Model Simulation Studies of Hurricane Isabel in Chesapeake Bay Jian Shen Virginia Institute of Marine Sciences College of William and Mary

Isabel: The 100-Year Storm !

Background of Storm Surge Modeling Numerical models have been successfully applied to simulate and predict tide and storm surge in coastal seas –SLOSH (Sea, Lake, and Overland Surges for Hurricanes –ADCIRC (Advanced Circulation Model) Impact of the storm surge at any particular location is sensitive to meteorological and topographic parameters Inundation is crucial for disaster planning Prediction of flooding areas depends on model grid resolution

New Challenges for Numerical Modeling More high resolution terrain data are available –LIDAR (LIght Detection And Ranging) More real-time observation data are available –Surface elevation –Vertical velocity profile –Wave Real-time simulation vs. prediction –Rescue –Inundation How to integrate high resolution terrain and real-time observation data into models ?

VIMS Real-Time Observation System

Current Observation at Gloucester Point

Airborne LIDAR Data LIDAR (LIght Detection And Ranging) Infrared laser ranger provides distance to ground Differential GPS provides aircraft location Inertial reference system provides aircraft orientation Post-processing provides x,y,z coordinates of ground surface Construction of Digital Elevation Models (DEMs)

DTMS 3 Sec (80-90 m) DTM Vertical Res. 1 m 10 DTM Vertical Res. 0.3 m

Elevation (feet) Elevation (feet) USGS 10m DEM LIDAR 10m DEM Example of LIDAR Data (Miami)

Model Domain Representation Small domain is inadequate for storm simulation Coarse grid is inadequate to resolve irregular shoreline and small topographic features in estuary Structured grid is difficult to represent complex bathymetric in estuary Unstructured grid has advantage of storm surge modeling –Use nested grids –Place fine grid in the areas of interest and coarse grid in the remaining large areas

Model Requirements Must resolve complex shoreline Must resolve land features –coastal ridge, dam, inlet, and river –small scale on the order of meters Must cover large modeling domain Must be computationally efficient

Example of Unstructured Grid (Miami)

Example of Nested Model Grids

Unstructured 3D Model (UnTRIM) “UnTRIM” incorporates an Unstructured grid into TRIM model (Tidal, Residual, Intertidal Mudflat), originally developed by Vincenzo Casulli It simulates three-dimensional hydrodynamic and transport processes It uses an orthogonal unstructured grid It conserves mass locally as well as globally It uses Eulerian-Langangian transport scheme It employs semi-implicit finite difference and finite volume method- very efficient computationally It is capable of simulating wet-dry processes

Grid Structure Use polygons to represent a prototype estuary (3-, 4-, 5-sides) Better fitting complicated geometry in estuarine and coastal environment Using orthogonal grid simplifies the numerical algorithm

Model Simulation Studies Study the accuracy of model prediction of Isabel forced by a stationary, circular wind model Compare model prediction with and without simulating inundation Study influence of open boundary condition specification on surge simulation –still boundary condition vs. inverse pressure adjust boundary condition Study influence of model domain size on surge prediction Study influence of wind field on model prediction Study influence of hurricane on transport

Model Grids Surface elements =121,338 Surface elements =239,541

Grid layouts at York and James Rivers

Model Calibration Calibrate model for tide forced by 9 tidal constituents M 2, S 2, K 1, O 1, Q 1, K 2, N 2, M 4, and M 6 Model was run for 3 months and the results of the last 29 days were used for computing tidal harmonics Time step = 5 min.

Tidal Simulation (M 2 tide)

Tidal Simulation (K 1 )

Observation Stations

Tidal Constituents Comparison (Amplitude) Amplitude is in m Observations are based on 1992 data

Tidal Constituents Comparison (phase) Phase is in degree

Wind Model (Myers and Malkin, 1961) r = the distance from the storm center p(r) = pressure, p a = central pressure,  = the inflow angle across circular isobar toward the storm center V is the wind speed, f = Coriolis parameter, k s and k n are friction coefficients.

Example of Wind Field

Isabel Simulation Results With and Without Simulating inundation

Comparison of Model Results With and Without Simulating Inundation

Test Influence of Open Boundary Condition Apply inverse pressure adjustment at BC Run large domain model (east coast) and apply time series output from large domain model to force small domain model

Large Domain Model Simulation

Influence of Open Boundary Condition Inverse Pressure Adjustment Nested Grids

Influence of Wind Field

Wind Field Analysis

Comparison of Using Different Wind Fields

Current Simulation at Gloucester Point Model Wind Field Modified Wind Field

Conclusions Unstructured model is very efficient in simulation tide and storm surge Open boundary condition specification influences the surge prediction Wind field is critical in the accurate simulation of storm surge

Thanks !