UNIVERSITY OF HAWAl'I LIBRARY

HINDCAST MODELING OF STORM SURGE AND WAVES IN

THE GULF COAST REGION

A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE

UNIVERSITY OF HAWAI'I IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF

iMASTER OF SCIENCE

IN

OCEAN AND RESOURCES ENGINEERING

AUGUST 2005

By

Robert H.Crabtree

Thesis Committee:

Kwok Fai Cheung, Chair

Hans-Jtirgen Krock

Mark A. Merrifield

~q 7°

V'II rC,V ..r!

"'.,,'~,...",.,_.,..--~--------...,~.,. ..., ""'"""

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fI,·~C4.}f ;1~/,'~ of

.5forr1 5Lt"~ (~Vt2, i" ft.tL

(;I«,c ~.4.s-:f i?~10""

ACKNOWLEDGEMENTS

I would like to thank my entire committee for taking the time to review my work. I

would also like to thank Dr. Kwok Fai Cheung for my research assistantship, without

which this may have not been possible. Funding for this study, in the form of a research

assistantship, is provided by the ENDEAVOR project, which us funded by the Office of

Naval Research via grant number N00014-02-1-0903.

There have been several people who have contributed to the development of this project:

Dr. Rachel Tang, Mr. Demont Hansen, Mr. Long Chen, and Dr. Zhixia Zhu at the

University of Hawaii, Dr. Hendrik Tolman and Dr. Y.Y. Chao of NOAA, and the help

desk at MHPCC. Thank you all for your help. I would also like to thank Edith and Azy

in the department office.

Special thanks to Marney for putting up with all of the stress that goes along with

graduate school.

111

ABSTRACT

A hurricane model package has been developed to simulate the storm surge and waves in

the Gulf Coast region. Four component models are implemented at two nested levels of

the ocean environment, namely the ocean and coastal regions. The wind and pressure

fields from a given hurricane are generated by a parametric hurricane model, and are used

as input into the subsequent component models. The wave spectrum, generated by the

hurricane wind field, is modeled by WAYEWATCH III from the ocean region into the

coastal region, where the nearshore model SWAN continues the simulation. Both

WAYEWATCH III and SWAN implement higher resolution nested runs within the two

regions for greater model accuracy. The water surface elevations are computed from the

hurricane wind and pressures fields and the astronomical tides by the Estuarine and

Coastal Ocean Model (ECOM). The water surface elevations from the nested ECOM

runs are used as input into the nested SWAN runs. The hurricane model package has

been used for the hindcast of Hurricane Ivan, which made landfall along the Gulf Coast

region in September 2004. The computed wind, wave, and storm surge data is compared

with the recorded data. The modeled results indicate reasonable agreement with the

recorded data.

IV

TABLE OF CONTENTS

ACKNOWLEDGEMENTS iii

ABSTRACT iv

TABLE OF CONTENTS v

LIST OF FIGURES vii

LIST OF TABLES viii

1. INTRODUCTION 1

2. STORM-INDUCED WAVES AND STORM SURGE 4

3. STORM SURGE AND WAVE MODELING 6

3.1. Hurricane Model Package Components 6

3.1.1. Parametric Wind Models 7

3.1.2. WAVEWATCHIII(WW3) 11

3.1.3. Simulating WAves Nearshore (SWAN) 13

3.1.4. Estuarine and Coastal Ocean Model (ECOM) 15

3.2. Hurricane Model Package Input 16

3.2.1. Bathymetric Description 17

3.2.2. Astronomical Tides 17

3.2.3. Storm Event 17

3.3. Regional Modeling 18

3.3.1. Ocean Region 18

3.3.2. Coastal Region 18

4. CASE STUDY 20

4.1. Study Area - Gulf of Mexico 20

4.2. Hurricane Ivan 21

4.2.1. Background 21

4.2.2. Hurricane Wind Model Results 26

v

4.2.3. Ocean Region Results 29

4.2.4. Coastal Region Results 37

5. CONCLUSIONS AND RECCOMENDATIONS 47

REFERENCES 49

APPENDIX A: Parametric Hurricane Model Input 52

APPENDIX B: WW3 INPUT FILE (Ocean Region) 56

APPENDIX C: ECOM INPUT FILE (Layer 1) 61

APPENDIX D: SWAN INPUT FILE (Layer 1) 63

APPENDIX E: ANIMATION DESCRIPTIONS 65

vi

LIST OF FIGURES

Figure 1: Hurricane Package Flowchart (Hurricane Ivan test case) 7

Figure 2: Gulf of Mexico Buoy and Station Locations 21

Figure 3: Hurricane Ivan Track 24

Figure 4: Hurricane Model Wind Comparisons 28

Figure 5: Hurricane Model Direction Comparisons 29

Figure 6: WW3 Significant Wave Height Comparison 30

Figure 7: WW3 Dominant Wave Period Comparison 31

Figure 8: WW3 Mean Wave Direction Comparison 32

Figure 9: Significant Wave Height Comparison between WW3 and Nested WW3 33

Figure 10: Nested WW3 Significant Wave Height Comparison 34

Figure 11: ECOM Water Level Comparison (Ocean Region) 36

Figure 12: Nest #1 ECOM Water Level Comparison (Coastal Region) 38

Figure 13: Nest #2 ECOM Water Level Comparison (Coastal Region) 39

Figure 14: Nest #3 ECOM Water Level Comparison (Coastal Region) 40

Figure 15: SWAN Wave Comparison 43

Figure 16: Chandeleur Islands Overwash 44

Figure 17: Chandeleur Lighthouse Location Before Hurriane Ivan 45

Figure 18: Chandeleur Lighthouse After Hurricane Ivan 46

Vll

LIST OF TABLES

Table 1: Hurricane Ivan Track and Intensity until Initial LandfalL 25

Table 2: NOAA Buoy and C-MAN Station Data 27

Table 3: CO-OPS Water Level Station Data 36

V111

1. INTRODUCTION

The Gulf Coast region of the United States is annually subjected to the effects of tropical

storms and hurricanes. The strong winds, heavy rains, and high seas from these

hurricanes cause extensive damage to areas within their paths. Coastal communities are

especially at risk due to their susceptibility to flooding. The Gulf Coast region contains

many coastal communities located on barrier islands or in low-lying areas, which are

extremely susceptible to the effects of storm surge and waves. Accurate modeling of the

waves and storm surge associated with hurricanes is crucial to minimize the damage to

coastal communities. The ability to accurately model the storm surge and waves is

crucial to the preparation for oncoming hurricanes, as well as, in the planning for future

coastal development. A comprehensive model or model package is needed for the Gulf

Coast region to provide accurate data to the coastal communities.

There are many aspects associated with hurricanes that require simultaneous simulation.

These aspects include: track, wind field, pressure distribution, storm surge, waves, and,

coastal and surf-zone processes. All of these elements operate on different length and

time scales; therefore, separate models are necessary to define the hurricane phenomenon.

Individual components have been modeled successfully, but a complete and accurate

package, which combines the individual models, is less readily available (Flather 2000).

Phadke et al. (2003) describes the application of parametric hurricane models with WAM,

a third generation ocean wave prediction model developed by WAMDI Group (1988), for

the hindcast of the wind and wave fields produced by Hurricane Iniki in 1992. A

reasonable representation of the wind and wave fields was obtained by the modified

Rankine vortex model for measurements near the core of the storm. Cheung et al. (2003)

describes a model package, which simulates the coastal flooding associated with the

storm surge and waves generated by hurricanes. This package provides results in

1

agreement with the recorded storm-water levels and overwash debris lines of Hurricanes

Iwa and Iniki, which hit the south shore of Kauai in 1982 and 1992 respectively.

The accuracy of the package described by Cheung et al. (2003) is dependent on the

accuracy of models within the package: WAM, SWAN, storm surge model (SSM), and

CaULWAVE. The third generation spectral model, WAM, simulates the growth and

propagation of surface waves in the open ocean based on wind energy input. SWAN

(Simulating WAves Nearshore) is a third generation spectral wave model that describes

the evolution of two-dimensional wave energy spectra in coastal and inland waters, for

given winds, currents, and bathymetry (Booij et aI., 1999, and Ris et aI., 1999). The

storm surge model (SSM) is based on the governing equations of Mastenbrook et al.

(1993) and the numerical scheme developed for tsunami modeling by Liu et al. (1995).

The model is capable of simulating the absorbing and reflecting conditions for open

boundaries as well as fixed or moving waterlines along the coast. CaULWAVE (Camel

University Long WAVE) is a Boussinesq-type equation model that.allows for the

evolution of fully nonlinear and weakly dispersive long and intermediate waves over

variable bathymetry (Lynett et aI., 2002). CaULWAVE provides a wave-by-wave

simulation of the wave processes in the surf and swash zones, and is capable of

simulating the wetting and drying of coastal land.

In August of 2001, WAVEWATCH III replaced WAM at the Fleet Numerical

Meteorology and Oceanography Center (FNMOC), which pioneered the use of spectral

ocean models (Wittmann, 2001). Much like WAM, WAYEWATCH III is a third

generation spectral wave model. WAYEWATCH III was developed at the National

Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental

Prediction (NCEP) as a third-generation wave model which addressed the limitations of

WAM, such as the poor performance when considering extremely short fetches (Tolman

and Chalikov, 1996). The storm surge can be modeled by the Estuarine and Coastal

2

Ocean Model (ECOM). ECOM is a three-dimensional hydrodynamic model for shallow

water environments such as rivers, lakes, estuaries and coastal oceans (Blumberg, 1996).

ECOM models the water surface elevations and currents of a specified geographic area.

With the incorporation of more accurate models within the package·described by Cheung

et al. (2003), the overall package will provide a more complete and accurate description

of the storm surge and waves caused by hurricanes.

The objective of this work is to implement four component models, namely a parametric

hurricane wind model, WAYEWATCH III, SWAN, and ECOM, to describe the storm

surge and waves associated with intense hurricanes in the Gulf Coast region of the United

States. The component models have been selected from a range of numerical models

because of their proven performance and applicability to the objective of this work. The

overall package is compared to measurements from a recent hurricane in the Gulf of

Mexico as a means of calibration and testing. This thesis summarizes and documents the

knowledge gained through the assembly and testing of this hurricane model package, and

the sensitivity of the spectral wave models to the computational grid resolution.

3

2. STORM-INDUCED WAVES AND STORM SURGE

The storm surge and waves associated with hurricanes contribute greatly to the overall

destruction of coastal properties. There are many processes and variables that contribute

to and affect these factors. It is important to account for the interaction between these

various components and their effect on the accuracy of the results. Hurricanes typically

pass through three major regions of the ocean modeling environment: ocean, coastal, and

nearshore. The nearshore region can be incorporated into the coastal region modeling,

but the ocean region should be modeled separately for the better agreement with the

measured data.

There are two fundamental aspects, the low pressure and high speed wind, of hurricanes

that are mainly responsible for creating storm surge and waves. The pressure associated

with a hurricane is lowest in the core, or center, and increases towards atmospheric

pressure away from the core. The low pressure core creates a rise in local water surface

elevation, which is defined as the barometric tide. The barometric tide is a localized

dome of water centered at the core of a hurricane in the open ocean. The height of the

dome varies depending on the intensity of the hurricane and the bathymetry. The

barometric tide is just one of the components of storm surge. High speed winds are

responsible for creating wind setup, which contributes to storm surge in the coastal and,

nearshore region.

The high speed winds associated with hurricanes generate waves in the ocean and coastal

regions. The breaking of these large waves near the shore creates radiation stress that

causes water to accumulate in the surf zone. This, in turn, leads to an increase of water

surface elevation at the shore, or wave setup. Concurrent with the wave setup in the surf

zone, a decrease in water level, or wave setdown, occurs outside of the breaker line. In

the northern hemisphere, the highest wind speeds and largest waves associated with a

4

hurricane occur in the right-forward quadrant of the hurricane. This causes a gradient in

both wave and wind setup along the landfall site. As a hurricane makes landfall, the

winds in the right-forward quadrant are blowing onshore, while the winds in the left­

forward quadrant are blowing offshore. As the wind blows towards or away from shore,

the wind stress causes the water level to either increase or decrease at the shoreline. This

is known as wind setup and setdown. It is the combination of wind setup, wave setup,

and barometric tides that composes storm surge. In addition to storm surge, the

astronomical tides also playa role in the storm water level. The astronomical tides can

either increase or decrease the overall water surface elevation during the hurricane's

landfall.

Waves created by hurricanes are a major contributing factor to the overall damage caused

by hurricanes. These waves are formed by the high speed hurricane winds blowing over

a given fetch in open water. The fetch of hurricanes can be somewhat limited due to the

compact, concentric nature of the hurricane wind field. Nevertheless, the intensity of the

hurricane winds can generate very large wave heights. As these waves propagate towards

shore, they travel on an elevated water surface elevation due to the storm surge. This

allows the breaker line to be shifted closer to the shore than under normal breaking

conditions. This combination of wave activity and storm surge causes the run-up and

inundation of coastal areas during hurricane events.

5

3. STORM SURGE AND WAVEMODELING

3.1. Hurricane Model Package Components

The hurricane package consists of multiple numerical models that simulate the storm

surge and waves associated with hurricanes. Documented, proven models were selected

for this package based on their functionality, speed, and ease of interface. Message

Passing Interface (MPI) versions of the models were incorporated into the package,

where possible, to improve the computational time. The individual components as well

as the entire package was tested and calibrated based on a recent hurricane test case in the

Gulf Coast region.

The interaction between the component models is shown in Figure 1, along with the

resolutions used in the test case. The flow chart shown in Figure 1 depicts the

configuration and model component grid sizes and resolutions of the hurricane model

package for the test case of Hurricane Ivan. The ocean region section of the flow chart

covers the entire Gulf of Mexico region, including portions of the Caribbean Sea and the

Atlantic Ocean; therefore the package is capable ofmodeling any hurricane in this region.

The coastal region section of the flow chart shows the configuration setup for the landfall

location of the test case. The location of the component model runs, in the coastal region,

can be altered for other regions of the Gulf of Mexico and other test cases. Although the

coastal region modeling overlaps the nearshore region, a Boussinesq model can provide

wave by wave modeling as well as wave setup calculations nearshore. This package

currently provides the user with the boundary conditions and storm water level necessary

for a Boussinesq model.

6

3.1.1. Parametric Wind Models

The wind and pressure fields from a hurricane are generated by parametric wind models.

The wind field of the parametric models is based on concentric circles, where the wind

speed is zero at the core of the hurricane. The winds increase radially outward from the

core until the user-specified radius of maximum winds, Rmw• is reached. after which the

winds decrease towards zero as the distance from the Rmw increases. The pressure fields

for the models are computed as an exponential distribution, where the lowest pressure is

at the core of the hurricane and the pressure increases exponentially as the distance from

the core increases until atmospheric pressure is reached.

~3

(0.26"" (16 min)]

WW3 (nest # 1)[0.10· (6 mln)J

ECOM[0.10· (6 mln)J

SWAN ECO ne 1)[0.017· (1 In)J 1.-1----------..... [0.017- (1 m )J

SWAN (ne t .1) I..-I-----------fECO n 2)(0.0017" (8 ••c)] (0.001 (8 ••c)]

Figure 1: Hurricane Package Flowchart (Hurricane Ivan test case)

7

One program, which includes four separate parametric models, is used to generate the

wind and pressure fields. These parametric models have been shown to be valid for at

least one hurricane event in a particular region. The user can select one of the four

parametric models for any given model run: modified Rankine vortex (Hughes, 1952),

SLOSH wind model (Jelesnianski et aI., 1992), Holland wind model (Holland, 1980),

HURRECON wind model (Boose et aI, 1994; 1997; and 2001). All of the parametric

models use the same input file, with slight modifications. A documented example of the

input file is available in Appendix A.

The modified Rankine vortex model is the only parametric model that allows the wind

speed distribution in the radial direction to be adjusted

v = Vm~ (~J forr < R",.

v = V ( Rmw)X for r > ."m~ - ~~w

r

(3.1)

(3.2)

where r is the radial distance from the hurricane's core, Rmw is the radius of maximum

winds, and Vmax is the maximum wind speed. The adjustment is performed with a shape

parameter X, which has a range of0.4<X<0.6 (Hughes, 1952).

The SLOSH model is currently implemented at National Weather Service (NWS) for

storm surge computation of inland and coastal waters (Jelenianski et aI, 1992). The

SLOSH model, as part of its storm surge computations, also implements a parametric

wind model, which has been tested for validity against NOAA's Hurricane Research

Division's observed surface wind fields (Houston et aI., 1999). The wind speed for the

SLOSH model is provided by

(3.3)

8

Since the maximum wind velocity, Vman is not always available throughout a storm's

duration, the wind fields can be calculated based on the storm's central pressure, pc.

After studying numerous hurricanes in the western North Pacific, Atkinson and Holliday

(1977) developed an empirical relationship for Vmax based on pc.

v =344(1010- )0.644max· Pc (3.4)

This empirical relationship has been proven to be valid for hurricanes in the Atlantic,

Caribbean, and Gulf of Mexico (Powell and Houston, 1998). The modified Rankine

vortex, SLOSH, and HURRECON parametric models all use the Atkinson and Holliday

relationship to obtain Vmax•

The wind field for the Holland model (Holland, 1980) is determined from Schloemer

(1954), which uses an exponential distribution of the atmospheric pressure field

P~Pc =exp[_(~w)B]Pn Pc r

(3.5)

where B is the peakedness parameter, P is the pressure at radius, r, and Pn is the

atmospheric pressure. The wind field is then determined from the equilibrium between

the centrifugal force of the rotating air mass with the atmospheric pressure gradient and

the Coriolis forces. The wind speed, which is referred to as the gradient wind speed is

given by

(3.6)

where f is the Coriolis parameter and p is the air density. As the r ~ Rmw ' the Coriolis

force becomes relatively small compared to the centrifugal forces and gradient forces and

Eq. (3.6) becomes

9

Harper and Holland (1999) recommended an empirical relationship for B

p -900B =2 - C for 1.0 < B < 2.5.

160

(3.7)

(3.8)

The HURRECON model is based on the published empirical studies of multiple

hurricanes in Puerto Rico and New England (Boose et aI, 1994; 1997; and 2001). In

addition to information on the track, size, and intensity of a hurricane, the HURRECON

model accounts for whether the hurricane is over land or water in calculating the wind

velocity. The wind velocity, referred to as the sustained wind velocity, is calculated from

(3.9)

where F is the frictional scaling factor (water or land), S is the scaling parameter for

asymmetry due to the hurricane's forward motion, T is the clockwise angle between the

forward path of the hurricane and a radial line to any given point, and VF is the

hurricane's forward velocity. The HURRECON wind velocity equation has been adapted

from Holland's equation for cyclostrophic wind (Holland 1980).

The computed wind speeds from the parametric models are adjusted to the standard 10

meter elevation by

(3.10)

where Km is the correction factor. Powell and Black (1990) suggests that Km = 0.8 is a

valid correction factor for the SLOSH model, based on GPS dropwindsonde

measurements. This factor was also applied to the HURRECON and modified Rankine

10

vortex because both models use the same input Vmax as the SLOSH model. Harper and

Holland (1999) suggest that Km == 0.7 for the Holland model.

The parametric wind models assume a circular wind flow pattern, which does not

correctly describe actual surface wind directions that point towards the core of a

hurricane. An approximation for the inflow angle as a function of the radius was

determined by Bretschneider (1972)

(3.11)

(3.12)

(3.13)

where ~ is measured in degrees inward from the tangential flow.

In order to account for the forward motion of slow-moving hurricanes, the following

equation by lelesnianski (1966) is suggested by the Shore Protection Manual (1984) to

ensure that the forward velocity effects are limited

U (r) = R".wr v.R2 2 Fmw +r

(3.14)

where VF is the forward velocity of the hurricane and U is the correction term, which is

vectorally added parametric wind velocity. The HURRECON model can account for the

asymmetry due to forward velocity; therefore, it does not require this correction term.

3.1.2. WAVEWATCH III (WW3)

WAYEWATCH III (WW3) is a third generation spectral wave model, which was

developed at the NOAAlNCEP. Tolman et al. (1996) provides a detailed description of

11

the theoretical background ofWW3. Subsequent versions ofWW3 have been released in

order to address previous limitations and improve the overall program (Tolman, 2003).

The governing equation for propagation in WW3 is the wave action balance equation.

The wave action balance equation in a spherical grid is given by

aN 1 a· a· a . a· s-+---~NCOSe+-AN+-kN+-e N=-at cos t/J at/J aA ak aB g a

. cgcosB+Udit/J =--=-------'-R

i = ---,cg,,--s_in_B_+_U_A"-.

Rcost/J

B =B cg tan~ coseg R

(3.15)

(3.16)

(3.17)

(3.18)

where N is the wavenumber spectrum, Ais longitude, <I> is latitude, R is the earth's radius,

cg is the group velocity, U<t> and U).. are the current components, and S represents the

source terms. The general source terms, defined for the energy spectra, are given by

(3.19)

which includes wind-wave interactions, nonlinear wave-wave interactions, dissipation or

'whitecapping', and wave-bottom interactions, respectively. In order to avoid a loss of

spectral resolution in shallow water, the wave action balance equation is solved on a

variable wavenumber grid, which implicitly incorporates the kinematic wavenumber

changes due to shoaling (Tolman, 2003).

The input and operation requirements for WW3 are provided by Tolman (2003).

Running WW3 involves invoking multiple auxiliary programs through a single input file.

The user defines the size of the computational grid by supplying the bathymetry and

specifying the time step information. Initial conditions can be defined by the user, or

12

they can be read from a 'restart' file, which is generated from a previous WW3 run.

Multiple fields can be input into WW3 such as ice concentrations, water levels, winds

(including air-sea temperature difference), and currents. WW3 is capable of generating

nested output for multiple for multiple higher resolution runs. WW3 is also capable of

running on distributed memory machines (MPI) for a decrease in overall computation

time. Output is available in many forms, including but not limited to point output,

gridded field output, spectral output, GRIB output, and GrADS output.

WW3 has a long development history as well as a long history of use in both global and

regional scales. The National Weather Service (NWS) currently issues operational wind­

wave forecasts using the WAYEWATCH III (NWW3) Wave Model Suite, which

consists of four core wave model implementations and two specialized hurricane wave

models (Alves et aI., 2004). The two specialized wave models incorporate wind fields

from the Geophysical Fluid Dynamics Laboratory (GFDL) Hurricane Model runs and the

Global Forecast System (GFS) winds to model the regional waves produced by

hurricanes in the North Atlantic and the North Pacific (Chao et aI., 2004).

3.1.3. Simulating WAves Nearshore (SWAN)

Simulation WAves Nearshore (SWAN) is a third generation spectral wave model used

for obtaining realistic wave parameters in coastal areas, lakes and estuaries, for given

wind, bottom, and current conditions. SWAN was created at the Delft University of

Technology, which releases subsequent versions of the program to improve upon

previous limitations (Booij et aI., 2004). Booij et aI. (1999) and the SWAN Cycle II User

Manual (Booij et aI., 2004) provide a detailed description of the theoretical background

and implementation of SWAN. The governing equation in SWAN is the same as that of

WW3, the action balance equation. The action balance equation, for spherical

coordinates, in SWAN is given by

13

a a ( )-1 a a a s-N+-cAN+ coup -Ccp coscpN +-caN+-ceN =-.at a;t acp au ae u(3.20)

The first term on the left-hand side of the equation represents the local rate of change of

action density in time, and the second and third terms represent the propagation of action

in geographical space. The fourth term represents the shifting of the relative frequency

due to depth and current variations, and the fifth term represents the depth and current

induced diffraction. The term of the right-hand side represents the source terms, which

are similar to those of WW3, except SWAN places a greater emphasis on depth-induced

wave breaking.

SWAN integrates the action balance equation with finite difference schemes in all five

dimensions (time, geographic space, and spectral space). These are first described for the

propagation of waves without the source terms for generation, dissipation, and wave­

wave interactions, and then the implementation of these source terms are described.

Time is discretized by a user-specified time step for the simultaneous integration of the

propagation and the source terms. This differs from WW3, where the time step for

propagation can be different from that of the source terms. Geographic space is also

discretized by user-specified constant resolutions in latitudinal and longitudinal directions.

SWAN also allows users to specify the range for the discrete frequencies.

Similar to WW3, SWAN allows multiple inputs into the model, such as bathymetry,

water levels, currents, winds, and friction. SWAN also allows the user to select whether

nonlinear quadruplet wave interactions or triad wave-wave interactions are computed.

SWAN is also capable of generating nested grids for multiple runs. SWAN, like WW3,

is capable of running on distributed memory machines (MPI) in order to decrease

computational time. The output produced by SWAN can be in multiple forms, depending

on the end-use for the data.

14

Booij et al. (1999) conducted extensive testing of SWAN and validated the model for

coastal regions. The model was verified for locations along the Dutch and German coasts

in the southern North Sea by Ris et al. (1999). The Office of Naval Research (ONR) and

the Ministry of Transport, Public Works, and Water Management (The Netherlands)

support the use of SWAN as a community model. Current work by the Department of

Ocean and Resources Engineering has shown agreement between NOAA buoy data and

nested WW3 and SWAN models for the Hawaiian Islands and the Island of Oahu

(Hansen, 2005).

3.1.4. Estuarine and Coastal Ocean Model (ECOM)

The Estuarine and Coastal Ocean Model (ECOM) is a three-dimensional hydrodynamic

model for shallow water environments, such as rivers, bays, estuaries, reservoirs, lakes,

and the coastal ocean (Blumberg, 1996). ECOM is the shallow water version of the

Princeton Ocean Model (POM) (Blumberg and Mellor, 1987). ECOMSED is a version

of ECOM that includes a hydrodynamic model, wave model, and a sediment transport

model. ECOMSED is currently implemented in the hurricane model package, but both

the wave and sediment transport models are not included in the computations; therefore,

the model is referred to as ECOM for purposes of this research.

Blumberg (2002) provides descriptions of the theoretical background and the

implementation of ECOM. The underlying equations of the hydrodynamic model

describe the velocity, surface elevation, temperature, and salinity fields. Two simplifying

approximations are used, hydrostatic assumption and Boussinesq approximation. The

governing equation of the hydrodynamic model in ECOM is based on the Reynolds

momentum equations

au ~ au 1 ap a ( au)-=v·vu+w--jV=----+- KM - +Fxat az Po ax az az

15

(3.21)

av ~ av 1 ap a( av)-=v·vv+W--jU=---+- KM - +Fyat az Po ay az az

appg=-­az

(3.22)

(3.23)

where V is the horizontal velocity vector with components (U, V), V is the horizontal

gradient operator, KM is the vertical eddy diffusivity of turbulent momentum mixing, f is

the Coriolis parameter, and P is the pressure. The terms Fx and F y represent unresolved

processes and are given by

F =~[2A aU]+~[A (au + av)]x ax Max 8y M 8y ax

R =~[2A aV]+~[A (au + av)]y ax May ax M 8y ax

where AM is the horizontal diffusivity.

(3.24)

(3.25)

The governing equations, along with their boundary conditions, are solved by finite

difference techniques. ECOM implements a horizontally and vertically staggered lattice

of grid points for the computations, and adopts an implicit numerical scheme in the

vertical direction and a mode splitting technique in time for computational efficiency.

Although ECOM can be run as a three-dimensional model, only the two-dimensional,

horizontal model is implemented in the hurricane package. Input to the hydrodynamic

model of ECOM is provided by tidal boundary conditions from TPX06.2, which is a

medium resolution global inverse tide model (Egbertand and Erofeeva, 2002). Along

with the tidal input, synoptic wind and pressure fields and salinity and temperature

distributions can be provided as input into ECOM. Blumberg (2002) cites many recent,

successful applications ofECOM to oceanic, coastal, and estuarine regions.

3.2. Hurricane Model Package Input

16

3.2.1. Bathymetric Description

The success of the model package is dependent on the accuracy of the bathymetric data

used in the individual models. Figure I shows the grid size and resolution of the

component models. As a hurricane approaches shallow water, higher resolution

bathymetry is needed for the accuracy of the model results. Multiple levels of

rectangular nested grids in spherical coordinates are used in the package. The bathymetry

is provided by the National Geophysical Data Center's (NGDC) Coastal Relief Model at

varying resolutions (lOmin - 3sec) for portions of the Gulf of Mexico and the GEBCO 1­

min Global Bathymetric Grid.

3.2.2. Astronomical Tides

Accurate representations of the astronomical tide-induced water level fluctuations are

necessary for hindcasting and forecasting purposes. In the ocean region, water level

input from astronomical tides does not have a substantial effect on the modeled results,

but in the coastal and nearshore regions these fluctuations have a significant effect on the

modeled results. Fluctuations in water level affect the wave height as well as the breaker

line. TPX06.2 is currently used in the model to provide the boundary conditions from

the astronomical tides as input into ECOM. TPX06.2 can be used to predict tides as well

as provide past tides. Although ECOM can model the currents associated with tides, the

current component is not considered in this study.

3.2.3. Storm Event

Hurricane events are extremely difficult to predict, and this package does not predict

hurricanes. Although from the appropriate hurricane data, this package can hindcast or

forecast the waves and storm surge associated with a given event. While there are

multiple sources of wind measurements from a hurricane, most are hardly sufficient to

17

fully describe the three-dimensional, complex wind fields of hurricanes. However, there

are many hurricane models that are able to reasonably model hurricane wind and pressure

fields. While a two-dimensional, parametric hurricane model is included in this package,

wind and pressure fields from other hurricane models can be input into this package with

minor adjustments to the data format. The NOAA Geophysical Fluid Dynamics

Laboratory (GFDL) Hurricane Model is a three-dimensional hurricane model that is

currently used by NOAA to predict the track and intensity of hurricanes (Bender et aI,

2001). The wind and pressure fields generated by the GFDL model are compatible with

this hurricane model package.

3.3. Regional Modeling

3.3.1. Ocean Region

Most hurricanes, along with their waves, begin in the open ocean; therefore, ocean region

modeling is the start of the model package. Occurrences in the ocean region can greatly

affect the coastal and nearshore regions. WW3 is primarily a deepwater wave model that

simulates the spatial and temporal evolution of wave spectra. As the waves propagate

through this region, WW3 accounts for the nonlinear interactions, inputs, dissipations that

affect the wave spectrum. ECOM is also used to model the ocean region in this package,

although not to the geographical extent of WW3. The entire Gulf of Mexico is modeled

in ECOM to obtain the water surface elevations for the defined spatial and temporal

region. ECOM computes the water surface elevations generated by the astronomical tide,

barometric tide, and the wind-induced setup.

3.3.2. Coastal Region

Output from both WW3 and the ocean region run of ECOM are used to model the coastal

region with SWAN. The wave spectrum from WW3 and the water surface elevations

18

from ECOM, as well as the hurricane wind field, are used as input into SWAN. SWAN

is a coastal region model with the capability to model ocean regions, but WW3 is a much

more efficient wave model in the ocean region. WW3 provides the spectral boundary

conditions to the SWAN model, which then propagates the energy through the coastal

region, while accounting for wind and water levels. Like WW3, SWAN accounts for the

dissipation and nonlinear interactions. Since SWAN is a coastal model, greater emphasis

is placed on the effects of shallow water and nearshore bathymetry on the energy. Two

nested ECOM models are also used in this region for a better description of the water

surface elevations, as input into SWAN. A nested SWAN run is also implemented at a

higher resolution for increased model accuracy.

19

4. CASE STUDY

This section describes the implementation of the hurricane model package to simulate an

actual storm event that occurred in the Gulf Coast region. Model data is compared to

recorded data of the validation of the package. The input files associated with the

component models are located in the Appendices. A supplementary CD containing the

animations of the output data from the various component models is also provided.

4.1. Study Area - Gulf of Mexico

The Gulf of Mexico is an area that is annually affected by hurricanes. During the period

between 1900 and 2004, the Gulf Coast coast of the United States was the landfall site for

85% of the 68 intense hurricanes (Saffir/Simpson Category 3-5) according to Jarrell et al.

(2001). The warm waters of the Gulf of Mexico aid in the increase in intensity that most

hurricanes undergo in that region. There are many sources of data in the Gulf of Mexico

for past and present hurricanes from the multitude of NOAA buoys and stations (Figure

2.). The focus of this study is on Hurricane Ivan, which made landfall at the Alabama

coastline in September 2004. Therefore, this particular application of the hurricane

package will focus on the eastern Gulf of Mexico, more specifically, the Alabama

coastline and surrounding areas. Hurricane Ivan made landfall just west of Gulf Shores

Alabama, which is surrounded by barrier islands. These barrier islands as well as the

coastal property behind them were developed with many homes, condominiums, hotels,

and other structures, much of which was destroyed by the waves and storm surge caused

by Hurricane Ivan. Much of the shoreline along the Gulf Coast region consists of barrier

islands and back bays with fine siliceous sand or mud in certain areas, and minimal

coastal elevations. The bathymetry contours are relatively uniform and the nearshore

slope is relatively small in this region. The small nearshore slope causes large waves to

20

break at distances far from the shoreline, but when the waves propagate on the elevated

water levels due to storm surge, they can cause extensive damage to the shoreline area.

• 4~1

• 42003

Copvright 2003 STOAMSURF

I 1100 nautical ml"s

' .....":AAIP·_, •·,I.A·,.$·l··.·....'" ..

• 4?OO?

Figure 2: Gulf of Mexico Buoy and Station Locations

4.2. Hurricane Ivan

4.2.1. Background

Figure 3 depicts the track of Hurricane Ivan, and Table I displays the track and intensity

from the National Hurricane Center's HURDAT database and the Atlantic

Oceanographic and Meteorological Laboratory (AOML) analyzed radius of maximum

winds. Hurricane Ivan developed from a large tropical storm that moved off the coast of

Africa on 31 August 2004. Despite initially poor conditions for convection, convective

banding developed around the low-level center on 1 September. Ivan became a tropical

depression at approximately 1800 UTC 2 September. Twelve hours later, the system

21

became Tropical Storm Ivan despite its relatively low latitude (9.7°N). With its center

approximately 1000 n mi due east of Tobago in the southern Windward Islands, Tropical

Storm Ivan became Hurricane Ivan at 0600 UTC 5 September. Ivan underwent an 18 h

period of rapid intensification (rate> 30 kt/24 h) after reaching hurricane strength. After

reaching its first peak intensity of 115 kt at 0000 UTC 6 September, Ivan became the

southernmost major hurricane on record in the North Atlantic. As the hurricane

approached the southern Windward Islands, Ivan came under surveillance by the U.S. Air

Force Reserve reconnaissance aircraft. The aircrew reported that Ivan had strengthened

to a strong category-3 Saffir-Simpson Hurricane Scale (SSHS) hurricane as the center

passed about 6 n mi south-southwest of Grenada. Upon entering the southeastern

Caribbean Sea, the hurricane's intensity remained steady until another period of

intensification ensued at 1800 UTC 8 September. Twelve hours later, reconnaissance

aircraft data indicated that Ivan reached its second peak intensity of 140 kt. This was the

first of three occurrences oflvan reaching category-5 strength.

Ivan reached category-5 strength for the second time at 1800 UTC 11 September, but

only remained at category-5 status for 6 h before weakening to category-4 strength on 12

September. This status was also short-lived as Ivan reached category-5 strength for the

third and final time when it was centered approximately 80 n mi west of Grand Cayman

Island. Despite weakening as the center passed south of Grand Cayman, Ivan inflicted

sustained winds just below category-5 strength to the island. Damage to the island was

severe including extensive wind damage, wave heights of 20-30 ft, and storm surge of 8­

lOft, which resulted in more than 5-8 ft of water covering the entire island except for the

extreme northeast portion of the island. On 13 September Ivan turned northwestward and

slowed to 8-10 kt, while maintaining category-5 strength for the unusually long period of

30 h. This path spared major land masses from the full brunt of the hurricane because the

strongest winds and eye passed through the Yucatan channel, just off the extreme western

22

tip of Cuba. Although the effects of the hurricane on western Cuba were far less than

what occurred in Grenada, Jamaica, and Grand Cayman, there were storm surge reports

of 6-12 ft along the southern coast. After entering the Gulf of Mexico on 14 September,

unfavorable conditions caused Ivan to take a north-northwest path while it underwent a

slow steady weakening.

Ivan approached the u.S. Gulf coast on 15 September and came under the surveillance of

the National Weather Service (NWS) WSR-88D Doppler radars located in Slidell, LA,

Mobile, AL, and Eglin AFB, FL. Hurricane Ivan made landfall at approximately 0650

UTC 16 September, just west of Gulf Shores, Alabama, as a category-3 SSHS hurricane

with maximum sustained winds of 105 kt. After landfall, Hurricane Ivan crosses over to

the Atlantic and loops around Florida and back into the Gulf of Mexico, only to make a

second Gulf Coast landfall in Texas. Our simulation only lasts until approximately 11

hours after Ivan's initial landfall. By the time of the initial landfall, the eye diameter had

increased to 40-50 n mi, which resulted in some of the strongest winds near the southern

Alabama-western Florida panhandle border. In addition to extreme winds, rainfall, and an

abundance of tornadoes caused by Ivan, storm surge of 10-15 ft occurred along the coasts

from Destin in the Florida panhandle to Mobile Bay/Baldwin County, Alabama. Storm

surges of 6-9 ft were observed from Destin eastward to St. Marks in the Florida Big Bend

region. Even further south in Hillsborough Bay/Tampa Bay, Florida, a 3.5 ft storm surge

was recorded. NOAA Buoy 42040, located 64 n mi South of Dauphin, AL, recorded a

possible record observed wave height of 52.5 ft before it was damaged by the hurricane.

As much as a quarter-mile of the Interstate 10 bridge system across Pensacola Bay,

Florida were severely damaged as a result of wave action on top of 10-15 ft of storm

surge. In the Alabama and Florida panhandle areas, widespread overwash occurred along

much of the coastal highway system. Extensive beach erosion and scouring of the sand

underneath foundations caused severe damage or destruction to much of the coastal

23

structures. Hurricane Ivan was the most destructive hurricane to make landfall in this

area in more than 100 years.

IlIrric'il'!! I.<ln2·14$e~~

- HllOOaoe~--l--+---+~-~--+---+--i ...... flOpi::al Sl~ill'Ii

...... TlIlpillal Dip,

~..$J1.!lT,S'mn

suI.!lT.o~,

L.1wtw-

• roUTCI'Il~

• 12 UTC 1'Ils*r>n

~ PPP MIl. PIt_ (mil)

5L...i...o.................."""""-'~........~........L................L........w................""""-'-.....a........L.&...............L.o.............I...i............l..i....I................~L...i...o.........J

.95 .90.85 ·80 ·75 .70 .65 ·60 .55 .50 .45 .40 .35 ·30 .25

Figure 3: Hurricane Ivan Track

24

DatelTime Position PressureWind AOMLSpeed Analyzed Stage

(UTe) Lat. (ON) Lon. (OW) (mb) (kt) RMW (km)02/1800 9.7 27.6 1009 25 N/A tropical depression03/0000 9.7 28.7 1007 30 N/A ..03/0600 9.7 30.3 1005 35 N/A tropical storm03/1200 9.5 32.1 1003 40 N/A ..03/1800 9.3 33.6 1000 45 N/A ..04/0000 9.1 35.0 999 45 N/A ..04/0600 8.9 36.5 997 50 N/A ..04/1200 8.9 38.2 997 50 N/A ..04/1800 9.0 39.9 994 55 N/A ..05/0000 9.3 41.4 991 60 N/A ..05/0600 9.5 43.4 987 65 N/A hurricane05/1200 9.8 45.1 977 85 N/A ..05/1800 10.2 46.8 955 110 N/A ..06/0000 10.6 48.5 948 115 N/A ..06/0600 10.8 50.5 950 110 N/A ..06/1200 11.0 52.5 955 110 N/A ..06/1800 11.3 54.4 969 90 11.1 ..0710000 11.2 56.1 964 90 29.7 ..07/0600 11.3 57.8 965 95 24.5 ..07/1200 11.6 59.4 963 100 21.3 ..07/1800 11.8 61.1 956 105 11.1 ..08/0000 12.0 62.6 950 115 14.9 ..08/0600 12.3 64.1 946 120 20.8 ..08/1200 12.6 65.5 955 120 19.4 ..08/1800 13.0 67.0 950 120 14.4 ..09/0000 13.3 68.3 938 130 13 ..09/0600 13.7 69.5 925 140 13 "09/1200 14.2 70.8 919 140 13 ..09/1800 14.7 71.9 921 130 13 ..10 I 0000 15.2 72.8 923 130 11.1 ..10 I 0600 15.7 73.8 930 125 19 ..10/1200 16.2 74.7 934 125 19.4 ..10/1800 16.8 75.8 940 120 18.5 ..11/0000 17.3 76.5 926 135 17.2 "11/0600 17.4 77.6 923 130 29.2 ..11 11200 17.7 78.4 925 125 20.9 ..11/1800 18.0 79.0 920 145 16.7 ..12/0000 18.2 79.6 910 145 16.7 ..12/0600 18.4 80.4 915 135 18.1 ..12/1200 18.8 81.2 919 135 17.2 ..12/1800 19.1 82.1 920 130 33.4 ..13/0000 19.5 82.8 916 140 38.9 ..13/0600 19.9 83.5 920 140 38.9 ..13/1200 20.4 84.1 915 140 32 ..13/1800 20.9 84.7 912 140 29.7 ..14/0000 21.6 85.1 914 140 25.5 ..14/0600 22.4 85.6 924 140 33.9 ..14/1200 23.0 86.0 930 125 35.7 ..14/1800 23.7 86.5 931 120 40.8 "15/0000 24.7 87.0 928 120 38.9 ..15/0600 25.6 87.4 935 120 41.7 "15/1200 26.7 87.9 939 115 31.6 "15/1800 27.9 88.2 937 115 43.6 ..16/0000 28.9 88.2 931 110 36.2 ..16/0600 30.0 87.9 943 105 38 ..16/1200 31.4 87.7 965 70 37.1 ..16/1800 32.5 87.4 975 50 37.1 tropical storm

Table 1: Hurricane Ivan Track and Intensity until Initial Landfall

25

4.2.2. Hurricane Wind Model Results

Two hurricane wind models were compared with recorded data for Hurricane Ivan. All

four options of the parametric hurricane model are considered. The other model that was

compared was the NOAA GFDL Hurricane Model. The GFDL hurricane model is a

limited-area baroclinic model that receives its initial and boundary conditions from the

Aviation run of the Medium Range Forecast (MRF) model (Bender et aI, 2001). The

GFDL model differs from the parametric models because it is three-dimensional, predicts

hurricane tracks and intensities, and is coupled with an ocean model. The GFDL model

also incorporates triply-nested meshes (112°, 113°, 116°) over three ocean domains into its

computation of the hurricane wind field. The GFDL wind field that was used for the

comparisons was blended with the Global Forecast System (GFS) wind field for the

corresponding spatial and temporal locations. The resolution ofthis blended wind field is

0.25°x 0.25° over the same area as the WW3 North Atlantic Hurricane (NAH) model run

[00-500N, 98°-300W] from September I_30th (Chao et aI., 2004). The resolution of the

parametric hurricane model is user-selected and was chosen to be 0.1 °xO.l ° over 11 0_

32.5°N, 91°-54°W. Both wind model simulations began at 1800 UTC on September 6,

2004 and ended at 1800 UTC on September 16, 2004. The parametric models and the

GFDL model were compared at six different locations as indicated in Figure 2 and the

detailed information is provided in Table 2.

26

Station Number Station Location Water Depth Watch Radius Anemometer Ht. Ivan Proximity[ON] [oW] [m] [m] [m] [km]

42001 25.84 89.66 3246.0 2865.7 10 199.7242003 26.01 85.91 3164.0 2830.1 10 155.7642007 30.09 88.77 13.4 40.2 5 84.5042040 29.18 88.21 443.6 443.5 5 31.52DPIA1 30.25 88.07 N/A N/A 13.5 32.20BURL1 28.90 89.43 N/A N/A 30.5 119.80

Table 2: NOAA Buoy and C-MAN Station Data

The track and intensity data for Hurricane Ivan was obtained from the National Hurricane

Center (NHC) of NOAA. The radius of maximum winds (Rmw) is one of the parameters

of a hurricane that is not always available. For the parametric model runs, the Rmw was

obtained from the Atlantic Oceanographic and Meteorological Laboratory (AOML) of

NOAA. The AOML recorded the observed radius and speed of the maximum winds

from satellite imagery of the hurricane wind fields throughout its duration. The observed

Rmw from the satellite images were then reanalyzed with additional hurricane data for

greater accuracy in the description of Rmw • The AOML's analyzed Rmw were used as

input in the parametric models. This was not needed for the GFDL hurricane model,

because the size and structure of the storm are determined by the model itself.

Figure 4 shows the comparison between wind speeds from the hurricane models and the

measured data. The modified Rankine vortex model provides the best wind speed

comparison with the recorded data of all the parametric models; although, the

HURRECON model also performs well. The modified Rankine vortex is the only

parametric model that has a shape parameter that allows for wind speed distribution

adjustment in the radial direction. For better agreement with the measured data, the

shape parameter for the modified Rankine vortex model was set to X = 0.41. The GFDL

model accurately simulates the hurricane wind speed except for the peak of the winds,

where it tends to overestimate the wind speed. It should be noted that the parametric

hurricane wind models provide output every 30 minutes where the GFDL model's output

27

is every hour for four hours with a two hour gap in data between the four hour intervals.

This contributes to the spikes in the GFDL data as compared to the relatively smoother

parametric model data.

09117

09/11

09111

09/1609/15

Buoy 420034Or----~---~-------,

~.5. 30~J. 20

1!! 10 _.._.,I .0···..•·..·..

09/14 09/15 09116Buoy 42040

_ 60 .--------;;Bu~o-y--::4:::2-=-04-::0::-r--~----,.!!!E - Mod. Rankine- 40 --- SLOSH"I ........ Hollandlit 20 -,_ .. HURRECON1!! - GFDL0;; ~~,,;;,..~__-_-=... -:=:-.#..••~ 0 ......... - •. IItl ....,.u,,,··

09/14 09115 09116DPIA1

40 r--....".---,-----,~ ....,.---~---__,

~ Station DPlA1.5. 30 - Mod. Rankine~ --- SLOSH: 20 ,,'..... Hollandlit -.... HURRECON ",.~

, 1'_.-"10 .--, •..-- .......c '.~ ~..,- ,'..".I: ... .- ---- ~...'"o ----- '11 III tlUUI ...•

09/14

09111

09111

09117

09/16

.­...... ..

09/15 09116BURL1

09/15 09/16Buoy 42001

09/150 .....................u.lJJJ.==:..-------'-----::-----l

09/14

Buoy 4200130.------~---~--------.

'WE~ 20

liD~;:

O............................==.:..:.:.:....-------'--------J09/14

40 ...----~--------------,~.5.30

120

~10l-~~~~·

I

Figure 4: Hurricane Model Wind Comparisons

Figure 5 shows the comparison between the wind direction from the hurricane models

and that of the measured data. All of the parametric models provide approximately the

same wind directions regardless of what individual parametric model is run. Both the

GFDL and parametric models closely simulate the recorded wind direction. The only

significant discrepancy between the parametric models and the GFDL and recorded data

is on 09115. This discrepancy is attributed to a slight exaggeration of the hurricane's

overall size by the parametric models. It is also important to note that buoy 42001, where

this discrepancy occurs, has the largest distance from the core of Hurricane Ivan.

28

09111

09117

Buoy 42003

09/15 09/16DPlA1

09/15 09116

. Buoy 42040- Mod. Rankine--- SLOSH I\... "".. Holland-,-" HURRECON

GFDL[.... -l

...- -..

station DPlA1- Mod. Rankine .--- SLOSH ~HIlIIII Holland_.-" HURRECON

~.. ... ... ~.........~

!i'r 360;B 315c 270,g 2251:5 180.= 135c 90'g 45

I 0~/14!i'aI 360:£ 315c 210,g 225U 180.= 135c 90'g 45

I 0~14

!i'

1225

IS 180

I 135...C 90"ClC L~",""-:"'T

I 09lc...14---09....../1-5---0-9~/1-6---09J1-J 7Buoy 42040

09/17

0911709116

Buoy 42001

09115 09/16BURl1

09115

!i'aI 360:£ 315c 270,g 2251:5 180.= 135c 90 ••M ....

'g 45 ··•....-...-·.-··..·M....

I ~14

!i'al360-8 315~ 270o 225:U180'=135c 90'g 45I 0~11~4~~;;0:'91~15~--0-91-'---16---0---l9l17i' Buoy 42007

5!l36O:! 315IS 270_ 2251:5180.= 135c 90'g 45~"ila,~~~~~-.I 0~/14

Figure 5: Hurricane Model Direction Comparisons

4.2.3. Ocean Region Results

The ocean region results include the wave spectrum computed by WW3 and the water

surface elevations computed by EeOM. The wind field generated from the hurricane

models provides the input into WW3. A sample input file for WW3, which shows the

time steps, resolution, and other parameters of this model run, is provided in Appendix B.

Figure 6 shows the comparison between the significant wave height of the hurricane

models and that recorded by four NOAA buoys. The significant wave heights calculated

from the GFDL winds are a better comparison to the measured data than those calculated

from the modified Rankine vortex winds. It should be noted that buoy 42040 measured a

29

record observed wave height of 16 meters just prior to breaking as Hurricane Ivan passed

over the buoy.

0911709116091152~------'~--~----=-=--'

09114

Buoy 42003 (ST2 & STAB2)14 r---~----r=_==_~~"""""""~-____,E . Buoy 42003

.... 12 - WW3: Mod. RankineI - WW3:GFDL

110

I 8

~ 6u

i 4CiS

09/170911609115

o'--__----' ----'- -J

09114

Buoy 42001 (ST2 & STAB2)10.-------~---___,

gI 8'ii:I: 6

Iiiis

Buoy 42007 (ST2 & STAB2) Buoy 42040 (ST2 & STAB2)10 20... ...g g

~ 8 ~ 15"ii .

"ii:I:

6:I:

! 110~

4

!"'u 511= 2 ~~ ...Q

CiS CiS0 0

09114 09115 09116 09117 09114 09115 09116 09117

Figure 6: WW3 Significant Wave Height Comparison

Figures 7 and ~ show the comparison of dominant wave periods and mean wave

directions. The modeled periods do not compare well with the measured periods, but the

data from the GFDL wind input is slightly better than that from the parametric wind input.

The modeling of the waves periods associated with a hurricane is a difficult task because

of the diverse mix of short and long wave periods created by the intense hurricane winds.

With a higher resolution model, such as SWAN in the coastal region, a better agreement

between the computed and measured periods may occur. The computed mean wave

directions in Figure 8 compare reasonably well the measured data. There is still a little

carryover lag in the modeled direction from the modified Rankine vortex model, as was

seen in the wind direction comparisons.

30

0911709116091156'-------'----'-------'

09114

~42003 em & STAII2)14r---""';"T""----,~------___,

Buoy 42003• • - WN3: Mod. Rankine... - WN3:GFDL

~42001em & STAB2)16.--------.--.--~~--....,

~ 42007 em & STAB2)20.----~---~--__,

Buoy 42040 (Sn & STAa2)20r---~---~--_____,

oL...-__---'-__~~__~

08114 09115 09116 09117 09117

Figure 7: WW3 Dominant Wave Period Comparison

31

Buoy 42001 (S12 & STAB2) Buoy 42003 (ST2 & STAB2)

~ 2~ 360 CI 3151315 -8- "'270S 270 S¥ 225 i 225~ ~

c1~ C1~

~ 1:15 • ~ .III .'''' _.._.. ~ 1:15 ••••~ 90 .. :>

= 451------ = 9015 0 '--__----'_---"'--"-'...:..''-'L-•••_..._....-"••_....-J 2

09114 09115 09116 09117 09114

................-

• Buoy 42003- WW3: Mod. Rankine- WW3:GFDL

09/15 0 18 0911

Buoy 42007 (S12 & STAB2) Buoy 42040 (ST2 & STAB2)

091170911609/15

..

09114

2CI 270

!6 225

~ 180C!1:15~

Ii•s0911709116

2 360CI

! 315

6 270=¥ 225~

C 180

! 1:15 ~;~=::~~ 9OL--_--I 4515 O'------'--------'-----'"---J

09114 09115

Figure 8: WW3 Mean Wave Direction Comparison

Figure 9 displays a slight increase in the significant wave height for buoys 42007 and

42040 from the nested model run of WW3, which leads to a slightly better comparison

with the measured data in Figure 10. The resolution of nested WW3 run is 0.1°xO.l ° as

compared to 0.25°xO.25° of the larger WW3 run. The time step for the nested WW3 run

is approximately half that of the larger WW3 run. Also, the nested run begins four days

after the larger WW3 run at 1800 UTe September 10. The dominant wave periods and

mean wave directions remain the same for both runs of WW3.

32

42001: Mod. Rankine 42003: Mod. Rankine 42007: Mod. Rankine 42040: Mod. Rankine6 12 6 14

••

15 16 17

4

8

6

12'III.f.l'

5

2

-4.5.III%3

1 '--~~~~---J15 16 17 14 15 16 17

10

3

5

oL...-_,--~,------J

14 15 16 17september 2004

15

o'--~~~----'14 15 16 17

September 2004

4

2 '--~~~-----'14 15 16 17

september 2004

8

6

2 1--- ---"'-....,- GFDL

o --- GFDL (nest)14 15 16 17

September 2004

8

42001: GFDL model 42003: GFDL model 42007: GFDL model 42040: GFDL model10 14 8 20

12

g 6III% 4

Figure 9: Significant Wave Height Comparison between WW3 and Nested WW3

33

09/1709/1609/152 '-----__-'- ---'-_-----'!:::-...J

09/14

Buoy <&2003 (nested GULF)14,----~-___r_- .......- --___,

~ • Buoy 42003.::. 12 - WW3: Mod. Rankine:;. - WW3: GFDL110

i 8

i 6

i 4iij

091170911609/15O~--~-------'------J

09/14

Buoy 42001 (nested GULF)10r----~-------__,

i:2: 8ClI..

%: 6

i 4

ii 2iij

091170911609115o~__----L ~ ...J

09/14

Buoy 42040 (nested GULF)

091170911609/15O~--~-------""-------'

09/1<&

Buoy 42007 (nested GULF)10r----~-------_,

i:~ 8'ii%: 6

i 4

i-= 2i ... .> ..

iij

Figure 10: Nested WW3 Significant Wave Height Comparison

ECOM is the other component model in the ocean region. The Gulf of Mexico is a semi-

enclosed basin with tidal input only from the straits between Florida and Cuba and Cuba

and the Yucatan Peninsula. Although there are other inputs to the Gulf of Mexico that

can affect the water surface elevations, such as that from rivers, those inputs are

disregarded in this study. The ECOM model runs for longer duration than the component

models in order to allow for the tidal boundary conditions to fully propagate through the

model and fully describe the tidal cycle. The model is initialized with tidal boundary

conditions from TPX06.2 starting at 0000 UTC August 27. The hurricane wind and

pressure fields are then introduced 15 days later to allow the model to 'ramp-up' or

initialize prior to the hurricane fields. At the time that the hurricane wind and pressure

fields are introduced, the hurricane is still outside the Gulf of Mexico; therefore, the

34

withholding of the hurricane fields for the four days has a minimal effect on the water

surface elevations in the Gulf of Mexico. The ocean region run of ECOM uses a 10 sec

time step and a computational resolution of 6 min (0.1°).

Figure 11 shows the comparison between the ocean region run of ECaM and four water

level stations surrounding the landfall site of Hurricane Ivan. Table 3 shows the location,

mean tide level, and mean sea level of all of the water level stations compared in the

ECaM analysis. The data from ECOM in Figure 11 shows an overall agreement with the

recorded data, except for an underestimation of the water surface elevation as the

hurricane nears the locations. Station 8729210 is the only station located directly on the

Gulf of Mexico and hence has the best tidal agreement with the recorded data. The other

three stations are located in bays or locations sheltered from the Gulf of Mexico by

barrier islands. All of the stations are land-based; therefore, the relatively low resolution

of this model run may have a factor in the inaccuracy of the EcaM data. The wave setup

is also not computed by ECaM, so the amplitudes of the computed data are expected to

be lower than that of the recorded data. A minimum water depth criterion of2.5m is used

to stabilize the ocean region EcaM model in shallow water areas. This may also

attribute to the discrepancy in the results because some of the water level stations are

located in depths less than the criterion. The relatively mild slope of this region,

combined with the minimum depth criteria, also contributes to the inaccuracies of the

ECaM data for these specific land-based stations. A copy of the input file for the ocean

region run of ECOM is provided in Appendix C. Animations of the ocean region run of

ECaM as well as the two ocean region runs of WW3 are provided in the supplementary

CD.

35

station 8729210 station 87298402 2. WL station I . WL station I

1.5 - ECOM(1) 1.5 - ECOM(1)..- -.5. : ... .5.c 1 : c 10 ,.: 0

I ,J ICD 0.5 CD 0.5iii iii

0 0

~.5 ~.511 12 13 14 15 16 11 12 13 14 15 16

station 8735180 station 87617242 2. WL station . WL station..

1.5 - ECOM(1) 1.5 - ECOM(1)

- -.5. 1 .5. 1c c0 0

I 0.5 I 0.5CD CD

iii iii

0

~.511 12 13 14 15 16 12 13 14 15 16

Sept. 2004 Sept. 2004

Figure 11: ECOM Water Level Comparison (Ocean Region)

Station 10 State Location Latitude [ON] Longitude [oW] MTL[m] MSL[m]

8729210 FL Panama City Bch, Gun of Mexico 30°12.8' 85°52.7' 0.21 8.448729840 FL Pensacola. Pensacola Bay 30°24.2' 87°12.7' 0.19 2.768735180 AL Dauphin Island. Mobile Bay 30°15.0' 88°4.5' 0.18 1.058744117 MS Biloxi, Bay of Biloxi 30°24.7' 88°54.2' 0.27 6.568747766 MS Waveland, Mississippi Sound 30°16.9' 89°22.0' 0.24 8.708761724 LA Grand Isle, East Point 29°15.8' 89°57.4' 0.16 1.95

Table 3: CO-OPS Water Level Station Data

36

4.2.4. Coastal Region Results

The two component models implemented in the coastal region to simulate the wave

spectra and water surface elevations are SWAN and ECOM. There are two nested

ECOM runs in the coastal region. Refer to Figure 1 for the configuration of the models

in both the coastal and ocean regions. The first nested ECOM model in the coastal region

receives its boundary conditions every 15 minutes from the ocean region run of ECOM.

This nested ECOM model has a resolution of 1 min (0.0167°) compared to that of 6 min

(0.1°) for the ocean region run, and it uses a time step of 3 seconds. The first nest of the

coastal region model of ECOM begins at 0000 UTC September 11, and the hurricane

wind and pressure fields are introduced on the same day as the ocean region ECOM run.

The 15 minute time series of water surface elevations from this ECOM run is used as

input into the first coastal region SWAN model. As the resolution of the coastal region

ECOM models increase, so does the minimum water depth criteria. The lower resolution

coastal ECOM model uses a criterion of 3.5m, while that of higher resolution ECOM

models use a criterion of 4.5m.Figure 12 shows slightly better agreement between the

recorded data and the coastal region ECOM data for stations 8729840 and 8761724 than

that of the ocean region ECOM data. This model run of ECOM also provides the

boundary conditions to the highest resolution coastal ECOM run (nests 2 and 3).

37

station 8729840

14 15 16station 8735180

."

'."

.....h •

.-...

14 15 16station 8761724

. WLstadon-g - ECOM(2)

8I•m

13

- WLstatJong - ECOM(2)cQ

J•iii

.............- -.. . - .-..........~~~

1615

2r;::===:==:==:==:::Jr--------,----------,----------,------,WLstatJong 1.5 _ ECOM (2)

a 1

1 0.5

Iii 0-0.5 L- L- L- L- .1-- ----l

12 13 14Sept. 2004

Figure 12: Nest #1 ECOM Water Level Comparison (Coastal Region)

The highest resolution runs of ECOM, which have a resolution of 6 seconds (0.00167°)

and a time step of 1 second, begin at 0000 UTC September 12, and the hurricane wind

and pressure fields are introduced on September 13. The two high resolution ECOM runs

cover both sides of the hurricane landfall site. Therefore, the effects of wind setup and

setdown are evident in the animations of ECOM layers 3 and 4 in the supplementary CD.

The water surface elevations from these nested ECOM run are used as input into the

highest resolution SWAN runs. Figures 13 and 14 show the water level comparisons for

the highest resolution run of the ECOM model. The slight discrepancy in the results of

the ECOM runs may be attributed to the fact that these stations are located in bays and

not the Gulf of Mexico, and a minimum water depth criterion of 4.5m was applied to

38

these model runs. Wave setup is also a major contributor to these discrepancies as well

as increased river contributions caused by excessive rainfall.

alltlon 87351802 . WL stallan .

- ECOII(1).

1.5

g ".

~1

j 0.5.., . .....

CD .'.m .,. ...... .. ..........~.5

13 14 15 18

allltlon 87....1172 . WL station

1.5 - ECOII(1)

I 1& .' ." .1 .. '

0.5 ....m .....

.. '....

-0.513 14 15

sept. 2004

Figure 13: Nest #2 ECOM Water Level Comparison (Coastal Region)

39

stlllian 87288402rr==::::::=o::::=~=::===;---'--------"""----------'--------,

I . WL stlllian I- ECOM(1)

1.5

:§:1

S

I 0.5

.'0

-O'~'=3--------:1:":4:-------------=-'15=------------:1"'::8---------'

Sept. 2004

Figure 14: Nest #3 ECOM Water Level Comparison (Coastal Region)

The comparison of the various ECOM model's data with that of recorded water level

stations is difficult in the area of interest. All of the water level stations are land based

and are therefore difficult to resolve at lower resolutions. The vast majority of the water

level stations in this region are located ,on rivers, bays, and other bodies of water that are

somewhat disconnected from the Gulf of Mexico. This makes the modeling of the water

surface elevations in these locations very difficult, especially when ignoring wave setup

and river contributions. The minimum water depth criteria may also contribute to these

discrepancies, especially when considering the relatively mild nearshore slope of the Gulf

Coast region.

The increase in the water surface elevation in the nearshore region due to wave setup is

not accounted for in this study. This is evident in the water surface elevation

comparisons around the time of landfall shown in Figures 11, If., .u, and 14. All of the

water elevation stations in this study, except station 8729210, are separated from the Gulf

of Mexico by barrier islands. During the storm event, the barrier islands are overtopped

by waves and storm surge, thus allowing an increase in the water surface elevation in the

40

bays due to the wave setup. The overtopping of the barrier islands is not modeled in this

package; therefore, there is a difference in the modeled and recorded water surface

elevations at the water level stations in the bays. A maximum wave setup of 2.57m was

calculated using the method described in the Shore Protection Manual for the southern

shoreline of the Alabama's barrier islands, assuming that there is no overtopping of the

barrier islands (Coastal Engineering Research Center, 1984). The combination of the

calculated wave setup and the storm surge modeled in the package is within the surge

range provided outlined by the NOAA's National Hurricane Center for a category-3

hurricane.

The SWAN model propagates the wave spectrum from the nested WW3 model in the

ocean region through the coastal region while incorporating winds from the hurricane

wind model and water surface elevations from the two nested ECOM models. The

spatial resolutions of both SWAN models match the resolution of the nested ECOM

models in the coastal region, as shown in Figure 1. Both SWAN models include

nonlinear quadruplet wave interactions and triad wave-wave interactions as well as third

order propagation schemes.

Figure 14 shows the comparison of the first SWAN model with recorded data from two

NOAA buoys. The SWAN data at buoy 42040 shows an improvement in computed

significant wave height over that of the nested WW3 comparison, while that at 42007 is

still severely underestimating the significant wave height. This discrepancy is due to the

relatively shallow depth at the location of buoy 42007, which causes the waves to break

farther from shore in the model because the contribution from wave setup has not been

added into the overall water surface elevations. Another cause of this discrepancy can be

attributed to the proximity of the buoy 42007 to the Chandeleur Islands, which can

influence the modeled waves to refract and break along their shoreline prior to reaching

the buoy location. Extensive erosion and overtopping of the Chandeleur Islands occurred

41

while Hurricane Ivan passed the island chain. The evidence of this is apparent from

before and after aerial photos that show how much of the islands disappeared during the

event (Michot et aI., 2004). The extensive erosion and overtopping of the Chandeleur

Islands modified the local bathymetry and allowed larger waves propagate without

breaking to the location of buoy 42007. Figure 15 shows the number of overwash that

resulted from Hurricane Ivan. The partial overwash channel is defined as a channel that

cuts into the island from the Gulf of Mexico, but does not completely breach the island.

A minor overwash channel cuts all the way through the island in a curved or meandering

course, while a major overwash channel completely divides an island with a wide,

straight channel. Figures 16 and 17 show the erosion and overwash channels caused by

Hurricane Ivan on the portion of the Chandeleur Islands closest to Buoy 42007. These

occurrences are not accounted for in the simulation; therefore, the modeled waves near

buoy 42007 break before reaching that location.

42

Buoy 42007 Buoy 42040

0911709/15 09116Buoy 42040

• Buoy 42040- SWAN:MR1

51..-"",""1'"-o~__----'- """"'--__---J

09114

20 r;::::::====:::::===:;---.----i

-oS 10•%

09117

fl.- "!' fl.

09/15 09116Buoy 42007

• Buoy 42007- SWAN:MR1

o~------'------'---------'09/14

20 r;::::::====::::::::::::==:::;-~------,

-oS 5•%

0911709/15 09116Buoy 42040

5L--------'-----'-----109114

• Buoy 4204015 - SWAN: MR1

~..t- 10

09/17

....

09/15 09/16Buoy 42007

.- ­...................5L,..--J--

o~------'------'---------'09114

• Buoy 4200715 - SWAN: MR1

~ 10..t-

09116 09117

~".

0911709116

...

09/15

Z 270 • Buoy 42040i' 225 - SWAN: MR1:s 180

~ 135 .•••• :.: ••• : ...........~__'VIi 90 • eo.. • e' •

• 45:IEO'-------'------L.&------'

09/14

Z 360 [ • Buoy 42007 IOl 315 - SWAN'MR1~ 270 •~ 225.!::: 180ci 1~~ t......_.•_..._......_._...._......_.._...,,;..;==--==..;,.,:IE 45 '"0'-------'------'-....1.--------'

09/14 09/15

Figure 15: SWAN Wave Comparison

43

Chandeleur IslandsMain chain overwash count by overwash type

Courtesy of National Wetlands Research Center

160

140U-; 120ca! 100CI)

~ 80....o~ 60.!E 40:::JZ

20

o

• Partialo Minor• Major

2/5 7/15 3120 11a 3'26 31.21 91301999 I 2000 I 20011 2002

Survey date

Figure 16: Chandeleur Islands Overwash

1

20031

2004

A first order backward space, backward time (BSBT) scheme was selected for the higher

resolution, nested SWAN run in order to decrease the computational time. Wave

comparisons between at buoy 42007 for the nested SWAN run are nearly identical to that

of the larger SWAN model. The results of this are not shown to avoid redundancy. As

previously mentioned, there are some aspects of the buoy location of the simulation that

may have contributed to the discrepancy at this particular location. Regardless of the

discrepancy at buoy 42007, the results at buoy 42040 compare well with that of the

measured data; therefore, the SWAN simulation component of the hurricane package

provides a valid representation of the coastal wave climate.

44

Figure 17: Chandeleur Lighthouse Location Before Hurriane Ivan

45

Figure 18: Cbandeleur Lighthouse After Hurricane Ivan

46

5. CONCLUSIONS AND RECCOMENDATIONS

The various components required to model the storm surge and wave associated with

hurricanes have been implemented in the hurricane model package. Preliminary testing

and validation have been performed on the package, which has shown reasonable results

for Hurricane Ivan (Sept. 2004) in the Gulf of Mexico. Additional test cases, as well as, a

complete comparison with results from another hurricane model, such as the GFDL

model, have been performed on the package. The computed wind, wave, and storm surge

data indicate reasonable agreement with the recorded data.

There are many areas for improvement within the hurricane model package which can

improve the overall user-friendliness of the package. A single user interface, which

would provide input into all of the component models, would be a great improvement in

terms of user-friendliness. An upgrade to the parallel ECOM model would greatly reduce

the overall computational time of the package. The component structure of the hurricane

model package is very user-friendly in the sense that individual users can use a different

hurricane wind and pressure model. The hurricane model package is also upgradeable,

and newer versions of the component models will be implemented into the package once

they are made available. The improvement of the user-friendliness of the package is a

continuing process that improves over time from the feedback of multiple users.

In order to achieve a more accurate simulation, the wind field generated by the

parametric hurricane model should be blended with the GFS wind field before the wind

field is introduced into WW3. Further testing and calibration of ECOM should be

performed in order to make the model more robust and accurate in the Gulf of Mexico.

The package should also be applied to other regions affected by hurricanes, such as the

East Coast of the United States, which has similar bathymetry to that of the Gulf of

Mexico. Although the package has been tested and validated for a past hurricane event

47

on the Gulf Coast region, the package is not limited to such constraints. The package can

be implemented, with minor parameter adjustments, for both hurricane hindcasts and

forecasts at any location.

Nearshore region modeling through the use of a Boussinesq model is the next component

that should to be implemented into the model. Selection of an appropriate Boussinesq

model is also required for more accurate results. A parallel version of the Boussinesq

model, CaULWAVE, is currently being considered for future implementation into the

hurricane model package. The choice and implementation of a Boussinesq model for

nearshore modeling is currently left entirely up to the user.

48

REFERENCES

Alves, J-H.G.M, Tolman, H.L., Chao, Y.Y., 2004. Hurricane-generated wind-waveresearch at NOAAlNCEP. Proceedings from 8th Ocean Weather Conference, NorthShore, Hawaii, G3.

Atkinson, G.D., Holliday, C.R, 1977. Tropical cyclone minimum sea level pressure­maximum sustained wind relationship for the western North Pacific. MonthlyWeather Review, 105 (4),421-427.

Bender, M.A, Ginis, 1., Marchok, T.P., Tuleya, RE. 2001. Changes to the GFDLHurricane Forecast System for 2001 Including Implementation of the GFDLIURIHurricane-Ocean Coupled Model. Princeton, New Jersey.

Blumberg, AF., 1996. An Estuarine and Coastal Ocean Version of POM. Proceedings ofthe Princeton Ocean Model Users Meeting (POM96), Princeton, NJ.

Blumberg, AF., 2002. A Primer for ECOMSED Version 1.3. Users Manual. HydroqualInc., Mahwah, NJ.

Blumberg, AF., Mellor, G.L., 1987. A Description of a Three-Dimensional CoastalOcean Circulation Model. Coastal and Estuarine Sciences 4: Three-DimensionalCoastal Ocean Models, 1-16.

Booij, N.C., Haagsma, 1.J.G., Holthuijsen, L.H., Kieftenburg, A.T.M.M., Ris, RC., vander Westhuysen, AJ., Zilema, M. 2004. SWAN Cylce III version 40.41 user manual.Delft Institute of Technology, The Nethlands.

Booij, N.C., Ris, RC., Holthuijsen, L.H., 1999. A third-generation wave model forcoastal regions. Part I, Model description and validation. Journal of GeophysicalResearch, 104 (C4), 7649-7666.

Boose, E. R, K. E. Chamberlin, and D. R. Foster. 1997. Reconstructing historicalhurricanes in New England. In Preprints ofthe 22nd Conference on Hurricanes andTropical Meteorology, 388-389. Boston: American Meteorological Society.

Boose, E. R, K. E. Chamberlin, and D. R Foster. 2001. Landscape and regionaUmpactsofhurricanes in Puerto Rico. Ecological Monographs, 71,27-48.

Boose, E. R, D. R Foster, and M. Fluet. 1994. Hurricane impacts to tropical andtemperate forest landscapes. Ecological Monographs, 64, 369-400.

Chao, Y.Y., Burroughs, L.D., Tolman, H.L., 2004. The North Atlantic Hurricane WindWave Forecasting System (NAH). Technical Procedures Bulletin, Series No. 478,Office ofMeteorology, NWS.

49

Cheung, K.F., Phadke, AC., Wei, Y, Rojas, R., Douyere, YJ.-M., Martino, C.D.,Houston, S.H., 2003. Modeling of storm-induced coastal flooding for emergencymanagement. Ocean Engineering, 30 (11), 1353-1386.

Coastal Engineering Research Center, 1984. Shore Protection Manual Volume I. U.S.Government Printing Office, Washington D.C..

Egbert, G.D., and S.Y Erofeeva, 2002: Efficient inverse modeling of barotropic oceantides, J Atmospheric Oceanic Technology, 19(2), 183-204.

Emanuel, K.A, 1999. Thermodynamic control of hurricane intensity. Nature, 401, 665­669.

Flather, R.A, 2000. Existing operational oceanography. Coastal Engineering, 41 (1-3),13-40.

Hansen, D., 2005. Implementation and Validation of a Virtual Buoy Network for theIsland of Oahu Utilizing Nested Third Generation Wind Wave Models. MastersThesis, Department of Ocean and Resources Engineering, University of Hawaii,Honolulu, Hawaii.

Harper, B.A, Holland, G.J., 1999. An updated parametric model of the tropical cyclone.In: Proceedings of the 23rd Conference on Hurricane and Tropical Meteorology,Dallas, TX, 893-896.

Holland, G.J. 1980. An analytic model of the wind and pressure profiles in hurricanes.Monthly Weather Review, 108(8), 1212-1218.

Houston, S.H., Shaffer, W.A, Powell, M.D., Chen, J., 1999. Comparison of HRD andSLOSH surface wind fields in hurricanes: Implications for storm surge modeling.Weather and Forecasting,- 14 (5), 671-686.

Hughes, L.A, 1952. On the low level wind structure of tropical cyclones. Journal ofmeteorology, 9,422-428.

Jakobsen, F., and Madsen, H., 2004. Comparison and further development of parametrictropical cyclone models for storm surge modeling. Journal of Wind Engineering andIndustrial Aerodynamics,- 92, 375-391.

Jarrell, J.D., Mayfield, M., Rappaport, E.N., Landsea, C.W., 2001. The Deadliest,Costliest, Most Intense United States Hurricanes from 1900 to 2000. NOAA TechnicalMemorandum NWS TPC-l. Miami, Florida.

Jelesnianski, C.P., Chen, J., Shaffer, W.A, 1992. SLOSH: Sea, lake, and overland surgesfrom hurricanes. NOAA Technical Report, NWS 48, Silver Springs, Maryland.

Liu, P.L.-F., Cho, Y-S., Briggs, M.J., Kanoglu, D., Synolakis, C.E., 1995. Runup ofsolitary waves on a circular island. Journal ofFluid Mechanics, 302,259-285.

50

Lynett, P.J., Wu, T.R, Liu, P.L.-F., 2002. Modeling wave runup with depth-integratedequations. Coastal Engineering, 46(2), 89-108.

Mastenbrook, C., Burgers, G., Janssen, P.A.E.M., 1993. The dynamical coupling of awave model and a storm surge model through the atmospheric boundary layer.Journal ofPhysical Oceanography, 23(8), 1271-1285.

Michot, T.C., Wilson, S. 2004. Posthurricane Survey of Chandeleur Islands, Louisiana.http://www.nwrc.usgs.gov/hurricane/postivanphotos.htm.

Phadke, A.c., Martino, C.D., Cheung, K.F., Houston, S.H., 2003. Modeling of tropicalcyclone winds and waves for emergency management. Ocean Engineering, 30(4),553-578.

Powell, M.D., Black, P.G., 1990. The relationship of hurricane reconnaissance flight­level measurements to winds measured by NOAA's oceanic platforms. Journal ofWind Engineering and Industrial Aerodynamics, 36, 381-392.

Powell, M.D., Houston, S.H., 1998. Surface wind fields of 1995 Hurricanes Erin, OpalLuis, Marilyn and Roxanne at landfall. Monthly Weather Review, 126 (5), 1259-1273.

Ris, RC., Holthuijsen, L.H., Booij, N.C. 1999. A third-generation wave model for coastalregions. Part II, Verification. Journal ofGeophysical Research, 104 (C4), 7667-7681.

Schloemer, RW., 1954. Analysis and synthesis of hurricane wind patterns over LakeOkeechobee, FL. Hydromet Report No. 31, Government Printing Office, Washington,D.C.

Tolman, H. L., 2003. User manual and system documentation of WAVEWATCH-IIIversion 3.04. NOAA / NWS / NCEP / OMB.

Tolman, H.L. and D. Chalikov, 1996. Source terms in a third-generation wind-wavemodel. Journal ofPhysical Oceanography, 26(11),2497-2518.

WAMDI Group, 1988. The WAM Model: A third generation ocean wave predictionmodel. Journal ofGeophysical Research, 18(12), 1775-1810.

Wittmann, P.A., 2001. Implementation of WAVEWATCH III at Fleet NumericalMeteorology and Oceanography Center: Oceans 2001 MTS/IEEE ConferenceProceedings (available from The Marine Technology Society, 1828 L. Street, N.W.,Suite 906 Washington, DC 20035).

51

APPENDIX A: Parametric Hurricane Model Input

1. Start time

2. End time

3. Time interval

4. Year of occurence

5. Number of input entries

6. yymmddhhmm yearlmonthldaYlhour/mina. Latitude [ON]b. Longitude [0°-360°]

7. Maximum sustained winds (umax) [knots]

8. Central pressure [mB]

9. Radius ofmaximum winds [km]

10. Hurricane shape factor (X-factor) (0.4<X<0.6)

11. Incremental change in latitude

12. Incremental change in longitudea. Start latitude [ON]b. End latitude [ON]c. Start longitude [0°-360°]d. End longitude [0°-360°]

13. Porward speed correction (IPSC)

a. 1 = IPSC is applied

b. 0 = IPSC is not applied

14. Wind cutoff radius: multiple ofRMW where to cutoffwind field (Xmax)

15. Wind model selection

a. 0 = uniform cyclonic wind field model (30 [m/s])

b. I = simple Rankine vortex model

c. 2 = modified Rankine vortex model

d. 3 = SLOSH wind model

52

e. 4 = Holland wind model

f. 5 = HURRECON wind model

16. Atmospheric pressure (PRESATM) [kPa]

17. Density of air [hkg/m3]

18. Wind speed correction factor (0 < Km <1)

a. Holland model

i. Km = 0.7 (Harper & Holland, 1999)

b. SLOSH model

i. 0.75 < Km < 0.8 (Powell, 1987)

ll. Km = 0.8 (Powell & Black, 1990) [use this value for SLOSH]

c. Modified Rankine vortex model

i. Km = 0.8 (b/c model uses same input Vmax as SLOSH model)

d. HURRECON model

i. Km = 0.8 (b/c model uses same input Vmax as SLOSH model)

19. Number of points of interest for time series outputa. Longitude [00-360 0J Latitude [oNJ

20. Radius of tradewind cutoff: mult. ofRMW where to cutoff hurricane winds (Tmax)

21. Umax mode = 1 (Umax is derived from the pressure)

22. Time series wind direction output file name

23. Time series wind magnitude output file name

53

CC Hurricane Ivan (Sept. 2004 )CC - Best track information from NHC/NOAAC - RMW data from AOML (analyzed winds)CCC Modified Rankine vortex model (KIn 0.8)CC Note: C = commented lineCC (1 ) (2) (3) (4 )

0409061800 0409161800 1800 2004C (5)

42C (6) (7 ) (8 ) ( 9) (10) (11) (12 )

0409061800 11. 3 305.6 90 969 11.1 0.410409070000 11.2 303.9 90 964 29.7 0.410409070600 11. 3 302.2 95 965 24.5 0.410409071200 11. 6 300.6 100 963 21. 3 0.410409071800 11.8 298.9 105 956 11.1 0.410409080000 12.0 297.4 115 950 14.9 0.410409080600 12.3 295.9 120 946 20.8 0.410409081200 12.6 294.5 120 955 19.4 0.410409081800 13.0 293.0 120 950 14.4 0.410409090000 13.3 291. 7 130 938 13.0 0.410409090600 13.7 290.5 140 925 13.0 0.410409091200 14.2 289.2 140 919 13.0 0.410409091800 14.7 288.1 130 921 13.0 0.410409100000 15.2 287.2 130 923 11.1 0.410409100600 15.7 286.2 125 930 19.0 0.410409101200 16.2 285.3 125 934 19.4 0.410409101800 16.8 284.2 120 940 18.5 0.410409110000 17.3 283.5 135 926 17.2 0.410409110600 17.4 282.4 130 923 29.2 0.410409111200 17.7 281. 6 125 925 20.9 0.410409111800 18.0 281. 0 145 920 16.7 0.410409120000 18.2 280.4 145 910 16.7 0.410409120600 18.4 279.6 135 915 18.1 0.410409121200 18.8 278.8 135 919 17.2 0.410409121800 19.1 277.9 130 920 33.4 0.410409130000 19.5 277.2 140 916 38.9 0.410409130600 19.9 276.5 140 920 38.9 0.410409131200 20.4 275.9 140 915 32.0 0.410409131800 20.9 275.3 140 912 29.7 0.410409140000 21. 6 274.9 140 914 25.5 0.410409140600 22.4 274.4 140 924 33.9 0.410409141200 23.0 274.0 125 930 35.7 0.410409141800 23.7 273.5 120 931 40.8 0.410409150000 24.7 273.0 120 928 38.9 0.410409150600 25.6 272.6 120 935 41.7 0.410409151200 26.7 272 .1 115 939 31. 6 0.410409151800 27.9 271. 8 115 937 43.6 0.410409160000 28.9 271. 8 110 931 36.2 0.410409160600 30.0 272 .1 105 946 38.0 0.410409160730 30.4 272 .1 96 951 37.1 0.410409161200 31.4 272.3 70 965 37.1 0.41

54

0409161800 32.5 272.6 50 975 37.1 0.41

25.8426.0130.0929.1828.9030.25

(18 )306.0

(24)0.80

(16) (17)32.5 269.0

C 'Buoy 42001'C 'Buoy 42003'C 'Buoy 42007'C 'Buoy 42040'C 'BURL1'C 'OPIA1'

(15)11. 0

(23)0.01165

(14 )0.10

C

C (13)0.10

C (19)1

C (20)250

C (21) (22)3 1013.2

(25)

6270.34274.09271.23271. 79270.57271. 93

C (26) (27)8 1

C (28)winddir ts.dat

C (29)windrnag_ts.dat

55

APPENDIX B: WW3 INPUT FILE (Ocean Region)

switchesthewithcompiled

Fortran 90 compilerShared memory model4 byte wordsAll output files written by first processLongitude-Iattitude grid.Propagation scheme (UQ w/ averaging).Basic source terms (Tolman and Chalikov, 1996).Discrete interaction approximation (DIA)JONSWAP bottom friction formulationLinear wind interpolationLinear current interpolationNo Grib package includedOutput of namelists in grid preprocessorOutput of boundary points in grid preprocessorOutput of grid point status map in grid preprocessorAdd. output in loop over fields in field preprocessoPrint plot of norm 1d energy spect in init condsId. 2d energy spectrumId. spatial distribution of wave heightsEcho input data for homogeneous fields in genSeeding of high frequency energySwitching on retuning and stability correction

isModel

!/F90!/SHRD!/LRB4!/IOS2!/LLG!/PR3!/ST2!/NL1!/BT1!/WND1!/CUR1! /NOGRB!/oo!/01!/02!/03!/04!/05!/06!/07!/SEED!/STAB2

#!/bin/sh######################################################################## Script for WW-III, NAH propagation of Hurricane Ivan (Sept. 2004).########################### Remarks:# winds from modified Rankine vortex parametric wind model#######################################################################

# o. Preparations

ww3 env=' .wwatch3.env' # setup file

# O.a Set-up variables

cdif [ -f $ww3 env ]then

set 'grep WWATCH3 DIR $ww3 env shiftmain dir="$*"set 'grep WWATCH3_TMP $ww3 env' shifttemp_dir="$*"

elseecho "*** Set-up file $ww3 env not found ***"exit

fi

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path_w="/u/robcrab/NAH/IVAN/MODRANK"path_e="$main_dir/exe"path_o="$path_w"

grads='yes'

# O.b Clean-up

rm -f $path_o/ww3 ????outrm -f $path_o/gx_????outrm -f $path_o/log.ww3rm -f $path_o/test.ww3rm -f $path_o/tab??ww3rm -f $path_o/*.ps

cd $path_wrm -f corerm -f *.gs

# work directory# path for executables# path for output files

# Run GrADS for graphics

echo' ,echo 'echo 'echo 'echo' ,

echo' ,======> WAVEWATCH III (v3.04) <====== ,

Hurricane Ivan model 0.25 degr'

# 1. Grid pre-processor -----------------------------------------------

echoechoechoechoecho

, ,,+--------------------+,'I Grid preprocessor I',+--------------------+,, ,

cat> ww3_grid.inp « EOF

$ WAVEWATCH III Grid preprocessor input file$ -------------------------------------------

'NAH 0.25deg, Ivan 2004 ,$

1.1 0.04177 25 24 O.$

F T T T F T$

900. 900. 900. 300.$

&S8T1 GAMMA = -0.019 /&PR03 WDTHCG = 4.00, WDTHTH = 4.00 /&MISC FLAGTR = 4, CICEO = 0.25, CICEN

END OF NAMELISTS$$ bathymetry$

0.75 /

$

2750.25

261. 75

2030.25

-0.251. 001. 00

57

-0.05 7.50 11 -0.1 1 112 0.001 1 1

'( )' 'NAME''( )' 'NAME'

'wna.bot''wna.obs'

$o o F

$$ Define output boundary points$

268.1 29.5 0.00 -0.10 60268.2 23.6 0.10 0.00 103278.4 23.7 0.00 0.10 9278.4 24.7 0.00 0.10 12

$ Close listo. o. o. o. 0

$$ End of input fileEOF

echo" Screen output routed to $path_o/ww3 grid. out"$path_e/ww3 grid> $path_o/ww3_grid.out

rm -f ww3 grid.inp

# 2. Initial Condi tions -----------------------------------------------

echoechoechoechoecho

, ,,+--------------------+,'I Initial Conditions I',+--------------------+,, ,

cat> ww3_strt.inp « EOF$ WAVEWATCH III Initial conditions input file$ -------------------------------------------

4$

1.055825*0.0

$$ End of input fileEOF

echo" Screen output routed to $path_o/ww3 strt.out"$path_e/ww3 strt > $path_o/ww3 strt.out

rm -f ww3 strt.inp

# 3. Input field ------------------------------------------------------

echoechoechoechoecho

, ,,+---------------+,'I Input field I ',+---------------+,, ,

cat> ww3_prep.inp « EOF$ WAVEWATCH III Field prepocessor input file

58

$ -------------------------------------------$

'WND' 'LL' T$

262.307. 45110.31.211$

, NAME' 2 1 '( .... )' '( .... )'11 'wind4ww3.dat'

$$ End of input fileEOF

echo" Screen output routed to $path_o/ww3_prep.out"$path_e/ww3_prep > $path_o/ww3_prep.out

rm -f wW3_prep.inp

# 4. Main program -----------------------------------------------------

echoechoechoechoecho

, ,'+--------------------+,, I Main program I ''+--------------------+,, ,

cat> ww3_shel.inp « EOF$ WAVEWATCH III shell input file$ ------------------------------

F FF FT FFFFF

$20040906 18000020040916 180000

$$ Type 1: Fields of mean wave parameters$

20040906 180000 1800F F T F F T F T T T

20040916 180000F F F T F F F T

$$ Type 2 : Point Output$

20040906 180000 1800 20040916 180000$

270.34 25.84 'Buoy_42001'274.09 26.01 'Buoy_42003'271.23 30.09 'Buoy_42007'271.79 29.18 'Buoy_42040'

$0.0 0.0 'STOPSTRING'

$

59

$ Type 3: Output along track$

20040906 180000 0 20040916 180000$$ Type 4: Restart files$

20040906 180000 0 20040916 180000$$ Type 5: Boundary data$

20040910 180000 1800 20040916 180000$$

'STP'$$ End of input fileEOF

/usr/bin/runrnpi_grn $path_e/ww3 shel

rrn -f ww3 shel.inp

# Clean uprrn -f test???ww3

echo ' , ; echo ' ,echo 'echo 'echo 'echo ' ,

======> END OF WAVEWATCH III <======'HURRICANE IVAN INPUT

# End

60

of ww3_IVAN_input

APPENDIX C: ECOM INPUT FILE (Layer 1)

******INPUT FILE FOR HYDRODYNAMICS MODEL OF ECOM (OR POM)*******INTERNAL !HYDTYPE = 'INTERNAL', or 'EXTERNAL'NEGLECT lWAVEDYN = 'NEGLECT " 'SMBMODEL', 'DONMODEL', 'EXTERNAL'NEGLECT !TRACER = 'NEGLECT', or 'INCLUDE'NEGLECT !SEDTRAN = 'NEGLECT', or 'INCLUDE'NEGLECT !CHEMTRAN = 'NEGLECT', or 'INCLUDE'NEGLECT !PARTICLE = 'NEGLECT', or 'INCLUDE'BOTH !SEDTYPE = 'BOTH', 'SAND', or 'MUD'COLD START !RESTAR = 'COLD START', or 'HOT START'BAROTROPIC !TOR = 'BAROTROPIC', 'PROGNOSTIC', or 'DIAGNOSTIC'NON-LINEAR !ADVECT = 'LINEAR', or 'NON-LINEAR'SMOLAR_R !SCHEME = iCENTRAL', 'UPWIND', 'SMOLAR_R', or 'SMOLAR_2'SCR !DEV = 'SCR' for 15 columns, or 'LPR' for 25 columns in "gcmprt"Y !VSX = 'Y'-vertical slices, or 'N'-no vertical slices in x5 !JROW = j number in x, or ° for VSX='N'Y !VSY = 'y'-vertical slices, or 'N' no vertical slices in y16 !IROW = i number in y, or ° for VSY='N'Y !PTU = 'Y' for U velocity included in "gcmprt", or 'N' for omitN !PTV = 'Y' for V velocity included in "gcmprt", or 'N' for omitN !PTW = 'Y' for W velocity included in "gcmprt", or 'N' for omitN !PTAM = 1 for horizontal mixing included in "gcmprt", or 2 for omitN !PTS = 'Y' for S salinity included in "gcmprt", or 'N' for omitN !PTT = 'Y' for T temperature included in "gcmprt", or 'N' for omitN !PRHO = 'Y' for density included in "gcmprt", or 'N' for omitN !PTQ2 = 'Y' for turbulent kinetic energy included in "gcmprt", or "N' for omitN !PTL = 'Y' for mixing length included in "grmprt", or 'N' for omitN !PTKM = 'Y' for mixing K_M included in "grmprt", or 'N' for omitN !PTKH 'Y' for mixing K H included in "grmprt", or 'N' for omit

2004,09,09,0,1010.,1,12.number186,12.,48.

167,132262.0,278.518.0,31.0

!Year, month, day, hour and number of step of different model!Time step in s, num of time step between inter/external models and ramped in step

!Total computed during(hour), print interval, Time begin print (hour)

!Total number of x, and y direction!Longitude range of computational domain!Latitude range of computational domain

61

forusedonlycondition,

0.1 for recommended value1 for implicit scheme; 0.225 for recommended

o for no relaxationfor barotropic radiation

!boundary relaxation (time 'hours'),!friction tiem scale (hours)

!bottom friction coefficient!bottom roughness coefficient in meters!coefficient in time filter (non-dimensional),

!weighting factor (0-1); 0 for explicit and

0.00250.00140.10.225valueo10'BCTYPE'='PCLAMP10 ! time scale -----number of time step between updates of bottom friction coefficientCLAMPED !BCTYPE = 'CLAMPED', 'PCLAMP', 'OCLAMP', 'RANDB', or 'MIXED'

0.11.0CLOSURE

!value used as a constant or in Smagorinsky's formula!horizontal Prandtl number; 1.0 for recommended value!HORZMIX = 'CONSTANT', or 'CLOSURE'

1. Oe-61.0CLOSURE

!constant or background mixing in mA 2/sec, 1.0e-6 for recommend if VERTMIX!vertical Prandtl number; 1.0 for recommended value!VERTMIX = 'CONSTANT', or 'CLOSURE'

2

120048o

!interval in time (second) for plotting in "gcmplt"!first time (hour) for plotting in "gcmplt"!interval in number for user specified grid points in "gcmtsr"; 0 for no output

!ITRNFORM = 0 for user specified time steps for writing output; or 1 for ECOM generate the

!number of times for water quality model input!interval in hour----- number of time steps for averaging the elevations and current as in

ITRNFORM=O'grm_tran' ;!IZERO number ofhour ---- time steps to skip before start to writingigno

!IWET = 0 for entire grid output, or 1 for wet grd only output

o0.5wqrn1block24foro

10 !number of standard levels «50)-5,-100,-200,-300,-400,-500,-700,-800,-1000,-7000 !depth of standard level in meters w.r.t waterlevelDATA lOPTTSI = 1 for 'DATA', getting data in "init_tands", 2 for 'FIXED', given dataSYNOPTIC lOPTMBC = 'AVERAGED', 'SYNOPTIC', ... , (SEE P110), Meteorological Data Option0.0,0.0 ! (Longitude, Latitude) in degree0.0 !Fraction of short wave rediation absorbed in surface layer0.0 !Wind sheltering coefficient*****************END OF INPUT FILE OF ECOM********************************************************

62

APPENDIX D: SWAN INPUT FILE (Layer 1)

$ ---------------------------------------------------------------------$ 1.a Start-up commands$ ---------------------------------------------------------------------PROJECT 'SWAN_MODRANK' 'MR1' 'Hurricane Ivan, 2004'SET NAUTICALSET 0.226MODE NONSTATIONARY TWODIMENSIONALCOORD SPHERICALTEST 70$$ ---------------------------------------------------------------------$ 1.b Commands for model description$$CGRID REG 270.0 28.5 0.0 5.0 2.5 300 150 CIRCLE 24 0.0313 1.0 25INPGRID BOT REG 270.0 28.5 0.0 300 150 0.0166667 0.0166667READINP BOT -1.0 'GEODAS_9ulf_1min_5x2.5.bot' 2 0 FREEINPGRID WLEV REG 269.9833 28.4833 0.0 301 151 0.0166667 0.0166667 NONSTAT 20040912.000000 15 MIN20040916.183000READINP WLEV 1.0 'elev_ECOM_layer2.dat' 4 0 1 FREEINPGRID WIND REG 270.0 28.5 0.0 50 25 0.1 0.1 NONSTAT 20040913.000000 30 MIN 20040916.180000READINP WIND 1.0 'wind4swan.dat' 4 0 1 0 FREE$$ -----------------------------------------------$ 1.d. Boundary and initial conditions$BOUNDNEST3 WWIII 'ww3.04091300.spc' OPENINITIAL ZERO$GEN3 KOMEN AGROWQUAD iquad=8FRICTION JONSWAPTRIAD$ -------------------------------------------------------------$ Output$ ----------------------------~--------------------------------POINTS 'By_42007' 271.23 30.09

63

'NEST01' 272.0 30.0 0.0 1.0 0.5'NEST02' 271.0 30.0 0.0 1.0 0.5'NEST03' 273.0 30.0 0.0 1.0 0.5

20040916.180000MIN1

'hs_gc_f1.frame' LAY 3 HS OUTPUT 20040913.000000 30 MIN'per_gc_f1.frame' LAY 3 PER OUTPUT 20040913.000000 30 MIN'rtp_gc_f1.frame' LAY 3 RTP OUTPUT 20040913.000000 30 MIN'dir_gc_f2.frame' LAY 3 DIR OUTPUT 20040913.000000 30 MIN

'nest01.ngrd' OUTPUT 20040914.000000 15 MIN'nest02.ngrd' OUTPUT 20040914.000000 15 MIN'nest03.ngrd' OUTPUT 20040914.000000 15 MIN

NOHEADNOHEADNOHEADNOHEAD

'NEST01''NEST02''NEST03'

'FRAME1''FRAME1''FRAME1''FRAME2'

POINTS 'By_42040' 271.79 29.18$NGRIDNGRIDNGRID$NESTOUTNESTOUTNESTOUT$FRAME 'FRAME1' 270.0 28.5 0.0 5.0 2.5 300 150FRAME 'FRAME2' 270.0 28.5 0.0 5.0 2.5 30 15$BLOCKBLOCKBLOCKBLOCK$TABLE 'By_42007' HEADER 'Buoy_42007.tab' TIME DEPTH HS DIR RTP PER WIND OUTPUT 20040913.000000 30 MINTABLE 'By_42040' HEADER 'Buoy_42040.tab' TIME DEPTH HS DIR RTP PER WIND OUTPUT 20040913.000000 30 MIN$COMPUTE 20040913.000000STOP$$ ------------------------------------------------------$ End of input file$ ------------------------------------------------------

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APPENDIX E: ANIMATION DESCRIPTIONS

AnimationTitle

ECOM layer1ECOM layer2ECOM layer3ECOM layer4

SWAN layer1 ...SWAN layer2 ...SWAN layer3 ...

Wind BLENDWind MODRANKWW3 BLEND Hs

WW3 BLEND nest HsWW3 MODRANK Hs

WW3 MODRANK nest Hs

LatitudeRange [N]

15°-31°28S-31°30°-30.5°300-30S28S-31°300-31 °300-31 °0°_50°0°_50°0°_50°

23S-31°0°_50°

23.5°-31°

LongitudeRange [W]

98°-60°90°-85°88°-8r89°-88°90°-85°88°-8r89°-88°98°-30°98°-30°98°-30°

92°-81S98°-30°

92°-81S

Resolution

0.10° (6min)0.017° (1min0.0017° (6sec)0.0017° (6sec)0.017° (1min0.001r (6sec0.0017° (6sec0.25° (15min0.25° (15min0.25° (15min0.10° (6min0.25° (15min)0.10° (6min)

Bathymetry Input Spatial and Temporal Resolution to AnimationsSource Wind Field Press. Field Wave Spec. Astro. Tides W.S. Elev.GEBCO I 0.100 @30min I 0.100@30min I N/A IB.C.@15min I N/A

GEODAS I 0.01r@30min I 0.017°@30min I N/A I N/A I B.C.@15minGEODAS I0.001r@30minl 0.0017°@30min I N/A I N/A I B.C.@15minGEODAS I 0.001r@30minl 0.0017°@30min I N/A I N/A I B.C.@15minGEODAS I 0.100@30min I N/A I 0.05°@1hr I N/A I 0.01r@15minGEODAS I 0.100@30min I N/A I 0.017°@15min I N/A 10.001r@15minGEODAS I 0.100@30min I N/A I 0.017°@15min I N/A 10.001r@15min

NOAA NAH I 0.25°@1hr* I N/A I N/A I N/A I N/ANOAA NAH I 0.100@30min I N/A I N/A I N/A I N/ANOAA NAH I 0.25°@1hr* I N/A I N/A I N/A I N/A

GEBCO I 0.25°@1hr* I N/A I 0.100 @30min I N/A I N/ANOAA NAH I 0.100 @30min I N/A I N/A I N/A I N/A

GEBCO I 0.100@30min I N/A I 0.100 @30min I N/A I N/A* GFDL winds are every 1hr for 4hrs with a 2hr gap in between the 4hr intervals

65