Award Abstract # 2322270
MCA Pilot PUI: Validating and Constraining Catastrophe Models with Paleo Tropical Cyclone Data for Enhanced Risk Management

NSF Org: OCE
Division Of Ocean Sciences
Recipient: FLORIDA GULF COAST UNIVERSITY
Initial Amendment Date: July 10, 2023
Latest Amendment Date: July 10, 2023
Award Number: 2322270
Award Instrument: Standard Grant
Program Manager: Gail Christeson
gchriste@nsf.gov
 (703)292-2952
OCE
 Division Of Ocean Sciences
GEO
 Directorate for Geosciences
Start Date: July 15, 2023
End Date: June 30, 2026 (Estimated)
Total Intended Award Amount: $262,393.00
Total Awarded Amount to Date: $262,393.00
Funds Obligated to Date: FY 2023 = $262,393.00
History of Investigator:
  • Joanne Muller (Principal Investigator)
    jmuller@fgcu.edu
Recipient Sponsored Research Office: Florida Gulf Coast University
10501 FGCU BLVD S
FORT MYERS
FL  US  33965-6502
(239)590-7582
Sponsor Congressional District: 19
Primary Place of Performance: Florida Gulf Coast University
10501 FGCU BLVD S
FORT MYERS
FL  US  33965-6502
Primary Place of Performance
Congressional District:
19
Unique Entity Identifier (UEI): ENCFSMNC3PT1
Parent UEI:
NSF Program(s): Marine Geology and Geophysics
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 101Z, 1304, 1324, 1620
Program Element Code(s): 162000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

Tropical cyclones (TCs) are a serious threat for densely populated coastal communities. This is particularly true for the Florida coastline. Along the Florida coast, sprawling concentrations of people and properties have resulted in a recent rapid increase in human exposure to TC landfalls. Hurricane Ian made landfall on the Southwest Florida coast on September 28, 2022. This storm presented all three of the hazards commonly associated with hurricanes: wind, rain, and storm-tide surge. But by far the most catastrophic impacts were from the storm-tide surge. High water marks on Fort Myers Beach reached near 16 feet. Hurricane Ian could be one of the costliest natural disasters in US history at $112.9 billion USD. In the risk industry, such low-probability, high-impact events like these are known as ?Tail-Risk Events.? Tail-Risk Events often cause widespread economic chaos, and they are also often associated with substantial and devastating loss of life. This research will extend the Southwest Florida hurricane record back thousands of years by means of Paleotempestology. Sediment cores from coastal ?blue holes? will be analyzed to reconstruct the history of TCs in the area. This will result in a more robust understanding of the TC frequency distribution along the US coastline, thereby reducing the loss of life and infrastructure attributable to TCs. This project will also connect to the broader risk management and modelling communities. These partnerships will ensure that the paleo research can appropriately attach to catastrophe risk decision-makers. Project data generated will not only be used by the risk industry, but by other stakeholders as well. The other stakeholders include agricultural businesses; habitat restoration groups; coastal land managers; individual property owners, municipalities, scientists, and business. The data can further be used to outreach to emergency managers, the media, community leaders and the community at large. This project will also have a significant impact on diversity in STEM by supporting underrepresented minorities in STEM.

This Mid-Career Advancement (MCA) project will involve four different, but highly interconnected and interdisciplinary activities: 1) With the mentorship and collaboration from the Woods Hole Oceanographic Institution (WHOI) the team will build on Southwest Florida?s long-term TC dataset, by adding new reconstructions from Southwest Florida blue holes; 2) With the mentorship and collaboration from partner Oasis the PI will receive training on the Oasis Loss Modeling Framework (LMF), attend training workshops and deploy models, and learn about how catastrophe (Cat) models are used to inform views of risk; 3) With the mentorship and collaboration from partner Reask the PI will learn how stochastic TC data sets are developed, how they feed into dynamical storm surge models, and how they combine to produce risk estimates. The research will identify what types of storms in stochastic catalogues are able to deposit geologic TC layers and complete sensitivity analyses for field sites of interest; and 4) With the mentorship and collaboration from partner Maximum Information the research will bring new intense TC landfall paleo datasets, that are temporally an order of magnitude greater than the existing instrumental historical record, to risk modeling firms and (re)insurance companies. In summary, the estimated paleo TC return periods calculated during this study will be used in baseline Cat model validation, calibration and deterministic scenario (stress) testing (which inform views of Maximum Probable/Possible Loss).

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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