© 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

The need for a coastal estuary/inland flood risk damage potential index

L. J. Pietrafesa, L. Xie, E. Buckley, D. Hildebrand, M, C. Peng &D, Dickey College of Physical & Mathematical Sciences, North Carolina State University, United States

Abstract

The present tropical cyclone intensity scale is based on wind-damage potential, which is derived from a wind-engineering approach. The damage potential to fixed structures at different wind speeds and wind energy were analyzed and used to assign the intensity of tropical cyclones. On the offshore side of coastlines, because wind intensity, to a large extent, does determine the magnitude of storm surge, wind speed implicitly reflects the damage potential due to storm surge and offshore, coastal flooding. However, in estuary and inland regions, the damage due to tropical cyclones often results from a combination of wind and flooding damage. Generally after making landfall, a ‘tropical cyclone’s damage potential due to wind normally decreases but its’ damage potential due to flooding normally increases. However, the latter effect is not represented by the widely used and brilliantly conceived Saffir-Simpson tropical cyclone scale. The damage to North Carolina incurred during the passage of tropical cyclones over a 75 year period, 1925-1999 show that

Saffir/Simpson scale Categories 1, 2 and 3 hurricanes have accounted for 7’7% of the damage and these events have also tended to be very wet. Further, we find that in general, extreme rainfall events appear to have only a weak relationship to the Saffu-Simpson damage potential scale of tropical cyclones. So we are confronted with a dilemma. Much damage due to hurricanes striking North Carolina can be attributed to flooding, yet flooding is only weakly tied to the wind intensity scale. Moreover, the flood forecasts presently being generated and used by the government are based on outdated and incomplete physical and mathematical models, So presently, flood forecast information is not readily available, is not accurate, is unreliable, and cannot be easily communicated or © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

562 Risk Analysis III

understood. These shortcomings translate to a threat to life and property. As a consequence, this paper suggests that a flood potential damage risk index based on complete physics using the state of the science numerical model is needed. Further, it suggests that while the physical observations required and the mathematical architecture needed for a flood index are more complicated than that of the well regarded wind intensity scale, it must be complimentary to the wind scale and it must be capable of being easily communicated and understood. The physical basis is established and the mathematical architecture is proposed in the paper.

Introduction

Tropical cyclones have caused significant property damage and loss of life to North Carolina (NC), a state located on the central southeast coast of the United States. In Figure 1, an advanced very high-resolution radiometer sea surface satellite image, NC is to the right of the “U” in NCSU and the left of the western boundary current, the Gulf Stream. The damage incurred by these tropical storms has not been limited to NC’s vulnerable coastline but has extended throughout the entire state and has been due to high winds and flooding. But what are tropical cyclones? The term Tropical Cyclone (TC) has been defined as a cyclone that originates over the tropical oceans and includes hurricanes, tropical storms, tropical depressions, and tropical disturbances (Rittuschke, 1959). According to the Saffir/Simpson classification scheme or scale, TCS with winds between 29- 37nis are Category 1s (Cat 1s), 37-43 m/s are Cat 2s, 43-51rn/s are Cat 3s, 51- 60rnls are Cat 4s and > 60m/s are Cat 5s. In this study, we assess the damage incurred by storms of a tropical storm origin, including extra-tropical storms that were once classified as tropical cyclones, specifically as they have caused damage in North Carolina (NC). Since 1996, Hurricanes Bertha (1996), Fran (1996), Bonnie (1998), and Floyd (1999), along with Hurricane turned Tropical Storm Dennis (1999) and Tropical Depression Danny (1997) have devastated NC with damage totaling over $12 billion. The inland flooding attributed to Floyd (actually due to Dennis and Floyd, Pietrafesa et al,, 2001) in September of 1999, has been regarded as the worst flooding in the state’s history. And, 56 human lives were lost during Floyd’s passage, Previous studies on tropical cyclone damage assessments have focused on the United States in general and not on individual states (Pielke and Landsea, 1998; ‘Pielke and Landsea, 1999). Moreover, previous studies have assessed the level and amount of damage in terms of the Saffir/Simpson TC scale. This paper looks at the damage incurred in NC and raises the question of whether or not there is a need for more detailed damage assessments to determine whether the damage is truly proportional to wind intensity or whether flooding also contributes in a significant way. This study liberally relies on the considerations of co-operative ongoing work by the co-authors of this paper. These works include a Master of Science degree thesis (at North Carolina State University) focusing on damage assessment (Hildebrand, expected in 2002), a PhD doctoral dissertation (at North © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

Risk Analysis III 563 Carolina State University) dealing with coupled coastal and estuary flooding and inundation (Peng, expected in 2002), and the flooding due to Dennis and Floyd reported on by Pietrafesa et al. (2001a). Damage data from 98 TCS that have impacted North Carolina from 1925-1999 were used in this study, Damage data prior to 1925 were deemed unreliable due to incomplete data sets, Impacts included damages directly attributable to the storm as defined by Changnon (1996), rainfall-induced flooding, high wind, tornado, storm surge, and beach erosion damage. Loss of life was included as an impact but a dollar amount was not attempted. A human loss factor needs to be included to determine the true economic impact but is beyond present study scope.

North Carolina Tropical Cyclone History

North Carolina ranks 2“d to Florida as the most exposed state to TC activity along the US eastern seaboard (cf. Figure 1 for the NC setting). NC is extremely vulnerable because its’ coastline protrudes eastward into the Atlantic Ocean and during the late summer and fall, TCS are often carried northward on the continental side of the clockwise rotating Azores Bermuda (atmospheric) High pressure system (Weisberg and Pietrafesa, 1983). Furthermore, the warm water body, the Gulf Stream is located offshore of NC, and can refuel TCS (Bright et al, 200 1). Also, TCS sometime interact with mid-latitude weather systems and become severe flooding events. Examples include Floyd (1999), David (1979), and Agnes (1972).

Figure 1. The coastal study area of NC as seen in an AVHRR SST image. The Pamlico-Albemarle Sound systemj a coastal lagoon, and the Gulf Stream are visible. NC is to the right of the “U” in NCSU and to the left of the Gulf Stream.

The National Oceanic and Atmospheric Administration’s (NOAA) TC database warehoused at the National Climatic Data Center was the source of information (NCDC, 2001) used in this study. Over the period 1900 to 1999, there have been a total of 120 TCS that have impacted the state of NC, including 49 hurricanes, 41 tropical storms, 22 tropical depressions, and 8 extra-tropical storms. Based on the tracks of these storms, 37 made direct landfall along the NC © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

5fj4 Risk Analysis III

coast, 10 had a close encounter with the coast, 27 remained offshore, and 46 made landfall to the south of NC, before passing over the state. It is worth noting that the eyes of TCS do not have to hit land directly to cause serious damage. All that is required is a close encounter (Pietrafesa et al,, 1997), Figure 2 shows the annual number of hurricanes, tropical storms, and tropical depressions that have impacted North Carolina from 1900-1999. The most active TC periods were the mid 1940’s, mid 1950’s, and late 1990’s. The most intense hurricane was Hurricane Hazel in 1954, a Category 4 hurricane that made landfall just north of the southernmost NC border. The least active periods were from 1917 to 1943 and 1965 to 1983, Xie et al. (2002) have conducted an anatomy of the overall time series of TCS which have struck NC.

Damage Trends

In terms of the value of time based monetary currency or “unadjusted” dollars, there have been but four billion-dollar hurricane disasters in NC. The first one was Hurricane Hugo, which struck the coast just north of Charleston, SC, in 1989 before lashing the Charlotte, NC metropolitan area with hurricane force winds. Since then, Hurricanes Fran (1996), Bonnie (1998), and Floyd (1999) have all individually been at or above the 5 billion-dollar mark. A time series of annual TC damage shows a large increase since 1989 (Figure 3), In fact, it appears from the unadjusted values of NC’s TC damage that the past decade has been unprecedented. However, to accurately compare damage totals from year- to-year, measures of currency need to be adjusted to one standard value for a specific year of reference. We choose 1996 following Hildebrand’s (2002) thesis work, which in turn was based on the method of PieIke and Landsea (1998) who utilized three factors, population, housing and wealth, and inflation. The computation is: damage value times an inflation factor times population times a wealth factor. The 1‘t point to note is that dollar values are adjusted according to their yearly purchasing power and 1996 is used as our standard year. A 2nd point is population increase and Figure 4 clearly illustrates the need for a population growth factor. From 1900-1999, the coastal population has grown by -320% and appears to be increasing exponentially, More people imply more property at risk. The increase in coastal housing and the value of housing has been even more dramatic, with an -3 10% increase over the past 50 years. The 3’d point is total value increase, i.e. wealth, which is determined by the “fixed reproducible tangible wealth”, This economic statistic, kept by the Bureau of Economic Analysis (1993), accounts for the trend that Americans have more wealth than in the past (bigger houses, more expensive cars, etc.). © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

Risk Analysis III 565

Figure2. Tropical Cyclones impacting North Carolina from 1900-1999 (source NCDC, 2001),

Amual North Carolina Tropical CycloIIe Damage (Unadju@ed) 1925.1999 $107 $653B $6,08B 1000 .

Soo

800

700- g

s 600 -

E ~ 600.

& I

g 400 I m 300.

2W -. 1

400 . 1

0. 1 1, 1, In J-

~g];$g~g$g$ ~~gg

Year

Figure 3, Annual NC TC damage estimates from 1925 to 2001, Damage data in units of the value at the time of occurrence, Data from NOAA National Climatic Data Center (NCDC, 2001).

The method introduced by Pielke and Landsea (1998) is the basis for the normalization method used in this study. However, Hildebrand (2002) introduced some key differences in his reformulation of their equation. The method used to determine normalized damage totals used in this study is: NL96 ‘= Ly x Iy x Wy x Py, where, NL96 = normalized loss to the 1996 value. The inflation factor takes into account y = year of storm’s impact, Ly = storm’s damage (unadjusted), Iy = inflation factor based on 1996 Consumer Price Index to that of year y, Wy = wealth factor based 1996 fixed reproducible tangible wealth expressed, as per capita (state) to that of year y, Py = population factor, based on the change in population from year y to 1996. Population figures include only those residents who live in areas most affected by a storm. By way of example, using the general formula on Hurricane Hazel, which struck NC in 1954, gives the following, L1954= $254,000,000, 11954= 5.89, W1954 = 1.96, © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

566 Risk Analysis III

and P 1954= 1.688, So, the Normalized Total Damage becomes, NL96 = $4,930M. Compare this figure to the estimate of the time of $254M. It should also be noted that the Consumer Price Index (CPI) is used in Hildebrand’s and this study instead of the implicit price deflator used by Pielke and Landsea for the gross national product. The CPI is widely held as the most accurate measure of inflation, The weights of the components are based on consumer spending patterns. Using the above adjustments, the time-series of normalized annual North Carolina TC damage totals shows a very different trend (cf. Figure 5) compared to the unadjusted trend (cf. Figure 3). Figure 5 shows the damage totals of the 1990’s are not unprecedented, This is not to say the damage trend is not alarming. Over $12 billion in damage have occurred from 1996-1999 from only 4 TCS. The active hurricane period of the mid 1950’s caused over $8 billion in (adjusted) damage. By comparing Figures 3 to 5, it is clear that NC has experienced two significant periods of TC damage, the mid 1950’s and late 1990’s. In between these periods, there was relative calm, Only 4 TCS provided significant damages to NC during the period of 1956-1995. In those forty years, only hurricanes Helene (1958), Donna (1960), and Diana (1984), and Hugo (1989) caused significant damage, Not coincidentally, greater coastal construction and population growth occurred during the 1960’s through the 1990’s. During the period 1950-1990, the number of housing units tripled, North Carolina Coastal Population (1990.1999)

Soo,mo~ ,,, .,, ,,,

Soo,ooo t 700,0W

300,000

200 ,PQo

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0

Figure 4, NC coastal population from 1900-1999 (source Hildebrand, 2002),

Interpretation of damage

Pielke and Landsea (1998) concluded that the majority of tropical cyclone damage (over 83Yo) in the United States was caused by major hurricanes (Saffir- Simpson Categories 3,4, and 5). However, major hurricanes do not account for nearly as much damage in North Carolina as the statistics show for the United States. Table 1 lists the top ten most damaging NC TCS, Only 3 of the 10 (30%) are classified as “major” hurricanes. A large part of North Carolina damages can be attributed to coastal and inland flooding from weaker hurricanes and tropical storms. Table 2 gives the damage statistics fi-om all direct land-falling TCS in © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

Risk Analysis III 567 NC, Florida and Texas since 1925. For NC, Category 3 and 2 hurricanes have

caused the most damage, accounting for 47 ‘%0 and 26Y0, respectively of NC TC total damage, If we combine the “major” hurricane categories, these together account for 69°/0 of the total damage, However if we combine the lower three

Figure 5. Annual NC TC damage from 1925-1999 normalized to 1996 values using the method of Hildebrand (2002).

Table 1 Rank TC Name Year Intensity Normalized Damage

1 Dennis/ Floyd 1999 Cat 2 $5.292B 2 Fran 1996 Cat 3 $5.200B 3 Hazel 1954 Cat 4 $4.563B 4 Ione 1955 Cat 2 $1.706B 5 Hugo 1989 Tropical Storm $1.660B 6 Connie/Diane 1955 Cat 1 $1.560B 17 Donna 1960 Cat 2 $1.045B 8 Bonnie 1998 Cat 3 $0.825B 9 Bertha 1996 Cat 2 $0.816B 10 Hurricane 13 1933 Cat 2 $0.443B

Note: Hugo was a Cat 4 at landfall in Charleston, SC but was downgraded to a Tropical Storm when it struck Charlotte, NC, ‘Connie and Diane struck 5 days apart and Dennis and Floyd struck 10 days apart, © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

568 Risk Analysis III Table 2

STATE Cat % Frequency of Occurrence %Damage/Cat % Damage/Storm NC 1 28.0 4.55 0.65 2 24.0 25.67 4.28 3 44.0 47.06 4.28 4 4,2 22.27 22.27 5 0.0 0.00 0.0 FL 1 36.7 3.05 2.04 2 24.5 4.64 2.04

4 10.2 68.46 13.69 5 2.0 0.43 0.43 TX 1 50.0 6.22 0.44 2 10.7 8.48 2.83 3 16.3 54.64 6.83 4 10.7 30.67 10.22 5 0.0 0.00 0.0

categories, we find that they account for TT~o of the total damage. In fact Category 2 and 3 together account for 73% alone, significantly different than the 83’%.for the entire country found by Pielke and Landsea (1998), For Florida and Texas, the “major” TC categories account for 92~0 and 85?Z0of the respective damage. Remarkably, the collective average over the three states for darnage done by major category TCS was 82%, very close to the national statistic. Albeit, the risk assessment for NC is clear. NC has had a greater risk and damage potential from Cat 2 and 3 hurricanes than from the two major categories. This can be explained by the fact that Cat 2 and 3 hurricanes are destructive, by both wind and flooding potential, and because they have occurred more frequently in comparison to the more major hurricanes. It should be noted however, that on an individual storm basis, major hurricanes (Cat 4) still cause the greatest damage, Still, the record amount of precipitation and the subsequent flooding damage from the combined effects of Hurricane Floyd ( a weakening Cat 2) and Tropical Storm Dennis (a Cat 1 off the coast) were both the greatest in NC history. Figure 6 illustrates the weak correlation between the intensity of tropical cyclones and maximum rainfall. Based on 27 direct NC land-falling TCS, the average maximum rainfall is greatest for Cat 2 hurricanes. The six greatest rainfall events were Cat 2 or weaker, Clearly, there are many factors other than intensity that determines rainfall totals from tropical cyclones. This is currently an active area of research for tropical cyclones (Marks et al, 1998). Adding to the complicated issue, some tropical cyclones have paired up, like Connie and Diane in 1955 and Dennis and Floyd in 1999, leading to some unusually devastating outcomes. For example, Tropical Storm Dennis (originally a Cat 1) inundated the eastern half of North Carolina with rain and mechanically drove an enormous amount of coastal ocean water into Parnlico Sound, a large shallow coastal lagoon, only 10 days before Hurricane Floyd struck the same area, (Pietrafesa et al, 2001), As Parnlico Sound was relieving itself of the excess water derived from precipitation and coastal inundation, through tlmee narrow © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

Risk Analysis III 569 barrier island inlets (really outlets), along came Floyd. The rains fi-om both storms and the additional 40°/0 of water still present in Pamlico Sound resulted in unparalleled estuary/inland flooding, Drowning took 56 human lives. What kind of damage would Floyd have had if Dennis never existed? Much less according to Pietrafesa et al (2001a). Could the damage due to the combined effects of Dennis and Floyd been anticipated with the existing wind intensity risk potential damage index? The obvious answer is “no” on both accounts. Moreover, do present flooding models properly estimate the amount of flooding which can occur during the passage of a TC? Again the answer is “no”. In late August, 1993, Hurricane Emily, a Cat 2, followed the path shown in Figure 7a, Her eye never made landfall but she did incur significant coastal and estuary flooding (Pietrafesa et al., 1997). In one area of Pamlico Sound she created a 3 ,3m storm surge. In Figure 7b, the lateral area of the sound system which was flooded during the passage of Emily is estimated by three models. The 1st is the presently used government model (the dotted line) which estimates that an area of 70 kmz will be laterally inundated by the storm, The other estimates of predicted lateral flooding are based on the model developed by Xie and Pietrafesa (1999) and advanced by Peng in his dissertation, It not only allows for interaction between coastal and estuary waters via a direct connection through the inlets and it also conserves water; which no other model presently does. The output from this model (dashed and solid lines) show a very different outcome to the potential flooding associated with this non land-falling Category 2 TC. The 160 kmz for the filly coupled, mass conserving result (the solid line in Figure 7b) is significantly different, in fact -230% more, than what was predicted, This result was confirmed (Pietrafesa et al., 1997). Again, the notion of wind intensity being the controlling factor is not entirely accurate nor adequate, However, the overriding issue here is one of safety, A 240% underestimate of lateral flooding potential in a coastal region by a non-major category TC which did not make landfall gives pause for reflection.

Conclusions

The damage incurred by tropical cyclone winds and rainfall and the subsequent flooding have become increasingly important in the US in general. Additionally, at the local level, Hurricane Floyd (1999) in North Carolina, Irene (1999) in Florida, Mitch (1998) in Central America, and Tropical Storm Allison (2001) in Texas have all highlighted the dangers of inland flooding to life and property. These events speak to the need for a new “risk” hurricane scale that parallels the Saffu/Simpson intensity scale. This new “risk” scale should be temporally and spatially dependent and useful to emergency management officials, the public, and the media to portray all the inherent risks of a particular tropical storm about to make landfall, For example, Hurricane Floyd, a weakening category 2 hurricane at landfall, would have been a Category 4 or 5 risk hurricane due to the potential for record rainfall and subsequent flooding, especially as the conditions were favorable for flooding after Tropical Storm Dennis hit, Any better way to inform the public of the dangers of a particular storm would help save lives and property. © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

57(I Risk Analysis III

What is required? What should or could the components of a Flood Risk Index scale that is comprehensive, easily communicated and consistent with the physical phenomena and effects. The Saffir/Simpson scale is based on one key parameter, wind speed, and this is a well understood parameter. However, as has been shown in this paper, TC damage potential in coastal-estuary-inland areas cannot be adequately represented by a wind scale alone. A Flood Risk Index would contain the same architectural components but would have to be locally and phenomenologically based and be consistent with the Saffu/Simpson scale,

As one walks through the physical-mathematical architecture of flooding processes, it is clear that an area specific atmosphere-coast-estuary-river-basin coupled model must be in place, It should be based on the time and space history of wind and precipitation events by amount, duration and watershed, and on subsequent river discharge and flooding outcomes, The model must include vegetation, soil and terrain characteristics of individual watersheds, as lateral boundary conditions and water must be conserved, i.e. accounted for because of natural and human induced phase lags for water to be withdrawn from and then to be reintroduced into the system. This is not an insignificant challenge.

Mz&tumfi&llw, T~Intemsity

1 —Average Maximum 1 Rainfall

Figure 6, Observed precipitation versus wind intensity from 27 TCS making landfall on the NC coast. (Source NCDC, 2001). © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

Risk Analysis III 571

,L_l._22

Figure. 7. Hurricane Emily (Category 2). (a) Path of TC “eye”, (b) Predicted lateral flooding following non-conservative model (dotted line), non-coupled but water conserved model (solid line) and coupled and conserved model (dashed line). (Source Peng, 2002) Acknowledgements

The authors appreciate the research support for this study under National Oceanic & Atmospheric Administration Grant #NA060C0373-O0 1 through the Charleston NOAA Coastal Services Center to The Waterstone Group, Inc. and North Carolina State University, Jim Epps contributed significantly in figure preparation and along with Michele Kephart assisted in the document formatting. References [1] Rittuschke,: Glossary of Meteorolo~. Boston, MA: American Meteorological Society, 638 pp., 1959, [2] Pietrafesa, LJ,, Xie, L,, Dickey, D,, Keeter, K,, Harried, S,, Coastal and inland Flooding Due to Hurricanes Floyd and Dennis. Pps. in Facing Our future; Hurricane Floyd and recovery in the Coastal Plain, Ed, J, Maiolo, J. Whitehead, M. McGee, L, King, J. Johnston, H, Stone. Coastal Carolina Press, 2001a. [3] Pielke Jr., R. L., and Landsea, C.W,, Normalized hurricane damages in the United States: 1925-95, Wea. Forecasting, 12,621-631, 1998. © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email [email protected] Paper from: Risk Analysis III, CA Brebbia (Editor). ISBN 1-85312-915-1

572 Risk Analysis III

[4] Pielke Jr., R,L. and Landsea, C.W,, La Nina, El Nine, and Atlantic hurricane damages in the United States. Bull. Amer. Meteor. Sot., 80,2027-2033, 1999. [5] Hildebrand, D., Damagepotential of Tropical Cyclones in North Carolina. Master of Science Degree Thesis. North Carolina State University, 2002. [6] Peng, M,C. Coupled coastal ocean-estuary modeling with inundation and retreat in the Albemarle-Pamlico Sound system. PhD Dissertation. North Carolina State University, 2002, [7] Changon, S.A. The Great Flood of 1993: Causes, Impacts, and Responses. Westview Press, 319 pp., 1996, [8] Weisberg, R.H. and Pietrafesa, L.J., Kinematics and correlation of the surface wind field in the South Atlantic Bight, Jour. Geophys. Res., 17, 4, 455-469, 1983. [9] Bright, R., Intens@cation of tropical Cyclones by the Gu~Stream. Master of Science Degree Thesis at North Carolina State University, 2002. [10] National Climate Data Center,: Hurricane damage estimates: accessed August, 2001, at http:llwww,ncdc. noaa.govl, 2001 [11] Pietrafesa, L.J., Xie, L., Morrison, J,M., Janowitz, G. S., Pellissier, J., Keeter, K., and Neuherz, R., Numerical modeling of storm surge in and around the Pamlico-Albemarle sound system during Hurricane Emily, August, 1993, Mausam, 48,4, 567-578 pages, 1997. [12] Xie L., Pietrafesa, L. J., Wu, K, J., The climatology of landfalling tropical cyclones in North Carolina. (Chapter). Coastal Hazards, In press, 2002. [13] Bureau of Economic Analysis,: Fixed Reproducible Tangible Wealth in the United States, 1925-1989, January, US GPO: Washington, D, C., 1993. [14] Marks, F. L,, Shay, L., Barnes, G.j Black, P,, DeMaria, M,, McCaul, B., Molininari, J., Powell, M,, Smith, J., Tuleya, B,, Tripoli, G., Xie, L., and Zehr, R,, Landfalling tropical cyclones: forecast problems and associated research opportunities. Bull. Amer. Met. Sot., 79, 305-318, 1998, [15] Pietrafesa, L. J., Xie, L. and Dickey, D., Coastal and Inland Flooding : Potential and Reali@ and the Strategy for Prognostication. North Carolina State University Technical Report, 200 lb. [16] Xie, L. and Pietrafesa, L,J., System wide modeling I the Albemarle-Pamlico sound system. Jour. Coastal Res., 15,4,1163-1177, 1999,