NOAA Technical Report NOS CS 27

COUPLING A FINITE ELEMENT STORM SURGE MODEL OF 

THE NORTH CAROLINA SOUNDS WITH OPERATIONAL 

OCEAN AND WEATHER PREDICTION MODELS 

Silver Spring, Maryland 

October 2010 

noaa National Oceanic and Atmospheric Administration 

U.S. DEPARTMENT OF COMMERCE 

National Ocean Service 

Coast Survey Development Laboratory 
Office of Coast Survey 

National Ocean Service 

National Oceanic and Atmospheric Administration 

U.S. Department of Commerce

The Office of Coast Survey (OCS) is the Nation’s only official chartmaker. As the oldest 

United States scientific organization, dating from 1807, this office has a long history. 

Today it promotes safe navigation by managing the National Oceanic and Atmospheric 

Administration’s (NOAA) nautical chart and oceanographic data collection and 

information programs. 

There are four components of OCS: 

The Coast Survey Development Laboratory develops new and efficient techniques 

to accomplish Coast Survey missions and to produce new and improved products 

and services for the maritime community and other coastal users. 

The Marine Chart Division acquires marine navigational data to construct and 

maintain nautical charts, Coast Pilots, and related marine products for the United 

States. 

The Hydrographic Surveys Division directs programs for ship and shore-based 

hydrographic survey units and conducts general hydrographic survey operations. 

The Navigational Services Division is the focal point for Coast Survey customer 

service activities, concentrating predominately on charting issues, fast-response 

hydrographic surveys, and Coast Pilot updates. 
NOAA Technical Report NOS CS 27 

COUPLING A FINITE ELEMENT STORM SURGE MODEL OF 

THE NORTH CAROLINA SOUNDS WITH OPERATIONAL 

OCEAN AND WEATHER PREDICTION MODELS 

Yuji Funakoshi, Jesse C. Feyen, and Frank Aikman III 

Office of Coast Survey, Coast Survey Development Laboratory, 

Silver Spring, MD 

Carlos Lozano and Hendrik Tolman 

National Centers for Environmental Prediction, 

Environmental Modeling Center, Camp Springs, MD 

October 2010

noaa National Oceanic and Atmospheric Administration 

U. S. DEPARTMENT National Oceanic and National Ocean Service 

OF COMMERCE Atmospheric Administration John H. Dunnigan 

Gary Locke, Secretary Jane Lubchenco, Ph.D. Assistant Administrator 

 Under Secretary 

Office of Coast Survey Coast Survey Development Laboratory 

Captain Steven R. Barnum, NOAA Mary Erickson 
ii 

NOTICE 

Mention of a commercial company or product does not constitute an 

endorsement by NOAA. Use for publicity or advertising purposes of 

information from this publication concerning proprietary products or the 

tests of such products is not authorized.
iii 

TABLE OF CONTENTS

LIST OF FIGURES .........................................................................................................................v

LIST OF TABLES ......................................................................................................................... ix

LIST OF ACRONYMS AND ABBREVIATIONS ........................................................................x

EXECUTIVE SUMMARY ........................................................................................................... xi

1. INTRODUCTION .......................................................................................................................1

2. DATA SOURCES .......................................................................................................................3

2.1. Bathymetry Data .................................................................................................................. 3

2.2. Topographic Data................................................................................................................. 4

2.3. Digital Elevation Model ....................................................................................................... 4

2.4. Meteorological Data............................................................................................................. 5

2.5. Water Surface Elevation Data .............................................................................................. 6

2.6. High Water Marks................................................................................................................ 7

3. COASTAL FLOODING AND HYDRODYNAMIC MODELING ...........................................9

3.1. The ADCIRC Model ............................................................................................................ 9

3.2. Model Grid Development .................................................................................................. 10

3.3. Bathymetric and Topographic data for the Regional CFM ............................................... 11

3.4. Tidal Forcing of the Regional and Basin-Scale CFM ........................................................ 12

4. HURRICANE ISABEL AND METEOROLOGICAL MODELS ............................................15

4.1. Hurricane Isabel ................................................................................................................. 15

4.2. Meteorological Models ...................................................................................................... 17

4.3. Adjustment of Wind Average Time Period and Height ..................................................... 18

4.4. Adjustment of Wind Forcing Interval ................................................................................ 20

4.5. Blending Meteorological Models ...................................................................................... 20

5. LATERAL BOUNDARY CONDITION ..................................................................................23

5.1. The Lateral Boundary Condition from Basin-Scale CFM ................................................. 23

5.2. Real-Time Ocean Forecast System .................................................................................... 23

5.3. The Lateral Boundary Condition from RTOFS ................................................................. 25

6. RESULTS AND DISCUSSION ................................................................................................23

6.1. Validation of Hurricane Isabel Wind Fields ...................................................................... 27

6.2. Validation of Water Surface Elevation .............................................................................. 38

6.3. Validation of High Water Marks ....................................................................................... 41

6.4. Validation of Blended Meteorological Models .................................................................. 44

6.5. Validation of Lateral Boundary Conditions ....................................................................... 53

6.6. Skill Assessment ................................................................................................................ 60

6.7. Water Surface Elevation Skill Assessment ........................................................................ 60

7. SUMMARY AND CONCLUSIONS ........................................................................................67 

ACKNOWLEDGMENTS .............................................................................................................69

REFERENCES ..............................................................................................................................69

APPENDIX A. FEMA Coastal High Water Marks .......................................................................73
iv 

APPENDIX B. HYDRODYNAMIC MODEL PARAMETERS ..................................................77

B.1. Wind Stress ....................................................................................................................... 77

B.2. Atmospheric Pressure Gradient ......................................................................................... 77

B.3. ADCIRC Input File (fort.15) ............................................................................................. 77
v 

LIST OF FIGURES 

Figure 1. North Carolina Albemarle-Pamlico sound system. .......................................................2

Figure 2. Construction of the continuous bathy/topo DEM application. ......................................5

Figure 3. Locations of NDBC stations (red triangles) in the study area. ......................................6

Figure 4. Locations of NOS stations (red squares) in the study area. Only the last four digits 

of the station numbers are shown; the first three digits are 865 for all stations (see 

Table 2). .........................................................................................................................7

Figure 5. Locations of FEMA CHWMs (red circles) in the study area. .......................................8

Figure 6. The regional CFM in the North Carolina region; the MHW shoreline is shown in 

green and the sample point of the lateral boundary condition as a red circle in 

Section 5.3....................................................................................................................10

Figure 7. The regional CFM of Pamlico Sound and surrounding areas; the MHW shoreline 

is shown in green. ........................................................................................................11

Figure 8. The basin-scale CFM grid. ...........................................................................................12

Figure 9. National Hurricane Center best track positions for Hurricane Isabel, 6 – 19 

September 2003 (Beven and Cobb 2004). ...................................................................15

Figure 10. Wind speed (m/s) from meteorological models on September 18 2003 before 

Hurricane Isabel made land fall on the North Carolina’s Outer Banks from 

H*Wind (a), GFDL (b), and GFS (c). Red box in the GFDL panel shows the 

boundary of its nested grid. ..........................................................................................19

Figure 11. RTOFS orthogonal grid with approximate grid spacing contours (a) and 

bathymetry (b). .............................................................................................................24

Figure 12. The lateral boundary condition at the sample location along outer boundary of the 

regional CFM (see Figure 6); 1) Tide (black), 2) the basin-scale CFM (red), 3) 

RTOFS (blue), and 4) detrended RTOFS (green). .......................................................25

Figure 13. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of NDBC 

continuous wind data (black dot) at NDBC location 41001. .......................................29

Figure 14. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of NDBC 

continuous wind data (black dot) at NDBC location 41002. .......................................30
vi 

Figure 15. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of NDBC 

continuous wind data (black dot) at NDBC location 44014. .......................................31

Figure 16. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of NDBC 

continuous wind data (black dot) at NDBC location DUCN7. ....................................32

Figure 17. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of NDBC 

continuous wind data (black dot) at NDBC location CLKN7. ....................................33

Figure 18. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for 

Isabel: H*Wind (a), GFDL (b), and GFS (c) at 1200 UTC September 17, and 

H*Wind (d), GFDL (e), and GFS (f) at 1800 UTC September 17. .............................34

Figure 19. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for 

Isabel: H*Wind (a), GFDL (b), and GFS (c) at 0000 UTC September 18, and 

H*Wind (d), GFDL (e), and GFS (f) at 0600 UTC September 18. .............................35  

Figure 20. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for 

Isabel: H*Wind (a), GFDL (b), and GFS (c) at 1200 UTC September 18, and 

H*Wind (d), GFDL (e), and GFS (f) at 1500 UTC September 18. .............................36

Figure 21. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for 

Isabel: H*Wind (a), GFDL (b), and GFS (c) at 1800 UTC September 18, and 

H*Wind (d), GFDL (e), and GFS (f) at 2100 UTC September 18. .............................37

Figure 22. The comparison of water surface elevations provided by H*Wind (red), GFDL 

(blue), and GFS (green) with observations (black) at Duck FRF Pier (a) and 

Oregon Inlet Marine Pamlico Sound (b). .....................................................................39

Figure 23. The comparison of water surface elevations provided by H*Wind (red), GFDL 

(blue), and GFS (green) with observations (black) at Cape Hatteras Fishing Pier 

(a) and Beaufort Duke Marine Lab (b). .......................................................................40

Figure 24. The distribution of maximum storm surge (m NAVD 88) in the basin-scale CFM 

from each meteorological model (from left to right H*Wind, GFDL, and GFS); 

circles denote FEMA CHWMs; (a) – (c) illustrates the entire North Carolina 

sound system, and (d) – (f) show the enlargement of west side of Palmico Sound 

including the Neuse and Pamlico Rivers. ....................................................................41

Figure 25. The HWMs from H*Wind (a) and GFDL (b) forcingminus observed FEMA 

HWMs for Hurricane Isabel (excluding marks that were not flooded in each 

simulation). ..................................................................................................................43

Figure 26. The HWMs from GFS forcing minus observed FEMA HWMs for Hurricane 

Isabel (excluding marks that were not flooded in the simulation). ..............................44
vii 

Figure 27. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 41001. .....................................................................................45

Figure 28. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 41002. .....................................................................................46

Figure 29. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 44014. .....................................................................................47

Figure 30. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location DUCN7. ..................................................................................48

Figure 31. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location CLKN7. ..................................................................................49

Figure 32. The comparison of water surface elevations provided by the blended 

meteorological forcing (red) against observations (black) at Duck FRF Pier (a) 

and Oregon Inlet Marine Pamlico Sound (b). ..............................................................50

Figure 33. The comparison of water surface elevations provided by the blended 

meteorological forcing (red) against observations (black) at Cape Hatteras Fishing 

Pier (a) and Beaufort Duke Marine Lab (b). ................................................................51

Figure 34. The distribution of maximum storm surge (m NAVD88) in the North Carolina 

sound system from the blended meteorological forcing; circles denote FEMA 

CHWMs. ......................................................................................................................52

Figure 35. The HWMs from the blended meteorological forcing minus observed FEMA 

HWMs for Hurricane Isabel (excluding marks that were not flooded in the 

simulation). ..................................................................................................................52

Figure 36. The comparison of water surface elevations forced by tide (red), basin-scale CFM 

(blue), and RTOFS (green) lateral boundary conditions with observations (black) 

at Duck FRF Pier (a) and Oregon Inlet Marine Pamlico Sound (b). ...........................54

Figure 37. The comparison of water surface elevations forced by tide (red), basin-scale CFM 

(blue), and RTOFS (green) lateral boundary conditions with observations (black) 

at Cape Hatteras Fishing Pier (a) and Beaufort Duke Marine Lab (b). .......................55

Figure 38. The comparison of water surface elevations forced by basin-scale CFM (red), 

RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions with 
viii 

observations (black) at Duck FRF Pier (a) and Oregon Inlet Marine Pamlico 

Sound (b). .....................................................................................................................56

Figure 39. The comparison of water surface elevations forced by basin-scale CFM (red), 

RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions with 

observations (black) at Cape Hatteras Fishing Pier (a) and Beaufort Duke Marine 

Lab (b). .........................................................................................................................57

Figure 40. The comparison of subtidal water surface elevation forced by basin-scale CFM 

(red), RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions 

with observations (black) at Duck FRF Pier (a) and Oregon Inlet Marine Pamlico 

Sound (b). .....................................................................................................................58

Figure 41. The comparison of subtidal water surface elevation forced by basin-scale CFM 

(red), RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions 

with observations (black) at Cape Hatteras Fishing Pier (a) and Beaufort Duke 

Marine Lab (b). ............................................................................................................59
ix 

LIST OF TABLES 

Table 1. NDBC stations in the study area. .......................................................................................5

Table 2. NOS stations in the study area. ..........................................................................................6

Table 3. Sample of the tidal constituents and harmonic constants used for the regional CFM. ....13

Table 4. The best track positions and intensities (Beven and Cobb 2004). ...................................16

Table 5. Wind fields for Hurricane Isabel interpolation onto the basin-scale CFM. .....................27

Table 6. Skill assessment statistics (from Hess et al., 2003). ........................................................60

Table 7. Skill assessment statistics of different meteorological forcings in the basin-scale 

CFM. ...............................................................................................................................62

Table 8. The comparison of peak storm surge heights and times of occurrence in both 

observations and simulations in the basin-scale CFM. ...................................................63

Table 9. Skill assessment statistics of different lateral boundary condition forcings in the 

regional CFM. .................................................................................................................64

Table 10. The comparison of peak storm surge heights and times of occurrence in both 

observations and simulations in the regional CFM. ......................................................65
x 

LIST OF ACRONYMS AND ABBREVIATIONS 

ADCIRC ADvanced CIRCulation model

AOML Atlantic Oceanographic and Meteorological Laboratory 

CFM Coastal Flooding Model 

CHWM Coastal High Water Mark 

C-MAN Coastal-Marine Automated Network 

CO-OPS Center for Operational Oceanographic Products and Services 

CSDL Costal Survey Development Laboratory 

DEM Digital Elevation Model

EC95 East Coast 1995 modeled tidal database 

EC2001 East Coast 2001 modeled tidal database 

EMC Environmental Modeling Center 

FEMA Federal Emergency Management Agency 

GEODAS GEOphysical DAta System 

GFDL Geophysical Fluid Dynamics Laboratory Hurricane Model 

GFS Global Forecast System 

GPS Global Positioning System 

HWM High Water Mark 

HRD Hurricane Research Division 

HWRF Hurricane Weather and Research Forecasting model 

H*Wind Hurricane Wind analysis system 

HYCOM HYbrid Coordinate Ocean Model 

LIDAR LIght Detection And Ranging 

LWD Low Water Datum 

MLW Mean Low Water 

MLLW Mean Lower Low Water 

MSL Mean Sea Level 

NCCOS National Centers for Coastal Ocean Science 

NCEP National Centers for Environmental Prediction 

NDBC National Data Buoy Center 

NED National Elevation Dataset 

NGDC National Geophysical Data Center 

NOS National Ocean Service

NOAA National Oceanic and Atmospheric Administration 

NWS National Weather Service 

NAD 83 North American Datum of 1983 

NAVD 88 North American Vertical Datum of 1988 

POM Princeton Ocean Model 

RTOFS Real-Time Ocean Forecast System 

RHWM Riverine High Water Mark 

SSH Sea Surface Height 

TPC Tropical Prediction Center 

USACE United States Army Corps of Engineers 

USGS United States Geological Survey 

UTC Coordinated Universal Time 

WSE Water Surface Elevation
xi 

EXECUTIVE SUMMARY 

The National Ocean Service (NOS) of the National Oceanic and Atmospheric Administration 

(NOAA) is studying the impacts of storm surge on the coastal region in the sounds and estuaries 

of North Carolina. NOS’ Coast Survey Development Laboratory and the National Centers for 

Environmental Prediction (NCEP) of the NOAA’s National Weather Service are cooperating to 

develop advanced storm surge modeling capability that will be useful to emergency managers. 

The approach is to simulate storm surge for the coastal region using a high resolution Coastal 

Flooding Model (CFM) of the North Carolina sound system. In addition, the approach also 

examines the impact of boundary and meteorological forcing from a suite of NCEP models. 

Boundary conditions are provided to the CFM in the North Carolina region both by a basin-scale 

ADvanced CIRCulation (ADCIRC) model and by the NCEP Real-Time Ocean Forecast System 

(which is based on a HYbrid Coordinate Model basin-scale ocean circulation model). The 

meteorological forcing fields (e.g. the hurricane wind and pressure fields) being tested include 

the Hurricane Wind analysis system (H*Wind), the Geophysical Fluid Dynamics Laboratory 

Hurricane Model, and the Global Forecast System. Our test period focuses on Hurricane Isabel 

(2003). 

The coupled system may provide products with which coastal inundation can be predicted via the 

inclusion of the high resolution ADCIRC coastal model. Furthermore, the outcomes of the 

coupled system will guide the direction of more accurate prediction, and new decision support 

tools. Using the expertise in several parts of NOS and NOAA as well as having partners in other 

federal and state agencies, will ensure that a variety of needs are addressed and that the outcomes 

are based on an integrated approach that makes the best use of data, modeling approaches, 

displaying results, and outreach. 

Key Words: hydrodynamic model, storm surge, coastal flooding model, Hurricane Isabel. 
xii 
1 

1. INTRODUCTION 

The National Ocean Service (NOS) of the National Oceanic and Atmospheric Administration 

(NOAA) is studying the impacts of storm surge on the coastal region in the sounds and estuaries 

of North Carolina (see Figure 1). NOS’ Costal Survey Development Laboratory (CSDL) and the 

National Weather Service’s (NWS) National Centers for Environmental Prediction (NCEP) are 

cooperating to develop advanced hurricane storm surge modeling capability as part of a coupled 

atmosphere-ocean modeling system. 

The approach is to simulate storm surge for the coastal region using a high resolution Coastal 

Flooding Model (CFM) of the North Carolina sound system. The finite element ADvanced 

CIRCulation (ADCIRC) model is the basis for the CFM, applying an unstructured grid to 

compute the water surface elevation and barotropic depth-averaged currents. The CFM is used to 

examine the impact of boundary and meteorological forcing by coupling to a suite of NCEP 

models. Hurricane storm surge height and coastal inundation distribution are strongly influenced 

by the geometry of the shelf and coast (especially for features which act as hydrodynamic 

controls) and by meteorological conditions. Hydrodynamic numerical models must represent the 

basin geometry in order to predict accurately the storm surge and the skill of these models is 

governed by the quality of their forcing at the surface and at open ocean boundaries. Therefore, 

NCEP is partnering with CSDL to investigate predictions of storm surge height by combining a 

coupled atmosphere-ocean modeling system with the high resolution CFM. 

As a preliminary step in simulating storm surge, CSDL has developed a predictive hydrodynamic 

CFM of North Carolina’s coastal areas that integrates bathymetry and topography using the 

VDatum vertical datum transformation tool (Spargo et al., 2005, 2006) in a combined modeling 

process. Using a digital elevation model (DEM) as well as the United States Geological Survey 

(USGS) National Elevation Dataset (NED), CSDL has integrated land areas with a 

hydrodynamic tidal model developed for VDatum to produce the CFM. This model is able to 

simulate not only the tidal response but also wind-driven (including hurricane) circulation within 

the system, including the resulting inundation. The purpose of the CFM is to study how storm 

surge will affect the coastal region, and the CFM is advantageous because it treats the landward 

and seaward areas as a single, continuous environment. 

Boundary conditions are provided to the CFM in the North Carolina region by two large-scale 

basin models: (1) a basin-scale version of the ADCIRC model, and (2) the NCEP Real-Time 

Ocean Forecast System (RTOFS), which is based on a Hybrid Coordinate Model (HYCOM) 

basin-scale ocean circulation model. The meteorological forcing fields (e.g. the hurricane wind 

and pressure fields) being tested include the Hurricane Wind analysis system (H*Wind), the 

Geophysical Fluid Dynamics Laboratory (GFDL) Hurricane Model, and the Global Forecast 

System (GFS) model. Our test period focuses on Hurricane Isabel (2003). Hurricane Isabel was 

the most powerful hurricane of the 2003 season and the first hurricane to make landfall on the 

east coast of the United States since 1999. After coming ashore on the Outer Banks of North 

Carolina on 18 September as a Category 2 hurricane, Isabel took a northward track into Virginia, 

causing high winds, storm surge flooding, and extensive property damage around Chesapeake 

Bay. 
2 

Figure 1. North Carolina Albemarle-Pamlico sound system. 

The following sections describe the technical approach in executing the major components of the 

study: 

o Creation of the DEM and development of the CFM 

o Meteorological models and wind forcing adjustment 

o NCEP RTOFS and lateral boundary conditions 

o Results and discussion 

Oregon Inlet 
3 

2. DATA SOURCES 

In order to conduct this coastal inundation study several different types of data sources are 

required to build and validate the model. The CFM for the Pamlico Sound region of North 

Carolina was developed as part of a project to study the ecological effects of sea level rise 

(Feyen et al., 2006). This project was funded by NOS’ National Center for Coastal Ocean 

Science (NCCOS), and resulted in construction of a bathymetric/topographic DEM, a tidal 

model, and a regional VDatum application. These products provide the basis for the CFM, and 

require several types of source data, which are described here. Bathymetric data comes from 

NOS hydrographic soundings and United States Army Corps of Engineers (USACE) surveys of 

dredged areas, which are primarily tidal inlets. Two different data sources, Federal Emergency 

Management Agency (FEMA) LIght Detection And Ranging (LIDAR) data and the USGS NED, 

are used for topographic data. The DEM built by NOS’ National Geodetic Survey/Remote 

Sensing Division (White and Sellars, 2004) combines the bathymetric data with the topographic 

data using VDatum to create a continuous bathy/topo dataset adjusted to a common vertical 

datum (i.e., the North American Vertical Datum of 1988 (NAVD 88)). The process of model 

validation, including Hurricane Isabel forcing, depends on the comparison with observations: 

meteorological data observed by the National Data Buoy Center (NDBC), observed water 

surface elevation from the Center for Operational Oceanographic Products and Services (COOPS) gauge stations, and High Water Marks (HWMs) measured by FEMA. 

2.1. Bathymetry Data 

Water depths from historic NOS bathymetric surveys of the North Carolina coast are selected 

from the GEOphysical DAta System (GEODAS) created by NOAA’s National Geophysical Data 

Center (NGDC); information on this dataset is available at 

http://www.ngdc.noaa.gov/mgg/geodas/geodas.html/. About 90% of the study area is covered by 

NOS sounding data. Bathymetric data sets were processed during development of the tidal model 

in support of VDatum (Hess et al., 2005) This processing involved transformation of all surveys 

to common horizontal and vertical datums: the North American Datum of 1983 (NAD 83) for 

horizontal referencing, and NAVD 88 for vertical referencing. The surveys were also sorted 

chronologically so that the most recent data was used across the domain. According to NGDC, 

the horizontal accuracy of NOS soundings is generally 30 m, although accuracy has improved 

with recent surveys that employ a differential Global Positioning System (GPS). Vertical 

accuracy of the NOS soundings conforms to the international hydrographic standard: 0.30 m in 0 

to 20 m of water, 1.0 m in 20 to 100 m of water, and 1% of the water depth in waters of 100 m 

depth or deeper. 

The USACE has the responsibility to maintain navigational channels to design depths through its 

dredging program. Therefore these regions are subject to concentrated, repeated, highly refined 

hydrographic surveys to ensure bathymetric depths are sufficient. A suite of these surveys for the 

CFM region was obtained and applied to supersede NOS surveys because of their generally 

recent collection and high resolution. These surveys were also transformed to the common datum 

references (i.e., NAD 83 and NAVD 88). 
4 

2.2. Topographic Data 

Topographic data for floodplains were obtained from FEMA sponsored LIDAR collection to 

support the flood insurance mapping program, and USGS’s NED. These two datasets were 

combined in creation of the high resolution DEM. 

 

The raw FEMA LIDAR data has a horizontal resolution of 4 to 6 m and a vertical accuracy of 

0.20 m in coastal counties and 0.25 m in inland counties. The available elevations consist of the 

original LIDAR returns and a post-processed bare earth dataset. The bare earth data have been 

thinned from the original returns to consist of only the LIDAR returns that represent the ground 

surface. This includes removing LIDAR returns capturing vegetation, buildings, power lines, 

birds, and so forth. (more information is available at http://www.fema.gov/plan/prevent/fhm/

lidar_4b.shtm). 

The USGS NED is a raster product assembled to provide a national elevation DEM that tries to 

use the latest topographic observation. The NED is designed to provide national elevation data in 

a seamless form with a consistent datum, elevation unit, and projection. The NED has a 

resolution of approximately 30 m for the conterminous United States. NAD 83 and NAVD 88 

are consistently used as the horizontal and vertical datum, respectively (more information is 

available at http://seamless.usgs.gov/products/3arc.php/). 

2.3. Digital Elevation Model 

A high resolution DEM was constructed for the western Pamlico Sound portion of North 

Carolina. The DEM was built for this region as input to a study of sea level rise impact (Feyen et 

al., 2006). The DEM primarily utilizes high resolution FEMA LIDAR elevation data for 

topographic information and NOAA soundings for bathymetric information. The DEM was 

constructed with 6 m resolution in the horizontal direction. Any small gaps in topographic data 

were filled by other sources such as the USGS NED. Vertical accuracy depends on the source 

data (e.g., 0.20 to 0.25 m where FEMA LIDAR data is utilized, 0.30 m for hydrographic 

soundings in less than 20 m of water). 

The bathymetric data comes from NOS hydrographic soundings are referenced to Mean Low 

Water (MLW), Mean Lower Low Water (MLLW), or Low Water Datum (LWD). Using the 

vertical datum transformations from the VDatum software, these bathymetric data are first 

adjusted to Mean Sea Level (MSL) and then to NAVD 88. These converted bathymetric data are 

combined with topographic data relative to NAVD 88 to create a continuous bathy/topo dataset. 

The methodology for construction of the continuous bathy/topo DEM model application is 

shown in Figure 2. 
5 

Figure 2. Construction of the continuous bathy/topo DEM application. 

2.4. Meteorological Data 

Meteorological data are obtained from NDBC buoys and Coastal-Marine Automated Network 

(C-MAN) stations in continuous winds format; more information is available at 

http://www.ndbc.noaa.gov/. NDBC locations and descriptions in the study area are shown in 

Figure 3 and Table 1. Ten-minute averaged wind speed (m/s) and wind direction measurements 

in degrees clockwise from true north, quality controlled and processed by NDBC, are used to 

validate Hurricane Isabel wind fields. 

Table 1. NDBC stations in the study area. 

No. Station ID Latitude Longitude Station Name (Location) 

1 41001 34.68 -72.66 150 NM East of Cape Hatteras 

2 41002 34.62 -76.52 S Hatteras - 250 NM East of Charleston, SC 

3 44014 36.61 -74.84 Virginia Beach 64 NM East of Virginia Beach, VA 

4 DUCN7 36.18 -75.75 Duck, NC 

5 CLKN7 32.31 -75.35 Cape Lookout, NC 
6 

Figure 3. Locations of NDBC stations (red triangles) in the study area. 

2.5. Water Surface Elevation Data 

Time series of water surface elevation are available from NOS for four stations around the 

region, as shown in Figure 4; more information is available at http://tidesonline.nos.noaa.gov/. 

These are used for comparison with the CFM output. Station locations are given in Table 2. Sixminute interval water surface elevation data from the quality-controlled CO-OPS database are 

adjusted to NAVD 88 and used for comparison with modeled water surface elevation. 

Table 2. NOS stations in the study area. 

No. Station ID Latitude Longitude Station Name (Location) 

1 8651370 36.183 -75.747 Duck FRF Pier 

2 8652587 35.795 -75.548 Oregon Inlet Marina NC 

3 8654400 35.223 -75.635 Cape Hatteras Fishing Pie 

4 8656483 34.720 -76.670 Beaufort Duke Marine Lab 

33.0 

35.0 

-77.0 -75.0 -73.0 

34.0 

36.0 

-76.0 -74.0 

44014 

41001 

41002 

DUCN7 

CLKN7 

32.0 
7 

Figure 4. Locations of NOS stations (red squares) in the study area. Only the last four 

digits of the station numbers are shown; the first three digits are 865 for all 

stations (see Table 2). 

2.6. High Water Marks 

HWMs are available from FEMA’s Hurricane Isabel rapid response coastal high water mark 

collection (FEMA 2003). FEMA categorizes a HWM as either Coastal (CHWM) or Riverine 

(RHWM) based on an evaluation of the type of flooding (coastal surge or riverine) at each 

location. The CHWMs, used for model validation, are obtained by field surveys and through 

interviews with local residents and witnesses. The CHWMs are identified based on general 

guidelines for HWM spacing (approximately 1 CHWM per 1.6 km of affected shoreline) using 

GPS. CHWM locations are surveyed horizontally in NAD 83 and vertically in NAVD 88. 

CHWM locations have been surveyed to within accuracies of 0.07 m vertically and 3 m 

horizontally with a 95% confidence level. 
8 

CHWMs are also classified as either Storm Surge or Stillwater CHWMs. The classification is 

based on a combination of the physical flood evidence and interviews with witnesses. Coastal 

Storm Surge HWMs are associated with flooded areas where there is evidence of damage from 

the wave action associated with a storm surge. Typically, Coastal Stillwater HWMs are 

associated with a slow rising flood that causes more water damage than structural damage. The 

approximate locations of the FEMA CHWMs used in this study are shown in Figure 5 and Table 

A.1 in Appendix A (FEMA 2003). 

Figure 5. Locations of FEMA CHWMs (red circles) in the study area. 

35.0 

36.0 

-77.0 -76.0 
9 

3. COASTAL FLOODING AND HYDRODYNAMIC MODELING 

As part of the CFM development, a high-resolution finite element hydrodynamic model was 

constructed for the study area. Bathymetry and topography data referenced to NAVD 88 were 

used to populate the grid with depths and land elevations. The model was originally developed as 

a tidal model which extended up to the MHW shoreline in order to support the development of 

the VDatum tool (Hess et al., 2005). This tidal model was run to simulate astronomical tides, and 

revised and calibrated until it produced sufficiently accurate tidal datum information for 

VDatum. The CFM was then built from the tidal model by adding additional grid resolution over 

low-lying coastal land. The storm surge simulations were run on this CFM. 

3.1. The ADCIRC Model 

The CFM is an application of ADCIRC, the ADvanced CIRCulation model for oceanic, coastal 

and estuarine waters. The CFM runs in two-dimensional (i.e., barotropic) mode on an 

unstructured grid composed of triangular elements; this type of grid is ideally suitable for 

representing complex coastlines to any desired resolution, and can be easily modified to add 

spatial resolution in any geographic area with little effort. The grid must then be populated by 

bathymetry and topography to represent the region, and boundary forcing must be added to 

simulate astronomical tides, storm surge, and other causes of water level variability. 

The ADCIRC model was developed by Rick Luettich at the University of North Carolina at 

Chapel Hill, Institute of Marine Sciences, and Joannes Westerink at the University of Notre 

Dame, Department of Civil Engineering and Geologic Sciences (Luettich et al., 1992; Luettich 

and Westerink 2004). This model is a system of computational algorithms that solve timedependent, free surface circulation and transport problems in two and three dimensions. The 

ADCIRC Two-Dimensional Depth Integrated (2DDI) version, used for the North Carolina area 

studies, is the barotropic version of the model. ADCIRC utilizes the finite element method in 

space, taking advantage of highly flexible, irregularly spaced grids. Numerous studies have 

shown this model to be robust throughout the Western North Atlantic and Gulf of Mexico 

regions (Luettich et al., 1994; Mukai et al., 2001; Westerink et al., 2008) 

ADCIRC has a wetting and drying algorithm for modeling inundation that works as follows. 

When the water surface elevation at any node is less than a user-specified depth (here 0.10 m), 

that node becomes temporarily inactive (i.e., dry). When surrounding water surface elevation is 

sufficiently high to push water into the nodal area to make the water surface elevation rise above 

the 0.10 m value, the node is activated (i.e., wet). During the model runs, some nodes become 

‘ponded’ when their depths are at or near 0.10 m, because the surrounding nodes are inactive and 

there is not a sufficient gradient for the water to flow out of them. For further information on the 

wetting and drying algorithm see Westerink et al. (2008). 

The modeling of wind stress formulation and other parameters are discussed in detail in 

Appendix B. 
10 

3.2. Model Grid Development 

The modeling strategy is to create a regional grid of central coastal North Carolina by using a 

portion of a larger scale grid, in this case, a Western North Atlantic Ocean grid (Luettich et al., 

1994). Then, grid elements covering Pamlico and Albemarle Sounds and Beaufort Inlet 

developed by Luettich et al. (1999) were incorporated. Finally, additional elements were added 

by NOS to parts of the region within the DEM area where more resolution was needed, including 

the Intracoastal Waterway. The grid contains 36,409 nodes, and the smallest elements in that 

area had node spacing on the order of 13 m (Hess et al., 2005). 

Based on this regional model grid, the CFM adds land areas and continuous contours of 

bathymetric and topographic data relative to a single referenced datum (i.e., NAVD 88). A 15 m 

topographic contour (relative to NAVD 88) was generated from the 30 m horizontal resolution 

USGS NED and used as the landward boundary. Computational mesh has been added between 

the prior MHW shoreline and this land boundary, including all island areas, as shown in Figure 

6. The 15 m contour was chosen since this will allow the CFM to model severe storm surge 

conditions. Resolution ranges from 5 km offshore down to 20 m within narrow channels such as 

the Intracoastal Waterway. Resolution of inlets is generally from 100 to 200 m, with more than 

10 elements across these inlets. Mesh size within sounds ranges between several hundred meters 

to nearly two kilometers, and rivers are discretized ranging from many nodes across to a pair of 

elements only 50 m in size. The regional CFM grid is shown in Figures 6 and 7. 

Figure 6. The regional CFM in the North Carolina region; the MHW shoreline is shown in 

green and the sample point of the lateral boundary condition as a red circle in 

Section 5.3. 

34.0

35.0

36.0

-- -
11 

Figure 7. The regional CFM of Pamlico Sound and surrounding areas; the MHW shoreline 

is shown in green. 

A basin-scale grid (Figure 8) was also created by incorporating the regional CFM into a Western 

North Atlantic grid developed for a 1995 East Coast (EC95) tidal database (Luettich et al., 1994). 

The resolution of the EC95 grid is rather coarse due to the limited computing resources available 

at the time, resulting in a domain of 31,435 nodes and resolution of approximately 75 km in the 

open ocean. However, it has been shown to effectively model tides and predict storm surge when 

integrated with a high resolution regional model grid (Westerink et al., 2008). While the EC95 

grid has been used previously for tidal simulation, a solely tidally forced simulation is first run to 

successfully validate this combined CFM and EC95 domain application. 

3.3. Bathymetric and Topographic data for the Regional CFM 

The regional CFM grid was populated by depths and elevations in a consistent vertical datum 

(NAVD 88). In order to produce accurate predictions of storm surge, it is necessary to have 

accurate and continuous elevation (bathymetric and topographic) information. The VDatum 

software was used to transform bathymetric sounding data from tidal datums (e.g., relative to 

MLW or MLLW) to the same orthometric datum (NAVD 88) used for topographic data. The 

regional CFM elevations were derived directly from the DEM where it provided coverage. The 

DEM does not cover all of the regional CFM mesh, however; it is limited to the area that ranges 

from southwest of the White Oak River to northeast of Hatteras Inlet. In areas the DEM does not 

cover, NOS sounding data was used for bathymetric depths and the USGS NED for topographic 

heights. All bathymetric and topographic data were applied to the computational mesh by 

interpolating at the local mesh scale. This was done by averaging all data points within the 

cluster of elements surrounding each node. 
12 

Figure 8. The basin-scale CFM grid. 

3.4. Tidal Forcing of the Regional and Basin-Scale CFM 

The outer coastal boundary of each ADCIRC grid is forced with periodic water level variations 

to simulate astronomical tides (Schureman 1958). The water surface elevation, relative to the 

model’s zero elevation, at each node along the outer boundary is 

          n n n n n H h0 f A cos  t V0 u 

where H is the total water surface elevation (m), 0 h represents a constant offset, and the 

remaining terms represent the astronomical tide. An is the constituent amplitude (m), n is the 

constituent speed (degrees/hr), t is the time relative to Coordinated Universal Time (UTC), 

 n V  u 0 is the equilibrium angle (degrees), and  n is the phase relative to UTC (degrees). 

Therefore a unique set of harmonic constants is required at each grid node along the coastal 

boundary; a sample is shown in Table 3. 

10.0 

-90.0 -80.0 -70.0 -60.0 

20.0 

30.0 

40.0 
13 

Table 3. Sample of the tidal constituents and harmonic constants used for the regional 

CFM. 

Constituent Amplitude (m) Phase (deg) 

An  n

K1 0.091433 177.978 

O1 0.068979 191.636 

M2 0.408000 351.313 

S2 0.074515 10.154 

N2 0.096141 336.247 

The open boundary of the regional CFM grid (Figure 6) is located roughly along an arc 

approximately 100 km of the coast. An updated version of the Western North Atlantic tidal 

database was created for the East Coast in 2001 (EC2001; Mukai et al., 2001). This tidal 

database is used to provide the set of harmonic constants for forcing the tidal signal in the 

regional CFM. 

The open boundary of the basin-scale CFM grid (Figure 8) is located along the 60o

 W longitude. 

A unique set of harmonic constants, M2, N2, S2, K1, and O1 tidal constituents from Schwiderski’s 

global tidal model (Schwiderski 1980) were used at each grid node along the open ocean 

boundary. This forcing dataset matches that used for the EC95 model grid, from which the basinscale CFM is built. 

Tidal forcing is normally imposed in ADCIRC via time and space varying conditions along the 

open boundaries of the model domain. However, ADCIRC also includes terms representing the 

Newtonian tidal potential and the corrections due to the effect of the Earth tides. The tidal 

potential term forces tides within the model domain. This term appears in the momentum 

equations, as spatial gradients that are subtracted from the spatial gradient of the free surface 

elevation. In continental shelf areas, the free surface elevation gradient is typically larger than the 

tidal potential term and therefore they are safely neglected. However, the free surface gradient 

can be very small in the deep ocean, and therefore, when significant areas of the deep ocean are 

included in the model domain, this tidal potential term may be significant. The Newtonian tidal 

potential and Earth tides are expressed as (Reid 1990): 

      

   















 

 

n j jn jn

jn jn jn j T j t

t t

t C f t L , 0

0

0

2 , , cos

 



    

where 0t is reference time,  jn is reduction in the field of gravity due to Earth tide, Cjn is 

Newtonian equilibrium tidal potential amplitude, jn f is time-dependent nodal factor, T jn is tidal 

period,  jn is time-dependent astronomical argument, j (j  0,1,2 ) is tidal species, in which 

j  0 (declinational), j  1 (diurnal), and j  2 (semidiurnal): 3sin   1 2 L0    , sin2 L1 

and    2

2 L  cos . In addition, Reid (1990) consolidated the value of the effective earth elasticity 

factor,  jn , which is typically applied as 0.69 for all tidal constituents (Schwiderski 1980) even 
14 

though the value has been shown to be slightly constituent dependent. Tidal potential forcing 

was included for al ADCIRC simulations produced for this report. 
15 

4. HURRICANE ISABEL AND METEOROLOGICAL MODELS 

Hurricane Isabel was chosen to evaluate the performance of the CFM because it was a recent 

well-documented hurricane that made a direct hit to the central North Carolina coast. The history 

of Hurricane Isabel is briefly described below. Meteorological conditions for Hurricane Isabel 

are provided by the Hurricane Wind analysis system (H*Wind) from the Hurricane Research 

Division (HRD) of the Atlantic Oceanographic and Meteorological Laboratory (AOML), the 

Geophysical Fluid Dynamics Laboratory (GFDL) Hurricane Model, and the Global Forecast 

System (GFS) from NCEP. Adjustment of wind average time period, height, and time interval, 

including blending meteorological models, is discussed to define appropriate meteorological 

forcing for storm surge modeling. 

4.1. Hurricane Isabel 

Hurricane Isabel was the most powerful hurricane of the 2003 season and the first hurricane to 

make landfall on the east coast of the United States since 1999. After coming ashore on the Outer 

Banks of North Carolina on 18 September as a Category 2 hurricane (Saffir-Simpson Hurricane 

Scale), Isabel took a northward track through Virginia, causing high winds, storm surge flooding, 

and extensive property damage. Isabel produced a devastating storm surge to the North Carolina 

Outer Banks and Virginia coastline and a record-breaking storm surge in the Chesapeake Bay 

because of its strong wind toward inland. Figure 9 shows the best track chart of Isabel 

(http://www.nhc.noaa.gov/2003isabel.shtml/). 

Figure 9. National Hurricane Center best track positions for Hurricane Isabel, 6 – 19 

September 2003 (Beven and Cobb 2004). 
16 

Isabel reached a major hurricane in a few days after its formation in the western tropical Atlantic 

Ocean, about 7 September 2003. The best track positions and intensities are listed in Table 4. 

According to advisories published subsequently by the Tropical Prediction Center (TPC), at 

1500 UTC on September 7, Isabel had become a Category 1 hurricane. Over the next few days 

Isabel gradually gained strength, reaching Category 5 status at 2100 UTC on September 11 with 

maximum sustained winds of 72 m/s. Isabel retained this strength through early September 15. 

Thereafter it gradually weakened, dropping to Category 2 strength with sustained winds of 46 

m/s on 1500 UTC September 16. When landfall occurred on early September 19, Isabel retained 

this strength (NOAA, USACE, and FEMA 2005). 

 Table 4. The best track positions and intensities (Beven and Cobb 2004). 

Date/Time Position Pressure Wind Speed 

(UTC) Lat. Lon. (hPa) (m/s) Stage 

 (°N) (°W) 

 06 / 0000 13.8 31.4 1009 15 tropical depression 

 06 / 1200 13.6 33.9 1003 21 " 

 07 / 0000 13.5 35.8 994 28 " 

 07 / 1200 14.4 37.3 987 33 hurricane 

 08 / 0000 15.8 39.7 976 41 " 

 08 / 1200 17.1 42.0 952 57 " 

 09 / 0000 18.2 44.1 948 59 " 

 09 / 1200 19.4 46.3 948 59 " 

 10 / 0000 20.5 48.3 952 57 " 

 10 / 1200 21.1 50.4 948 59 " 

 11 / 0000 21.2 52.3 935 64 " 

 11 / 1200 21.4 54.0 925 69 " 

 12 / 0000 21.6 55.7 920 72 " 

 12 / 1200 21.6 57.4 920 72 " 

 13 / 0000 21.8 59.1 925 69 " 

 13 / 1200 22.1 61.0 935 69 " 

 14 / 0000 22.9 63.3 935 69 " 

 14 / 1200 23.5 65.8 935 69 " 

 15 / 0000 24.3 67.9 937 67 " 

 15 / 1200 24.8 69.4 946 62 " 

 16 / 0000 25.7 70.2 952 54 " 

 16 / 1200 26.8 70.9 959 49 " 

 17 / 0000 28.1 71.5 957 49 " 

 17 / 1200 29.7 72.5 957 46 " 

 18 / 0000 31.5 73.5 953 46 " 

 18 / 1200 33.7 75.2 956 46 " 

 19 / 0000 36.7 77.7 969 33 " 

 19 / 1200 40.9 80.3 997 18 extratropical 

 20 / 0000 48.0 81.0 1000 13 " 

 11 / 1800 21.5 54.8 915 75 minimum pressure

 18 / 1700 34.9 76.2 957 46 landfall at Drum Inlet, North Carolina 
17 

4.2. Meteorological Models 

Three different types of atmospheric models are employed in order to provide meteorological 

forcing to the CFM. One is an analytical model, H*Wind, which integrates all available surface 

weather observations to analyze tropical cyclones. The others are dynamical forecast models 

(called the GFDL and GFS models) which solve a set of basic laws of physics to predict the 

atmosphere. Although the resolution, coverage, and accuracy are different between the models, 

each model is used as meteorological forcing, and their performances are evaluated. 

 

The H*Wind analysis system developed by AOML (Powell et al., 1996a) is an integrated 

tropical cyclone observing system that enables real-time interaction with, and analysis of, 

observations gathered in tropical cyclones. All available surface weather observations (e.g., 

ships, buoys, coastal platforms, surface aviation reports, reconnaissance aircraft data adjusted to 

the surface, etc.) are used to produce high-quality wind snapshots. All data are quality controlled 

and processed to conform to a common framework for height (10 m), exposure (marine or open 

terrain over land), and averaging period (maximum sustained 1 minute wind speed) using 

accepted methods from micrometeorology and wind engineering. H*Wind is available for 

tropical storms and hurricanes at 3 to 6 hour intervals. 

The GFDL hurricane model is an operational hurricane forecast model applying a nested grid 

system with an outermost domain and 2 nested grids with resolutions of 55, 27 and 9 km 

respectively; it uses 42 vertical levels. A spin-up vortex initialization is used with an 

axisymmetric version of the forecast model forced by intensity and structure parameters provided 

operationally by the NHC. The GFDL hurricane model is coupled to a high-resolution version of 

the Princeton Ocean Model (POM) for the Atlantic Basin. The ocean initialization system uses 

observed altimeter observations to provide a more realistic Loop Current and Gulf Stream 

condition. Hurricane forecasts are produced on demand every 6 hours at 00, 06, 12, and 18 UTC 

for up to 4 tropical storms at a time and provide hourly output. 

The GFS operated by NCEP is a global spectral data assimilation and forecast model system. 

GFS forecasts are produced every six hours at 00, 06, 12 and 18 UTC. The GFS are based on a 

70 km grid and are available at six hour increments out to 384 hours. NCEP implemented major 

changes to GFS on May 31, 2005, so the Isabel results were completed on the earlier version of 

the model. The GFS contains a full suite of parameterized physics as well as accompanying seaice and land-surface models. 

The specification of grid resolution and wind field snapshot time interval from these 

meteorological models is important for model accuracy due to its significant contribution to the 

storm surge generation. Figure 10 illustrates the comparison of wind fields from the 

meteorological models H*Wind (panel a), GFDL (panel b, red box shows the boundary of its 

nested grid), and GFS (panel c), on September 18, 2003 just before Hurricane Isabel made 

landfall on the North Carolina Outer Banks. H*Wind has the highest resolution, as it’s 1000 km 

square domain has a resolution of 6 km, although it has a limited domain size. GFDL has a 9 km 

inner nested grid that is constantly following the hurricane eye, and an outermost domain to 

capture far-field dynamics. GFS, with resolution of approximately 50 km for Hurricane Isabel, 

doesn’t specifically resolve the hurricane dynamics; however, GFS is the only system with both 

observation-based reanalysis and model-generated forecast products. 
18 

H*Wind records for Hurricane Isabel are composited for the storm over a 3 to 6 hour interval (25 

analyses of Isabel’s surface wind, starting at 1730 UTC on September 11 and ending 1630 UTC 

on September 18). GFDL produces hourly predictions of wind and atmospheric pressure reduced 

to MSL (from 0000 UTC September 7 to 1200 UTC September 18) which based on simulations 

start every 6 hours. GFS provides wind field and atmospheric pressure reduced to MSL at every 

6-hour intervals from 0000 UTC September 7 to 0000 UTC September 21. 

 

Two issues arise when applying H*Wind to hurricane storm surge modeling. First, H*Wind 

doesn’t provide atmospheric pressure predictions. Since a water surface elevation response is 

associated with the atmospheric pressure deficit, it is one of the important components in storm 

surge generation. This is termed the inverted barometer effect; the rise is approximately 0.01 m 

for each hPa drop in pressure. Second, the H*Wind grid is limited in size to produce wind 

snapshots of the main storm. H*Wind has enough grid size to cover the entire hurricane, locating 

the center of the grid on the hurricane eye; however, it doesn’t provide the far-field wind that 

generates set-up outside the H*Wind domain. In order to resolve these issues it is necessary to 

blend H*Wind with other meteorological models. 

4.3. Adjustment of Wind Average Time Period and Height 

When dealing with hurricane storm surge modeling, the issue of the appropriate wind averaging 

time period has not been clearly defined. The length of the wind averaging time period will 

affect the reported wind speed and thus the surface stress applied to the water column of the 

storm surge model. This is because the shorter the averaging period, the higher the reported wind 

speed. Therefore, any time averaging should consider the time scale of the conditions being 

simulated in order to account for this factor. 

It is important to recognize that wind averaging time period varies depending upon the 

application. Calculating wind impact on structures is generally based on a short wind duration 

(gust or peak sustained 1 minute average) due to their failure mechanism. However, wave 

generation is controlled by the fetch length, which would define the wind averaging time period. 

For inland lakes and rivers this can be as short as 1 to 5 minutes; over the open ocean this 

response time is reported to be 10 to 30 minutes. 

Since the drag coefficient is controlled by sea surface roughness (i.e., wave conditions), it could 

be theorized that storm surge models should use the same wind averaging time period as used by 

the wave modeling community (i.e., 10 to 30 minutes). Thus, it is suggested that a time average 

between 10 and 30 minutes is acceptable for storm surge modeling. The winds produced by 

many parametric models most likely correspond to values within this time range (e.g., a 10 

minute average is common). However, it is important to adjust observations and meteorological 

forcing to a common sampling period for comparison. In practice, use of a 10 minute averaging 

period has been found to be accurate in storm surge modeling (W. Shaffer pers. comm.) and can 

be used for direct comparison with continuous winds data collected at many NOAA 

observational platforms (i.e., NDBC buoy data). Furthermore, Powell and Reinhold (2007) report 

that hurricane winds over a 10 minute period are relatively stable (for computing a mean) while 

considerable changes occur over a longer time period such as an hour. 
19 

Figure 10. Wind speed (m/s) from meteorological models on September 18 2003 before 

Hurricane Isabel made land fall on the North Carolina’s Outer Banks from 

H*Wind (a), GFDL (b), and GFS (c). Red box in the GFDL panel shows the 

boundary of its nested grid. 

40.0 

-90.0

30.0 

-80.0 -70.0 -60.0 

40.0 

-90.0

30.0 

-80.0 -70.0 -60.0 

40.0 

-90.0

30.0 

-80.0 -70.0 -60.0 

(a) H*Wind

(b) GFDL 

(c) GFS 

Boundary of 

nested grid 
20 

In developing meteorological forcing for storm surge models and comparing these winds to 

observations, it is necessary to transform the winds to a common framework. Wind time 

averaging lengths are not standardized, as various observation platforms can report a 1 minute, 2 

minute, or 10 minute averaged wind. For example, H*Wind provides 1-minute sustained winds 

(applying an adjustment value of 1.11 for determining 1 minute peak winds from 10 minute 

averaged winds) to conform with advisories and warnings issued to the public by NHC. Powell 

et al. (1996b) report that adjustments to convert sampling height and averaging period to a 

common framework are accurate to within 10%; however, comparison of observations taken 

with different techniques can lead to errors of 15% to 40%. Therefore all reported observations 

and model output were adjusted to a 10 minute average. Data from H*Wind were adjusted by 

1.11 to convert from a 1 minute to 10 minute average. 

Wind observations are generally taken from an unobstructed 10 m platform and drag coefficient 

relationships are also defined at a 10 m height. Therefore meteorological forcing or observations 

should also be adjusted to the 10 m reference height if not so provided (meteorological models in 

this study provide the 10 m reference height wind). The USACE’s Coastal Engineering Manual

provides formulae for the elevation correction of wind collection height (Resio et al., 2006). 

Failure to correct the height will lead to errors due to (among other things) the parabolic nature 

of the boundary layer. Therefore, all model output was selected to be at the 10 m level, and all 

observations were adjusted to the 10 m height for comparison. 

4.4. Adjustment of Wind Forcing Interval 

The meteorological models have different intervals for updating their output data. Simulation of 

Hurricane Isabel from GFDL provides hourly output from a 6-hr forecast cycle. GFS provides a 

6-hr updates for its analytical wind and 6-hr intervals in its forecast wind up to 96 hours. 

H*Wind has 3- or 6-hr updates depending on the NHC advisory (if the NHC issues a hurricane 

warning and forecast advisories every three hours, H*Wind switches to 3-hr update). In order to 

create consistent wind forcing time intervals, it is necessary to use an interpolation method to 

adjust their output data. The method chosen for temporal and spatial interpolation is an 

interpolation polynomial in the Lagrange form (Jeffreys and Jeffreys 1988). The interpolation 

polynomial in the Lagrange form is chosen because it gives a solution that has a constant slope 

between output data. In addition, it is the simplest way to interpolate between output data, even 

though it does not incorporate any physics. Therefore all model output data in space and time 

were adjusted to an hourly wind forcing interval using the interpolation polynomial in the 

Lagrange form. 

 

4.5. Blending Meteorological Models 

In order to improve the Hurricane Isabel storm surge hindcast, it is necessary to create the best 

available wind field. For Isabel the best available wind field is generated by blending 

meteorological models. This is because H*Wind is an observations-based analysis system which 

has shown the most skill in capturing the characteristics of the hurricane, but it lacks far-field 

and post-landfall winds, and pressure throughout. By combining aspects of the other 

meteorological models a forcing field can be built that supersedes their qualities individually. 
21 

There are two steps in blending meteorological models. The first step is the combining wind 

fields spatially by blending them within an overlapping region. The blending ratio is dependent 

on the grid resolution; since H*Wind has higher grid resolution than GFDL and GFS, the value 

of H*Wind is used when each grid overlaps. The next step is integrating atmospheric pressure. 

Atmospheric pressure from GFDL is utilized because GFDL properly resolves hurricane 

dynamics, while H*Wind does not provide atmospheric pressure. A resulting blended wind field 

is hourly interpolated onto the basin-scale CFM using the interpolation polynomial in the 

Lagrange form. 
22 
23 

5. LATERAL BOUNDARY CONDITION 

The non-tidal lateral boundary condition for the regional CFM is provided by both the basinscale CFM and the NCEP Atlantic Real-Time Ocean Forecast System (RTOFS). Time series of 

water surface elevations (WSE) from the basin-scale CFM simulation are applied to the regional 

CFM along the outer boundary. RTOFS is a forecast system based on the Hybrid Coordinate 

Ocean Model (HYCOM). Sea Surface Height (SSH), including mean dynamic topography due to 

temperature variations in the ocean and currents like the Gulf Stream, is provided to the regional 

CFM as the lateral boundary condition. 

The regional CFM grid can be efficiently run for multiple scenarios. However, this grid is not 

able to capture the response that occurs across the larger basin without an appropriate boundary 

condition. Therefore, several strategies are evaluated to understand their impact on CFM model 

skill. The basin-scale CFM was designed to accurately capture the physical dynamics associated 

with the propagation of the storm surge over the basin. The regional CFM is more suitable from 

the point of view of model efficiency when multiple runs are needed. Therefore, incorporating 

the lateral boundary condition produced by the basin-scale CFM into the regional CFM is the 

best option to satisfy both model accuracy and efficiency. In addition, applying the lateral 

boundary condition obtained from RTOFS helps to understand the baroclinic effects (i.e., mean 

dynamic topography due to temperature variations in the ocean and baroclinic currents) for storm 

surge. 

5.1. The Lateral Boundary Condition from Basin-Scale CFM 

Time-series of water surface elevation from the basin-scale CFM are used to provide the lateral 

boundary condition for the regional CFM. The meteorological model used to create the lateral 

boundary condition is the GFS model. Six-hour interval meteorological forcing is interpolated on 

the basin-scale CFM grid. The hourly interpolation approach using the interpolation polynomial 

in the Lagrange form (see Section 4.4) is not used because RTOFS uses a 6-hr interval of GFS 

meteorological forcing in their simulation of Hurricane Isabel, and it is important to make a 

uniform comparison of techniques. Computed time series of water surface elevation is forced 

every hour at each grid node along the coastal boundary of the regional CFM. 

5.2. Real-Time Ocean Forecast System 

RTOFS (Spindler et al., 2006; more information is available at http://polar.ncep.noaa.gov/ofs/) is 

an operational high resolution (eddy resolving) ocean forecast system for the NWS that provides 

short-term forecasts (approximately 1-week) of the Atlantic Basin, including both deep and 

coastal waters. The system provides nowcasts and forecasts of sea level, currents, temperature 

and salinity. Figure 11 illustrates the grid and bathymetry of RTOFS. 

RTOFS is an ocean forecast system based on HYCOM (Bleck 2002). HYCOM is the result of 

collaborative efforts among the University of Miami, the Naval Research Laboratory, and the 

Los Alamos National Laboratory as part of the multi-institutional HYCOM Consortium for Data-
24 

Assimilative Ocean Modeling. The goal is to develop and evaluate a data-assimilative hybrid 

isopycnal-sigma-pressure coordinate ocean model. RTOFS uses curvilinear coordinates in the 

horizontal (1200 x 1684 points) and hybrid vertical coordinates in the vertical (21 isopycnal and 

5 z-level for a total 26 vertical coordinates). 

Figure 11. RTOFS orthogonal grid with approximate grid spacing contours (a) and 

bathymetry (b). 

(a)

(b)
25 

5.3. The Lateral Boundary Condition from RTOFS 

SSH from RTOFS is tested as the lateral boundary condition for the regional CFM. In order to 

investigate the baroclinic effects in the boundary forcing, two cases of the lateral boundary 

conditions are applied. The first lateral boundary condition is with a SSH which includes the 

mean dynamic topography due to temperature variations in the ocean and large-scale currents, 

the tidal signal, and the ocean surface response to meteorological forcing. The second lateral 

boundary condition is a SSH without the mean dynamic topography, calculated by filtering to 

remove the 14 day linear mean value in the SSH. Each SSH is hourly-interpolated onto each 

node along the open boundary of the regional CFM. 

Figure 12 shows an example of the lateral boundary condition, including tidal forcing (harmonic 

tidal constituents, see Section 3.4), at the sample location (see Figure 6); 1) tide, 2) the basinscale, 3) RTOFS, and 4) detrended RTOFS. This figure clearly describes sub-tidal effects and the 

height of mean dynamic topography in the deviation of the mean of the blue line from the others. 

Figure 12. The lateral boundary condition at the sample location along outer boundary of 

the regional CFM (see Figure 6); 1) Tide (black), 2) the basin-scale CFM (red), 3) RTOFS 

(blue), and 4) detrended RTOFS (green).
26 
27 

6. RESULTS AND DISCUSSION

As a part of the Hurricane Isabel hindcast, model evaluations are carried out in several ways. 

First, model-generated Hurricane Isabel wind fields over the basin-scale CFM domain are 

compared with NDBC data. Second, time series of observed water surface elevation from NOS 

are used for the validation of the modeled storm surge. Third, FEMA CHWMs are used to assess 

the inundation predicted by the basin-scale CFM. In addition, validation of the lateral boundary 

condition is investigated using the regional CFM. Skill assessment, including Mean Error (ME), 

Root Mean Square Error (RMSE), Standard Deviation (SD), and peak difference in amplitude 

and phase, is performed to evaluate model accuracy. 

6.1. Validation of Hurricane Isabel Wind Fields 

The quality of the wind fields from meteorological models is assessed in two ways. First, time 

series of wind speed and direction applied to the basin-scale CFM are compared with NDBC 

continuous wind data (see Table 1 and Figure 3). Second, the wind fields in the basin-scale CFM 

are used to evaluate the intensity of Hurricane Isabel. In order to maintain consistency while 

comparing the meteorological forcing, H*Wind is adjusted to a 10 minute averaged value and all 

wind data are a 10 m height. In addition, to be consistent with hourly wind intervals from GFDL, 

hourly H*Wind and GFS wind fields are generated using the interpolation polynomial in the 

Lagrange form. Table 5 shows the detail of wind fields for Hurricane Isabel as applied to the 

basin-scale CFM. 

Table 5. Wind fields for Hurricane Isabel interpolation onto the basin-scale CFM. 

Model Grid Time Comment 

H*Wind 1000 km by 1000 km 

square domain with 

resolution of 6 km 

3-6 hour interval (1730 UTC 

September 11 to 1630 UTC 

September 18) 

Hourly increments using the 

interpolation polynomial in 

the Lagrange form 

GFDL 2 nested grids with 

resolutions of 9 and 

55 km 

Hourly output from 6 hour 

forecast cycle (0000 UTC 

September 7 to 1200 UTC 

September 18) 

Continues using forecast 

wind after last cycle at 1200 

UTC September 18 

GFS Approximately 50 

km grid 

6 hour output (0000 UTC 

September 7 to 0000 UTC 

September 21) 

Hourly increments using the 

interpolation polynomial in 

the Lagrange form 

NDBC continuous wind data are used to validate wind speed and direction in the basin-scale 

CFM domain. NDBC continuous wind data is averaged over 10 minutes and adjusted to 10 m 

height. Wind direction is also a 10-min average value, measured in degrees clockwise from true 

North. The comparisons of wind speed and direction provided by meteorological models against 

NDBC continuous wind data at observation locations (see Table 1 and Figure 4) are shown in 

Figures 13 through 17. In the figures, any undefined value outside the H*Wind domain is set to 

be zero, and time is displayed in ordinal date (from September 11 to September 21 2003). 
28 

At buoy locations 41001 and 41014 (Figures 13 and 14), all models capture the wind direction 

sufficiently as Isabel approaches landfall. GFDL has good agreement with observations in both 

wind speed and direction. GFS overestimates wind speed since GFS can’t resolve the hurricane 

dynamics in the absence of a high resolution nested grid, and for Isabel it overestimated the size 

of the storm (Tolman et al., 2003). At buoy location 41002 (Figure 15), located on the left side of 

the hurricane Isabel track, timing of maximum wind speed from all models is delayed 

approximately six hours. At the land location of DUCN7, maximum peak winds from H*Wind 

and GFS show good agreement with observations; however, GFDL is lower than the 

observations by approximately 10 m/s due to an underestimated storm size (Figures 16). The 

reason for this underestimation is that GFDL used the forecasted wind after 1200 UTC 

September 18, just prior to landfall. At CLKN7, located near the hurricane landfall point, all 

models match up well with the observations in both wind speed and direction (Figure 17). 

The wind fields in the basin-scale CFM are examined visually for comparing the intensity of 

Hurricane Isabel. Wind and atmospheric pressure fields were linearly interpolated onto the basinscale CFM grid. Figures 18 and 19 show every 6-hour interval from 0000 UTC September 17 to 

1800 UTC September 18. Figures 20 and 21 illustrate every 3-hour interval from 1200 UTC 

September 18 to 2100 UTC September 18 as Isabel makes landfall. H*Wind doesn’t provide 

wind data after Hurricane Isabel made landfall as shown in Figures 20 and 21. 

While Isabel is a Category 3 hurricane (1200 UTC September 17), the GFDL generally captures 

the structure of the wind field well, but wind speeds are generally lower than those from H*Wind 

(Figure 18). The GFS wind speeds are stronger than H*Wind and GFDL, but the GFS has similar 

structure of the wind field as H*Wind. Through September 17 (Figures 18 and 19), wind speed 

from all models are gradually weakened. Since the model wind fields are interpolated onto the 

basin-scale CFM grid, the hurricane eye is extended due to coarser spatial resolution in the deep 

ocean. As Isabel approaches the coastline (where model grid has more resolution), all models 

capture the eye of the hurricane clearly (Figure 19 and 20); however, the 6-hour temporal 

interpolation in the GFS produces an irregular hurricane eye (Figure 20). The GFDL wind speed 

intensities are realistic (see Figures 13 – 17), but the spatial extent of its wind field is generally 

smaller than H*Wind. In addition, since the GFDL uses long term forecast data after 1200 UTC 

September 18, the hurricane eye in the GFDL is gradually located to the left of the best available 

hurricane track. During this period, the GFS wind field shows better representation of the size of 

Isabel; however, the GFS overestimates wind speed. 
29 

Figure 13. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of 

NDBC continuous wind data (black dot) at NDBC location 41001. 

(a)

(b)
30 

Figure 14. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of 

NDBC continuous wind data (black dot) at NDBC location 41002. 

(a)

(b)
31 

Figure 15. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of 

NDBC continuous wind data (black dot) at NDBC location 44014. 

(a)

(b)
32 

Figure 16. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of 

NDBC continuous wind data (black dot) at NDBC location DUCN7. 

(a)

(b)
33 

Figure 17. The comparison of wind speed (a) and direction (b) provided by H*Wind (red 

triangle), GFDL (blue asterisk), and GFS (green cross) with observation of 

NDBC continuous wind data (black dot) at NDBC location CLKN7.

(a)

(b)
34

Figure 18. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for Isabel: H*Wind (a), GFDL (b), and GFS (c) 

at 1200 UTC September 17, and H*Wind (d), GFDL (e), and GFS (f) at 1800 UTC September 17. 

30.0 

32.0 26.0 28.0 

-76.0 -74.0 -72.0 -70.0 

(a) H*Wind (b) GFDL (c) GFS

3432.0 

.0 

28.0 30.0 

-68.0 -76.0 -74.0 -72.0 -70.0 -68.0 -76.0 -74.0 -72.0 -70.0 -68.0

-76.0 -74.0 -72.0 -70.0 -68.0

3432.0

.0

28.030.0

-76.0 -74.0 -72.0 -70.0 -68.0 

3432.0

.0

28.030.0

-76.0 -74.0 -72.0 -70.0 -68.0

(d) H*Wind (e) GFDL (f) GFS

30.0

32.026.028.0

30.0

32.026.028.0
35

Figure 19. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for Isabel: H*Wind (a), GFDL (b), and GFS (c) 

at 0000 UTC September 18, and H*Wind (d), GFDL (e), and GFS (f) at 0600 UTC September 18. 

3432.0 

.0 

28.0 30.0 

-76.0 -74.0 -72.0 -70.0 -78.0 

3432.0

.0

28.030.0

-76.0 -74.0 -72.0 -70.0 -78.0

3432.0

.0

28.030.0

-76.0 -74.0 -72.0 -70.0 -78.0

(a) H*Wind (b) GFDL (c) GFS

3432.0 

.0 

28.0 30.0 36.0 

-76.0 -74.0 -72.0 -70.0 -78.0 

3432.0

.0

28.030.036.0

-76.0 -74.0 -72.0 -70.0 -78.0

3432.0

.0

28.030.036.0

-76.0 -74.0 -72.0 -70.0 -78.0

(d) H*Wind (e) GFDL (f) GFS
36

Figure 20. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for Isabel: H*Wind (a), GFDL (b), and GFS (c) 

at 1200 UTC September 18, and H*Wind (d), GFDL (e), and GFS (f) at 1500 UTC September 18. 

-76.0 -74.0 -72.0 -78.0 

3432.0 -80.0 

.0 

30.0 38.0 36.0 

-76.0 -74.0 -72.0 -78.0

3432.0-80.0

.0

30.038.036.0

-76.0 -74.0 -72.0 -78.0 -80.0

3432.0

.0

30.038.036.0

3432.0 

.0 

30.0 38.0 36.0 

-76.0 -74.0 -72.0 -78.0 -80.0 

3432.0

.0

30.038.036.0

3432.0

.0

30.038.036.0

-76.0 -74.0 -72.0 -78.0 -80.0 -76.0 -74.0 -72.0 -78.0 -80.0

(a) H*Wind (b) GFDL (c) GFS(d) H*Wind (e) GFDL (f) GFS
37

Figure 21. Track of Isabel (solid black line) and wind speeds at 10 m height in ms-1 for Isabel: H*Wind (a), GFDL (b), and GFS (c) 

at 1800 UTC September 18, and H*Wind (d), GFDL (e), and GFS (f) at 2100 UTC September 18. 

-76.0 -74.0 -72.0 -78.0 -80.0 

3432.0 

.0 

38.0 36.0 

-76.0 -74.0 -72.0 -78.0 -80.0

3432.0

.0

38.036.0

-76.0 -74.0 -72.0 -78.0 -80.0

3432.0

.0

38.036.0

(a) H*Wind (b) GFDL (c) GFS

-76.0 -74.0 -72.0 -78.0 -80.0 

3432.0 

-82.0 

.0 

40.0 38.0 36.0 

-76.0 -74.0 -72.0 -78.0 -80.0 -82.0

3432.0

.0

40.038.036.0

-76.0 -74.0 -72.0 -78.0 -80.0 -82.0

3432.0

.0

40.038.036.0

(d) H*Wind (e) GFDL (f) GFS
38 

6.2. Validation of Water Surface Elevation 

Time series of water surface elevation are compared with observed water surface elevation at 

NOS tide gauge stations (see Table 2 and Figure 4). Simulations are run for 14 days, from 0000 

UTC September 7 to 0000 UTC September 21, with a 4 day hyperbolic tangent ramping function 

and a 2 second time step. Time series of water surface elevation are saved at 6-min intervals 

from 254 to 264 in ordinal date (September 10 to 21). Comparison figures are shown in Figure 

22 and 23. Boundary condition forcing is specified by harmonic constants for 5 tidal constituents 

from Schwiderski’s global tidal model (Schwiderski 1980) as used in Luettich et al. (1994). The 

eddy viscosity coefficient is set to 5.0 m2

/s, and a hybrid quadratic bottom friction formulation is 

specified which applies a traditional quadratic function. A non-dimensional friction coefficient of 

0.0025 in water deeper than 0.50 m is applied, and this coefficient increases exponentially in 

water shallower than 0.50 m to represent the increased friction during overland inundation (see 

Appendix B.3) 

As shown in Figure 22a, the peak surge as well as the time of arrival of the surge compare very 

well with the observations at the Duck Field Research Facility (FRF) Pier. Peak surge from 

H*Wind is lower than observations because of the absence of the inverted barometer effect. The 

Oregon Inlet Marina station (Figure 22b) is located inside of Pamlico Sound and just north of the 

inlet. The tidal signal is relatively small at this location compared to the Atlantic side. After 

Isabel made landfall, the wind turned from east/southeast to south and southwest and drove the 

water in Pamlico Sound up against the east side of the sound, causing a water level rise at the 

Oregon Inlet Marina station. GFDL and GFS both capture this water level rise in the Pamlico 

Sound. Since H*Wind does not provide wind data after Isabel made landfall, there is no surge 

inside the sound as the storm passes, but only the tidal signal. At the Cape Hatteras Fishing Pier 

(Figure 23a) the tide gauge was destroyed before the peak storm surge arrived, so it is not 

possible to capture the peak surge. Storm surge from each model starts lower than the 

observations but does captures the rate of rise of the water. At the Beaufort Duke Marine Lab 

located inside Beaufort Inlet (Figure 23b), the GFDL results in the best match with the 

observations. 
39 

Figure 22. The comparison of water surface elevations provided by H*Wind (red), GFDL 

(blue), and GFS (green) with observations (black) at Duck FRF Pier (a) and 

Oregon Inlet Marine Pamlico Sound (b). 

(a)

(b)
40 

Figure 23. The comparison of water surface elevations provided by H*Wind (red), GFDL 

(blue), and GFS (green) with observations (black) at Cape Hatteras Fishing Pier 

(a) and Beaufort Duke Marine Lab (b).

(a)

(b)
41 

6.3. Validation of High Water Marks 

According to the FEMA report, the highest storm surge occurred across the lower reaches of the 

Neuse and Pamlico Rivers. On the Neuse River, the highest surge was between Clubfoot Creek 

and Adams Creek where water rose to 3.2 m above NAVD 88. Significant flooding was reported 

in the Harlowe area in Craven Country and in the Town of Oriental in Eastern Pamlico County. 

Water levels rose 1.80 and 2.10 m on the Pamlico River, causing flooding in the City of 

Washington, NC. 

Figure 24 illustrates the spatial distribution of maximum storm surge in the basin-scale CFM 

along with plots of 160 FEMA CHWM values; Figures 24 (a-c) show the entire basin-scale CFM 

domain and (d-f) show an enlargement of the west side of Pamlico Sound, including the Neuse 

and Pamlico Rivers. Figure 24 includes results driven by each meteorological model; from left to 

right, H*Wind, GFDL and GFS, respectively. H*Wind produces strong onshore wind effects and 

higher maximum peak surge than GFDL and GFS around the Pamlico-Neuse region. However, 

the missing wind after landfall, blowing from west/southwest to east/northeast, causes lower 

surge and no water rise inside Pamlico and Albemarle Sounds (see Figure 22b at Oregon Inlet 

Marina, Pamlico Sound). GFDL and GFS result in a similar distribution throughout the domain; 

however GFDL produces lower maximum peak surge because of a smaller storm in its forecast 

after 1200 UTC September 18. 

Maximum storm surges from each run are compared to FEMA CHWMs (see Table A.1 and 

Figure 5). A total of 166 locations are surveyed by FEMA in October 2003. The 160 model/data 

pairs of values, excluding 6 locations due to undefined values, are subtracted from each other 

(i.e. modeled HWMs minus FEMA CHWMs) and a histogram of the differences are created as 

shown in Figures 25 and 26. The sample number of HWMs was limited to those flooded by each 

simulation. In H*Wind, the HWM errors have a mean of -0.73 m NAVD 88 across 99 marks. 

HWM errors from GFDL and GFS have a mean of -0.63 m NAVD 88 across 100 marks and -

0.63 m NAVD 88 across 102 marks, respectively. These error characteristics are depicted in the 

legend of Figures 25 and 26. As can be seen, most of the errors are negative, which means that 

FEMA CHWMs are larger than the model results. This is partially due to the fact that the FEMA 

CHWMs have a wave-induced contribution included in the storm surge value that is not included 

in our model. 
Figure 24. The distribution of maximum storm surge (m NAVD 88) in the basin-scale CFM from each meteorological model (from 

left to right H*Wind, GFDL, and GFS); circles denote FEMA CHWMs; (a) – (c) illustrates the entire North Carolina 

sound system, and (d) – (f) show the enlargement of west side of Palmico Sound including the Neuse and Pamlico Rivers. 

-77.0 

35.0 

-76.0 

36.0 

-77.0

35.0

-76.0

36.0

-77.0

35.0

-76.0

36.0

35.0 

-77.0 -76.5 

35.0

-77.0 -76.5

35.0

-77.0 -76.5

(a) H*Wind (b) GFDL (c) GFS(d) H*Wind (e) GFDL (f) GFS

41 
43 

Figure 25. The HWMs from H*Wind (a) and GFDL (b) forcingminus observed FEMA 

HWMs for Hurricane Isabel (excluding marks that were not flooded in each 

simulation).

No. of observations: 99 

Mean error: -0.7272 

Std deviation: 0.4928 

No. of observations: 100 

Mean error: -0.6272 

Std deviation: 0.4225 
44 

Figure 26. The HWMs from GFS forcing minus observed FEMA HWMs for Hurricane 

Isabel (excluding marks that were not flooded in the simulation). 

6.4. Validation of Blended Meteorological Models 

The blended wind field is built by combining meteorological models to create the best available 

wind field (see Section 4.5). Figures 27 through 31 illustrate the comparison of blended model 

wind speeds and directions with the NDBC continuous wind data. The advantage of the blended 

wind field is that it combines the strong peak winds in the H*Wind model with the far-field and 

post-landfall winds of the GFDL and GFS models. Additionally, the blending adds the pressure 

field from GFDL, which H*Wind lacks. 

Figures 32 and 33 show the comparison of time series of water surface elevation between the 

model and observations at NOS tide gauge stations. These plots indicate the advantages of the 

blended meteorological forcing. First, the pre-storm and post-landfall water levels are improved 

over those from the H*Wind forcing due to the additional wind fields at those times. Second, the 

peak surge corresponds to the H*Wind forcing, which provided the best peak across the North 

Carolina coast and sound system. 

The distribution of maximum peak storm surge and plots of FEMA CHWM values are illustrated 

in Figure 34. Figure 35 illustrates the difference of HWMs (in m NAVD 88) between the 

blended model and FEMA CHWMs. HWM error has a mean of -0.40 m at 123 marks, which is a 

significant improvement over any of the individual meteorological model runs. 

No. of observations: 102 

Mean error: -0.6252 

Std deviation: 0.5513 
45 

Figure 27. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 41001. 

(a)

(b)
46 

Figure 28. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 41002. 

(a)

(b)
47 

Figure 29. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location 44014. 

(a)

(b)
48 

Figure 30. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location DUCN7. 

(a)

(b)
49 

Figure 31. The comparison of wind speed (a) and direction (b) provided by the blended 

models (red asterisk) with observations of NDBC continuous wind data (black 

dot) at NDBC location CLKN7. 

(a)

(b)
50 

Figure 32. The comparison of water surface elevations provided by the blended 

meteorological forcing (red) against observations (black) at Duck FRF Pier (a) 

and Oregon Inlet Marine Pamlico Sound (b). 

(a)

(b)
51 

Figure 33. The comparison of water surface elevations provided by the blended 

meteorological forcing (red) against observations (black) at Cape Hatteras 

Fishing Pier (a) and Beaufort Duke Marine Lab (b).

(a)

(b)
52 

Figure 34. The distribution of maximum storm surge (m NAVD88) in the North Carolina 

sound system from the blended meteorological forcing; circles denote FEMA 

CHWMs. 

Figure 35. The HWMs from the blended meteorological forcing minus observed FEMA 

HWMs for Hurricane Isabel (excluding marks that were not flooded in the 

simulation). 

-77.0 

35.0 

-76.0

36.0 

Blended

No. of observations: 123 

Mean error: -0.3996 

Std deviation: 0.5079 
53 

6.5. Validation of Lateral Boundary Conditions 

Three types of the lateral boundary condition are provided to the regional CFM at each node 

along the open ocean boundary: 1) periodic tidal forcing using harmonic tidal constituents 

derived from the East Coast 2001 (EC2001) database (Mukai et al., 2001); 2) barotropic water 

level time series using WSE obtained from the basin-scale CFM; and 3) baroclinic water level 

time series using SSH from RTOFS. With RTOFS SSH, two cases of the lateral boundary 

condition are applied here. The first case is SSH including the mean dynamic sea surface 

topography caused by baroclinic effects along with the barotropic signal. The second case is SSH 

without mean dynamic topography, obtained by filtering to remove the 14 day mean linear trend 

(detrending) in the SSH. Furthermore, subtidal water surface elevation, obtained by detiding the 

water surface elevation, is compared with detided observations. Since RTOFS uses 6-hour 

interval GFS forcing for its meteorological forcing, all of these simulations employ the same 

GFS forcing to make consistent comparisons. 

Time series of water surface elevation are compared with the observations at four NOS tide 

gauge stations. Figures 36 and 37 show the comparison of time series of water surface elevation 

forced by three different types of the lateral boundary condition: 1) Tide (harmonic tidal 

constituents), 2) WSE provided by the basin-scale CFM, and 3) SSH from RTOFS. The simple 

tidal forcing is shown to underpredict the storm surge due to the lack of surge build-up on the 

shelf outside the regional CFM. By providing the lateral boundary condition from the basin-scale 

CFM the peak surge is improved at all locations. The lateral boundary condition provided by 

RTOFS results in a deviation of the modeled tidal signal in both amplitude and phase prior to the 

peak surge; RTOFS generates too large of a tidal signal whose phase slightly leads the observed 

time. More importantly, the lateral boundary condition from RTOFS does not do a better job in 

forcing the storm surge than the simple tidal forcing as they underpredict the surge by a similar 

amount. 

Figures 38 and 39 illustrate the comparison of time series of water surface elevation forced by 1) 

the basin-scale CFM, 2) RTOFS, and 3) detrended RTOFS. By detrending, the long term mean 

primarily driven by baroclinic effects is removed, leaving the barotropic signal similar to the 

basin-scale CFM. The tidal signal and peak surge are significantly improved at Oregon Inlet 

Marina, Pamlico Sound; however, smaller improvements are recognized at other locations as 

well. In general, the error in the mean water level is improved but the under-predicted peak surge 

is not improved. These comparisons show that the basin-scale CFM provides better lateral 

boundary conditions than either RTOFS condition. 

Figures 40 and 41 show the comparison of subtidal water surface elevation forced by 1) the 

basin-scale CFM, 2) RTOFS, and 3) detrended RTOFS, along with the observations at NOS tide 

gauge stations. Subtidal signals are calculated by subtracting the actual observations from NOS 

tidal predictions. It is clear that removing baroclinic effects from the RTOFS forcing results in 

noticeable improvements in the subtidal signal, but that the basin-scale CFM barotropic model 

does the best job of representing the ocean’s meteorological response to the hurricane. 
54 

Figure 36. The comparison of water surface elevations forced by tide (red), basin-scale 

CFM (blue), and RTOFS (green) lateral boundary conditions with observations 

(black) at Duck FRF Pier (a) and Oregon Inlet Marine Pamlico Sound (b). 

(a)

(b)
55 

Figure 37. The comparison of water surface elevations forced by tide (red), basin-scale 

CFM (blue), and RTOFS (green) lateral boundary conditions with observations 

(black) at Cape Hatteras Fishing Pier (a) and Beaufort Duke Marine Lab (b). 

(a)

(b)
56 

Figure 38. The comparison of water surface elevations forced by basin-scale CFM (red), 

RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions with 

observations (black) at Duck FRF Pier (a) and Oregon Inlet Marine Pamlico 

Sound (b). 

(a)

(b)
57 

Figure 39. The comparison of water surface elevations forced by basin-scale CFM (red), 

RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions with 

observations (black) at Cape Hatteras Fishing Pier (a) and Beaufort Duke 

Marine Lab (b). 

(a)

(b)
58 

Figure 40. The comparison of subtidal water surface elevation forced by basin-scale CFM 

(red), RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions 

with observations (black) at Duck FRF Pier (a) and Oregon Inlet Marine 

Pamlico Sound (b). 

(a)

(b)
59 

Figure 41. The comparison of subtidal water surface elevation forced by basin-scale CFM 

(red), RTOFS (blue), and detrended RTOFS (green) lateral boundary conditions 

with observations (black) at Cape Hatteras Fishing Pier (a) and Beaufort Duke 

Marine Lab (b). 

(a)

(b)
60 

6.6. Skill Assessment 

Skill assessment is an objective measurement of the performance of a model when systematically 

compared with observations. NOS skill assessment criteria were created for evaluating the 

performance of operational nowcast/forecast circulation models (Hess et al., 2003), and a 

software package was subsequently developed to evaluate these criteria using standard file 

formats output from the models (Zhang et al., 2006). The software can compute the skill 

assessment automatically using files containing observations, predictions, and nowcast/forecast 

model results. A standard suite of skill assessment statistics is defined in Table 6 (Hess et al., 

2003). In addition, peak differences (model peak minus observed peak) of amplitude (in meters) 

and phase (in minutes) are added to the skill assessment. 

Table 6. Skill assessment statistics 

Variable Explanation 

Error The error is defined as the predicted value, p , minus the reference (observed or 

astronomical tide value), r: i i i e  p  r . 

SM Series Mean. The mean value of a series y. Calculated as 



N

i

i y N y

1

1

RMSE 

Root Mean Square Error. Calculated as 



N

i

N i RMSE e

1

1 2

SD 

Standard Deviation. Calculated as   

 

N

i

N i SD e e

1

2 1

6.7. Water Surface Elevation Skill Assessment 

Skill assessment statistics are calculated for each model hindcast simulation (each 

meteorological forcing and lateral boundary condition forcing). Hurricane Isabel hindcast 

simulations are made from September 7 to September 21 2003, and time series of water surface 

elevation are saved in six minute intervals at locations where observations are available (see 

Table 2 and Figure 5). The last 10 days (September 10 to September 21 2003) in the simulation 

period are used for calculating skill assessment statistics. Due to failure of the Cape Hatteras 

Fishing Pier water level gauge, no peak difference could be computed and only the last 8 days 

(September 10 to September 18 2003) at this location are used for calculating skill assessment 

statistics. Filtering of values in a time series is common to remove short period variations and 

noise; however, filtering does not apply for these calculations in order to capture the peak surge. 

The standard suite of statistics for hindcast simulations of the basin-scale CFM using different 

meteorological forcing are presented in Table 7. The RMSE at the four NOS tide gauges ranges 

from 0.11 m to 0.29 m. The H*Wind forced simulation consistently has the highest RMSE 

because of its poor performance before and after the main storm winds. The GFS, GFDL, and 

blended forcings tend to have similar RMSE except at station 8656483 (Beaufort Duke Marine 
61 

Lab), where a larger RMSE reflects that the blended forcing does not do as well as GFDL and 

GFS before the main surge event. 

Comparisons of peak storm surge heights and times of occurrence in both observations and 

simulations are shown in Table 8. The last two columns in Table 8 are peak difference in 

amplitude and phase, which is calculated by gauge peak minus model peak. The peak difference 

in amplitude and phase at the three NOS tide gauges range from -1.26 m and -108 minutes at 

Oregon Inlet Marina to 0.47 m and +120 minutes at Duck, FRF Pier. GFS produces 

approximately a two-hour peak difference in phase at two NOS tide gauge locations because the 

model is leading the data due to the overpredicted size of the storm. This might also be caused by 

the interpolated error in creating hourly meteorological forcing from the GFS’ 6-hour update 

interval. These results clearly show an advantage in the blended forcing which almost uniformly 

has the smallest errors in peak height and timing. 

The standard suite of statistics for the hindcast simulations of the regional CFM using different 

lateral boundary condition forcings are presented in Table 9. The RMSE indicates two things. 

First, it is seen that both RTOFS boundary conditions perform worse that either the tidal or the 

basis-scale CFM forcings, although detrending RTOFS to remove the baroclinic variability does 

help. Second, the basin-scale CFM is most consistent in minimizing RSME. Comparison of the 

peak storm surge heights and times of occurrence in both observations and simulations is shown 

in Table 10. Peak difference in amplitude ranges from -0.74 m at Oregon Inlet Marine to 0.31 m 

at Duck, FRF Pier. Lateral boundary conditions from the detrended RTOFS improve all values in 

comparison with RTOFS at the four NOS tide gauges, which indicates that the primarily 

baroclinic long term trend does not improve a barotropic storm surge prediction. The basin-scale 

CFM domain is shown to minimize error, particularly in the peak surge amplitude. 
62 

Table 7. Skill assessment statistics of different meteorological forcings 

 in the basin-scale CFM. 

NOS Station ID Meteorological Forcing SM RMSE SD 

(m) (m) (m) 

8651370 

H*Wind -0.122 0.204 0.163 

GFDL 0.036 0.130 0.125 

GFS 0.082 0.126 0.095 

Blended 0.046 0.123 0.114 

8652587 

H*Wind -0.122 0.286 0.259 

GFDL -0.036 0.108 0.102 

GFS -0.023 0.111 0.109 

Blended -0.013 0.111 0.110 

8654400 

H*Wind -0.171 0.241 0.169 

GFDL -0.036 0.146 0.142 

GFS -0.031 0.150 0.147 

Blended -0.037 0.149 0.144 

8656483 

H*Wind -0.092 0.182 0.156 

GFDL 0.054 0.111 0.097 

GFS 0.060 0.123 0.108 

Blended 0.048 0.181 0.175 
63 

Table 8. The comparison of peak storm surge heights and times of occurrence in both observations and simulations in the basinscale CFM. 

NOS 

Station 

ID 

Gauge 

Peak 

Time of Gauge 

Peak Meteorological 

Forcing 

Model 

Peak 

Time of Model 

Peak 

Peak Difference 

Amplitude Phase 

(m 

NAVD 88) (UTC) (m NAVD 88) (UTC) (m NAVD88) (min) 

8651370 1.716 9/18/2003 16:06 

H*Wind 1.330 9/18/03 16:06 -0.386 0 

GFDL 1.283 9/18/03 16:54 -0.433 48 

GFS 2.189 9/18/03 18:06 0.473 120 

Blended 1.748 9/18/03 16:18 0.032 12 

8652587 1.439 9/19/2003 3:48 

H*Wind 0.186 9/19/03 5:18 -1.264 90 

GFDL 0.875 9/19/03 3:48 -0.575 0 

GFS 1.253 9/19/03 2:00 -0.197 -108 

Blended 0.988 9/19/03 3:24 -0.462 -24 

8654400 N/A N/A 

H*Wind 1.376 9/18/03 16:06 

N/A* N/A GFDL 1.394 9/18/03 16:48 GFS 1.746 9/18/03 18:18 

Blended 1.895 9/18/03 16:12 

8656483 1.121 9/18/2003 18:42 

H*Wind 0.710 9/18/03 19:36 -0.412 54 

GFDL 1.147 9/18/03 19:06 0.026 24 

GFS 1.271 9/18/03 18:06 0.150 -36 

Blended 1.108 9/18/03 18:42 -0.013 0 

* N/A indicates no data was available for this analysis.
64 

Table 9. Skill assessment statistics of different lateral boundary condition forcings 

in the regional CFM. 

NOS Station ID L.B.C. Forcing SM RMSE SD 

(m) (m) (m) 

8651370 

Tide -0.131 0.191 0.140 

Basin-Scale CFM 0.062 0.193 0.183 

RTOFS -0.218 0.374 0.304 

Detrended RTOFS -0.122 0.335 0.312 

8652587 

Tide -0.147 0.182 0.106 

Basin-Scale CFM -0.028 0.116 0.112 

RTOFS -0.240 0.301 0.182 

Detrended RTOFS -0.096 0.172 0.142 

8654400 

Tide -0.140 0.222 0.172 

Basin-Scale CFM -0.030 0.197 0.195 

RTOFS -0.387 0.481 0.286 

Detrended RTOFS -0.150 0.327 0.290 

8656483 

Tide -0.040 0.115 0.108 

Basin-Scale CFM 0.059 0.184 0.175 

RTOFS -0.165 0.291 0.240 

Detrended RTOFS -0.007 0.249 0.249 
65 

Table 10. The comparison of peak storm surge heights and times of occurrence in both observations and simulations in the 

regional CFM. 

NOS 

Station 

ID 

Gauge 

Peak 

Time of Gauge 

Peak L.B.C. Forcing 

Model 

Peak Time of Model Peak Peak Difference Amplitude Phase 

(m 

NAVD88) (UTC) (m NAVD88) (UTC) (m NAVD88) (min) 

8651370 1.716 9/18/2003 16:06 

Tide 1.198 9/18/03 18:18 -0.518 126 

Basin-Scale CFM 2.022 9/18/03 18:18 0.306 126 

RTOFS 0.985 9/18/03 17:24 -0.731 78 

Detrended RTOFS 1.100 9/18/03 17:18 -0.616 72 

8652587 1.439 9/19/2003 3:48 

Tide 0.931 9/19/03 2:06 -0.519 -102 

Basin-Scale CFM 1.147 9/19/03 2:00 -0.303 -108 

RTOFS 0.711 9/19/03 2:18 -0.739 -90 

Detrended RTOFS 0.874 9/19/03 2:18 -0.576 -90 

8654400 N/A N/A 

Tide 1.343 9/18/03 18:18 

N/A N/A Basin-Scale CFM 1.485 9/18/03 18:12 

RTOFS 0.860 9/18/03 18:00 

Detrended RTOFS 1.041 9/18/03 18:00 

8656483 1.121 9/18/2003 18:42 

Tide 0.871 9/18/03 18:24 -0.250 -18 

Basin-Scale CFM 1.100 9/18/03 18:24 -0.022 -18 

RTOFS 0.536 9/18/03 17:42 -0.585 -60 

Detrended RTOFS 0.623 9/18/03 17:36 -0.499 -66 

* N/A indicates no data was available for this analysis. 
66 
67 

7. SUMMARY AND CONCLUSIONS 

NOS has been partnering with the NWS in a storm surge project to couple a coastal finite 

element model with operational weather prediction models. The goal is to improve storm surge 

simulations over that available from the models independently by combining their different 

capabilities. NOAA’s NWS develops and implements atmosphere and ocean models used for 

forecast guidance at NCEP’s Environmental Modeling Center (EMC). These numerical 

modeling applications include widely used, large scale atmosphere and ocean models. This suite 

of developmental and operational models includes meteorological (e.g., the GFDL) and general 

ocean circulation (e.g., the RTOFS) models which capture hurricane activity. 

The CFM (basin-scale and regional) has been developed to predict the impact of storm surge 

flooding by utilizing a DEM which has a continuous bathy/topo dataset relative to a single 

referenced datum (i.e., NAVD 88). The 15 m contour was chosen as the landward boundary, 

since this will allow the CFM to model severe storm surge conditions. Mesh size within sounds 

ranged between several hundred meters to nearly two kilometers, and rivers were discretized 

ranging from many nodes across to a pair of elements only 50 m in size. 

Wind field comparisons of NDBC observations with H*Wind, GFDL, and GFS models were 

performed for Hurricane Isabel. Wind field comparisons considered wind speed and direction at 

three NDBC buoy locations and two NDBC land locations along the North Carolina coast. Each 

of the models performed favorably to the observations at all locations; however, there were 

discrepancies at the time of maximum wind for most of the locations. Blending meteorological 

models produced the best available wind field in comparison to observations at most of the 

locations. 

Comparison of time series of water surface elevation with observations showed that both 

versions of the CFM produce reasonable results regardless of meteorological forcing. However, 

one exception was for H*Wind at the Oregon Inlet Marina. Because H*Wind did not provide 

wind data after landfall, both CFMs did not capture water rise generated inside Pamlico Sound. 

Blended meteorological forcing resulted in the best performance in maximum peak heights and 

times of occurrence at most NOS tide gauge locations. Comparison of 160 FEMA CHWMs in 

North Carolina yielded storm surge model errors of high water marks with a majority of model 

values within plus or minus 20 percent of FEMA CHWMs. 

Applying two cases of lateral boundary conditions from RTOFS indicated that removing the 

mean dynamic topography improved time series of water surface elevation at all of NOS tide 

gauge locations. Also, detided time series of water surface elevation produced similar 

conclusions. These results implied that the mean dynamic topography primarily caused by 

baroclinicity did not have an effect on the storm surge. 

SM, RMSE, and SD in time series of water surface elevation and peak difference in amplitude 

and phase of peak water level are calculated to evaluate model performances. Considering the 

total skill assessment, the blended meteorological forcing produced better results than other 

models in the basin-scale CFM. Also, the lateral boundary condition created by the basin-scale 

CFM resulted in better skill assessment statistics than other lateral boundary condition forcing. 
68 

Future work may include Hurricane Isabel hindcast using the Hurricane Weather and Research 

Forecasting (HWRF) model (http://www.emc.ncep.noaa.gov/HWRF/index.html/), which 

recently became an operational hurricane model at NCEP. In addition, SSH generated by future 

versions of RTOFS will continue to be evaluated as a lateral boundary condition in order to 

evaluate their effectiveness. 
69 

ACKNOWLEDGMENTS 

The author would like to acknowledge CSDL’s Rich Patchen, Edward Myers, and Jiangtao Xu 

for their support on final quality control review of this report. 

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72 
73 

APPENDIX A. FEMA Coastal High Water Marks 

Table A.1. FEMA CHWMs in the study area (An undefined value is identified as 999). 

No. Latitude Longitude Flood Elevation [m NAVD88] Historical Mark 

1 35.534 -76.615 1.7 ISA-03-1011 

2 35.537 -76.610 1.7 ISA-03-1012 

3 35.549 -76.628 1.7 ISA-03-1013 

4 35.552 -76.641 1.7 ISA-03-1014 

5 35.548 -76.607 1.6 ISA-03-1015 

6 35.560 -76.576 1.6 ISA-03-1016 

7 35.534 -76.547 1.6 ISA-03-1017 

8 35.531 -76.536 1.7 ISA-03-1018 

9 35.519 -76.648 1.6 ISA-03-1019 

10 35.509 -76.664 1.6 ISA-03-1020 

11 35.499 -76.687 1.5 ISA-03-1021 

12 35.574 -76.662 1.6 ISA-03-1022 

13 35.339 -76.694 2.1 ISA-03-1109 

14 35.346 -76.667 1.3 ISA-03-1110 

15 35.324 -76.627 1.5 ISA-03-1111 

16 35.377 -76.749 1.5 ISA-03-1112 

17 35.428 -76.740 1.2 ISA-03-1113 

18 35.397 -76.609 1.7 ISA-03-1114 

19 35.401 -76.634 3.0 ISA-03-1115 

20 35.402 -76.633 1.6 ISA-03-1116 

21 35.448 -76.606 1.6 ISA-03-1117 

22 36.212 -76.041 1.3 Floyd-0001 

23 36.290 -76.148 1.7 Floyd-0002 

24 36.212 -76.041 0.9 ISA-03-0001 

25 36.255 -76.097 1.7 ISA-03-0002 

26 36.279 -76.116 1.3 ISA-03-0003 

27 36.290 -76.148 1.0 ISA-03-0004 

28 35.004 -76.314 2.4 ISA-03-0623 

29 34.993 -76.309 2.2 ISA-03-0624 

30 34.808 -76.457 1.8 ISA-03-0625 

31 34.846 -76.755 2.5 ISA-03-0702 

32 34.827 -76.637 1.1 ISA-03-0721 

33 34.808 -76.631 0.9 ISA-03-0722 

34 34.790 -76.604 1.1 ISA-03-0723 

35 35.018 -76.315 1.9 ISA-03-1122 

36 34.984 -76.300 2.2 ISA-03-1123 

37 34.886 -76.332 2.3 ISA-03-1124 

38 34.877 -76.390 2.1 ISA-03-1125 

39 34.845 -76.420 1.9 ISA-03-1126 

40 34.843 -76.753 999 ISA-03-NF06 

41 34.868 -76.758 2.8 ISA-03-0700 

42 34.894 -76.766 2.4 ISA-03-0703 

43 34.907 -76.763 2.4 ISA-03-0704 

44 34.881 -76.762 2.6 ISA-03-0705 

45 34.921 -76.728 2.2 ISA-03-0706 

46 34.939 -76.715 2.7 ISA-03-0707 

47 34.899 -76.686 2.3 ISA-03-0708 

48 34.917 -76.752 2.6 ISA-03-0709 
74 

49 34.953 -76.708 2.9 ISA-03-0710 

50 34.956 -76.689 2.7 ISA-03-0711 

51 34.946 -76.672 2.3 ISA-03-0712 

52 34.875 -76.767 2.5 ISA-03-0713 

53 34.926 -76.785 3.7 ISA-03-0714 

54 34.936 -76.811 2.4 ISA-03-0715 

55 34.918 -76.853 1.2 ISA-03-0716 

56 34.906 -76.916 2.0 ISA-03-0717 

57 34.937 -76.938 2.0 ISA-03-0718 

58 34.969 -76.925 3.1 ISA-03-0719 

59 34.984 -76.948 2.4 ISA-03-0720 

60 35.267 -75.519 2.6 ISA-03-0400 

61 35.229 -75.629 2.7 ISA-03-0401 

62 35.229 -75.626 3.1 ISA-03-0402 

63 35.222 -75.654 1.9 ISA-03-0403 

64 35.585 -75.462 2.4 ISA-03-0404 

65 35.599 -75.464 3.8 ISA-03-0405 

66 35.216 -75.674 3.2 ISA-03-0406 

67 35.209 -75.696 1.6 ISA-03-0407 

68 35.216 -75.685 2.1 ISA-03-0408 

69 35.224 -75.682 1.1 ISA-03-0409 

70 35.606 -75.465 2.6 ISA-03-0410 

71 35.329 -75.508 1.1 ISA-03-0500 

72 35.289 -75.516 1.5 ISA-03-0501 

73 35.344 -75.504 1.3 ISA-03-0502 

74 36.034 -75.668 3.9 ISA-03-0503 

75 36.047 -75.677 4.9 ISA-03-0504 

76 36.057 -75.686 2.7 ISA-03-0505 

77 35.909 -75.669 0.7 ISA-03-0506 

78 35.920 -75.661 0.6 ISA-03-0507 

79 35.867 -75.573 3.7 ISA-03-0508 

80 35.700 -75.742 0.9 ISA-03-0509 

81 35.690 -75.737 1.3 ISA-03-0511 

82 35.939 -75.705 999 ISA-03-NF07 

83 35.107 -75.986 0.9 ISA-03-0622 

84 35.406 -76.329 2.1 ISA-03-1000 

85 35.421 -76.317 1.7 ISA-03-1001 

86 35.406 -76.307 1.6 ISA-03-1002 

87 35.408 -76.264 0.8 ISA-03-1003 

88 35.391 -76.314 2.2 ISA-03-1004 

89 35.407 -76.245 0.9 ISA-03-1005 

90 35.427 -76.307 1.3 ISA-03-1006 

91 35.403 -76.338 2.3 ISA-03-1007 

92 35.395 -76.326 2.2 ISA-03-1008 

93 35.413 -76.339 2.1 ISA-03-1009 

94 35.431 -76.350 1.5 ISA-03-1010 

95 35.465 -76.490 1.3 ISA-03-1023 

96 35.481 -76.459 1.1 ISA-03-1024 

97 35.449 -76.459 1.3 ISA-03-1025 

98 35.434 -76.449 1.9 ISA-03-1026 

99 35.429 -76.466 1.7 ISA-03-1027 

100 35.424 -76.483 1.4 ISA-03-1028 

101 35.495 -76.452 1.6 ISA-03-1029 

102 35.503 -76.512 1.5 ISA-03-1030 

103 35.448 -76.487 1.2 ISA-03-1031 
75 

104 35.432 -76.506 1.5 ISA-03-1032 

105 35.461 -76.545 1.6 ISA-03-1033 

106 35.463 -76.444 1.5 ISA-03-1034 

107 35.462 -76.376 1.4 ISA-03-1035 

108 35.480 -76.011 1.3 ISA-03-1222 

109 35.439 -76.070 1.4 ISA_03-1223 

110 35.113 -75.965 999 ISA-03-NF48 

111 35.119 -75.974 999 ISA-03-NF49 

112 34.973 -76.792 2.6 ISA-03-0611 

113 34.971 -76.817 2.4 ISA-03-0612 

114 34.999 -76.860 2.8 ISA-03-0613 

115 35.027 -76.866 2.3 ISA-03-0614 

116 35.022 -76.898 3.0 ISA-03-0615 

117 35.022 -76.899 3.0 ISA-03-0616 

118 35.056 -76.916 2.1 ISA-03-0617 

119 34.998 -76.736 2.5 ISA-03-0800 

120 35.020 -76.706 2.2 ISA-03-0801 

121 35.028 -76.689 2.4 ISA-03-0802 

122 35.087 -76.636 2.2 ISA-03-0803 

123 35.095 -76.631 2.1 ISA-03-0804 

124 35.096 -76.606 2.1 ISA-03-0805 

125 35.124 -76.618 2.0 ISA-03-0806 

126 35.144 -76.631 2.0 ISA-03-0807 

127 35.161 -76.666 2.0 ISA-03-0808 

128 35.146 -76.690 2.1 ISA-03-0809 

129 35.146 -76.690 3.0 ISA-03-0810 

130 35.138 -76.723 2.0 ISA-03-0811 

131 35.137 -76.745 2.1 ISA-03-0812 

132 35.158 -76.736 2.0 ISA-03-0814 

133 35.183 -76.663 2.0 ISA-03-0815 

134 35.170 -76.685 2.7 ISA-03-0816 

135 35.205 -76.652 2.0 ISA-03-0817 

136 35.177 -76.624 2.1 ISA-03-0818 

137 35.198 -76.608 2.0 ISA-03-0819 

138 35.243 -76.591 1.7 ISA-03-0820 

139 35.245 -76.562 1.8 ISA-03-0821 

140 35.320 -76.561 1.4 ISA-03-1118 

141 35.301 -76.573 1.3 ISA-03-1119 

142 35.245 -76.561 1.8 ISA-03-1120 

143 35.025 -76.695 2.3 ISA-03-1121 

144 35.143 -76.769 999 ISA-03-NF50 

145 36.308 -76.213 1.3 Floyd-0003 

146 36.308 -76.213 1.4 Floyd-0004 

147 36.280 -76.189 1.8 Floyd-0005 

148 36.266 -76.175 1.9 Floyd-0006 

149 36.242 -76.135 1.7 Floyd-0007 

150 36.297 -76.221 1.2 ISA-03-0005 

151 36.308 -76.212 1.0 ISA-03-0006 

152 36.287 -76.203 1.5 ISA-03-0007 

153 36.280 -76.189 1.3 ISA-03-0008 

154 36.267 -76.176 1.2 ISA-03-0009 

155 36.267 -76.176 1.6 ISA-03-0010 

156 36.242 -76.135 1.6 ISA-03-0011 

157 36.261 -76.149 999 ISA-03-NF51 

158 36.142 -76.342 1.4 ISA-03-0012 
76 

159 36.147 -76.380 2.0 ISA-03-0013 

160 36.188 -76.432 2.7 ISA-03-0014 

161 36.200 -76.464 2.0 ISA-03-0015 

162 36.191 -76.468 1.7 ISA-03-0016 

163 36.183 -76.466 2.1 ISA-03-0017 

164 36.163 -76.437 2.1 ISA-03-0018 

165 36.152 -76.414 2.2 ISA-03-0019 

166 35.942 -76.349 1.3 ISA-03-1219 
77 

APPENDIX B. HYDRODYNAMIC MODEL PARAMETERS 

B.1. Wind Stress 

The wind speeds provided by meteorological models are used to generate wind stress conditions 

in the ADCIRC model (Luettich and Westerink, 2004). In order to correlate wind speed to wind 

stress, ADCIRC employs the following formulation, 

sx Cd  air W Wx   , 

sy Cd  air W Wy   , 

where  air is air density, Cd is frictional drag coefficient defined   3 0.75 0.067 10  W  as 

developed by Garrett (1977), W is the magnitude of wind velocity and Wx and Wy are 

components of wind velocity in the x and y direction. All wind velocities are taken at the 10 m 

height above the mean water level. 

B.2. Atmospheric Pressure Gradient 

The ADCIRC model converts a pressure gradient to an equivalent water column height through 

the transformation p g  w / , where p is the pressure gradient,  w is density of sea water, and g

is acceleration due to gravity. 

B.3. ADCIRC Input File (fort.15) 

A typical model control file for the hurricane simulations is presented below. Further details on 

model parameter settings can be found within this abbreviated file. 

Basin-Scale CFM: 14-day Run ! 32 CHARACTER ALPHANUMERIC RUN DESCRIPTION 

V47.22 ! 24 CHARACTER ALPHANUMERIC RUN IDENTIFICATION 

1 ! NFOVER - NONFATAL ERROR OVERRIDE OPTION 

1 ! NABOUT - ABREVIATED OUTPUT OPTION PARAMETER 

1 ! NSCREEN - OUTPUT TO UNIT 6 PARAMETER 

0 ! IHOT - HOT START OPTION PARAMETER 

2 ! ICS - COORDINATE SYSTEM OPTION PARAMETER 

0 ! IM - MODEL RUN TYPE: 0=2DDI, 1=3DL(VS), 2=3DL(DSS) 

2 ! NOLIBF - NONLINEAR BOTTOM FRICTION OPTION 

2 ! NOLIFA - OPTION TO INCLUDE FINITE AMPLITUDE TERMS 

1 ! NOLICA - OPTION TO INCLUDE CONVECTIVE ACCELERA 

1 ! NOLICAT - OPTION TO CONSIDER TIME DERIVATIVE 

0 ! NWP - VARIABLE BOTTOM FRICTION AND LATERAL VISCO 

1 ! NCOR - VARIABLE CORIOLIS IN SPACE OPTION 

1 ! NTIP - TIDAL POTENTIAL OPTION PARAMETER 

-5 ! NWS - WIND STRESS AND BAROMETRIC PRESSURE OPTION 

1 ! NRAMP - RAMP FUNCTION OPTION 

9.81000 ! G - ACCELERATION DUE TO GRAVITY - DETERMINES 

-3 ! TAU0 - WEIGHTING FACTOR IN GWCE 
78 

0.005 0.2 ! TAU0FULLDOMAINMIN, TAU0FULLDOMAINMAX 

2.00000 ! DT - TIME STEP (IN SECONDS) 

0.00000 ! STATIM - STARTING SIMULATION TIME IN DAYS 

0.00000 ! REFTIME - REFERENCE TIME (IN DAYS) 

3600 ! WTIMINC - METEOROLOGICAL WIND TIME INTERVAL 

14.00000 ! RNDAY - TOTAL LENGTH OF SIMULATION (IN DAYS) 

4.00000 ! DRAMP - DURATION OF RAMP FUNCTION (IN DAYS) 

0.350000 0.300000 0.350000 ! TIME WEIGHTING FACTORS FOR THE GWCE EQUATION 

0.010000 0 0 0.010000 ! H0, NODEDRYMIN, NODEWETMIN, VELMIN - MINIMUM 

-79.000000 35.000000 ! SLAM0, SFEA0 - LONGITUDE AND LATITUDE 

0.002500 1.00 10.00 0.333330 ! FFACTORMIN, HBREAK, FTHETA, FGAMMA - BOTTOM FRIC 

5.000000 ! EVM - SPATIALLY CONSTANT HORIZONTAL EDDY VISCO 

0.000000 ! CORI - CONSTANT CORIOLIS COEFFICIENT 

5 ! NTIF - NUMBER OF TIDAL POTENTIAL CONSTITUENTS 

K1 ! TIPOTAG - NAME OF TIDAL POTENTIAL CONSTITUENT 

0.14156500 0.000072921158358 0.736 1.077 249.170 ! TPK, AMIGT, ETRF, FFT, FACET - CONST 

O1 ! TIPOTAG - NAME OF TIDAL POTENTIAL CONSTITUENT 

0.10051400 0.000067597744151 0.695 1.125 215.130 ! TPK, AMIGT, ETRF, FFT, FACET - CONST 

M2 ! TIPOTAG - NAME OF TIDAL POTENTIAL CONSTITUENT 

0.24233400 0.000140518902509 0.693 0.978 101.610 ! TPK, AMIGT, ETRF, FFT, FACET - CONST 

S2 ! TIPOTAG - NAME OF TIDAL POTENTIAL CONSTITUENT 

0.11284100 0.000145444104333 0.693 1.000 0.000 ! TPK, AMIGT, ETRF, FFT, FACET - CONST 

N2 ! TIPOTAG - NAME OF TIDAL POTENTIAL CONSTITUENT 

0.04639800 0.000137879699487 0.693 0.979 40.750 ! TPK, AMIGT, ETRF, FFT, FACET - CONST 

5 ! NBFR - NUMBER OF PERIODIC FORCING FREQUENCIES 

K1 ! BOUNTAG - FORCING CONSTITUENT NAME 

0.000072921158358 1.077 249.170 

O1 ! BOUNTAG - FORCING CONSTITUENT NAME 

0.000067597744151 1.125 215.130 

M2 ! BOUNTAG - FORCING CONSTITUENT NAME 

0.000140518902509 0.978 101.610 

S2 ! BOUNTAG - FORCING CONSTITUENT NAME 

0.000145444104333 1.000 0.000 

N2 ! BOUNTAG - FORCING CONSTITUENT NAME 

0.000137879699487 0.979 40.750 

K1 ! EALPHA - FORCING CONSTITUENT NAME AGAIN 

0.095800 241.020 ! EMO, EFA 

0.095800 241.020 ! EMO, EFA 



This portion of the input has been eliminated 



0.087300 85.720 ! EMO, EFA 

0.087300 85.720 ! EMO, EFA 

O1 ! EALPHA - FORCING CONSTITUENT NAME AGAIN 

0.081900 230.730 ! EMO, EFA 

0.081900 230.730 ! EMO, EFA 



This portion of the input has been eliminated 



0.061000 331.610 ! EMO, EFA 

0.061000 331.610 ! EMO, EFA 

M2 ! EALPHA - FORCING CONSTITUENT NAME AGAIN 

0.461400 220.790 ! EMO, EFA 

0.461400 220.790 ! EMO, EFA 



This portion of the input has been eliminated 
79 



0.502300 345.330 ! EMO, EFA 

0.502300 345.330 ! EMO, EFA 

S2 ! EALPHA - FORCING CONSTITUENT NAME AGAIN 

0.162700 267.410 ! EMO, EFA 

0.162700 267.410 ! EMO, EFA 



This portion of the input has been eliminated 



0.136100 17.760 ! EMO, EFA 

0.136100 17.760 ! EMO, EFA 

N2 ! EALPHA - FORCING CONSTITUENT NAME AGAIN 

0.100300 196.500 ! EMO, EFA 

0.100300 196.500 ! EMO, EFA 



This portion of the input has been eliminated 



0.117200 323.680 ! EMO, EFA 

0.117200 323.680 ! EMO, EFA 

110 ! ANGINN - MINIMUM ANGLE FOR TANGENTIAL FLOW 

-1 0.000000 14.000000 180 ! NOUTE, TOUTSE, TOUTFE, NSPOOLE - FORT 61 OPTIONS 

170 ! NSTAE - NUMBER OF ELEVATION RECORDING STATIONS, 

-75.739410 36.183532 ! 8651370 Duck, FRF, Pier, NC 

-75.551568 35.790577 ! 8652587 Oregon Inlet Marine, Pamlico Sound, NC 

-75.634436 35.215867 ! 8654400 Cape Hatteras Fishing Pier, NC 

-76.670699 34.719819 ! 8656483 Beaufort Duke Marine Lab, NC 

-76.614700 35.534300 ! 5.60 FEMA CHWMs 

-76.609800 35.537400 ! 5.50 FEMA CHWMs 



This portion of the input has been eliminated 



-76.414300 36.151500 ! 7.20 FEMA CHWMs 

-76.349200 35.941700 ! 4.20 FEMA CHWMs 

0 0.000000 20.000000 180 ! NOUTV, TOUTSV, TOUTFV, NSPOOLV - FORT 62 OPTIONS 

0 ! NSTAV - NUMBER OF ELEVATION RECORDING STATIONS, -1 

0.000000 14.000000 300 ! NOUTM, TOUTSM, TOUTFM, NSPOOLM - METEOROLOCIAL 

5 ! NSTAM - NUMBER OF ELEVATION RECORDING STATIONS, 

-75.750000 36.180000 ! DUCN7 

-74.840000 36.610000 ! 44014 

-72.660000 34.680000 ! 41001 

-76.520000 34.620000 ! CLKN7 

-75.350000 32.310000 ! 41002 

-1 9.000000 14.000000 1800 ! NOUTGE, TOUTSGE, TOUTFGE, NSPOOLGE - (UNIT 63) 

-1 9.000000 14.000000 1800 ! NOUTGV, TOUTSGV, TOUTFGV, NSPOOLGV - (UNIT 64) 

-1 9.000000 14.000000 1800 ! NOUTGM,TOUTSGM,TOUTFGM,NSPOOLGM - (UNIT 73/74) 

0 ! NHARF - NUMBER OF FREQENCIES IN HARMONIC ANA 

0.000000 0.000000 0 0.000000 ! THAS,THAF,NHAINC,FMV - HARMONIC ANALYSIS PARA 

0 0 0 0 ! NHASE,NHASV,NHAGE,NHAGV - UNITS 51,52,53,54 

0 8640 ! NHSTAR,NHSINC - HOT START FILE GENERATION PARA 

1 0 0.000001 25 ! ITITER, ISLDIA, CONVCR, ITMAX - ALGEBRAIC SOLUTION