Sensitivity Studies of the New Coastal Surge and Inundation

Prediction System Andrew Condon1,2 and Jay Veeramony2

1American Society for Engineering Education, 2Naval Research Laboratory, Stennis Space Center, USA

andrew.condon.ctr@nrlssc.navy.mil, jay.veeramony@nrlssc.navy.mil

4. Baseline Simulation The baseline simulation captures the

coastal water levels accurately but does

not perform as well in capturing the

inundation due to the coarse domain

resolution.

Figure 2. Domains, station locations, and track of Hurricane Ike used in hindcast

simulations

2. The Modeling System Delft3D is an integrated modeling suite, which simulates 2D and

3D flow, sediment transport and morphology, waves, water quality

and ecology. This study utilizes two Delft3D modules:

• FLOW – hydrodynamic module

• WAVE – wave module

FLOW is dynamically coupled to WAVE by passing water level,

currents, winds, and bed level to WAVE and in return gets

radiation stresses for wave setup calculations.

The Delft Dashboard (Figure 1) is a GUI specific to Delft3D

FLOW/WAVE and allows for the rapid setup of storm surge and

inundation simulations, including:

• Selection of an area from the world map; specifying the size

and resolution to create a rectangular grid

• Interpolation of bathymetry from available datasets

• Specifying type of boundary conditions and forcing

• Nesting domains and defining observation points

• Defining wave parameters and FLOW / WAVE coupling

6. Conclusions As expected the model results are very sensitive to a number of

input parameters

• Proper grid resolution is necessary for quality inundation

results, can get by with coarse resolution to model coastal

water levels

• Bathymetry / Topography data matter – High resolution data

can have a large influence even on a coarse grid

• Land cover / bottom roughness data is needed to improve

inundation simulation results

References • Amorocho, J and JJ DeVries, "A new evaluation of the wind stress coefficient over water surfaces,"

J. Geophys. Res., vol. 85, no. C1, pp. 433 - 442, 1980.

• Donelan, MA, et al., "On the limiting aerodynamic roughness of the ocean in very strong winds,"

Geophys. Res. Let., vol. 31, no. L18306, 2004.

• Garratt, JR, "Review of drag coefficients over oceans and continents," Mon. Wea. Rev., vol. 105,

pp. 915 - 929, 1977.

• Holland, GJ, "An analytic model of the wind and pressure profiles in hurricanes," Monthly

Weather Review, vol. 108, pp. 1212 - 1218, 1980.

• Jarosz, E, Mitchell, DA, Wang, DW and WJ Teague, "Bottom-up determination of air-sea

momentum exchange under a major tropical cyclone," Science, vol. 315, pp. 1707 - 1709, 2007.

• Large. WG and S Pond, "Open ocean momentum flux measurements in moderate to strong winds,"

J. Phys. Ocean., vol. 11, pp. 324 - 336, 1981.

• Mattocks, C, and C Forbes, "A real-time, event-triggered storm surge forecasting system for the

state of North Carolina," Ocean Modelling, vol. 25, pp. 95 - 119, 2008.

3. Domains The sensitivity studies involved hindcast simulations of Hurricane

Ike (2008) in the multiple domains depicted in Figure 2.

5. Sensitivity Studies

Model setup Gulf of Mexico domain

Bathymetry / Topography data:

• SURA inundation testbed GoM dataset

• NOAA NGDC Coastal Relief Model

• SRTM topography data

• GEBCO 08

Riemann (weakly reflective) boundary conditions

Tidal constituents:

• OSU global model of ocean tides based on

TOPEX7.2 satellite altimeter data

Initial water level: 0.11 m – seasonal trends

Wave coupling every 60 minutes

Variable bottom roughness (Manning’s N coefficient)

Wind drag coefficient from Powell et al. (2012)

Reanalysis winds from OceanWeather Inc. (OWI)

• 0.02° spatial resolution

• 10 min temporal resolution

NH21A-1583

1. Overall Objective To develop a tool (GUI) for storm surge and inundation prediction

which results in a minimization in man-hours and required operator

knowledge for model set-up as well as result in more optimal surge

and inundation forecasts.

Figure 1. The Delft Dashboard Graphical User Interface

Gulf of Mexico Domain • 0.1° x 0.1°

• 179 x 129

• 1 day runtime ~ 30

min @ Δt = 10 min

Nearshore Domain • 0.02° x 0.02°

• 462 x 302

• 1 day runtime ~ 60

min @ Δt = 5 min

Coastal Domains • 0.004° x 0.004°

• Various sizes

• 1 day runtime ~ 30

min @ Δt = 1 min

LAWMA Freshwater

Canal Locks

Calcasieu

Pass

Sabine

Pass North

Galveston

Pleasure Pier

High Water

Marks

-12.34 -0.59 0.78 4.49 1.72 23.72

Table. 1. Percent error of peak water level at 5 NOAA stations and average for all HWMs

Figure 3. Hydrograph analysis at five coastal

locations and HWM analysis for baseline simulation

Air-Sea Drag Coefficient Considered 12 formulations (Figure 4)

Found best results with newer formulations:

• Formulation of Powell et al. (2012)

produced the best results

• Peak CD at hurricane force

• Decrease in CD with higher wind speeds

Figure 4. 12 Drag coefficient formulations used in

sensitivity studies as a function of wind speed

Grid Resolution / Nesting Water level results are good with coarse resolution.

Inundation results improve with increasing resolution

as in Figure 5.

• 0.5° domain

• 2 – way nesting

• 0.1° to 0.004°

• 3 – way nesting

• 0.1° to 0.02° to 0.004°

Figure 5. HWM analysis for various 0.1, 0.05 resolution

GoM domains and 2-way and 3-way nesting

Bathymetry / Topography High resolution bathymetry / topography is not available worldwide. GEBCO bathy/topo and SRTM

topo are widely available and provide global coverage, but results are not as good (Figure 6).

GEBCO - Baseline GEBCO + SRTM - Baseline

Figure 6.

Comparison of

Baseline

simulation with

GEBCO only

bathy / topo

dataset and

GEBCO +

SRTM bathy

topo dataset

Forecast wind model Considered 3 analytic wind models and developed a new model.

Example: Ws = 95 KT, Rmax = 50 n. mi., Pn= 1007 hPa, Pc = 954 hPa,

RO = 300 n. mi.

64 KT… 105NE 90SE 60SW 75NW

50 KT… 150NE 150SE 90SW 105NW

34 KT… 240NE 205SE 150SW 175NW

Figure 7. Bathymetry and topography differences between GEBCO and GEBCO + SRTM and

Baseline

Figure 8. Wind snapshot from OceanWeather reanalysis

winds, 3 analytic wind models and newly developed model

Figure 9. Example of construction of wind field for

new wind model

• Place forecast

information on grid

(red data points)

• Obtain Holland B for

black data points

• Obtain wind speed at

black points using

Holland equation

• Use multivariate

interpolation to

determine velocity as a

function of distance

and angle from center Figure 10. HWM comparison between various wind models

Proper wind forcing is needed

• Many modeling studies use

older drag formulations with a

simple cap; newer formulations

may offer better results

• Various analytic wind models

can offer very different results

• New model offers promising

results … more testing is

needed

• Moon, IJ, Ginis, I, Hara, T and B Thomas, "A physics-based parameterization of air-sea

momentum flux at high wind speeds and its impact of hurricane intensity predictions," Mon. Wea.

Rev., vol. 135, pp. 2869 - 2878, 2007.

• Powell, MD, Vickery, PJ and TA Reinhold, "Reduced drag coefficient for high wind speeds in

tropical cyclones," Nature, vol. 422, pp. 279 - 283, 2003.

• Powell, MD, "High wind drag coefficient and sea surface roughness in shallow water," Final

Report to the Joint Hurricane Testbed, NOAA HRD-AOML, 2008.

• Powell, MD, Holthuijsen, L, and J Pietrzak, "Spatial variation of surface drag coefficient in

tropical cyclones," unpublished, 2012.

• Wu, J, "Wind-stress coefficients over sea surface from breeze to hurricane," J. Geophys. Res., vol.

87, no. C12, pp. 9704 - 9706, 1982.

• Xie, L, Bao, S, Pietrafesa, LJ, Foley, K, and M Fuentes, "A real-time hurricane surface wind

forecasting model: Formulation and verification," Mon. Wea. Rev., vol. 134, pp. 1355 - 1370,

2006.

• Zachry, BC, Letchford, CW, Zuo, D, Schroeder, JL, and AB Kennedy, "Surface drag coefficient

behavior during Hurricane Ike," in 11th Americas Conf. on Wind Engineering, San Juan, PR, 2009.

• Zijlema, M, van Vledder, GP, and LH Holthuijsen, "Bottom friction and wind drag for wave

models," Coastal Eng., vol. 65, pp. 19-26, 2012.