Forecasting Hurricane Impacts on CoastS - FHICS This technical proposal is pursuant to Task 4: Wave, Surge, Sediment Transport, Structure Response Forecasting
Abstract
Over the past few decades, the meteorological community has made considerable progress in forecasting hurricanes. Concurrently, the oceanographic and coastal communities have made significant advances in understanding physical hydrodynamic processes that drive coastal impacts due to hurricanes. While operational forecasts of storm surge and waves are now common practice and fairly robust, forecasts of morphological impacts are lagging. However, as much of the important physics has been incorporated in numerical models, which at the same time have become faster due to increased computational capabilities, it is now feasible to reliably compute the hydro-morphological response due to hydro-meteo events if accurate forcing and initial conditions (such as topography, vegetation, etc.) are known. In cooperation with US agencies such as the Office of Naval Research (ONR), Navy Research Laboratory (NRL) and United States Geological Survey (USGS), coastal processes have been incorporated in the numerical modeling package Delft3D, which has been under continuous development since the 90s and was acquired by the U.S Navy in 2001 as a platform for operational forecasts of nearshore hydrodynamics. In the ongoing ONR-funded Increasing Fidelity of Morphological Storm Predictions (IFMSIP) project, the new generation Delft3D-FM (Flexible Mesh) large-scale model was used to drive detailed morphodynamic XBeach models on domains of 10 x 2 kms with which accurate hindcasts of morphodynamic change including breaching were possible (Van der Lugt et al., 2019). USGS and Deltares are currently working on probabilistic coastal response models such as a Bayesian Network to predict storm impact at low computational cost across large spatial scales based on the Parameterized Island Gaussian Fit (PIG-F) method (Mickey et al., 2019) and CoSMoS-COAST (Vitousek et al. 2017, 2020 under review), a dataassimilated, ensemble Kalman filter shoreline model to predict shoreline change due to probabilistic hurricane tracks. We propose to integrate and further develop these existing components in order to make real-time forecasts of hurricane impacts on CONUS coasts. This technical proposal concerns Task 4 in the Research Description of Predicting Hurricane Coastal Impacts of continental US (CONUS) landing hurricanes over the period 2021-2024 by ONR. The Tasks of the Research Description1 are:Task 1: Year 1, the building of a Digital Elevation Model (DEM) and in Years 2-4 regular updates and quantitative post-hurricane impact summaries; Task 2: New quantitative capabilities in satellite remote sensing for both building a ground-truth DEM and quantitative geophysical measurements during the storms, for comparison to and possible assimilation into model forecasts; Task 3: In situ measurements to include offshore waves, and both offshore and inland water levels, for assimilation prior to landfall and ground truth evaluations afterward; and Task 4: Forecasting of wave, surge, sediment transport (erosion and accretion above and below mean sea level), structure interaction and damage.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2021
- Source ID
- N000142112196
Entities
People
- Cornelis Nederhoff
Organizations
- Office of Naval Research
- United States Navy