1342 WEATHER AND FORECASTING VOLUME 25

Modeling Extreme Rainfall, Winds, and Surge from (2003)

NING LIN,JAMES A. SMITH, AND GABRIELE VILLARINI Department of Civil and Environmental Engineering, Princeton University, Princeton,

TIMOTHY P. MARCHOK NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

MARY LYNN BAECK Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey

(Manuscript received 25 August 2009, in final form 19 May 2010)

ABSTRACT

Landfalling tropical cyclones present major hazards for the eastern United States. Hurricane Isabel (September 2003) produced more than $3.3 billion in damages from wind, inland riverine flooding, and flooding, and resulted in 17 fatalities. Case study analyses of Hurricane Isabel are carried out to investigate multiple hazards from landfalling tropical cyclones. The analyses focus on storm evolution following landfall and center on simulations using the Weather Research and Forecasting Model (WRF). WRF simulations are coupled with the 2D, depth-averaged hydrodynamic Advanced Circulation Model (ADCIRC), to examine storm surge in the . Analyses of heavy rainfall and flooding include an examination of the structure and evolution of extreme rainfall over land. Intercomparisons of simulated rainfall from WRF with Hydro-NEXRAD rainfall fields and ob- servations from rain gauge networks are presented. A particular focus of these analyses is the evolving distribution of rainfall, relative to the center of circulation, as the storm moves over land. Similar analyses are carried out for the wind field of Hurricane Isabel as it moves over the mid-Atlantic region. Outer , which are not well captured in WRF simulations, played a major role in urban flooding and wind damage, especially for the metropolitan region. Wind maxima in outer rainbands may also have played a role in storm surge flooding in the upper Chesapeake Bay.

1. Introduction Isabel produced heavy rainfall and flooding in the cen- tral Appalachian mountain region along the track of the In this study we examine multiple hazards from land- storm. Interaction of the circulation with falling tropical cyclones through case study analyses of the complex terrain of the central Appalachians played an Hurricane Isabel, which made landfall in the important role in flooding from Isabel and, more gen- of on 18 September 2003 as a category 2 erally, in the flood hydrology of the central Appalachians hurricane (Lawrence et al. 2005). Hurricane Isabel was (see Sturdevant-Rees et al. 2001; Atallah and Bosart directly responsible for 17 fatalities, of which 10 were due 2003; Hart and Evans 2001; Villarini and Smith 2010). to drowning and 7 were due to falling trees. The storm Extreme short-term rainfall rates from outer rainbands caused extensive property damage from riverine flood- are important flood agents in urban watersheds of the ing, storm surge flooding, and wind. The economic losses eastern United States (Bailey et al. 1975). exceeded $3.3 billion, and approximately 6 million cus- Wind damage from Hurricane Isabel extended far in- tomers were affected by power outages (NOAA 2004). land from the point of landfall. Damages were largely due to falling trees and power outages in the major urban areas of the mid-Atlantic (NOAA 2004). Wind damage Corresponding author address: James A. Smith, Dept. of Civil and Environmental Engineering, Princeton University, Princeton, was attributed partially to the wet antecedent soil mois- NJ 08544. ture during the period preceding the storm and drought E-mail: [email protected] conditions in preceding seasons, which weakened the tree

DOI: 10.1175/2010WAF2222349.1

Ó 2010 American Meteorological Society Unauthenticated | Downloaded 10/04/21 05:44 AM UTC OCTOBER 2010 L I N E T A L . 1343 stock (NOAA 2004). Wind damage was not restricted to The Weather Research and Forecasting Model (WRF) the region close to the track of the storm, but was also has been widely applied to assess weather hazards asso- associated with secondary wind maxima in hurricane ciated with heavy rainfall and extreme winds (e.g., Done rainbands. Wind damage is an important component of et al. 2004). In this study, simulations using the WRF the multiple hazards of tropical cyclones in the north- model are applied to examine multiple hazards induced eastern United States. by Hurricane Isabel: heavy rainfall, extreme wind, and Isabel produced record wave and surge conditions near severe storm surge. Radar rainfall fields from the Hydro- the Outer Banks of North Carolina. A significant wave Next-Generation Doppler Radar (Hydro-NEXRAD) height of 8.1 m, a record for 27 yr of monitoring, was system (Krajewski et al. 2008a) play an important role in measured by the U.S. Army’s Field Research Facility at investigating the rainfall distribution from Hurricane Isa- a waverider buoy in 20 m of water [U.S. Geological Sur- bel. For storm surge analyses, the WRF is coupled with vey (USGS) St. Petersburg Coastal and Marine Science the 2D, depth-averaged hydrodynamic model, Advanced Center]. Storm surges were 2–2.5 m above normal tide Circulation Model (ADCIRC). Detailed investigations levels near the point of landfall along the Atlantic coast of include the evolving distribution of heavy rainfall and the North Carolina and 1–2 m in the North Carolina estuaries impacts of complex terrain on rainfall and flooding, the of the Pamlico and Albemarle Sounds (Lawrence et al. evolving structure of extreme winds and the wind maxima 2005). The surge and waves created a new inlet, un- associated with rainbands, and the hurricane-induced officially named Isabel Inlet, by washing out a portion of storm surges in the urbanized areas in the Chesapeake between Hatteras and Frisco; the inlet Bay watershed. Data from a broad range of observing destroyed a portion of North Carolina Highway 12 and all systems are used to facilitate this investigation and, more utility connections to Hatteras Village (NOAA 2004). generally, to assess the current modeling systems’ capa- Extensive storm surge flooding also occurred in Ches- bility to simulate and forecast multiple inland hazards apeake Bay and the associated estuaries of the Potomac from tropical cyclones, which may have important ap- and James Rivers. Isabel was the worst hurricane to affect plications in emergency response agencies and the in- the Chesapeake Bay region since 1933; storm surges of 2– surance industry. 2.5 m above normal levels occurred in the upper Ches- The contents of the sections are as follow. We intro- apeake Bay (Lawrence et al. 2005). As the storm moved duce the models and observations used to examine the through , strong southeasterly and southerly multiple hazards from Hurricane Isabel in section 2. The winds in the right quadrants forced water into the bay general characteristics of the synoptic evolution of the and up to the northern bay region. In addition, extreme storm, including the track and intensity, are summarized local winds associated with outer rainbands enhanced in section 3. We examine extreme rainfall and inland the storm surge in the upper bay areas, resulting in severe flooding in section 4 based on the intercomparison be- flooding in Washington, D.C., Baltimore and Annapolis, tween rainfall fields simulated by WRF with radar rainfall . Hurricane storm surge represents a hazard that fields and observations from rain gauges. In section 5 has potentially devastating consequences in urbanized we examine the storm wind field from the perspectives coastal regions, such as Chesapeake Bay and of maximum wind distribution, radial wind profiles, and City’s harbor region (Colle et al. 2008). local wind time series from stations at the coast as well as The main purpose of this paper is to apply numerical inland. Storm surge simulations for the Chesapeake Bay, modeling and observational data analysis to investi- based on coupling the WRF model and the ADCIRC gate multiple hazards from tropical cyclones. Case study model, are presented in section 6. A summary and con- analyses of Hurricane Isabel are carried out with a focus clusions are presented in section 7. on its evolution during and after landfall (for analyses of Hurricane Isabel prior to landfall, see Montgomery et al. 2. Modeling, simulation, and data analysis 2006; Kossin and Schubert 2004; Bell and Montgomery a. WRF modeling and simulations 2008). For real-time forecasting, multiple hazards from landfalling tropical cyclones represent a particular chal- The WRF, developed by the National Center for At- lenge. Prediction of losses from landfalling tropical cy- mospheric Research (NCAR), is a nonhydrostatic, me- clones for insurance and reinsurance applications also soscale model that has been widely used for a broad range motivates the analyses in this paper (see, e.g., Powell of analyses of tropical cyclones (e.g., Davis et al. 2008). In et al. 1995; Watson and Johnson 2004). For these ap- this study, the Advanced Research version of the WRF plications, assessment of losses from multiple hazards (Skamarock et al. 2005) is used to simulate Hurricane in heavily populated inland settings presents a particu- Isabel, with a focus on processes that control the multiple lar challenge. hazards of the storm following landfall. The physics options

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FIG. 1. The WRF simulation domains. The three white boxes show the three nested domains. used for all simulations are the WRF Single-Moment National Centers for Environmental Prediction (NCEP), (WSM) three-class microphysics scheme (WSM3), the and the other is the 1/68 6-h model fields from the Geo- Kain–Fritsch cumulus parameterization (for domains with physical Fluid Dynamics Laboratory’s (GFDL) hurri- grid spacing larger than 10 km), the Monin–Obukhov cane model (Kurihara et al. 1998). The initialization of surface layer scheme, the Noah land surface scheme, and the GFDL model involves the controlled spinup of a re- the Yonsei University planetary boundary layer scheme alistic hurricane vortex with features on a scale consistent (similar to those used in Davis et al. 2008). with a higher-resolution model (Kurihara et al. 1993; Three domains (Fig. 1), all centered around coastal Bender et al. 1993). This may help overcome the problem North Carolina where Hurricane Isabel made landfall, of initializing a WRF model simulation with an analysis were used in the WRF simulations. The outer domain obtained from global models, which generally have hur- has a resolution of 12 km and covers a large area of the ricane vortices that are weaker than observed. background atmospheric environment. The middle do- The initial vortex for Hurricane Isabel at 0000 UTC main has a resolution of 4 km and covers the track from on 18 September 2003 obtained from the GFDL model 18 to 20 September 2003, the period of focus of this study. is stronger than that from the GFS model fields (Fig. 2). The inner domain has a resolution of 1.33 km and covers The GFS vortex has a minimum pressure of 974 mb the coastal and inland areas that were significantly af- (hPa) and a maximum wind speed of 44.7 m s21. The fected by Isabel. The starting time of the WRF simula- GFDL vortex has a minimum pressure of 942 mb and a tions is chosen as 0000 UTC on 18 September, about maximum wind speed of 51.8 m s21. Although within 17 h before landfall. Simulation runs initialized much the range of the observations, the intensity of the GFS earlier before landfall would induce large errors in the vortex is weaker and the GFDL vortex is stronger than prediction during and after landfall and thus are not suit- the National Oceanic and Atmospheric Administration able for hazards analysis. On the other hand, we start the (NOAA) best-track estimation of the storm intensity at simulation more than 15 h before landfall to investigate this time (953 mb and 46.3 m s21). The GFS vortex has the capability of the WRF model to forecast hazards. maximum winds to the north of the storm center, while We also consider allowing sufficient time (more than 12 h) the GFDL vortex has stronger and more symmetric for the initial adjustment of the vortex in the model winds in the eyewall region. simulations. To study the effects of the initial and boundary con- The initial and boundary conditions of the WRF simu- ditions on the storm development, and thus the associ- lations are taken from two sources: one is the 18 6-h model ated hazards, during and after landfall, we have carried fields from the Global Forecast System (GFS) from the out three WRF simulations: (i) using the GFS model fields

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FIG. 2. Forecast initialization at 0000 UTC 18 Sep 2003 from the (a) GFS and (b) GFDL models. Shading represents the 10-m wind speed (m s21) and contours represent the sea level pressure (mb). for both initial and boundary conditions (WRF-GFS run), Westerink et al. (2008) for New Orleans, Louisiana, and (ii) using the GFDL fields for the initial condition and Colle et al. (2008) for the harbor region. GFS fields for the boundary condition (WRF-GFDL/GFS These studies have demonstrated the high performance run), and (iii) using the GFDL fields for both the initial and flexibility of the ADCIRC model in simulating coastal and boundary conditions (WRF-GFDL run). All of the storm surge. simulations start at 0000 UTC 18 September 2003 and ADCIRC allows the use of an unstructured grid with end at 0000 UTC 20 September 2003. The results from the very fine resolution near the coast and much coarser three simulations are compared in the following sections. resolution in the open ocean. The grid used in this study, as shown in Fig. 3, was developed by Shen et al. (2005). b. Coupling with ADCIRC In the main channel of the Chesapeake Bay the grid has WRF simulations are coupled with the two-dimensional, a resolution of about 0.2–1 km. In the tributary main depth-integrated implementation of ADCIRC to examine stems, the resolution is approximately 150–500 m and the storm surge in the Chesapeake Bay. ADCIRC is a increases in the tidal rivers to 50–150 m. The bathymetric finite-element model developed by Luettich et al. (1992) data for grid cells were obtained from the 30 Coastal and Westerink et al. (1992) for the purpose of simulat- Relief Model bathymetric data and NOAA’s 29 Global ing hydrodynamic circulations along shelves, coasts, and Relief Model bathymetric data. The mean sea level was within estuaries. The 2D, depth-averaged module of used as the water level/tidal datum for the model. The ADCIRC is used in this study. ADCIRC has been used elevations of adjacent low-lying land areas were obtained by Shen et al. (2005) to simulate storm surge in the from USGS Digital Elevation Model (DEM) data, which Chesapeake Bay from Isabel. In their study, a parametric were based on the North American Vertical Datum wind model that is similar to that of the Sea, Lake, and (NGVD) and adjusted to the mean sea level (see Shen Overland Surges from Hurricanes model (SLOSH; et al. 2005). Jelesnianski et al. 1992) was used to generate the wind ADCIRC simulations were carried out for astronomi- and pressure forcing. Recent applications of ADCIRC cal tides in normal days and for storm tides (the sum of to study storm surge for other coastal areas include the astronomical tide and storm surge) during Hurricane

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North Dataset (HURDAT) best- track data (6-h interval) from NOAA’s Hurricane Re- search Division (HRD). Hydro-NEXRAD radar rainfall fields play a central role in examining the rainfall distribution and are used to assess simulated rainfall fields from Isabel. Rainfall fields were derived from four Weather Surveillance Radar–1988 Doppler (WSR-88D) sites: Sterling, Virginia (KLWX); Roanoke, Virginia (KFCX); Raleigh, North Carolina (KRAX); and Newport, North Carolina (KMHX). The rainfall fields are produced at 15-min time scales on the ‘‘super’’ Hydrologic Rainfall Analysis Pro- ject (SHRAP) grid, which has a resolution of approxi- mately 1 km. The generation of these rainfall fields is performed by processing level II radar data using the Hydro-NEXRAD system (Krajewski et al. 2007a, 2008a). Numerous customized modular radar rainfall algorithms are available in Hydro-NEXRAD (Krajewski et al. 2007b). In this study the tropical Z–R relationship (Fulton et al. 1998; Medlin et al. 2007) was used to convert the reflectivity Z (mm6 m23) into the rainfall rate R (mm h21). The merging of the different radars has been performed using the algorithms described in Krajewski et al. (2008b). FIG. 3. ADCIRC simulation grid for the Chesapeake Bay (developed by Shen et al. 2005). Additionally, the algorithm proposed by Steiner and Smith (2002) was applied to discriminate between non- meteorological (anomalous propagation and ground clut- Isabel’s passage. In the first case, ADCIRC was forced by ter) and meteorological returns [currently implemented tidal constituents along the ocean boundary. In the sec- in Hydro-NEXRAD; Krajewski et al. (2007b)], which ond case, ADCIRC was forced by tidal constituents as well Villarini and Krajewski (2010b) found to be very effec- as wind and pressure forces. Five principal tidal constitu- tive in improving the radar rainfall estimation, especially ents were considered in the simulations, including M2, K1, close to the radar site. O1, N2,andS2 (as used in Westerink et al. 2008; Colle et al. The radar data were complemented with rainfall mea- 2008). In the simulation of Isabel-induced storm surge, surements from 58 hourly cooperative observing rain 2-day (from 0000 UTC 18 September to 0000 UTC gauges (and archived by the National Climatic Data 20 September 2003) 15-min (interval) time series of sur- Center), scattered almost uniformly across the domain face wind velocity and sea level pressure generated from of interest. A bias correction algorithm (Smith et al. 1996; WRF simulations are applied as surface forcing. In setting Krajewski and Smith 2002; Germann et al. 2006; Ciach the parameterization of subgrid-scale processes, the bot- et al. 2007) is used to correct for systematic errors in radar tom stress is determined by a hybrid friction relationship rainfall estimates [for a recent review, consult Villarini (see Westerink et al. 2008) and the wetting and drying and Krajewski (2010a)] based on the ratio of mean rain algorithm is utilized. Model parameters are the same as gauge rainfall and mean radar rainfall at gauge locations. in Westerink et al. (2008). Because we are merging four different radars and given the presence of heterogeneous topography, we have c. Data and analysis methods created a bias field obtained by interpolating (using in- Data from a broad range of observing systems are verse distance-weighted interpolation) the bias values at analyzed and compared to examine the evolving struc- the 58 rain gauge locations (e.g., Seo et al. 2000) on the ture of the storm and the associated heavy rainfall and same spatial grid as the radar maps. This bias field is then flooding, extreme winds, and coastal storm surge. The multiplied to the radar rainfall fields to obtain bias- synoptic evolution of the storm is investigated from the corrected rainfall maps. perspective of track and intensity development. Storm To study the spatial structure of rainfall, the distri- location (i.e., the location of the minimum sea level bution of rainfall relative to the center of circulation for pressure), minimum sea level pressure, and maximum a specified time is computed by averaging azimuthally to wind speed from the simulations are verified against the provide the mean rainfall as a function of distance from

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FIG. 4. Track of Hurricane Isabel from the observations (NOAA best-track data) and from WRF simulations. the center of the circulation (radial profiles) and by av- Program (FCMP; Masters 2004). The inland forecast lo- eraging radially to provide the mean rainfall as a func- cal wind time series are compared with observations from tion of the azimuth (azimuthal profiles). The center of surface meteorological stations. circulation for the simulation analysis is the location of To investigate the capability of the WRF-ADCIRC the minimum sea level pressure. For the analysis of the coupled model in storm surge simulations for the case of composite Hydro-NEXRAD rainfall fields, the center Hurricane Isabel, simulated hourly time series of astro- of circulation is taken from the HURDAT best-track nomical tides and storm tides at locations in the Ches- data, with linear interpolation in time to provide loca- apeake Bay are compared with observations at gauge tions between HURDAT-reported times. stations of the NOAA Center for Operational Ocean- The evolving wind fields of Hurricane Isabel are ex- ographic Products and Services (CO-OPS). amined by analyzing the maximum wind distribution, radial wind profiles, and local wind time series from sta- 3. Synoptic evolution tions at the coast as well as inland. The spatial distribution of the maximum wind speed during the storm’s landfall is Hurricane Isabel was a long-lived hurricane that formed compared with the H*Wind surface wind analysis data from a off the coast of on 1 Sep- from HRD (Powell et al. 1998). Radial wind profiles, tember 2003 (Lawrence et al. 2005). Isabel reached cat- representing the distribution of the wind speed relative to egory 5 intensity on 11 September and made landfall near the center of circulation for specific times, are computed Drum Inlet on the Outer Banks of North Carolina as a by averaging wind speeds azimuthally in each of the four category 2 hurricane at 1700 UTC 18 September. After quadrants of the storm. Local forecast wind time histories landfall, Isabel moved northwest over North Carolina and on the coast are compared with observations from mobile Virginia to the northeast of at 0600 UTC towers implemented by the Coastal Monitoring on 19 September when it became a tropical storm. By

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1200 UTC 19 September, the extratropical transition of Isabel was completed and the system moved over into . WRF simulations start at 0000 UTC 18 September and end at 0000 UTC on 20 September 2003. WRF simulations of the storm start from approximately the same location as the observed storm at 0000 UTC 18 September, and the simulated tracks closely match the observed track until landfall, after which the simulated storms move slower than the observed storm (Fig. 4). Among the three simulated tracks (generated with dif- ferent initial and boundary data; see section 2a), the WRF- GFS track is the closest to the observed track. Since the steering flow for Isabel was the result of an interaction between an upper-level low to the west and a strong ridge to the northeast, it is likely that the better track of the WRF-GFS run resulted from the use of initial and boundary conditions that came directly from the global model. The track of the WRF-GFDL run is shifted to the left of the observed storm track. The storm intensity is assessed using both the minimum sea level pressure and the maximum sustained wind at 10-m elevation (Fig. 5). The initial GFS vortex is weaker, while the GFDL vortex is stronger than the observed storm at 0000 UTC 18 September. After initial adjust- FIG. 5. Intensities of Hurricane Isabel from the observations ments, all simulations obtained minimum pressures that (NOAA best-track data) and WRF simulations, for (a) minimum are close to the observation at 1200 UTC (Fig. 5a). The sea level pressure (mb) and (b) maximum 10-m winds (m s21). maximum wind from the WRF-GFS simulation, how- Data points are shown for every 6 h. Forecasts begin at 0000 UTC ever, is greater than those from observations and the 18 Sep 2003. other simulations at this time (Fig. 5b). Davis et al. (2008) found that significant adjustment of the vortex occurred with a weaker vortex, it experiences more dramatic ini- within 6–12 h of initialization when the GFDL initial tial intensification and less accurate decay after landfall, conditions were used in the WRF simulations, due to the compared to the GFDL-initialized runs. This observa- differences in numerical schemes and physical parame- tion merits further investigation. Improved initialization terizations between the GFDL model and the WRF of the storm structure and intensity was also identified by model. Our simulations, however, show that the adjust- other studies (e.g., Davis et al. 2008) as one of the crucial ment of the GFDL-initialized simulations is more gradual elements of improved forecasts. The resolution of the than the GFS-initialized simulation (Fig. 5). input data may also have important effects, especially for For the 6 h prior to landfall at 1800 UTC, the GFDL- intensity prediction. initialized storms have a faster drop in the maximum wind speed than the GFS-initialized storm and a drop 4. Rainfall and flooding that is somewhat faster than the observations. During this period, the increase in minimum pressure for the Hurricane Isabel produced heavy rainfall along its track. GFDL-initialized storm compares well with the obser- Rainfall from a landfalling tropical cyclone depends on vations. After landfall, the WRF-GFDL simulation has many factors, including storm track, intensity and trans- intensities that are the closest to the observations, while lational speed, track-relative distribution of rainfall, rain- the WRF-GFS run overestimates the intensities (Fig. 5). bands, vertical shear of the environmental wind, and local Because both the initial and boundary conditions of the topography (e.g., Rogers et al. 2003; Marchok et al. 2007). WRF-GFDL run are generated from the GFDL model, In this section we apply simulations and observations to this indicates that the structure and intensity of the initial examine the rainfall and flooding from Isabel, with a focus vortex can have significant effects on the development of on the spatial–temporal rainfall structure, topography the storm, even when the storm is initialized at a later effects, and outer rainbands. The spatial distribution of stage of its life cycle. Although the WRF-GFS run starts the storm total rainfall from landfall through the central

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FIG. 6. Total rainfall accumulations (mm; contours) from (a) radar data analysis (bias corrected) and (b) WRF simulations. Red dots represent the NOAA best track and yellow dots represent the simulated track. The contour interval is 25 mm. The WRF results are based on the WRF-GFDL run.

Appalachians is examined. Track-relative distributions the orographic enhancement of rainfall over the central of rainfall over time in the radial and azimuthal directions Appalachians, a central feature of the extreme flood hy- are analyzed. Also, heavy rainfall from rainbands and drology of the region (Sturdevant-Rees et al. 2001). the severe flooding in urban watersheds are highlighted Rainfall maxima near the track of the storm at the Blue for the Baltimore metropolitan region. Among the three Ridge are also well predicted in the simulation. Both WRF simulations, the WRF-GFDL run, which has both simulation and radar observations show 100–250-mm initial and boundary conditions generated from the GFDL accumulations in the interior of the central Appala- model with high resolution (1/68),hasbetterrainfallpre- chians with a sharp decrease to the west of the central dictions than the other two simulations, when compared Appalachians. with the radar and rain gauge observations. This feature A local inland maximum in storm total rainfall ap- is linked to the properties of storm evolution after landfall proximately halfway between landfall and the Blue Ridge discussed in the previous section. Thus, only the WRF- is shown in the observations as well as in the model GFDLrunisusedinthissectionforrainfallanalyses simulation (Fig. 6). This local maximum in rainfall lies [for a comparison of the total rainfall simulated from to the right of the storm track and is near the North the NCEP operational models for Hurricane Isabel, see Carolina–Virginia border. Analyses of the simulated wind Fig. 1in Marchok et al. (2007)]. field suggest that this local maximum resulted from the formation of a low-level jet, which led to strong low-level a. Heavy rainfall convergence after landfall, and when coupled with the The spatial distribution of the simulated storm total upper-level divergence pattern, produced the localized rainfall matches well with the observations from the heavy rainfall. composite Hydro-NEXRAD results (Fig. 6). Both the The model-simulated rainfall shows large spatial gra- model simulation and the radar observations show rain- dients near landfall, with a local maximum in rainfall fall accumulations along the track of the storm, ranging accumulation exceeding 225 mm that is approximately from 150 to 225 mm over the path from landfall through 40 km offshore and 80 km to the left of the simulated the central Appalachians. The model simulation captures track. Observed offshore rainfall also shows a ‘‘left of

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FIG. 7. Comparisons of the distribution of the WRF- and radar-based rainfall amounts (15-min accumulation) as a function of range from the center of the storm at four different times after landfall. The radar estimates are bias corrected and WRF is based on the WRF-GFDL run. track’’ maximum in rainfall (200 mm), but the spatial range dependence (Fig. 7). At landfall (Fig. 7a), the model gradients are weaker than in the simulated rainfall field. and observed rainfall fields have maxima between 75 and Both the radar and the model simulation show a transition 100 km from the center of circulation. Hydro-NEXRAD from a left-of-track maximum in rainfall before landfall to rainfall fields show intense eyewall forming a right-of-track inland maximum after landfall. A similar near landfall and producing a secondary maximum in secondary axis of rainfall in Isabel was also noted by rainfall at 25 km from the center of circulation. De- Marchok et al. (2007) in forecasts from various NCEP velopment of eyewall convection near landfall is an im- operational models. Model simulations underestimate portant element of the observed storm total rainfall rainfall accumulations in the northeastern portion of the distribution in the coastal environment, but it is not re- region illustrated in Fig. 6, due to the contribution of flected in the model simulation. The observed rainfall in outer rainbands (see additional discussion below). rainbands beyond 220 km from the center of circulation Analyses of the radial and azimuthal profiles of 15-min is significantly larger than the model-simulated rainfall rainfall are presented in Figs. 7 and 8, respectively, at 3-h and the difference increases with range. The mean ob- time intervals beginning after landfall at 1800 UTC served rainfall from the 250–400-km range from the cen- 18 September. The simulated rainfall profiles (relative ter of circulation is almost twice that of the mean rainfall to the simulated track) are compared with the Hydro- over the same range of values from the model simulations NEXRAD rainfall profiles (relative to the HURDAT (Fig. 7a). best track). Broad features of the track-relative distribu- Pronounced maxima in rainfall within 50 km of the tion of rainfall are captured in the model simulations, but center of circulation are prominent features of the ob- there are also important features that are not represented. served rainfall distributions at 2100 and 0000 UTC (Figs. The range dependence of the rainfall evolves during the 7b and 7c). These features are directly linked to the lo- 9-h period following landfall, but the model-simulated cal maximum (225 mm) in observed storm total rain- structure of the rainfall does not closely match the observed fall (Fig. 6a) located between landfall and the central

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FIG. 8. As in Fig. 7, but for the rainfall distribution as a function of azimuthal angle.

Appalachians. Model-simulated rainfall fields reflect this rainfall. Local maxima in the radial distribution of rainfall local maximum (Fig. 6b), but the maximum appears ear- associated with rainbands are also prominent at 0000 UTC lier and is located at farther range from the center of (90, 170, and 275 km; Fig. 7c). Model-simulated rainfall circulation in the simulation. Model-simulated rainfall fields do not capture the mesoscale details of the rain- fields at ranges greater than 200 km from the center of bands and these features are critical elements of urban circulation are comparable to the observed rainfall fields flooding, wind damage, and possibly storm surge in the at 2100 and 0000 UTC, reflecting the contributions of the upper Chesapeake Bay. orographic enhancement to the model-simulated rainfall. The agreement between the simulations and obser- At 0300 UTC (Fig. 7d), there are large contrasts in the vations for the azimuthal distribution of rainfall is better range-dependent distribution of the rainfall between the than the corresponding analyses for the radial distribu- observed and simulated rainfall fields. The center of tion (Fig. 8). From landfall through passage of the storm circulation at 0300 UTC is located southeast of the Blue through the central Appalachians, both the model and Ridge (see Figs. 4 and 6). Model-simulated rainfall shows the observations show that the rainfall maximum is con- a gradual increase in the rainfall distribution to 180 km centrated in the northern quadrants (08–908 and 2708– from the center of circulation and a gradual decrease 3608)ofthestorm. at greater range. The observed rainfall distribution at b. Inland flooding 0300 UTC shows an increasing maximum in rainfall from 25- to 100-km range and a sharp local maximum at 150-km The flooding from Hurricane Isabel in the central Ap- range. The close-range maximum in the observed rainfall palachians was most severe at small basin scales along field is associated with the orographic enhancement of the track of the storm, in areas receiving 200–250 mm of rainfall; this is not represented in the model-simulated rainfall in less than 6 h. Rapid movement of the storm rainfall field at this time, possibly due to the slow move- system, perpendicular to the strike of the major valleys ment of the simulated storm (see Fig. 4). The 150-km of the Blue Ridge and Valley and Ridge regions, reduced maximum is associated with outer maxima in the effectiveness of the storm in producing large-basin

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region, receiving the heaviest rainfall (see closed 225-mm rainfall contour in the WRF simulation; Fig. 6b), and extends to the northeast (along the contour of the oro- graphically enhanced rainfall in the WRF simulation; Fig. 6b). The largest flood peak in much of the Shen- andoah River basin was produced by , which moved from southwest to northeast up the catch- ment. Landfalling tropical cyclones account for 16% of the 77 annual peaks in the South Fork of the Shenandoah at 2795-km2 scale. For the ‘‘upper tail’’ of the flood peak distribution, the role of tropical cyclones is larger (Villarini and Smith 2010). For the South Fork of the Shenandoah, 7 of the 10 largest floods are produced by tropical cyclones (Fig. 9). In addition to flooding in the central Appalachians

FIG. 9. Time series of the annual maximum peak discharge for along the track of the storm, Isabel produced flooding in the South Fork of the Shenandoah River near Lynnwood (USGS small urban watersheds from extreme rainfall rates in 01628500). The black dots represent peaks caused by tropical cy- outer rainbands. The storm total rainfall observations clones. from a network of 17 double-rain-gauge stations in the 14.3-km2 Dead Run watershed in Baltimore ranged from 60 to 80 mm and produced out-of-bank flooding flooding, relative to tracks along the strike of the basin (Fig. 10). The flood peak response in Dead Run at basin (Sturdevant-Rees et al. 2001). In the South Fork of the scales ranging from 14.3 km2 (Fig. 10a) to less than 1 km2 Shenandoah, Isabel produced the ninth largest annual (Fig. 10b) was due to rain rates exceeding 100 mm h21 flood peak at 2795-km2 scale (drainage area of the South for a period of 5–10 min, shortly after 0400 UTC. Fork of the Shenandoah River near Lynnwood, Virginia) Extreme rainfall rates in Dead Run were produced by in a 77-yr record (Fig. 9). The South Fork of the a rainband that passed over the Chesapeake Bay from Shenandoah lies immediately west of the Blue Ridge 0330 to 0400 UTC and over the Baltimore metropolitan

FIG. 10. Time series of the basin-averaged rainfall (shading) and discharge (contour) for two basins in the Baltimore area: (a) Dead Run and (b) DR1, which is a subbasin of Dead Run.

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FIG. 11. Rain-rate maps based on the KLWX radar site on 19 September at (a) 0342:28, (b) 0347:26, (c) 0357:27, and (d) 0402:26 UTC. The tropical Z–R was used to convert the reflectivity into a rainfall rate. The gray line marks the boundary of Baltimore, while the black lines mark the basins in the Baltimore area. region around 0400 UTC (Fig. 11). Although the WRF 5. Extreme winds simulation captures some aspects of the rainband struc- ture before and during landfall, it does not accurately The extreme winds from Hurricane Isabel induced simulate the outer rainbands over inland regions (Figs. 7c significant damage along the coast as well as inland. and 7d) and thus cannot capture this particular rain- Thousands of coastal residences were damaged by the band (see Franklin et al. 2005; Hence and Houze 2008; combined surge, wave, and wind forces (Rogers and Tezak Houze et al. 2006, for related analyses on hurricane 2004). A large number of trees were knocked down, rainbands). In addition to flash flooding, extreme winds causing seven fatalities and severe damage to houses and from this rainband were responsible for extensive prop- power lines, even far inland. In this section, we study the erty damage due to falling trees and extended power wind structure of Hurricane Isabel by examining the outages over Baltimore City and Baltimore County, as spatial distribution of the maximum winds and the radial discussed below. Extreme winds from this rainband wind profiles calculated by averaging wind speeds azi- may also have played a role in the extreme storm surge muthally in each of the four quadrants of the storm. We in the upper Chesapeake Bay, as discussed in section 6 also investigate the time series of local winds, which were below. directly responsible for the severe local wind damage.

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21 FIG. 12. Distribution of 10-m maximum winds (m s ) during the passage of Isabel from (a) H*Wind analysis data, and (b) WRF-GFS, (c) WRF-GFDL/GFS, and (d) WRF-GFDL simulations. Red dots represent the NOAA best track and yellow dots represent the sim- ulated tracks.

The spatial distribution of the maximum wind speed WRF-GFDL run is smoother than that of the WRF- during the passage of the storm is shown in Fig. 12 for the GFS run.) H*Wind surface analysis data and for our three WRF The observed wind fields show that the maximum winds simulations (see section 2a), respectively. The observed of the storm were to the right of the track. The WRF maximum wind speed at the coast was approximately simulations, however, have the maximum winds centered 45 m s21 (Fig. 12a). The WRF-GFS simulation has a on the track, especially the GFDL-initialized simula- maximum wind speed of 43 m s21 (Fig. 12b) and the tions (Figs. 12c and 12d), due to its very symmetrical other two GFDL-initialized simulations have lower wind initial vortex (Fig. 2b). The H*Wind data at 2230 UTC speeds of about 37 m s21(Figs. 12c and 12d). Pronounced 17 September and 0130 UTC 18 September (not shown) maxima approximately 250 km offshore in the maxi- suggest the existence of the wavenumber-1 asymmetry mum wind fields of the WRF simulations (Figs. 12c and of the winds in the northeastern quadrant of the storm. 12d) are associated with the storm location and in- Neither the GFS nor the GFDL initialization (at 1800 UTC tensity around 1200 UTC 18 September (see Figs. 4 and 18 September; Fig. 2) captures this strong wind band 5b). GFDL-initialized simulations may be too sensitive away from the eyewall, which may explain the under- to the surface effects as the storm approaches land and estimation of the winds to the right of the track in the thus underestimate the maximum wind at the coast (also WRF simulations. This observation again suggests the see Fig. 5b). (However, the hourly recorded track of the significance of proper initialization, which affects simulated

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21 FIG. 13. Radial profiles of the 10-m winds (m s ) by quadrant from the H*Wind analysis data and from WRF simulations, at 1330 UTC 18 Sep 2003. storm properties and coastal and inland damage pre- Local wind conditions are examined by comparing the diction. Also, the model simulations in Fig. 12 do not simulated and observed wind time series at coastal and capture the local amplification of the winds due to rain- inland stations. WRF-simulated winds match the observed bands (see additional discussion below). mean wind speeds and directions well at most stations, but The model-simulated and H*Wind radial profiles of simulated wind speeds are lower than the 1-min sustained the 10-m winds by quadrant at 1330 UTC 18 September winds and wind gusts at inland stations, which are mainly are compared in Fig. 13. Simulated profiles in the left responsible for local wind damage. quadrants compare relatively well with the observations Observed and model-simulated 1-min wind velocities (Figs. 13a and 13c). WRF simulations underestimate the at two coastal locations (Fig. 14), Wilmington, North wind profiles in the right quadrants, which are espe- Carolina (to the left of the track), and Elizabeth City, cially high for Hurricane Isabel (Figs. 13b and 13d). North Carolina (to the right of the track), show good Among the three simulations, the two GFDL-initialized general agreement. Elizabeth City experienced much runs have better wind predictions in the left quadrants higher wind speeds than Wilmington. The development and within the in the right of the peak simulated winds is delayed relative to the quadrants, as their initial intensities in the eyewall re- observations (Figs. 14b and 14d), due to the slower gion are strong enough (Fig. 2b). The WRF-GFS run movement of the simulated storms compared to the produces a better simulation for the 10-m winds beyond observations (see Fig. 4). the radius of maximum winds in the right quadrants. Its The wind damage from Hurricane Isabel extended far initial vortex is not as symmetrical as the GFDL initial inland, and the wind damage was large for inland cities, vortex (Fig. 2). Similar underestimation of the radial including Washington, D.C.; Richmond; and Baltimore wind profiles was observed for 700-mb winds in the WRF (NOAA 2004). Comparisons of time series of observed simulation of Davis et al. (2008) for surface wind velocities and model simulations at four (2005). inland stations (Fig. 15) highlight the strengths and

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FIG. 14. Coastal wind time series from observations (FCMP data) and from WRF simulations. Locations of coastal FCMP meteorological towers are shown in Fig. 4. weaknesses of the simulated wind fields. WRF-simulated We investigate the storm surge in Chesapeake Bay from wind speeds compare well with the observed mean wind Isabel in this section through coupled WRF–ADCIRC speeds, but are lower than the observed wind gusts. simulations. As the storm was moving through Virginia Richmond experienced high wind gusts during 18 Sep- along the west side of the Chesapeake Bay, strong south- tember through the early hours of 19 September, with easterly and southerly winds forced water into the mouth maximum wind speeds reaching 25 m s21. of the bay. Extreme local winds associated with outer Baltimore City experienced even higher winds with rainbands were also elements of the storm surge envi- 1-min speeds reaching 27 m s21 (Fig. 16). Extreme winds ronment for the upper Chesapeake Bay. in Baltimore were associated with the rainband, which To check the capability of the ADCIRC model and produced extreme rainfall and flooding (Figs. 10 and 11). the simulation grid for Chesapeake Bay, astronomical WRF simulations underestimate the wind speeds for this tides were first simulated for normal days, assuming zero location, although the wind directions are better predicted surface wind force and standard atmospheric pressure. (Fig. 16). The secondary wind maxima in the hurricane Simulated astronomical tides are compared with the rainbands over land were responsible for the significant NOAA gauge observations. The tides in the lower bay inland wind damage. area are well predicted by the ADCIRC simulation, while the tidal peaks in the upper bay are underestimated by about 0.2 m (figure not shown). 6. Storm surge The Isabel-induced storm surge in the Chesapeake Bay Due to high surface winds and low sea level pressure, was simulated (Fig. 17) by coupling WRF simulations extensive storm surge flooding occurred along the At- with the ADCIRC model through the surface wind speeds lantic coast and into Chesapeake Bay during Hurricane and surface pressure generated from WRF. In the lower Isabel’s passage. Severe storm tides (above mean sea bay region (Kiptopeke, Virginia; the Chesapeake Bay level) were observed in Richmond (2.7 m); Washington, Bridge Tunnel; and the Sewell’s Point area near Nor- D.C. (2.5 m); Baltimore (2.2 m); and Annapolis (2.0 m). folk), storm tides attained their peaks (1.5–2.0 m) around

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FIG. 15. Inland wind time series from observations (data source: Plymouth State Weather Center, Plymouth, NH) and from WRF simulations. Locations of inland meteorological stations are shown in Fig. 4.

1800 UTC 18 September (1 h after landfall). The ADCIRC Maryland). However, the simulations significantly un- simulation with the WRF-GFS run forcing only slightly derestimate the storm tides in the upper bay (Fig. 17). A underestimates the magnitude of the peaks, but has a small portion (0.2 m) of this is attributable to the un- time delay of approximately 2 h, due to the slower move- derestimation of the astronomical tides in the upper bay. ment of the simulated storm compared to the observations Previous studies (Shen et al. 2006; Li et al. 2006) showed (Fig. 4). Simulations with the WRF-GFDL/GFS (and that the large surge in the upper Chesapeake Bay was similarly WRF-GFDL; not shown) forcing captured the caused predominantly by the wind forcing, especially phase of the storm tides well, but underestimated the the local wind forcing, rather than being due to the wave magnitude of the peaks by about 0.5 m. There are mul- propagation from the lower bay. Shen et al. (2006) found tiple reasons to explain why the storm surge is under- that their parametric wind model [which is similar to the estimated. The WRF simulations started at 0000 UTC on SLOSH wind model (Jelesnianski et al. 1992)] also un- 18 September and thus the wind and pressure forcing are derestimated the wind and pressure forcing of Hurri- only applied from this time for 2 days. However, wind and cane Isabel in the upper Chesapeake Bay region, and they pressure fields over the far ocean during the storm de- had to increase the pressure drop by 10% and corre- velopment affected the storm surge in the bay, and water spondingly increase the wind speeds in order to achieve levels were already about 0.2 m higher than the normal accurate surge heights. Thus, the main reason for the tides around 0000 UTC 17 September (see Fig. 17), which underestimation of the surge in our study is that the WRF were not represented in the simulations. The GFDL- simulation does not capture effects of elevated winds in initialized WRF simulations underestimated the maxi- the upper bay. The rainband over the Chesapeake Bay, mum wind speed at the coast (Fig. 12). Also, radial winds which produced extreme rainfall rates (Figs. 10 and 11) in the right quadrants were underestimated in the WRF and strong winds in Baltimore (Fig. 16), may also have simulations (Figs. 13b and 13d). played a role in the storm surge in the upper Chesapeake Storm surge was most extensive in the upper Ches- Bay. In addition, Fig. 17 includes the simulated storm tides apeake Bay (Annapolis, Baltimore, and Cambridge, for Richmond and Washington. The ADCIRC simulation

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and thus on the associated hazards. The simulation initialized with the GFS data has better track pre- dictions, while simulations initialized by the GFDL model yield better predictions of storm intensity. 2) Broad features of the rainfall distribution associated with storm track and orographic amplification in the central Appalachians are represented in the model simulations. The GFDL-initialized simulations pro- duce the best simulations of rainfall in this case, compared with the Hydro-NEXRAD rainfall fields derived from the regional WSR-88D network. The radial distribution in rainfall relative to the center of the circulation is not, however, well represented in our model simulations. The model simulations cap- ture the azimuthal distribution relatively well. 3) The spatial distribution of the wind field is generally represented in the model simulations. However, the simulated wind maxima are centered along the track rather than to the right of the track as observed; the simulations underestimate the wind speeds in the right quadrants of the storm. A possible reason is that nei- ther the GFS nor the GFDL initializations captures the wavenumber-1 asymmetrical wind bands away from the eyewall region and in the right quadrants of the initial vortex. This again suggests the significance FIG. 16. Wind velocity time series at Baltimore from observa- of proper initialization in hurricane forecasting and tions [data source: University of Maryland, Baltimore County coastal and inland damage prediction (also see the (UMBC) Weather Station] and from WRF simulations. Location first conclusion above). of the UMBC station is shown in Fig. 4. 4) Model simulations capture the variability of winds in the near-coastal environment and inland. Mesoscale with the WRF-GFS-simulated forcing accurately predicts details, especially tied to rainbands, are not captured. the peak at Richmond (2.7 m) located at a southern Outer rainbands from Isabel produced major wind tributary, but underestimates the peak at Washington damage and flash flooding in the major urban areas of (2.5 m), located at a northern tributary. the region, including Richmond, Washington, and Baltimore MD. 7. Conclusions 5) Storm surge simulations for Chesapeake Bay are car- ried out through a coupled modeling system consisting Multiple hazards from landfalling tropical cyclones of WRF and the 2D, depth-averaged hydrodynamic are investigated through case study analyses of Hurri- model, ADCIRC. Storm surge at the lower Ches- cane Isabel, which was directly responsible for 17 fatal- apeake Bay is well represented, but the simulated ities and more than $3.3 billion in damage from wind, storm surge in the upper bay does not match the fea- inland flooding, and storm surge flooding during Sep- tures associated with the significant flooding damage. tember 2003. Simulations with the Weather Research Local terrain effects on wind or stronger winds from and Forecasting Model (WRF) are used as the basis for rainbands (see the fourth conclusion above) may ex- combined analyses of Hurricane Isabel. Current mod- plain the inability of the model to capture the magni- eling capabilities for simulating and forecasting multi- tude of coastal flooding in the upper Chesapeake Bay. ple, inland hazards from tropical cyclones are explored. Principal conclusions are the following. Future work will be carried out to investigate the ef- 1) Hurricane track and intensity during and after landfall fects of tropical cyclone rainbands on inland damage from are relatively well predicted in the WRF, although the wind, riverine flooding, and storm-surge flooding. Ideal- motion of the simulated storms is slower than that of ized models of rainfall distribution relative to storm track the observed storm after landfall. Initial conditions will be developed, building on prior studies (e.g., Lonfat have significant effects on the storm development et al. 2007; Tuleya et al. 2007; Langousis and Veneziano

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FIG. 17. Storm tides (above mean sea level) in Chesapeake Bay from observations (CO-OPS data) and from ADCIRC–WRF simulations. Locations of NOAA stations are shown in Fig. 3. (The observed peak for Richmond is 2.7 m; the time series data for this location are not available.)

2009). Similar analyses, combining numerical simulations cyclones. The ‘‘correlation’’ of multiple hazards associ- and empirical analyses, will be carried out for the eastern ated with tropical cyclones will also be further examined. United States, for multiple storms during the period of comprehensive radar coverage (beginning in the late Acknowledgments. This research was funded by the 1990s). Lagrangian analyses, similar to those carried out Willis Research Network, the National Science Foun- for Hurricane Isabel, will be a central element of future dation (NSF Grants CMMI-0653772 and ITR-0427325), studies of rainfall and flooding from landfalling tropical the NOAA Cooperative Institute for Climate Science,

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