The ability to accurately forecast coastal change from large storms such as hurricanes is necessary to characterize military battlespace and civilian hazards. Important oceanic and terrestrial parameters include wave characteristics (height, period, and direction), water levels, currents, coastal morphologic response, and damage to infrastructure. Numerical models of coastal atmosphere-ocean processes and morphological change resolve complex physics and can make detailed forecasts. The fidelity of these types of models, when hindcasting past extreme storm events, depends on several factors, including atmospheric forecast uncertainty, model physics, open boundary conditions, model spatial resolution, and coastal elevation and land use.
Forecasting the coastal impacts of extreme storms poses technical and scientific challenges. Given the urgent societal need for accurate coastal impact forecasting systems, it is imperative that we 1) develop the computational architecture needed to run these types of models in forecast mode, 2) run the coastal impact models in real-time forecast mode, 3) verify the results of the model, and 4) analyze the most efficient ways of disseminating the results and the uncertainty associated with these results to the public.
We will develop a real-time forecasting system to meet these needs, based on the Coupled Ocean Atmosphere Waves Sediment Transport (COAWST) framework to predict the coastal impacts from landfall hurricanes, including waves, total water levels, flooding extent and duration, maximum current speeds, sediment transport (erosion and accretion above and below mean sea level), integrated hydrographs, structure interaction, and damage. COAWST dynamically couples multiple models, including the Regional Ocean Modeling System (ROMS), Simulating WAves Nearshore (SWAN), WAVEWATCH III, the Weather Research and Forecasting (WRF) model, the INfragravity WAVE model (INWAVE), and the Community Sediment Transport Modeling System (CSTMS). In the recent ONR project “Increasing the Fidelity of Morphological Storm Impact Predictions”, we used COAWST to hindcast coastal erosion and generation of the breaches observed during Hurricanes Sandy (2012) in Fire Island, NY, and Matthew (2016) south of Matanzas Inlet, FL. The model demonstrated skill in reproducing critical hydrodynamic features driving observed morphological change. COAWST is unique in that it includes 2-way nesting and downscaling capabilities while simultaneously considering key processes affecting coastal hazards, including morphological changes, wave breaking-induced currents and water level changes, compound flooding, and the three-dimensional nature of the ocean and nearshore circulation. COAWST will be used to forecast Wave, Sediment, Surge, and Structure Response (WSSSR). This COAWST-WSSSR forecasting system will be applied to directly predict the coastal response to landfall hurricanes. The system is conceptualized such that it is easily transferable within the community and allows further nesting for specific applications and the inclusion of new grids. A series of static and dynamic grids will enable prediction of gross coastal hazards at the regional scale and detailed morphological change at the local scale, where the highest impacts are predicted.
Results from this exemplary NOPP project (e.g. development/verification of coastal flooding, erosion and infrastructure damage forecasting systems) will be highly beneficial to other government research and coastal management programs focused on coastal hazards and risk
(NOAA, FEMA, USGS, NSF, NPS, and many other agencies).
by Martha Schönau, Luca Centurioni, Steve Jayne, and Elizabeth Sanabia
Hurricane Ian was the first 2022 hurricane to make landfall in the continental USA with strong Cat 5 winds and large amounts of rain. The team of Deltares USA, Deltares Netherlands, USGS and NRL successfully applied the COSMOS modelling system to forecast hurricane Ian’s flood and morphological impact.