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Storm Surge Modeling

Inundation due to storm surge is a severe coastal hazard that threatens communities along the U.S. Gulf of Mexico and East coasts. The Marine Modeling and Analysis Programs (MMAP) branch of the Coast Survey Development Laboratory is participating in several projects to examine the ability of state of the art high resolution models to predict storm surge. These projects are studying model forcing and evaluating model accuracy and efficiency. Furthermore, high resolution storm surge modeling is being combined with NOAA expertise in coastal observations, Geographic Information Systems (GIS) and community outreach to generate products.

MMAP is constructing high resolution computational grids for storm surge modeling with the finite element model ADCIRC. ADCIRC uses high performance computing to efficiently compute velocity and surface elevation over a large area. High resolution unstructured grids are advantageous because they can resolve complex geography while using lower resolution in more straightforward areas. The resulting model grid resolves coastal flow and features at their local scale while minimizing costly resolution elsewhere. For example, resolution in a tidal inlet can be less than 100 m while being 10 km in the deep ocean. For storm surge modeling applications, high grid resolution is provided over land for simulation of flooding and draining. Barriers to flooding that are smaller than grid size (such as levees and roadways) are represented by grid features that allow overtopping. Finally, an accurate storm surge simulation requires a consistent, continuous elevation field for the model grid. For MMAP model applications, bathymetric and topographic data are adjusted to a common vertical datum through the use of the VDatum tool . Therefore, the unstructured grid can model storm surge as it travels from the deep ocean to the coast and then inland by using a continuous elevation field and by varying model resolution.

The high resolution storm surge models developed by MMAP are run on NOAA’s high performance computing resources. The storm surge model is equipped to use a parallel computing environment and has efficiently performed simulations on 256 or more processors. This enables fast run times for a highly resolved, large scale model. MMAP remotely accesses NOAA systems at the Earth Systems Research Laboratory in Boulder, CO, and at the National Centers for Environmental Prediction (NCEP) in Camp Springs, MD to run storm surge models.

 

 Figure 1. High resolution finite element grid of Pamlico Sound and surrounding areas; the NAVD 88 datum is shown in green.
 Figure 1. High resolution finite element grid of Pamlico Sound and surrounding areas; the NAVD 88 datum is shown in green

Coupled Storm Surge Modeling Project: North Carolina Sound System
MMAP is currently partnering with the National Weather Service (NWS) in a storm surge project to couple a coastal finite element model with operational weather prediction models. The goal is to improve storm surge simulations over that available from the models independently by combining their different capabilities. NOAA’s NWS develops and implements atmosphere and ocean models used for forecast guidance at NCEP’s Environmental Modeling Center (EMC). These numerical modeling applications include widely used, large scale atmosphere and ocean models. This suite of developmental and operational models includes meteorological (e.g., the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane forecast system), general ocean circulation (e.g., the HYbrid Coordinate Model (HYCOM)), and ocean wave (WAVEWATCH III) models which capture hurricane activity. By coordinating NCEP operational modeling experience with MMAP expertise in coastal finite element modeling, large scale models such as these are being tested for coupling with high resolution inundation models to produce storm surge simulations. In this way the capabilities of each model can be leveraged to produce a high quality storm surge prediction. For example, the GFDL model has high resolution representation of a hurricane event but does not have the spatial coverage of the Global Forecast System model. By combining these two outputs a superior forcing product is developed that can drive both a general ocean circulation model and a coastal flooding model. In particular, the larger scale ocean and wave models are being used to provide forcing for the coastal finite element model. The high resolution inundation model can resolve storm surge propagation at the coast and over land, where larger domain models have more spatial coverage but coarser resolution. The project is testing a range of model coupling strategies by varying domain size, boundary conditions, and forcing to determine an approach that is an optimal combination of accuracy and cost. Initial testing is being done in the North Carolina sound system by hindcasting Hurricane Isabel (2003) and by simulating future significant hurricane events.

 

Figure 2.  Storm surge model grid and bathymetric countours (m NAVD 88) at entrance to Pensacola Bay with subgrid-scale flood obstructions along the barrier islands in red lines. 
 Figure 2. Storm surge model grid and bathymetric contours (m NAVD 88) at the entrance to Pensacola Bay with subgrid-scale flood obstructions along the barrier islands in red lines

Gulf of Mexico Storm Surge Partnership Project: Pensacola, FL
The Gulf of Mexico Storm Surge Partnership Project (SSPP) is an NOS-wide effort with the goal of enhancing the resilience of coastal communities to storm surge. The Gulf of Mexico coast is very vulnerable to devastating hurricane flooding as has been shown in recent years. The project covers the Alabama-Florida Panhandle region, centering on Pensacola, FL, which was severely impacted by Hurricane Ivan in 2004. The project focuses on integrating state of the art technology and expertise from across NOS and outside partners.

The SSPP combines storm surge modeling with high resolution data sets, improved coastal observations, a continuous elevation field, and innovative management products such as GIS-based inundation maps. Two benchmark tasks for the SSPP were the organization of two workshops, one a technical workshop on community inundation modeling and one an outreach workshop with coastal managers to discuss inundation products and services. More details about all of the project tasks are available on the project website: http://www.csc.noaa.gov/sspp/.

MMAP has an important role in three critical project tasks. The first is to co-organize the technical workshop that brought together inundation model developers and users from across government, academic, and private sectors to begin a community modeling effort. The second task is to codevelop an application of the VDatum tool for the area stretching from Mobile Bay, AL to Cape San Blas, FL. The third is to develop a demonstration storm surge model for the project region based upon high resolution elevation data and a high resolution model grid. This storm surge model application utilizes the VDatum tool to create a continuous elevation field by adjusting all elevation data to NAVD 88 before populating the model grid. Extensive use of high resolution elevation data is made to define the topography and bathymetry of the region as accurately as possible. This data comprises LIght Detection And Ranging (LIDAR) where available, which generally has horizontal spacing on the order of 10 m and vertical accuracy of 20 cm; an inventory of this data was developed for this project by NOS’ Coastal Services Center (CSC). Storm surge model grid resolution averages 100 to 200 m along the coast but becomes smaller in narrow inlets and coastal waterways. Features such as barrier islands and elevated roadways are represented in the model grid as hydraulic structures. The demonstration storm surge model application utilizes the ADCIRC finite element model to simulate water heights during storm events as driven by tides and meteorological effects. The model will be validated by hindcasting 2004’s Hurricane Ivan, which caused extensive flooding of Pensacola and surrounding regions.
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