Understanding Hurricane Storm Surge Generation and Propagation Using a Forecasting Model, Forecast Advisories and Best Track In

Journal of Marine Science and Engineering

Article Understanding Hurricane Storm Surge Generation and Propagation Using a Forecasting Model, Forecast Advisories and Best Track in a Wind Model, and Observed Data—Case Study Hurricane Rita

Abram Musinguzi 1, Muhammad K. Akbar 2,*, Jason G. Fleming 3 and Samuel K. Hargrove 2 1 Department of Civil and Architectural Engineering, Tennessee State University, Nashville, TN 37209, USA; [email protected] 2 Department of Mechanical and Manufacturing Engineering, Tennessee State University, Nashville, TN 37209, USA; [email protected] 3 Seahorse Coastal Consulting, 3103 Mandy Ln, Morehead City, NC 28557, USA; jason.ﬂ[email protected] * Correspondence: [email protected]; Tel.: +1-615-963-5392

Received: 22 February 2019; Accepted: 15 March 2019; Published: 21 March 2019

Abstract: Meteorological forcing is the primary driving force and primary source of errors for storm surge forecasting. The objective of this study was to learn how forecasted meteorological forcing influences storm surge generation and propagation during a hurricane so that storm surge models can be reliably used to forecast actual events. Hindcasts and forecasts of Hurricane Rita (2005) storm surge was used as a case study. Meteorological forcing or surface wind/pressure fields for Hurricane Rita were generated using both the Weather Research and Forecasting (WRF) full-scale forecasting model along with archived hurricane advisories ingested into a sophisticated parametric wind model, namely Generalized Asymmetric Holland Model (GAHM). These wind fields were used to forecast Rita storm surges. Observation based wind fields from the OceanWeather Inc. (OWI) Interactive Objective Kinematic Analysis (IOKA) model, and Best track wind data ingested into the GAHM model were used to generate wind fields for comparison purposes. These wind fields were all used to hindcast Rita storm surges with the ADvanced CIRCulation (ADCIRC) model coupled with the Simulating Waves Nearshore (SWAN) model in a tightly coupled storm surge-wave model referred to as ADCIRC+SWAN. The surge results were compared against a quality-controlled database of observed data to assess the performance of these wind fields on storm surge generation and propagation. The surge hindcast produced by the OWI wind field performed the best, although some high water mark (HWM) locations were overpredicted. Although somewhat underpredicted, the WRF wind fields forecasted wider surge extent and wetted most HWM locations. The hindcast using the Best track parameters in the GAHM and the forecast using forecast/advisories from the National Hurricane Center (NHC) in the GAHM produced strong and narrow wind fields causing localized high surges, which resulted in overprediction near landfall while many HWM locations away from wind bands remained dry.

Keywords: storm surge generation and propagation; weather research and forecasting model; hurricane advisories and Best track; Generalized Asymmetric Holland Model; circulation and wave coupled model; hurricane forecast and hindcast

1. Introduction A hurricane brings extreme winds, rain, waves, storm surges and ﬂooding, especially during its land-fall. To avoid loss of life and properties due to storm surge, evacuation protocols have been

J. Mar. Sci. Eng. 2019, 7, 77; doi:10.3390/jmse7030077 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2019, 7, 77 2 of 30 developed in US coastal regions [1]. To predict storm surge and overland floods, two fundamentally different approaches can be used [2]: (a) pre-generated composite storm surges stored in a database, and (b) real-time simulation-based forecasting. The pre-generated composite approach uses a set of climatologically generated synthetic hurricanes that can affect a particular coastal region. Storm surges can then be predicted based on the current hurricane forecast, and the pre-generated storm surge of the closest match can be chosen through a table lookup or using a statistical method [3–7]. While this method is very fast, its accuracy is limited due to the variability of the wind and track parameters of the current hurricane [1]. The second method uses a storm surge hydrodynamic model in real-time based on the hurricane forecasts [2,8–15]. It accounts for the wind parameters and tracks of the actual hurricane on hand, although the resolution and model domain may be limited by the computational resources available. The meteorological forcing needed in this approach can be created from a full-scale meteorological forecasting model [16–18], parametric vortex model [19–26], or coupled multi-physics model [27–32]. The parametric wind model is the simplest and fastest option, which can re-create the wind fields and surface pressure from a limited amount of storm parameters that are typically reported in advisories or the Best track. These approaches assume the wind is unaffected by waves or ocean circulation, which may not be the most accurate option [27–32], however, it is widely used [19–26]. Observational wind fields, such as OceanWeather Inc. (OWI) [24] and Hurricane WIND (HWIND) [26], that are typically used for storm surge hindcast are fundamentally different than those used in prediction models. More importantly, observational wind fields are not available during an actual forecasting period. Although the hindcasting of hurricane storm surges is reasonably accurate [14,33–36], the uncertainties associated with hurricane tracks, intensities, sizes, and structures in a forecasting situation are substantially larger, which inevitably impacts the associated storm surges [2,12,37]. Therefore, emergency management almost always resorts to a conservative approach of over prediction of the surge during the decision-making process [2]. Although it is known that hurricane meteorological forcing is the main bottleneck in prediction of storm surge development and propagation, limited studies have been published that quantify how well forecast advisories perform against that of a full scale forecasting model [8,38] or against that of a fully coupled forecasting model [12]. How these forecasting results compare against those from observation based or parametric wind models are not fully understood either. Moreover, hurricanes are often structurally and geographically different from each other, and a generalized forecasting approach may not yet be possible. A variety of numerical and statistical models have been developed for forecasting and/or hindcasting hurricane wind fields (e.g., [39–44]). The most common approaches used in surface wind modeling for tropical cyclones may be categorized as:

(a) Simple analytical parametric models, such as the original Holland model [19]. Such models can be used for both hindcast and forecast of hurricane storm surges, depending on the type of wind data ingested. (b) Dynamical models such as the Planetary Boundary Layer (PBL) model of Chow [20] as later implemented by Cardone et al. [21], Shapiro [45], Thompson and Cardone [22], and Vickery et al. [23]; the Dynamic Holland Model [46], the Asymmetric Holland Model [47,48] and Generalized Asymmetric Holland Model (GAHM) [49]. These can be used for both hindcast and forecast of hurricane storm surges, depending on the type of wind data ingested. (c) Full scale physics-based dynamical models such as Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) [16], Geophysical Fluid Dynamics Laboratory (GFDL) model [17], and Weather Research and Forecasting (WRF) model [18]. These can primarily be used to forecast the hurricane storm surges. (d) Kinematical methods, most notably Hurricane WIND (HWIND) [26] Interactive Objective Kinematic Analysis (IOKA) by OWI [24,25]. These are primarily used to hindcast hurricane storm surges. J. Mar. Sci. Eng. 2019, 7, 77 3 of 30

In this study a numerical experiment is done with different wind fields from OWI, Best track ingested in GAHM, WRF forecasting, and advisories ingested in GAHM model. Wind fields from these are used as meteorological forcing to forecast and hindcast Hurricane Rita’s storm surge using the ADvanced CIRCulation (ADCIRC) + Simulating Waves Nearshore (SWAN) coupled model. The results are compared against observed data to understand the hurricane storm surge generation and propagation with the objective of improved forecasting capabilities during an actual event. The rest of the paper is organized as follows: Section2 presents model details, Section3 presents simulation cases and capability criteria, Section4 presents results and discussion, and finally, Section5 presents concluding remarks.

2. Model Details

2.1. Hydrodynamic Model and Model Mesh The ADCIRC+SWAN is a tightly-coupled model that simulated hurricane storm surge and wave generation and propagation. It is an unstructured grid, finite element-based ocean circulation model that solves the equations of moving fluid on a rotating earth [50–53]. The ADCIRC model solves shallow-water equations to model hurricane storm surges. The SWAN model is a third-generation wave model [54] which is tightly coupled with ADCIRC to produce random, short-crested wind-generated waves on top of storm surges. The SWAN+ADCIRC model takes atmospheric pressure and horizontal wind velocity to compute water surface elevation, depth-integrated velocity, significant wave height, and wave period. The ADCIRC+SWAN model is used to hindcast and forecast the storm surge of Hurricane Rita (2005). Hurricane Rita formed on 18 September and hit the coast of southwestern Louisiana at a Category 3 at 0740 Coordinated Universal Time (UTC) 24 September of 2005 [55]. On arrival into the Gulf of Mexico, Rita rapidly strengthened to a Category 5. Gradually, it weakened to Category 4 and then maintained a Category 3 status up to the time of landfall between Sabine Pass, Texas and Holy Beach, Louisiana [55]. The spread of the surge extended from the Mississippi coast in the east and Port O’Connor region (a small unincorporated village between Galveston and Corpus Christi in Texas) in the west. The Rita hindcast conducted by Kerr et al. [56] using ADCIRC+SWAN using the OWI wind field is taken as the default case in the present study. However, the semi-implicit solver option of ADCIRC is adopted in the present study, instead of the lumped-explicit one used by Kerr et al. The ULtralite-Levee-Removed (ULLR) mesh (417,642 nodes, 826,866 linear triangular elements), created by Kerr et al. as a part of the U.S. IOOS Coastal and Ocean Modeling Testbed [56], is used to run ADCIRC+SWAN (see Figure1a). Note that this mesh does not have levees because it was originally created to compare different storm surge models [56] and some of those do not have levee overflow features implemented. Since the present study is a comparative study and the region of study for Hurricane Rita is away from major levee systems of Louisiana, the usage of ULLR mesh here is well justified. The region of interest along with Hurricane Rita’s track is shown in Figure1b. A spatially varying distribution of Manning’s roughness coefficient derived from land-use databases, as listed in [56], is used for computing the bottom friction in ADCIRC. The same spatially varying Manning’s n coefficients are exported to use in SWAN. J. Mar. Sci. Eng. 2019, 7, 77 4 of 30 J. Mar. Sci. Eng. 2019, 7, 77 4 of 32

(a)

(b)

Figure 1.1. Unstructured ULtralite-Levee-RemovedULtralite-Levee-Removed (ULLR) [56] [56] mesh (a) resolution;resolution; ((b)) observationobservation station locations locations with with respect respect to Hurricane to Hurricane Rita track. Rita Note track. that Note the bathymetry that the bathymetry is artiﬁcially is constrained artificially toconstrained be between to 1 be m and between−1 m 1 to m delineate and −1 mthe to shoreline. delineate Here the ashoreline. negative bathymetryHere a negative represents bathymetry above searepresents level. above sea level.

2.2. Meteorological Forcing In SectionSection1 1 different different approaches approaches forfor obtaining obtaining hurricanehurricane windswinds areare discussed.discussed. InIn thisthis section,section, more details of the wind models applied in the present study are discussed. In a similar approachapproach to Kerr et al. [[56],56], thethe firstfirst andand defaultdefault windwind modelmodel usedused herehere isis thethe OWI,OWI, aa kinematicalkinematical model.model. In this model, the the structured structured and and data-assimilated data-assimilated wind wind and pressure and pressure fields forfields Rita for are Rita generated are generated by blending by theblending TC96 (shortthe TC96 for (short Thompson for Thompson and Cardone, and 1996)Cardone, mesoscale 1996) mesoscale model [22], model with an[22], inner with core an windinner fieldcore transformedwind field transformed to 30 min averaged to 30 min sustained averaged winds sustained with gulf winds scale with winds gulf using scale the winds IOKA using system the [24IOKA,25]. Thesystem hindcast [24,25]. winds The hindcast use measurements winds use frommeasurements anemometers, from airborneanemometers, and land-based airborne and Doppler land-based radar, microwaveDoppler radar, radiometers, microwave buoys, radiometers, ships, aircraft, buoys, coastal ships, stations, aircraft, and satellite coastal measurements. stations, and The satellite OWI windmeasurements. fields are typically The OWI available wind fields only forare hindcast typically of available hurricane only storm for surge. hindcast Therefore, of hurricane OWI is storm used forsurge. hindcast Therefore, of the wholeOWI is or used segment for hindcast of surge forof the which whole the windor segment information of surge is supposed for which to bethe known. wind informationThe second is supposed wind field to be to known. be used in the present study for the hindcast of the surge is the Best trackThe data second ingested wind in thefield GAHM to be used model. in the Hurricane present Beststudy track for orthe forecast hindcast data of the contains surge someis the basic Best information,track data ingested including in the eye GAHM location model. and time, Hurricane maximum Best wind track speed or forecast and radius, data andcontains central some pressure. basic Theinformation, Dynamic including Holland modeleye location [19] calculates and time, somemaximum parameters wind speed from and those radius, data toand apply central in empiricalpressure. equationsThe Dynamic to calculate Holland the model atmospheric [19] calculates pressure some and parameters gradient wind from velocity, those data from to which apply wind in empirical velocity equations to calculate the atmospheric pressure and gradient wind velocity, from which wind velocity at 10 m height is calculated [46]. This model assumes symmetric distribution of the wind

J. Mar. Sci. Eng. 2019, 7, 77 5 of 30 at 10 m height is calculated [46]. This model assumes symmetric distribution of the wind field. However, hurricanes often have asymmetric wind field distributions. The Asymmetric Holland Model (AHM) uses either R64, R50, or R34 distance to strongest wind isotach (i.e., 64 kt, 50 kt, or 34 kt away from the eye) to solve for a different maximum radius in each storm quadrant (NE, NW, SW, SE) [47,48]. In other words, the AHM uses the single strongest isotach in each quadrant. The AHM is a significant improvement over the Dynamic Holland Model. A further improvement over the AHM model is the GAHM [49]. The GAHM is an adaptation from the asymmetric Holland model [47,48] that has been modified to use information from all available isotachs, and the wind structure information includes radii of maximum winds for the 34, 50, 64, and 100 knots isotachs reported [57] in the four quadrants (NE, SE, SW, and NW). The third wind data sets to be used for the forecast of storm surge are produced from WRF, a numerical weather forecasting model, which is designed to serve both operational forecasting and atmospheric research needs [18,44,58]. The atmosphere is a fluid of air parcels in constant motion, which turns completely chaotic during a hurricane. Mathematical equations are derived to describe various motions and interactions that occur in the atmosphere and oceans. The WRF model numerically solves those equations. WRF needs a domain of study, its topological and geographical features, meteorological initial and boundary conditions, etc. The output of WRF includes hurricane wind velocities and free surface pressure, which are the input for ADCIRC+SWAN. WRF is known to generate reasonable details of hurricane dynamics [59]. The WRF model configuration used in the present study is presented below in Table1, which is taken from literature [30,32,60].

Table 1. Weather Research and Forecasting (WRF) model conﬁguration.

Parameter Conﬁguration Initial conditions NCEP 1◦ by 1◦ ﬁnal analysis (FNL) Map projection Lambert Horizontal grid distance 15 km NCEP time interval 6 h Time step 60 Microphysics WSM6 Longwave radiation RRTM Shortwave radiation Dudhia Cumulus parameterization Kain-Fritsch PBL parameterization Yonsei University (YSU) scheme Land Surface option NOAH land surface model

The fourth wind products to be used for forecast of storm surges are the archived advisories of Hurricane Rita ingested in the GAHM wind model. Advisories contain some basic information of the forecasted hurricane including projected eye location, time, maximum wind speed, hurricane radius, and estimated minimum central pressure. The GAHM wind model produces wind and pressure fields from the limited advisory data. The impact of meteorological forcing from abovementioned hindcast and forecast sources on the generation and propagation of storm surges is investigated. High fidelity spatially varying nodal attributes of Manning’s roughness coefficient, directional roughness length, primitive weighting in continuity equations, etc., tidal, and lateral boundary conditions are used and kept same for all runs to rule out their influences on the comparative study. The wind drag coefficient formulation due to Powell [61] with a cap of Cd ≤ 0.002 is used in both ADCIRC and SWAN. The main tidal constituents, K1, O1, Q1, P1, M2, K2, N2, and S2 are generated from the EC2001 tidal database [62,63].

3. Simulation Cases and Capability Criteria Two hindcast simulations using wind fields from OWI and Best track ingested in GAHM, and ten forecast simulations using wind fields from WRF and advisories ingested in GAHM were performed J. Mar. Sci. Eng. 2019, 7, 77 6 of 30 in this study. The starting dates for WRF forecast and advisory cases range from 3.5 days to 0.2 days before the landfall. Since ADCIRC+SWAN needs a longer run duration, wind fields of the earlier part of the hurricane are filled in with OWI, which are supposed to be already known at the beginning of the forecast. Alternatively, the Best track wind data ingested in GAHM model could be used instead of the OWI wind field for the pre-forecast durations. Each simulation is cold started on 0000 UTC 13 August 2005, with a 36-day tides-only period that allows the tides to reach a dynamic equilibrium. This is followed by a 7.2-day Rita simulation from 0000 UTC 18 September of 2005 to 0500 UTC 26 September of 2005. That means the OWI wind field is used from 0000 UTC 18 September of 2005 until the WRF forecast and advisory starting times. Qualitative and quantitative comparisons using water level time series and high-water marks (HWM) of simulated results and observed data are presented for the station locations (see Table2). These observation station locations with respect to the Hurricane Rita track are shown in Figure1b. Eight stations are located on the right (or east), and four stations are on the left (or west) side of the track.

Table 2. Locations of United States Geological Survey (USGS) [64] Deployed (DEPL) observation stations. Note: LA10, LC13, LF5, etc. are identiﬁcation tags for station locations.

ID Station Longitude (◦) Latitude (◦) C USGS-DEPL LA10 −92.67552 29.70658 D USGS-DEPL LA12 −93.11494 29.7861 E USGS-DEPL LA9 −92.32792 29.74476 F USGS-DEPL LC13 −93.75285 29.76407 G USGS-DEPL LC6a −93.34333 30.00432 H USGS-DEPL LC8a −93.32886 29.79764 I USGS-DEPL LC9 −93.47052 29.81823 J USGS-DEPL LF5 −92.12703 29.88604 8770570 Sabine Pass North, TX −93.87000 29.72833 8770971 Rollover Pass, TX −94.51000 29.51500 8771341 Galveston Bay Entrance, North Jetty, TX −94.72500 29.35667 8771013 Eagle Point, Galveston Bay, TX −94.91833 29.48000

Simulation capability is quantified using the capability criterion used in Kerr et al. [56]. These are repeated here for clarity: Coefficient of determination (R2 is a number that indicates how well data fit a regression line, with an ideal value of one), root mean square error (ERMS is a measure of the magnitude of error, with an ideal value of zero), mean error (E), slope of the best fit line (m, with an ideal value of one), mean normalized bias (Bmn is a measure of the model’s magnitude of overprediction or underprediction normalized to the observed value, with an ideal value of zero):

1 ∑N E B = N i=1 i mn 1 N (1) N ∑i |Oi| where O is the observed value, E is the error in terms of simulated minus observed and N is the number of data points. Scatter index (SI), which is the standard deviation normalized by the mean observed value, with an ideal value of zero): v u 2 u 1 ∑N E − E SI = t N i=1 i 1 N (2) N ∑i=1|Oi|

Mean absolute error (MAE), and mean normalized error (ENORM, which is the mean error normalized by the mean observed value, with an ideal value of zero): v u 1 N 2 u ∑ (Ei) E = t N i=1 . (3) NORM 1 N 2 N ∑i=1(Oi) J. Mar. Sci. Eng. 2019, 7, 77 7 of 30

Throughout the simulations, some of the HWM’s locations are predicted to be dry, although this varies from case to case. In the statistical analyses of HWMs, only wet locations predicted by simulations are considered [56]. Note that the HWM points are distributed in Louisiana and Texas coasts, but most of the points are in Louisiana on the east side of Rita’s landfall location.

4. Results and Discussion To understand the storm surge generation and propagation of a hurricane, relevant meteorological forcing used in ADCIRC+SWAN must be analyzed first. The OWI model is used here as the default meteorological forcing source, as in some of the previous studies [56,65]. Another popular wind field source is the Best track wind data ingested into the GAHM model. Comparison of wind fields and storm surges produced by using the Best track in GAHM against those of OWI are discussed in the following subsection. Comparison of wind fields and storm surges produced using WRF and advisory forecasts in GAHM against those using OWI are discussed in the subsequent subsections.

4.1. Comparison of Storm Surge Hindcasts Using OWI and Best Track Ingested in GAHM Wind fields from OWI and from Best track ingested in GAHM produce distinctive patterns as shown in Figure2a,b (maximum wind fields created using OWI and Best track in the GAHM model). The hurricane actual track line is shown on all color plots. These plots clearly illustrate that the right sector of Hurricane Rita had higher wind velocity than the left one, as expected. However, the wind field from Best track in the GAHM is much stronger than that of OWI. The OWI has a noticeably weaker wind field near landfall area than that of Best track in GAHM. Far away from the landfall area, the wind field gradually decays in OWI, whereas the wind field from Best track in GAHM dies off more quickly. These contrasting representations can be observed from Figure2c,d, which show the wind vectors at 8:30 a.m. on 24 September of 2005. The asymmetry of wind from the Best track in GAHM is not as pronounced as that of OWI. Unique geographical features around the landfall of Hurricane Rita produce the distinctive hindcast of water elevation and velocity. Water is pushed against the shoreline near Pecan Island (see Figure1b) to cause about 5 m surge at the right/east of landfall, while water at the left/west side could slide past the coast, near the Galveston area, very easily, causing not more than 3 m surge there, as reported in [65]. Figure2e,f shows water elevations and velocity vectors at 8:30 a.m. on 24 September of 2005 obtained using OWI and Best track in GAHM wind fields, respectively. A closer inspection shows that Best track in GAHM (Figure2f) causes peak surge in a more narrow geographical area mostly on the right side of the track, and its southward velocity vectors are weaker than those of OWI (Figure2e). Figure2g displays maximum water elevation for OWI, which inundates a broader coastal area from Louisiana to Texas. Figure2h, on the other hand, shows maximum water elevation from Best track in GAHM (while similar to that of OWI), more localized near the landfall area. The maximum water velocities are shown in Figure2i,j. The maximum surge velocity is more pronounced and localized for the Best track in GAHM than OWI, which is consistent with the former’s narrower and stronger wind field (Figure2b). Both OWI and Best track in GAHM seem to be good candidates to be the default case for inter-model comparison purposes, at least qualitatively. However, it was found that OWI was a better choice after results were quantitatively compared against buoy tide gages and high water marks, as is discussed in the subsequent subsections. Therefore, all pertinent comparisons are eventually done against OWI hindcast results. J. Mar. Sci. Eng. 2019, 7, 77 8 of 30

J. Mar. Sci. Eng. 2019, 7, 77 8 of 32

(a) (b)

(e) (f)

(g) (h)

Figure 2. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 9 of 30

J. Mar. Sci. Eng. 2019, 7, 77 9 of 32

(i) (j)

FigureFigure 2. Wind2. Wind ﬁeld field and and storm storm surge surge hindcast hindcast resultsresults using Oceanweather Inc. Inc. (OWI (OWI)) (a (,ca,,ec,,ge,,ig) ,andi) and BestBest track track in in Generalized Generalized Asymmetric Asymmetric HollandHolland ModelModel (GAHM)(GAHM) −− NWSNWS = =20 20 option option (b (,db,,fd,h,f,,jh),, j(),a, (ba), b) maximummaximum wind wind track; track; (c (,cd,d)) Wind Wind vector vector atat 8:308:30 a.m.,a.m., 24 September September of of 2005; 2005; (e (,ef,)f Water) Water elevation elevation and and velocityvelocity vector vector at at 8:30 8:30 a.m., a.m. 24, 24 September September ofof 2005;2005; (g,,h) maximum water water elevation; elevation; (i, (ji), jmaximum) maximum waterwater velocity. velocity.

4.2.4.2. Storm Storm Surges Surges Using Using WRF WRF Forecasts Forecasts FiveFive WRF WRF simulations simulations are are performed performed toto examineexamine the sensitivity sensitivity of of ‘forecasted’ ‘forecasted’ storm storm intensities intensities andand tracks tracks to to their their starting starting or or initialization initialization times.times. The first first simulation simulation (WRF (WRF Run Run 1) 1) was was initialized initialized at at 09/22/200509/22/2005 0000 0000 UTC,UTC, approximatelyapproximately 56 h befo beforere the the landfall. landfall. The The initialization initialization times times of ofsubsequent subsequent simulationssimulations were were decreased decreased by by 12 12 h. h. DetailsDetails of of simulation simulation initialization initialization times times are are summarized summarized in in TableTable3. All3. All simulations simulations were were stopped stopped at at 1200 1200 UTC UTC onon 2525 SeptemberSeptember of 2005. WRF WRF outputs outputs were were processedprocessed to prepareto prepare the the wind wind fields fields for ADCIRC+SWAN.for ADCIRC+SWAN. For For the durationthe duration from from 09/18/2005 09/18/2005 0000 0000 UTC UTC to WRF initialization times, the OWI wind fields were used in ADCIRC+SWAN to produce the to WRF initialization times, the OWI wind fields were used in ADCIRC+SWAN to produce the hindcast hindcast of Rita storm surges and to create hot start files. These hot start files were then used in of Rita storm surges and to create hot start files. These hot start files were then used in ADCIRC+SWAN ADCIRC+SWAN to restart the simulation with WRF wind fields to forecast the surge. Note that wind to restart the simulation with WRF wind fields to forecast the surge. Note that wind fields from the fields from the Best track in GAHM were originally used for the hindcast durations (when the storm Best track in GAHM were originally used for the hindcast durations (when the storm was still far from was still far from shore) and the influence of wind fields in the middle of the ocean on coastal surges shore)occurring and the days influence later was of not wind significant. fields in Since the middle OWI wind of the fields ocean are on observation coastal surges-based, occurring considered days latermore was reliable, not significant. and should Since be OWIavailable wind for fields hindcast are observation-based,periods, a decision was considered made to more use OWI reliable, win andd shouldfields be instead available of those for hindcast of Best track periods, in GAHM a decision for all was ‘forecast’ made tostudies use OWI performed wind fields here. instead of those of Best track in GAHM for all ‘forecast’ studies performed here. Table 3. Description of WRF runs and initialization times for surge forecasts. Table 3. Description of WRF runs and initialization times for surge forecasts. Simulation Number Initialization Time (UTC) Hours before Landfall SimulationWRF Run Number 1 Initialization9/22/2005 Time 0000 (UTC) Hours before56 Landfall WRFWRF Run Run 1 2 9/22/20059/22/2005 00001200 44 56 WRFWRF Run Run 2 3 9/22/20059/23/2005 12000000 32 44 WRFWRF Run Run 3 4 9/23/20059/23/2005 00001200 20 32 WRFWRF Run Run 4 5 9/23/20059/24/2005 12000000 208 WRF Run 5 9/24/2005 0000 8 4.2.1. Comparison of Wind Fields from WRF and OWI 4.2.1. Comparison of Wind Fields from WRF and OWI The hybrid OWI and WRF maximum wind fields are displayed in Figure 3. WRF maximum windThe fields hybrid are OWI noticeably and WRF wider maximum and weaker wind than fields that of are OWI displayed (either Figure in Figure 2a 3or. Figure WRF maximum 3f) or of windBest fields track arein GAHM noticeably (Figure wider 2b). andHowever, weaker WRF than hurricane that of OWIpredictions (either are Figure reas2onablya or Figure accurate3f) orand of Bestgenerally track in go GAHM over the (Figure track2 line,b). However, although the WRF exact hurricane curvature predictions of the track are is reasonably missing from accurate all WRF and generallywind fields. go over A thecareful track inspection line, although of Figure the exact 3a–c curvature reveals that of the the track landfall is missing locations from of all some WRF WRF wind fields.predicted A careful hurricanes inspection are slightly of Figure off3 aa–cs well. reveals For example, that the landfallWRF Run locations 3 lands ofa bit some west WRF of the predicted actual hurricaneslandfall location, are slightly and offits overall as well. wind For field example, is stronger WRF than Run those 3 lands of other a bit westWRF ofruns. the Although actual landfall this location,is a small and departure its overall from wind the field actual is stronger landfall than location, those it of makes other WRF an important runs. Although difference this in is surge a small departuregeneration from and the propagation actual landfall characteristics, location, it as makes discussed an important later. All difference WRF results in surge predicted generation reduced and

J. Mar. Sci. Eng. 2019, 7, 77 10 of 30 propagationJ. Mar. Sci. Eng. characteristics, 2019, 7, 77 as discussed later. All WRF results predicted reduced peak wind10 of speed 32 before landfall, correctly indicating the weakened status of Rita at that point, which is obvious in the peak wind speed before landfall, correctly indicating the weakened status of Rita at that point, which OWI wind ﬁeld as well. The choice of WRF physics setup plays an important role in the accuracy of is obvious in the OWI wind field as well. The choice of WRF physics setup plays an important role in wind ﬁeld prediction. the accuracy of wind field prediction.

(a) (b)

(e) (f)

FigureFigure 3. 3.Rita Rita maximum maximum wind wind track track plots plots using using wind wind ﬁelds fields from from WRF WRF and and OWI OWI models. models. (a )(a WRF) WRF Run 1, (Runb) WRF 1, (b) Run WRF 2, Run (c) WRF 2, (c) RunWRF 3, Run (d) 3, WRF (d) WRF Run 4,Run (e )4, WRF (e) WRF Run Run 5, and 5, and (f) OWI.(f) OWI.

4.2.2.4.2.2. Comparison Comparison of of Storm Storm Surges Surges UsingUsing WRFWRF and OWI Wind Wind Fields Fields FigureFigure4 shows4 shows the the maximum maximum water water elevationelevation color plots generated generated from from different different storm storm surge surge forecastsforecasts using using the the WRF WRF and and OWI OWI wind wind fields, fields, as shownas shown in Figurein Figure3. The 3. The water water surface surface elevations elevations were significantlywere significantly lower for lower all WRFfor all cases WRF (Figurecases (Figure4a–e) than4a–e) those than ofthose OWI of (FigureOWI (Figure4f). However, 4f). However, the extent the ofextent inundation of inundation was as broad was as or broad even greateror even thangreater the than extent the for extent OWI. for The OWI. finding The finding is somewhat is somewh expected,at givenexpected, that WRF given wind that WRF fields wind are wider. fields are Among wider. all Among WRF runs, all WRF Run runs, 3 seems Run to3 seems generate to generate a maximum a maximum water surface elevation closest to that of the OWI. Figure 5 shows the maximum water water surface elevation closest to that of the OWI. Figure5 shows the maximum water velocity color velocity color plots produced from different storm surge runs using the WRF and OWI wind fields, plots produced from different storm surge runs using the WRF and OWI wind fields, as shown in as shown in Figure 3. The velocity plots show significantly weaker maximum water velocity fields from WRF runs compared with OWI.

J. Mar. Sci. Eng. 2019, 7, 77 11 of 30

Figure3. The velocity plots show signiﬁcantly weaker maximum water velocity ﬁelds from WRF runs compared with OWI. J. Mar. Sci. Eng. 2019, 7, 77 11 of 32 J. Mar. Sci. Eng. 2019, 7, 77 11 of 32

(a) (b) (a) (b)

(e) (f) (e) (f) FigureFigure 4. Rita 4. Rita maximum maximum water water elevation elevation fromfrom ADvanced CIRCulation CIRCulation + Simulating + Simulating Waves Waves Nearshore Nearshore Figure 4. Rita maximum water elevation from ADvanced CIRCulation + Simulating Waves Nearshore (ADCIRC+SWAN)(ADCIRC+SWAN simulation) simulation results results using using windwind fields ﬁelds from from WRF WRF and and OWI OWI models. models. (a) WRF (a) WRF Run 1, Run 1, ((bADCIRC+SWAN) WRF Run 2, (c)) WRFsimulation Run 3, results (d) WRF using Run wind 4, (e )fields WRF fromRun 5,WRF and and (f) OWI.OWI models. (a) WRF Run 1, (b) WRF(b) WRF Run Run 2, (c 2,) WRF(c) WRF Run Run 3, (3,d ()d WRF) WRF Run Run 4, 4, ((ee)) WRFWRF Run Run 5, 5, and and (f ()f OWI.) OWI.

(a) (b) (a) (b)

Figure 5. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 12 of 30

J. Mar. Sci. Eng. 2019, 7, 77 12 of 32

(e) (f)

FigureFigure 5. Rita 5. Rita maximum maximum water water velocity velocity from from ADCIRC+SWANADCIRC+SWAN simulation simulation results results using using wind wind fields ﬁelds fromfrom WRF WRF and and OWI OWI models. models. (a )(a WRF) WRF Run Run 1, 1, ( (bb)) WRFWRF Run Run 2, 2, (c ()c )WRF WRF Run Run 3, ( 3,d) ( WRFd) WRF Run Run 4, (e) 4, WRF (e) WRF Run 5,Run and 5, (andf) OWI. (f) OWI.

4.2.3.4.2.3. Quantitative Quantitative Differences Differences between between the the WRF WRF ForecastForecast and and OWI OWI Hindcast Hindcast To quantifyTo quantify differences, differences, maximum maximum wind, wind, maximummaximum water water elevation elevation and and velocity velocity of WRF of WRF runs runs were subtracted from those of the OWI run. For brevity, differences only between OWI and WRF Run were subtracted from those of the OWI run. For brevity, differences only between OWI and WRF 3 results are reported here in Figure 6 since it (i.e., WRF Run 3) appeared to be the best WRF case. Run 3Figure results 6a areshows reported that the hereWRF inRun Figure 3 maximum6 since wind it (i.e., speed WRF near Run the 3)coastal appeared regions to was be theweaker best by WRF case.about Figure 106a m/s shows (see that inside the purple WRFRun oval) 3 maximumthan that of wind OWI, speed which near can thebe coastalqualitatively regions verified was weaker by by aboutcomparing 10 m/s Figure (see 3c inside,f. Otherwise, purple Figure oval) than6a shows that that of OWI, WRF wind which was can stronger, be qualitatively at some places verified by by comparing20 m/s, Figurethan that3c,f. of OWI Otherwise, on the left Figure side of6a the shows track. that On the WRF right wind side wasof the stronger, track, the atOWI some wind places was by 20 m/s,slightly than stronger that of OWI near onthe thetrack left and side at ofsome the track.scattered On places. the right Although side of WRF the track, wind thevectors OWI at wind 8:30 was slightlya.m. stronger, 24 September near the of track2005 were and atstronger somescattered near landfall, places. as seen Although in Figure WRF 6b, wind the presence vectors of at 8:30land a.m., 24 Septemberweakened of its 2005 wind were very stronger quickly, leading near landfall, to the situation as seen indescribed Figure6 inb, Figure the presence 6a (purp ofle landoval). weakened Most its windlikely very this quickly,weakening leading is directly to therelated situation to the physics described and land in Figure resistance6a (purple setup used oval). in WRF. Most Overall, likely this the WRF wind vortex is more symmetric than that of OWI. weakening is directly related to the physics and land resistance setup used in WRF. Overall, the WRF The maximum water elevation generated by the OWI wind field was higher by 1 m than that of windWRF vortex Run is 3 more on the symmetric right/eastside than of thatthe track, of OWI. as seen in Figure 6c. On the east side of the Rita landfall Thelocation maximum near Pecan water Island, elevation water was generated pushed byagainst theOWI the shoreline, wind field more was so higherfor the OWI by 1 wind m than field that of WRFthat Run is3 on asymmetric the right/eastside in nature of and the stron track,ger as near seen shoreline.in Figure 6Onc. On the the other east hand, side of water the Rita on landfall the locationleft/westside near Pecan of the Island, landfall water location was pushedflowed southward against the uninterrupted, shoreline, more especially so for for the OWI OWI due wind its field that isweaker asymmetric wind field in nature there. andWRF stronger Run 3 generated near shoreline. about 1 m On higher the other water hand, elevation water on on the the west left/westside side of of thethe landfall track. locationAs seen in flowed Figure southward6d, the maximum uninterrupted, water velocity especially generated for OWIby the due OWI its wind weaker field wind was field there.consistently WRF Run higher 3 generated by 1 m/s about on the 1 east m higher side of waterthe track, elevation but similarly on the lower west than side that of theof WRF track. Run As 3 seen in Figureon the6d, west the side. maximum These findings water velocity are consistent generated with the by relevant the OWI wind wind fields. field was consistently higher by 1 m/s on the east side of the track, but similarly lower than that of WRF Run 3 on the west side. These findings are consistent with the relevant wind fields.

J. Mar. Sci. Eng. 2019, 7, 77 13 of 30

J. Mar. Sci. Eng. 2019, 7, 77 13 of 32

(a) (b)

FigureFigure 6. 6.Differences Differences and and contrasts contrasts between between OWI OWI hindcasthindcast andand WRF Run 3 3—initialized—initialized at at 9/23/05 9/23/05 0000 0000 forecastforecast results results of of Hurricane Hurricane Rita Rita storm storm surges:surges: (a) difference of of maximum maximum wind wind speed, speed, (b ()b contrast) contrast ofof wind wind vectors vectors at at landfall, landfall, ( c()c) difference difference ofof maximummaximum water water elevation, elevation, and and (d ()d difference) difference of ofwater water velocity.velocity. The The black black dots dots are are the the locations locations of ofeight eight stationsstations listed in Table Table 22..

4.2.4.4.2.4. Comparison Comparison of of Surge Surge Time Time Series Series UsingUsing WRF,WRF, OWI,OWI, and Best Track Track in in GAHM GAHM Winds Winds TheThe ADCIRC+SWAN ADCIRC+SWAN water water level level time time series series were were compared compared to observed to observed water levels water at stations levels at stations(displayed (displayed on Figure on 1b). Figure Awa1b).y from Away landfall from at landfall station at(J), station Figure (J),7a indicates Figure7 athat indicates OWI simulation that OWI simulationaccurately accurately predicted predictedthe surge propagation, the surge propagation, but with an but early with peak an arrival early peakby about arrival 3~4 by h. aboutKerr et 3~4 al. h. Kerr[56] et indicated al. [56] indicated a possible a error possible in the error hydraulic in the connectivity hydraulic connectivityin the marsh inas the reason. marsh asTheir the study reason. Theirindicated study indicated that bottom that friction, bottom mesh friction, resolution, mesh resolution, and other and features other may features have may contributed have contributed to the mismatch between simulated results and observed data. The station seemed to be inundated hours to the mismatch between simulated results and observed data. The station seemed to be inundated before the arrival of the peak, whereas the simulation predicted zero water elevation at the beginning hours before the arrival of the peak, whereas the simulation predicted zero water elevation at the and then a subsequent sudden rise of water. The Best track in GAHM simulation behaved about the beginning and then a subsequent sudden rise of water. The Best track in GAHM simulation behaved same, except for a closer match of the peak with the observed data. The peak arrivals for WRF runs about the same, except for a closer match of the peak with the observed data. The peak arrivals for were hastened or delayed by different durations, although the peak magnitudes matched reasonably WRF runs were hastened or delayed by different durations, although the peak magnitudes matched well with the observed data. Weather Research and Forecasting Run 3 seems to have a delayed arrival reasonablyof the peak well by withabout the 3 h observed, however. data. Recall Weather that WRF Research Run 3 land andfall Forecasting is on the west Run side 3 seems of the to actual have a delayedlandfall arrival (refer ofto theFigure peak 4c), by i.e., about further 3 h, however.away from Recall station that J. Therefore, WRF Run a 3 delayed landfall peak is on arrival the west was side ofexpected the actual for landfall this run. (refer to Figure4c), i.e., further away from station J. Therefore, a delayed peak arrivalIn was the expected region of for landfall, this run. Figure 7b–e at stations (H, I, D, and F), both OWI and Best track in GAHMIn the cases region overpredict of landfall, the Figurewater elevation7b–e at stations peak by (H,0.5 I,m D,to and1 m at F), most both stations, OWI and some Best of trackwhich in GAHMKerr et cases al. [56] overpredict attributed theto improper water elevation road resolution. peak by All 0.5 WRF m to 1runs m atunderpredict most stations, the somepeak by of which0.25 Kerrm to et al.1 m [ 56at ]most attributed stations, to probably improper directly road resolution. related to Alltheir WRF weak runs wind underpredict fields. Expectedly, the peak WRF by Run 0.25 m to 13 mhas at delayed most stations, peak arrivals probably by directlyabout 3 relatedh. Otherwise, to their WRF weak Run wind 3 peak ﬁelds. heights Expectedly, are the WRF highest Run and 3 has delayedclosest peak to the arrivals observed by ones about among 3 h. Otherwise, all WRF runs. WRF Run 3 peak heights are the highest and closest to the observedAt inland ones stations among (E, all C, WRF and runs. G) (Figure 7f–h), both OWI and the Best track in GAHM cases overpredictedAt inland stations the peak (E, water C, andlevels G) with (Figure a phase7f–h), lead both by 1 OWI to 7 andh. All the WRF Best runs track also in overpredicted GAHM cases overpredictedthe water elevation the peak peak, water although levels somewh with a phaseat less in lead extent by 1and to 7with h. Allsome WRF reduced runs phase also overpredicted lead/delay. theThe water phase elevation lead or peak,delay of although WRF runs somewhat varied significantly. less in extent The and Run with 3 seemed some reducedto have the phase least lead/delay. amount Theof phasephase leaddifference or delay from of WRFthe observation runs varied data, signiﬁcantly. which again The was Run due 3 seemedto the distant to have landfall the least locatio amountn

J. Mar. Sci. Eng. 2019, 7, 77 14 of 30 of phase difference from the observation data, which again was due to the distant landfall location J. Mar. Sci. Eng. 2019, 7, 77 14 of 32 from these stations. For station C, WRF Run 3 had a delayed peak arrival by about 3~4 h, which can be attributedfrom these to the stations. station For not station being C, directly WRF Run in its3 had surge a delayed generation peak arrival and propagation by about 3~4 path. h, which can beFour attributed stations to are the chosenstation not on thebeing west directly side in of its the surge landfall. generation Stations and K, propagation N, and O arepath. along the coast, while theFour station stations Q is are inside chosen the on Galveston the west side Bay of area the (seelandfall. Figure Stations1b). AsK, N, shown and O in are Figure along7 thei–k, coast, the OWI and Bestwhile trackthe station in GAHM Q is inside winds the Galveston generally Bay overpredict area (see Figure the surge 1b). As with shown some in Figure phase 7i– leads.k, the OWI Modeled surgesand propagate Best track quicklyin GAHM along winds the generally Texas coast overpredict uninterrupted the surge and with the some early phase arrivals leads. of Modeled the peaks at surges propagate quickly along the Texas coast uninterrupted and the early arrivals of the peaks at stations K, N, and O conﬁrm this. The double surge peaks shown by OWI and Best track in GAHM is stations K, N, and O confirm this. The double surge peaks shown by OWI and Best track in GAHM an interesting feature displayed at both stations N and O, probably resulting from the transient pattern is an interesting feature displayed at both stations N and O, probably resulting from the transient relevantpattern to thoserelevant wind to those ﬁelds. wind WRF fields. winds WRF generally winds generally predict slightlypredict slightly lower surgelower peakssurge peaks but with but some phasewith leads, some similar phase to leads, those similar of OWI to surges.those of The OWI double surges. peaks The double are not peaks visible are in not WRF visible surges in inWRF stations N andsurges O. As in shownstations inN Figureand O.7 Asl, the shown Galveston in Figure Bay 7l, station,the Galveston Q, is awayBay station, from theQ, is direct away pathfrom ofthe surge propagationdirect path and of all surge cases propagation generally predict and all the cases peak generally well with predict few phase the peak differences. well with Note few that phase station N haddifferences. a discontinuity Note that in station buoy data N had for a adiscontinuity few hours, andin buoy reason data isfor not a few known hours, to and the authors.reason is not knownOverall, to thethe Bestauthors. track in the GAHM simulation performed somewhat similarly to those of OWI for these limitedOverall, number the Best of track stations. in the However, GAHM simulation the HWM performed analysis somewhat presented similarly below with to those 144 of observation OWI for these limited number of stations. However, the HWM analysis presented below with 144 points reveals that storm surge generation and propagation simulated by Best track in GAHM was not observation points reveals that storm surge generation and propagation simulated by Best track in as accurate as those of OWI and WRF forecasts. GAHM was not as accurate as those of OWI and WRF forecasts.

(a) (b)

(e) (f)

Figure 7. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 15 of 30

J. Mar. Sci. Eng. 2019, 7, 77 15 of 32

(g) (h)

(i) (j)

(k) (l)

FigureFigure 7. 7Effect. Effect of of wind wind fieldsfields from from WRF, WRF, OWI, OWI, and and Best Besttrack track in GAHM in GAHM models:models: Observed Observed and andADCIRC+SWAN modeled modeled significant significant water waterlevel time level series time at seriesdifferent at observation different observation stations during stations the time of Hurricane Rita (9/22-25/05). (a) J—USGS-DEPL LF5; (b) H—USGS-DEPL LC8a; (c) I— during the time of Hurricane Rita (9/22-25/05). (a) J—USGS-DEPL LF5; (b) H—USGS-DEPL LC8a; USGS-DEPL LC9; (d) D—USGS-DEPL LA12; (e) F—USGS-DEPL LC13; (f) E—USGS-DEPL LA9; (g) (c) I—USGS-DEPL LC9; (d) D—USGS-DEPL LA12; (e) F—USGS-DEPL LC13; (f) E—USGS-DEPL C—USGS-DEPL LA10; (h) G—USGS-DEPL LC6a; (i) K—ID 8770570, Sabine Pass North, TX; (j) N— LA9; (g) C—USGS-DEPL LA10; (h) G—USGS-DEPL LC6a; (i) K—ID 8770570, Sabine Pass North, TX; ID 8770971, Rollover Pass, TX; (k) O—ID 8771341, Galveston Bay Entrance, North Jetty, TX; (l) Q—ID (j) N—ID8771013, 8770971, Eagle Poin Rollovert, Galveston Pass, Bay, TX; TX. (k ) O—ID 8771341, Galveston Bay Entrance, North Jetty, TX; (l) Q—ID 8771013, Eagle Point, Galveston Bay, TX. 4.2.5. Comparison of High Water Mark Using WRF, OWI, and Best Track in GAHM Winds 4.2.5. Comparison of High Water Mark Using WRF, OWI, and Best Track in GAHM Winds The maximum water elevations were compared for each of the simulations to measured high waterThe maximum marks (HWMs) water [64] elevations in Figure 8. were Just comparedas in Kerr et for al. each[56], only of the wet simulations stations were to used measured for all high watersimulated marks (HWMs)HWM analysis. [64] in The Figure summarized8. Just asstatistics in Kerr are et given al. [ 56in ],Table only 4. wetKerr stations et al. [56] were obtained used an for all simulatedR2 value HWM of 0.663 analysis. using the The lumped summarized-explicit solver statistics option are in given the ADCIRC+SWAN in Table4. Kerr etmodel al. [ to56 hindcast] obtained an R2 valueRita’s of storm 0.663 surge using usi theng the lumped-explicit OWI wind field. solver The present option study, in the which ADCIRC+SWAN used the semi-implicit model tosolver hindcast Rita’soption storm of surgeADCIRC+SWAN, using the OWI obtained wind 0.704 field. for The the presentOWI model, study, as whichshown usedin Table the 4. semi-implicit All WRF runs solver optionhad of higher ADCIRC+SWAN, correlation coefficients, obtained lower 0.704 mean for errors, the OWI Biases, model, SIs and as shownMAEs than in Table those4 of. AllOWI. WRF The runs number of dry locations was either 9 or 10 for WRF runs, whereas the OWI run had seven dry had higher correlation coefficients, lower mean errors, Biases, SIs and MAEs than those of OWI. locations. With 23 dry locations (a large number) the Best track in GAHM case had the lowest The number of dry locations was either 9 or 10 for WRF runs, whereas the OWI run had seven dry locations. With 23 dry locations (a large number) the Best track in GAHM case had the lowest correlation coefficient. As caveat, the correlation coefficient alone may be a misleading criterion to judge the HWM comparison [65]. A simulation may produce a lower inundation extent, yet score a J. Mar.J. Mar. Sci. Eng.Sci. Eng.2019 2019, 7,, 777, 77 16 of 3216 of 30

correlation coefficient. As caveat, the correlation coefficient alone may be a misleading criterion to highjudge correlation the HWM coefﬁcient comparison since [65]. dry A simulation locations aremay typically produce ignoreda lower inundation from thestatistics. extent, yetThe score case a was differenthigh correlation here, however. coefficient It was since remarkable dry locations that allare WRFtypically cases ignored had high from correlation the statistics. coefﬁcients, The case was yet most locationsdifferent were here, wet. however. The comparison It was remarkable against that the all orange WRF paritycases had line high shows correlation that low coefficients, surge HWMs yet were overpredictedmost locations and were high wet. surge The comparison HWMs were against underpredicted the orange parity by all line WRF shows cases. that low High surge Water HWMs Marks of bothwere OWI overpredicted and the Best and track high in surge GAHM HWMs were were closer underp to theredicted parity by line, all WRF although cases. High both Water overpredicted Marks the of both OWI and the Best track in GAHM were closer to the parity line, although both overpredicted surge in most wet locations. Considering only the wet nodes, the Best track in GAHM has lower or the surge in most wet locations. Considering only the wet nodes, the Best track in GAHM has lower comparable values of root mean square error (ERMS), mean error (E), mean normalized bias (BMN), or comparable values of root mean square error (ERMS), mean error (퐸̅), mean normalized bias (BMN), MAE E meanmean absolute absolute error error ( (MAE),) and, and mean mean normalized normalized error error (E (NORMNORM) than) than OWI. OWI. However, However, the scatter the scatter indicesindices (σ and (σ andSI SI) of) of Best Best track track inin GAHM are are larger larger than than those those of OWI. of OWI. On the On c theontrary, contrary, all error all and error and scatterscatter indices indices for for WRF WRF Run Run 3 3 are are less less thanthan those of of OWI. OWI.

Figure 8. Cont.

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J. Mar. Sci. Eng. 2019, 7, 77 17 of 32

FigureFigure 8. Scatter8. Scatter plots plots of of Rita Rita highhigh water marks marks (HWM (HWM’s)’s) from from ADCIRC+SWAN ADCIRC+SWAN simulations simulations using using windwind ﬁelds fields from from WRF, WRF, OWI, OWI, and and Best Best track track in in GAHM GAHM models. models. ((aa)) WRFWRF Run 1, 1, ( (bb)) WRF WRF Run Run 2, 2, (c ()c ) WRF RunWRF 3, (d Run) WRF 3, (d Run) WRF 4, Run (e) WRF 4, (e) RunWRF50, Run (f 50,) OWI, (f) OWI, and and (g) ( Bestg) Best track track in in GAHM. GAHM. Red Red diamonddiamond and and black trianglesblack triangles indicate indicate underprediction underprediction by the by model; the model; purple purple triangles triangles and and light light green green squares squares indicate overprediction.indicate overprediction. Dark green Dark circles green indicate circles aindicate match a within match 0.5within m. The0.5 m. black The lineblack represents line represents the best ﬁt lines.the The best orange fit lines. line The isorange the parity. line is the parity.

Table 4. HWM error statistics for Rita surge forecast and hindcast using wind ﬁelds from WRF, OWI, and Best Track in GAHM.

2 ¯ Case R ERMS (m) E (m) BMN (-) σ (m) SI (-) MAE (m) ENORM (-) Dry Wet WRF Run 1 0.760 0.459 0.256 0.108 0.629 0.407 0.534 0.068 10 134 WRF Run 2 0.769 0.443 0.295 0.125 0.598 0.387 0.520 0.068 10 134 WRF Run 3 0.745 0.515 0.391 0.166 0.604 0.392 0.564 0.077 9 135 WRF Run 4 0.749 0.470 0.153 0.065 0.671 0.435 0.525 0.070 9 135 WRF Run 5 0.784 0.435 0.208 0.088 0.628 0.408 0.511 0.065 9 135 OWI 0.704 0.598 0.480 0.203 0.609 0.394 0.616 0.088 7 137 Best Track in GAHM 0.625 0.591 0.138 0.056 0.759 0.480 0.625 0.081 23 121

J. Mar. Sci. Eng. 2019, 7, 77 18 of 30

J. Mar. Sci. Eng. 2019, 7, 77 19 of 32 4.3. Storm Surges Using Archived Forecast Advisories 4.3. Storm Surges Using Archived Forecast Advisories Rita storm surge ‘forecasts’ were performed using five archived advisories ingested in the GAHM windRita storm model surge to examine ‘forecasts’ thewere sensitivity performed using of advisories five archived in stormadvisories surge ingested generation in the and propagation.GAHM Thesewind model advisories to examine were issued the sensitivity during the of actualadvisories event in and storm are surge archived generation in the and database propagation. These advisories were issued during the actual event and are archived in the database of National Hurricane Center. Advisory wind fields ingested in the GAHM are typically used in of National Hurricane Center. Advisory wind fields ingested in the GAHM are typically used in the the ADCIRC+SWANADCIRC+SWAN model model to to predict predict hurricane hurricane storm storm surges surges during during an impending an impending event. event. The first The first simulationsimulation (Adv (Adv Run Run 1) was 1) was initialized initialized at at 09/22/2005 09/22/2005 0300 0300 UTC, UTC, approximately approximately 53 h 53before h before the the landfall.landfall. The The initialization initialization times times of of subsequent subsequent simulations simulations were were decreased decreased by 12 by h 12. Details h. Details of of simulationsimulation initialization initialization times times are are summarized summarized inin Table 55.. All All simulations simulations were were stopped stopped at 1200 at 1200UTC UTC on 25on September 25 September of 2005. of 2005. For For the the duration duration from from 09/18/2005 09/18/2005 0000 0000 UTC UTC to advisory to advisory run initialization run initialization times,times, wind wind fields fields of OWI of OWI were were used used in in ADCIRC+SWAN ADCIRC+SWAN to to simulate simulate the the storm storm surge surge from fromRita. Hot Rita. Hot start files were created after these runs, which were used in ADCIRC+SWAN to restart the simulation start files were created after these runs, which were used in ADCIRC+SWAN to restart the simulation with wind fields created from advisories in GAHM. with wind fields created from advisories in GAHM. Table 5. Description of Rita advisory runs and initialization times for surge forecasts. Table 5. Description of Rita advisory runs and initialization times for surge forecasts. Simulation Hours before Advisory Identification Initialization Time (UTC) SimulationNumber Number Advisory Identification Initialization Time (UTC) HoursLandfall before Landfall AdvAdv RunRun 1 1 AdvisoryAdvisory 1818 9/22/20059/22/2005 03000300 53 53 AdvAdv RunRun 2 2 AdvisoryAdvisory 2020 9/22/20059/22/2005 15001500 41 41 AdvAdv RunRun 3 3 AdvisoryAdvisory 2222 9/23/20059/23/2005 03000300 29 29 Adv Run 4 Advisory 24 9/23/2005 1500 17 AdvAdv RunRun 5 4 AdvisoryAdvisory 2624 9/24/20059/23/2005 03001500 17 5 Adv Run 5 Advisory 26 9/24/2005 0300 5

4.3.1. Comparison4.3.1. Comparison of Wind of Wind Fields Fields from from Advisories Advisories in GAHM and and OWI OWI The hybridThe hybrid OWI OWI and and Advisory Advisory maximum maximum windwind fields ﬁelds are are displayed displayed in Figure in Figure 9. Advisory9. Advisory wind wind ﬁeldsfields were were similar similar to that to that of theof the Best Best track trackin in GAHMGAHM (i.e., (i.e., Figure Figure 2b),2b), but but noticeably noticeably stronger stronger and and narrowernarrower than than that that of OWI. of OWI. Advisory Advisory 18 18 (Adv (Adv Run 1), 1), the the earliest earliest advisory advisory used used in the in present the present study, study, incorrectlyincorrectly predicted predicted landfall landfall south south of of Galveston Galveston area. The The later later advisories advisories predict predict the track the track and and curvature reasonably well. Except for the Adv Run 3, all advisories predicted reduced peak wind curvature reasonably well. Except for the Adv Run 3, all advisories predicted reduced peak wind speed before the hurricane landfall, correctly indicating the weakened status of Rita before speed before the hurricane landfall, correctly indicating the weakened status of Rita before landfall. landfall.

(a) (b)

Figure 9. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 19 of 30

J. Mar. Sci. Eng. 2019, 7, 77 20 of 32

(e) (f)

FigureFigure 9. Rita 9. Rita maximum maximum wind wind track track plots plots usingusing wind fields fields from from Advisories Advisories in GAHM in GAHM and OWI and OWI models. (a) Advisory(e 18) —Adv Run 1, (b) Advisory 20—Adv Run 2, (c) Advisory(f) 22—Adv Run 3, (d) models. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run 2, (c) Advisory 22—Adv Run 3, Advisory 24—Adv Run 4, (e) Advisory 26—Adv Run 5, and (f) OWI. (d) AdvisoryFigure 9. 24—AdvRita maximum Run 4,wind (e) Advisorytrack plots 26—Adv using wind Run fields 5, and from (f) Advisories OWI. in GAHM and OWI models. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run 2, (c) Advisory 22—Adv Run 3, (d) 4.3.2. Comparison of Storm Surges Using Advisories in GAHM and OWI Wind Fields 4.3.2. ComparisonAdvisory 24 of—Adv Storm Run Surges 4, (e) Advisory Using 26 Advisories—Adv Run in5, and GAHM (f) OWI. and OWI Wind Fields Figure 10 shows the maximum water elevation color plots of different storm surge forecasts Figure4.3.2.using Comparison 10 advisories shows the inof Storm GAHM maximum Surges and waterthe Using hindcast elevation Advisories using color in OWI GAHM plots wind ofand fields. different OWI As Wind anticipated, storm Fields surge Adv forecasts Run 1 using advisories in GAHM and the hindcast using OWI wind fields. As anticipated, Adv Run 1 incorrectly incorrectlyFigure 10shows shows that the the maximumprimary location water ofelevation the storm color surge plots is near of Galveston,different storm almost surge entirely forecasts west shows that the primary location of the storm surge is near Galveston, almost entirely west of the actual usingof the advisories actual track. in The GAHM rest of and the theadvisory hindcast cases using show OWI surge wind locations fields. similar As anticipated, to that of OWI. Adv For Run all 1 track.incorrectlythe The advisory rest ofshows thecases, advisorythat maximum the primary cases water showlocation elevations surge of the are locations storm significantly surge similar is nearoverpredicted to Galveston, that of OWI. in almost comparison For entirely all the to westthe advisory cases,ofOWI. maximum the actual However, track. water the The elevations east rest–west of the spreads are advisory significantly of their cases water show overpredicted elevat surgeion locations plots in are comparison similar narrower to that than to theof that OWI. OWI. of ForOWI. However, all This finding is not unexpected, given that the advisory wind fields are stronger and narrower. the east–westthe advisory spreads cases, maximum of their water water elevation elevations plotsare significantly are narrower overpredicted than that in of comparison OWI. This to finding the is Among all advisory runs, the Adv Run 5 water elevation seems to be the closest to that of OWI. not unexpected,OWI. However, given the thateast– thewest advisory spreads of wind their fieldswater areelevat strongerion plots and are narrower.narrower than Among that of all OWI. advisory However, most of the wind field of Adv Run 5 is from OWI; the actual contribution of the advisory runs,This the Adv finding Run is 5 not water unexpected, elevation given seems that to be the the advisory closest windto that fields of OWI. are strongerHowever, and most narrower. of the wind is only for the last five hours. Figure 11 shows the maximum water velocity color plots of different Among all advisory runs, the Adv Run 5 water elevation seems to be the closest to that of OWI. field ofruns Adv using Run advisories 5 is from inOWI; GAHM the actual and OWI. contribution The velocity of plotsthe advisory show significantly is only for stron theger last water five hours. However, most of the wind field of Adv Run 5 is from OWI; the actual contribution of the advisory Figurevelocities 11 shows from the advisory maximum wind water fields velocitythan that colorof OWI, plots due of to differentthe strong runswind usingfield mentioned advisories above. in GAHM is only for the last five hours. Figure 11 shows the maximum water velocity color plots of different and OWI. The velocity plots show significantly stronger water velocities from advisory wind fields runs using advisories in GAHM and OWI. The velocity plots show significantly stronger water than that of OWI, due to the strong wind field mentioned above. velocities from advisory wind fields than that of OWI, due to the strong wind field mentioned above.

(a) (b)

Figure 10. Cont. J. Mar. Sci. Eng. 2019, 7, 77 20 of 30

J. Mar. Sci. Eng. 2019, 7, 77 21 of 32

(e) (f)

Figure 10. Rita maximum(e) water elevation from ADCIRC+SWAN simulation (resultsf) using wind fields Figure 10. Rita maximum water elevation from ADCIRC+SWAN simulation results using wind ﬁelds from advisories in GAHM and OWI models. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run from advisoriesFigure 10. Rita in GAHM maximum and water OWI elevation models. from ( ADCIRC+SWANa) Advisory 18—Adv simulation Run results 1, ( usingb) Advisory wind fields 20—Adv 2, (fromc) Advisory advisories 22 in— AdvGAHM Run and 3, OWI (d) Advisory models. (a 24) Advisory—Adv Run 18— 4,Adv (e) RunAdvisory 1, (b) Advisory 26—Adv 20 Run—Adv 5, andRun (f) Run 2, (c) Advisory 22—Adv Run 3, (d) Advisory 24—Adv Run 4, (e) Advisory 26—Adv Run 5, and OWI.2, ( c) Advisory 22—Adv Run 3, (d) Advisory 24—Adv Run 4, (e) Advisory 26—Adv Run 5, and (f) (f) OWI.OWI.

(a()a ) (b()b )

(c()c ) (d()d ) Figure 11. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 21 of 30

J. Mar. Sci. Eng. 2019, 7, 77 22 of 32

(e) (f)

Figure 11.FigureRita 11. maximum Rita maximum water water velocity velocity from from ADCIRC+SWAN ADCIRC+SWAN simulation simulation results results using usingwind fields wind fields from advisories in GAHM and OWI models. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run from advisories in GAHM(e)and OWI models. (a) Advisory 18—Adv Run(f) 1, (b) Advisory 20—Adv 2, (c) Advisory 22—Adv Run 3, (d) Advisory 24—Adv Run 4, (e) Advisory 26—Adv Run 5, and (f) c d e Run 2, (FigureOWI.) Advisory 11. Rita 22—Advmaximum Runwater 3, velocity ( ) Advisory from ADCIRC+SWAN 24—Adv Run simulation 4, ( ) Advisory results using 26—Adv wind fields Run 5, and (f) OWI.from advisories in GAHM and OWI models. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run 4.3.3.2, Quantitative (c) Advisory 22Differences—Adv Run between 3, (d) Advisory Advisories 24—Adv in GAHM Run 4, (Forecaste) Advisory and 26 OWI—Adv Hindcast Run 5, and (f) 4.3.3. QuantitativeOWI. Differences between Advisories in GAHM Forecast and OWI Hindcast To quantify differences, maximum wind, maximum water elevation and velocity of advisory To quantifycases were differences, subtracted from maximum those of wind,the OWI maximum case. For brevity, water elevation differences and only velocity between of OWI advisory and cases 4.3.3. Quantitative Differences between Advisories in GAHM Forecast and OWI Hindcast were subtractedAdv Run from3 results those are ofreported the OWI here. case. Figure For 12a brevity, shows that differences the Advisory only 22 between maximum OWI wind and speed Adv Run 3 To quantify differences, maximum wind, maximum water elevation and velocity of advisory results arenear reported the coastal here. regions Figure was 12strongera shows by about that the 20 m/s Advisory than that 22 of maximum OWI. The advisory wind speed wind nearfield was the coastal casesconsistently were subtracted higher on fromboth sidesthose ofof thethe trackOWI thancase. that For ofbrevity, OWI. Asdiff seenerences in Figureonly between 12b, the OWI advisory and regions was stronger by about 20 m/s than that of OWI. The advisory wind field was consistently Advwind Run vortex 3 results was strongare reported and more here. symmetricFigure 12a thanshows that that of the OWI. Advisory The maximum 22 maximum water wind elevation speed higher onneargenerated both the coastal sides by Adv regions of Run the track3was wind stronger than field thatwas by abouthigher of OWI. 20 by m/s 1 As m than near seen that the in of coast. Figure OWI. The The 12 maximum b,advisory the advisory wind water field velocity wind was vortex was strongconsistentlygener andated more by higher the symmetric advisory on both wind sides than field of that the was track of consistently OWI. than Thethat higherof maximum OWI. by As 1 m/sseen water as in well. Figure elevation Both 12b, findings the generated advisory can be by Adv Run 3 windwindassociated field vortex with was was the higher strong higher byand wind 1 more m speed near symmetric of the Adv coast. Run than 3 The than that maximumthat of OWI. of OWI. The water maximum velocity water generated elevation by the advisorygenerated wind field by Adv was Run consistently 3 wind field higher was higher by 1 m/sby 1 m as near well. the Both coast. findings The maximum can be water associated velocity with the generated by the advisory wind field was consistently higher by 1 m/s as well. Both findings can be higher wind speed of Adv Run 3 than that of OWI. associated with the higher wind speed of Adv Run 3 than that of OWI.

(a) (b)

Figure 12. Differences and contrasts between OWI and Adv Run 3 hindcast results of Hurricane

Rita storm surges: (a) difference of maximum wind speed, (b) contrast of wind vectors at landfall, (c) difference of maximum water elevation, and (d) difference of water velocity. The black dots are the locations of eight stations listed in Table2. J. Mar. Sci. Eng. 2019, 7, 77 23 of 32

J. Mar. Sci. Eng. 2019 7 Figure 12., Differences, 77 and contrasts between OWI and Adv Run 3 hindcast results of Hurricane Rita 22 of 30 storm surges: (a) difference of maximum wind speed, (b) contrast of wind vectors at landfall, (c) difference of maximum water elevation, and (d) difference of water velocity. The black dots are the 4.3.4. Comparisonlocations of eight of Surge stations Time listed Series in Table Using 2. Advisories and Best Track in GAHM and OWI Winds The ADCIRC+SWAN water level time series were compared to observed water levels at stations 4.3.4. Comparison of Surge Time Series Using Advisories and Best Track in GAHM and OWI Winds (displayed on Figure1b). Away from landfall at station (J), Figure 13a indicates that Adv Run 3–5 predictedThe the ADCIRC+SWAN peak well, but water with level a phase time series lead. were Both compared Adv Runs to observed 1 and 2 water underpredicted levels at stations the peak. However,(displayed Adv on Run Figure 1 does 1b). not Away have from a phase landfall difference, at station which (J), Figure could 13a be indicates related to that the Adv distance Run 3 between–5 the stationpredicted and the landfall peak well, location but with wrongfully a phase lead. predicted Both Adv by this Runs advisory. 1 and 2 underpredicted the peak. However, Adv Run 1 does not have a phase difference, which could be related to the distance In the region of landfall, Figure 13b–e at stations (H, I, D, and F), Adv Run 1 underpredicted the between the station and landfall location wrongfully predicted by this advisory. peak as expectedIn the region due ofto landfall, the inaccurate Figure 13b landfall–e at stations location. (H, I, D, Adv and Run F), Adv 2, in Run general, 1 underpredicted predicted the peak wellpeak without as expected much phase due to difference. the inaccurat Adve landfall Runs 3 location. and 4 overpredicted Adv Run 2, in thegeneral, peak predicted with some the phase peak delay by aboutwell without 2 h. A carefulmuch phase inspection difference. of these Adv advisoryRuns 3 and wind 4 overpredicted ﬁelds revealed the thatpeak their with landfallsome phase locations weredelay slightly by about to the 2 west h. A ofcareful the actual/observed inspection of these landfall. advisory Adv wind Run fields 3 had revealed a landfall that slightlytheir landfall more west thanlocations that of Advwere Runslightly 4, andto the hence west of it hadthe actual/observed longer peak delays, landfall. up Adv to Run 2 h, 3 for had all a stations.landfall slightly Adv Run 5 seemedmore to west have than a reasonable that of Adv peak Run without4, and hence much it had phase longer difference. peak delays, However, up to 2 it h, contained for all stations. only 5 h of advisoryAdv Run wind 5 seemed on top to of have a wind a reasonable ﬁeld mostly peak produced without muc byh OWI phase forcing. difference. However, it contained only 5 h of advisory wind on top of a wind field mostly produced by OWI forcing.

(a) (b)

(e) (f)

Figure 13. Cont.

J. Mar. Sci. Eng. 2019, 7, 77 23 of 30

J. Mar. Sci. Eng. 2019, 7, 77 24 of 32

(g) (h)

(i) (j)

(k) (l)

FigureFigure 13. 13.Effect Effect of of wind wind fields fields from from AdvisoriesAdvisories in GAHM GAHM and and OWI OWI models: models: Observed Observed and and ADCIRC+SWAN modeled significant water level time series at different observation stations during ADCIRC+SWAN modeled significant water level time series at different observation stations during the time of Hurricane Rita (9/22-25/05). (a) J—USGS-DEPL LF5; (b) H—USGS-DEPL LC8a; (c) I— the time of Hurricane Rita (9/22-25/05). (a) J—USGS-DEPL LF5; (b) H—USGS-DEPL LC8a; USGS-DEPL LC9; (d) D—USGS-DEPL LA12; (e) F—USGS-DEPL LC13; (f) E—USGS-DEPL LA9; (g) c d e f ( ) I—USGS-DEPLC—USGS-DEPL LC9;LA10; ( (h)) D—USGS-DEPLG—USGS-DEPL LC6a; LA12; (i) K ( —)ID F—USGS-DEPL 8770570, Sabine LC13;Pass North, ( ) E—USGS-DEPL TX; (j) N— LA9;ID (g) 8770971, C—USGS-DEPL Rollover Pass, LA10; TX; ((hk)) G—USGS-DEPLO—ID 8771341, Galveston LC6a; ( Bayi) K—ID Entrance, 8770570, North SabineJetty, TX; Pass (l) Q North,—ID TX; (j) N—ID8771013 8770971,, Eagle Point, Rollover Galveston Pass, Bay, TX; TX. (k) (Advisory O—ID 8771341, 18—Adv Galveston Run 1: 9/22/05 Bay 0300; Entrance, Advisory North 20— Jetty,Adv TX; (l) Q—IDRun 2: 8771013, 9/22/05 1500; Eagle Advisory Point, Galveston 22—Adv Run Bay, 3: TX. 9/23/05 (Advisory 0300; Advisory 18—Adv 24 Run—Adv 1: 9/22/05Run 4: 9/23/05 0300; 1500; Advisory 20—AdvAdvisory Run 26 2:— 9/22/05Adv Run 1500;5: 9/24/05 Advisory 0300). 22—Adv Run 3: 9/23/05 0300; Advisory 24—Adv Run 4: 9/23/05 1500; Advisory 26—Adv Run 5: 9/24/05 0300). At inland stations (E, C, and G) (Figure 13f–h), Adv Run 1 underpredicted the water elevation Atpeak, inland as expected. stations For (E, station C, and E, G)Adv (Figure 2–5 performed 13f–h), Advbetter Run than 1 that underpredicted of OWI. Adv 2 the–5 runs water seemed elevation peak,to as predict expected. the water For station peak similarly E, Adv to 2–5 that performed of OWI for better station than C. For that station of OWI. G, Adv Runs 2–5 runs 2 and seemed 5 to predictperformed the water better peakthan OWI, similarly but Adv to that Runs of 3 OWI and 4 for overpredicted station C. Forthe peak station with G, reduced Adv Runs phase 2 and differences compared to the observed data. The actual phase difference, either early or delayed 5 performed better than OWI, but Adv Runs 3 and 4 overpredicted the peak with reduced phase arrival, depended on landfall locations, wind field width and strength, locations of the stations and differences compared to the observed data. The actual phase difference, either early or delayed arrival, their connectivity with water passages, etc. dependedAs on shown landfall in Figure locations, 13i–k, advisories wind field in widthGAHM andwinds strength, significantly locations overpredict of the surges, stations although and their connectivitythe phase with leads water are not passages, significantly etc. different than those of OWI surges. As expected, Adv Run 1 is As shown in Figure 13i–k, advisories in GAHM winds significantly overpredict surges, although the phase leads are not significantly different than those of OWI surges. As expected, Adv Run 1 is the worst run due to an incorrect landfall location. The double surge peaks are predicted by advisories in J. Mar. Sci. Eng. 2019, 7, 77 24 of 30

GAHM at stations N and O, similar to those of OWI. As shown in Figure 13l, the Galveston Bay station Q is awayJ. Mar. from Sci. Eng. the 2019 direct, 7, 77 path of surge propagation and all but Adv Run 1 cases generally25 of predict 32 the peak well with few phase differences. the worst run due to an incorrect landfall location. The double surge peaks are predicted by advisories in GAHM at stations N and O, similar to those of OWI. As shown in Figure 13l, the 4.3.5. Comparison of High Water Mark Using Advisories and Best Track in GAHM and OWI Winds Galveston Bay station Q is away from the direct path of surge propagation and all but Adv Run 1 Thecases peak generally water predict levels the were peak compared well with few for phase each differences. of the simulations to measured HWMs [64] in Figure 14. The summarized statistics for all HWM analyses using only wet locations are given in Table6. 4.3.5. Comparison of High Water Mark Using Advisories and Best Track in GAHM and OWI Winds Since the advisory wind field bands are narrower, but stronger than that of OWI, high localized surges wetted HWMsThe peak within water their levels bounds, were compared while many for each HWMs of the locationssimulations remained to measured dry. HWMs All advisory [64] in runs Figure 14. The summarized statistics for all HWM analyses using only wet locations are given in have more,Table ranging 6. Since from the advisory 9 to 48, wind dry locations field bands than are thatnarrower, of OWI but or stronger those ofthan WRF. that Most of OWI, advisory high runs, except forlocalized Adv Runsurges 3 wetted produced HWMs low within correlation their bounds, coefficients while many since HWMs plot data locations are scattered.remained dry. A simulationAll such asadvisory Adv Run runs 3 may have producemore, ranging less accuratefrom 9 to 48, inundation dry locations extent than yetthat scoreof OWI a or high those correlation of WRF. Most coefficient since dryadvisory locations runs, are except not plotted for Adv and Run are 3 pr ignoredoduced low when correlation computing coefficients the statistics. since plot The data comparison are againstscattered. the orange A simulation parity line such shows as Adv that Run some 3 may wet produce HWMs less are accurate overpredicted inundation byextent 1m yet or morescore a by most high correlation coefficient since dry locations are not plotted and are ignored when computing the advisory runs. Considering only the wet nodes, the Adv Run 3 has lower E , E, B , MAE, and statistics. The comparison against the orange parity line shows that someRMS wet HWMsMN are ENORM erroroverpredicted values thanby 1m those or more of OWI.by most However, advisory runs. the scatter Considering indices only (σ theand wetSI nodes,) of Adv the RunAdv Run 3 are larger than thoseindices of OWI.(σ and SI) of Adv Run 3 are larger than those of OWI.

10 10 y = 0.7513x + 0.686 9 y = 0.4241x + 0.7702 9 R² = 0.5684 8 R² = 0.4375 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1

0 0

Modeled High Water Mark (m) Mark Water High Modeled Modeled High Water Mark (m) Water ModeledHigh 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Measured High Water Mark (m) Measured High Water Mark (m) (a) (b) 10 10 9 y = 0.8556x + 0.5378 9 y = 0.8101x + 0.7194 R² = 0.7128 R² = 0.6151 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1

0 0 Modeled High Water Mark (m) Water ModeledHigh Modeled High Water Mark (m) Water ModeledHigh 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Measured High Water Mark (m) Measured High Water Mark (m) (c) (d)

Figure 14. Cont. J. Mar. Sci. Eng. 2019, 7, 77 25 of 30

J. Mar. Sci. Eng. 2019, 7, 77 26 of 32

10 10 9 y = 0.6454x + 0.997 9 y = 0.6951x + 1.1968 R² = 0.7008 R² = 0.7037 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1

0 0

Modeled High Water Mark (m) Water ModeledHigh Modeled High Water Mark (m) Water ModeledHigh 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Measured High Water Mark (m) Measured High Water Mark (m) (e) (f)

Figure 14.FigureScatter 14. Scatter plots plots of Rita of Rita HWM’s HWM’ froms from ADCIRC+SWANADCIRC+SWAN simulations simulations using using wind windfields from ﬁelds from advisories in GAHM and OWI. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run 2, (c) advisories in GAHM and OWI. (a) Advisory 18—Adv Run 1, (b) Advisory 20—Adv Run 2, (c) Advisory Advisory 22—Adv Run 3, (d) Advisory 24—Adv Run 4, (e) Advisory 26—Adv Run 5, and (f) OWI. 22—AdvRed Run diamond 3, (d) Advisoryand black triangles 24—Adv indicate Run 4, underprediction (e) Advisory 26—Advby the model; Run purple 5, and triangles (f) OWI. and Red light diamond and blackgreen triangles squares indicateindicate overprediction. underprediction Dark bygreen the circles model; indicate purple a match triangles within and 0.5 lightm. The green blacksquares indicateline overprediction. represents the best Dark fit greenlines. The circles orange indicate line represents a match the within parity. 0.5 m. The black line represents the best ﬁt lines. The orange line represents the parity. Table 6. HWM error statistics for Rita simulations using forecasted wind fields from archived Table 6.Advisories.HWM error statistics for Rita simulations using forecasted wind fields from archived Advisories.

ퟐ Case 푹 ERMS (m) ¯ 퐄̅ (m) BMN (-) σ (m) SI (-) MAE (m) ENORM (-) Dry Wet Case R2 E (m) B (-) σ (m) SI (-) MAE (m) E (-) Dry Wet Advisory 18: Adv Run 1 0.438RMS 1.050 E (m)−0.611 MN−0.253 0.827 0.529 0.850 0.151NORM 48 96 AdvisoryAdvisory 18: Adv Run20: Adv 1 Run 0.438 2 0.568 1.050 0.675 −0.6110.091 −0.2530.038 0.820 0.827 0.526 0.529 0.659 0.850 0.095 0.15123 48121 96 AdvisoryAdvisory 20: Adv Run22: Adv 2 Run 0.568 3 0.713 0.675 0.496 0.0910.193 0.0380.080 0.680 0.820 0.436 0.526 0.553 0.659 0.069 0.09536 23108 121 AdvisoryAdvisory 22: Adv Run24: Adv 3 Run 0.713 4 0.615 0.496 0.663 0.1930.266 0.0800.110 0.773 0.680 0.496 0.436 0.620 0.553 0.094 0.06923 36121 108 AdvisoryAdvisory 24: Adv Run26: Adv 4 Run 0.615 5 0.701 0.663 0.423 0.2660.167 0.1100.071 0.631 0.773 0.409 0.496 0.508 0.620 0.062 0.0949 23135 121 Advisory 26: Adv Run 5 0.701 0.423 0.167 0.071 0.631 0.409 0.508 0.062 9 135 OWI (repeated) 0.704 0.598 0.480 0.203 0.609 0.394 0.616 0.088 7 137 OWI (repeated) 0.704 0.598 0.480 0.203 0.609 0.394 0.616 0.088 7 137 Best Track (repeated) 0.625 0.591 0.138 0.056 0.759 0.480 0.625 0.081 23 121 Best Track (repeated) 0.625 0.591 0.138 0.056 0.759 0.480 0.625 0.081 23 121

5. Concluding Remarks 5. Concluding Remarks The objective of this study was to learn how forecasted meteorological forcing from different Thesources objective influence of this storm study surge was generation to learnhow and forecasted propagation meteorological during a hurricane. forcing Numerical from different sourcesexperiments influence storm were performed surge generation with different and propagationwind fields from during OWI aand hurricane. the Best track Numerical in GAHM experiments to were performedhindcast Hurricanewith different Rita wind surges. fields In addition, from OWI WRF and and the forecast/advisoriesBest track in GAHM from to hindcastthe National Hurricane Hurricane Center in GAHM were used to understand how forecasted wind fields impact storm surge Rita surges.generation In addition, and propagation WRF and in real forecast/advisories time. The OWI wind from field was the Nationalused for the Hurricane period before Center the WRF in GAHM were usedor advisory to understand in GAHM how was forecasted initialized. These wind wind fields fields impact were storm used as surge meteorological generation forcing and in propagation the in real time.ADCIRC+SWAN The OWI wind coupled field model. was The used ADCIRC+SWAN for the period setup before of theKerr WRF et al. or[56] advisory was taken in as GAHM the was initialized.benchmark, These except wind fieldsthat the were semi- usedimplicit as solver meteorological was used in the forcing present in study. the ADCIRC+SWAN The OWI model was coupled model.used The as ADCIRC+SWAN the default wind model, setup and of Kerr all results et al. were [56] compared was taken against as the it benchmark,and the observed except data. that the Statistical characterizations of different cases were reported, and summarized in Table 7. semi-implicit solver was used in the present study. The OWI model was used as the default wind model, and all results were compared against it and the observed data. Statistical characterizations of different cases were reported, and summarized in Table7.

Table 7. Summarized HWM error statistics for Rita surge forecast and hindcast using different wind ﬁelds.

2 ¯ Case R ERMS (m) E (m) BMN (-) σ (m) SI (-) MAE (m) ENORM (-) Dry Wet OWI 0.704 0.598 0.480 0.203 0.609 0.394 0.616 0.088 7 137 Best Track in GAHM 0.625 0.591 0.138 0.056 0.759 0.480 0.625 0.081 23 121 WRF Run 3 0.745 0.515 0.391 0.166 0.604 0.392 0.564 0.077 9 135 Adv Run 3 0.713 0.496 0.193 0.080 0.680 0.436 0.553 0.069 36 108 J. Mar. Sci. Eng. 2019, 7, 77 26 of 30

The Best track in GAHM had a stronger and narrower wind field than that of OWI. The station time series from the surge hindcast of Best track behaved similarly to that of OWI. Time series results of these hindcasts compared well with observed data with some overprediction and phase lead. Early peak arrivals are results of quick surge propagations. The HWM correlation coefficient for the Best track in the GAHM model was only 0.625 with 23 dry locations that were excluded, whereas it was 0.704 for OWI with seven excluded dry locations. Considering only the wet stations, the error indices are lower for Best track in GAHM than those of OWI, but their scatter indices are larger (see Table7). The wet HWMs of the surge hindcast using OWI and Best track in GAHM wind fields compared well with the measured data with some overpredictions. Weather Research and Forecasting forecast wind fields were weaker, but wider than that of OWI. In general, WRF hurricane track was correct, but without the actual curvature of the storm. The forecast initialized at 09/23/2005 0000 UTC had a landfall slightly west of the actual landfall. This in turn, reduced time series surge peak arrival gaps from the observed data. Overall, time series peaks compared well with the observed data with some overprediction and reduced phase difference. The HWM correlation coefficient for the WRF Run 3 case initialized at 09/23/2005 0000 UTC was 0.745 with nine excluded dry locations, which is remarkable as a forecast. Some low surge HWMs were overpredicted and high surge HWMs were underpredicted by all WRF cases. Both error and scatter indices are lower for the WRF Run 3 case than those of OWI (see Table7). The advisories in the GAHM model produced stronger, but narrower wind fields. The earliest advisory used in the present study was Advisory 18—Adv Run 1, issued at 09/22/2005 0300 UTC. This advisory produced incorrect location of the landfall, and all results were off, indicating the fact that early advisories should be used with caution. Otherwise, rest of the advisories produced reasonable tracks, except for stronger and narrower wind fields than that of OWI. Such wind fields overpredicted surge forecasts with phase leads, as the time series analyses reflect the fact. The HWM correlation coefficient for Advisory 22—Adv Run 3, issued at 09/23/2005 0300 UTC was 0.713 with 36 excluded dry locations. The HWMs surge levels in wet locations matched well with measured data, although there are some overpredictions by 1m or more. The error indices are lower for Adv Run 3 in GAHM than those of OWI, but their scatter indices are larger (see Table7). Although they are all widely used due to the simplicity of the GAHM parametric wind model, the advisory or Best track in GAHM does not perform as well as OWI and/or WRF forecast in storm surge generation and propagation for Hurricane Rita. Recall that Best track in GAHM uses limited Best track wind data to recreate a wind field using GAHM model. The OWI uses observational data to form a wind field after the hurricane passes. On the other hand, WRF is a full physics model that forecasts a wind field. A more comprehensive generalization cannot be made without investigating more hurricanes using a similar technique used in the present study, which authors are planning to do next. Since OWI and the Best track in GAHM are not available for a forecast period, perhaps using both WRF and advisories in GAHM to forecast a comprehensive picture of the storm surge in real time during an impending hurricane will be useful.

Author Contributions: A.M. performed all runs, post processed results, and initial analysis. M.K.A. designed the study, ran some cases, and analyzed results. J.G.F. helped with the ADCIRC + SWAN issues and wind model setups, did critical reviews, and S.K.H. secured student’s funding. Funding: This research received no external funding. Acknowledgments: Authors are grateful to the University of North Carolina’s Renaissance Computing Institute for the access to their high-performance computing platform. Conﬂicts of Interest: The authors declare sole responsibility of the research results. J. Mar. Sci. Eng. 2019, 7, 77 27 of 30

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