertical Wind Shear on Tornadoes and Their Attendant Supercells within Tropical Cyclones
Federal Award ID Number:2028151
DUNS ID:848348348
Parent DUNS ID:046862181
Program:Physical & Dynamic Meteorology
Program Officer:
  • Nicholas Anderson
  • (703) 292-4715

Awardee Location

Street:201 Stephenson Parkway
Awardee Cong. District:04

Primary Place of Performance

Organization Name:University of Oklahoma Norman Campus
Street:201 Stephenson Parkway
Cong. District:04

Abstract at Time of Award

Hurricane and tropical cyclone landfalls produce numerous hazards, from wind damage to flooding to storm surge. This project will address a lesser-studied aspect of tropical cyclone landfalls, tornadoes, and specifically the role of wind shear on their development. Tropical cyclone induced tornadoes are generally weaker than supercell tornadoes, but they are a public safety hazard. There is not a direct correlation between the strength of a tropical cyclone and the resulting number of tornadoes and forecast guidance is often generic. This award will provide a research-based understanding of tropical cyclone tornadoes which should allow operational weather forecasters to better alert the public of these hazards. The project will also involve multiple students as training for the next generation of researchers. The research team plans an analysis and modeling study of the role of vertical wind shear on the occurrence of tornadoes in landfalling tropical cyclones. Tornadoes frequently occur during hurricane landfall, but the number can vary by an order of magnitude among tropical cyclones that are otherwise of similar strength. These tornadoes are also much less predictable than the more common Great Plains tornadoes. This study will use observational analysis of the deep-tropospheric vertical wind shear and tropical cyclone-relative helicity from reanalysis data, other observations such as radar data and atmospheric soundings, and modeling with the WRF-based Warn on Forecast System (WOFS) to: 1) Test the variability of the relationship between tornadoes and deep convection in tropical cyclones and vertical wind shear with other relevant factors (e.g. diurnal cycle), 2) Assess the sensitivity of tornadic supercell predictability to vertical wind shear in hindcasts, and 3) Identify how vertical wind shear creates favorable environments for tropical cyclone tornadic supercells using observations and Lagrangian vertical vorticity budgets computed from hindcasts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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