A Combined Physical-Statistical Approach for Estimating Storm Surge Risk

• Activity Number: 450 - Uncertainty Quantification for Environmental Applications
• Type: Topic Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Whitney Huang* and Taylor Asher and Richard Luettich and Richard Smith
• Companies: Clemson University and University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill
• Keywords: storm surge; extremes; computer experiment; risk assessment; Hurricane; uncertainty quantification

Abstract

Storm surge is an abnormal rise of seawater caused by a storm. According to the National Hurricane Center, storm surge is often the most damaging part of a hurricane and poses the most severe threat to property and life in a coastal region. Thus, it is crucially important to assess the storm surge risk, typically summarized by r-year surge return level with return period r ranging from 10, 50, 100, or even much longer along a coastline. It is however very difficult to reliably estimate this quantity due to the limited storm surge observations in space and time. This talk presents an approach to integrate physical and statistical models to estimate extreme storm surge. Specifically, A physically-based hydrodynamics model is used to provide the needed interpolation in space and extrapolation in both time and atmospheric conditions. Statistical modeling is needed to 1) estimate the input distribution for running the computer model, 2) develop a statistical emulator in place of the computer simulator, and 3) quantify estimate uncertainty due to input distribution, statistical emulator, missing/unresolved physics.

This is joint work with SAMSI MUMS storm surge working group.