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Storm surge from Hurricane Irma along the Florida Peninsula
Journal Pre-proof Storm surge from Hurricane Irma along the Florida Peninsula Sangdon So, Braulio Juarez, Arnoldo Valle-Levinson, Matlack E. Gillin PII:
S0272-7714(19)30291-4
DOI:
https://doi.org/10.1016/j.ecss.2019.106402
Reference:
YECSS 106402
To appear in:
Estuarine, Coastal and Shelf Science
Received Date: 26 March 2019 Revised Date:
19 August 2019
Accepted Date: 2 October 2019
Please cite this article as: So, S., Juarez, B., Valle-Levinson, A., Gillin, M.E., Storm surge from Hurricane Irma along the Florida Peninsula, Estuarine, Coastal and Shelf Science (2019), doi: https:// doi.org/10.1016/j.ecss.2019.106402. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
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Storm surge from Hurricane Irma along the Florida Peninsula
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Sangdon So1, Braulio Juarez1, Arnoldo Valle-Levinson1, and Matlack E. Gillin1
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1
Civil and Coastal Engineering Department, University of Florida, Gainesville, Florida, USA.
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Corresponding author: Braulio Juarez ([email protected])
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Key Points:
6 7 8 9 10 11
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Effects of Hurricane Irma on Florida Peninsula were analyzed with water level and atmospheric forcing records.
•
Storm surges on the west coast of Florida were markedly different from those on the east coast.
•
Wind stress divergence is critical for determining storm surge and flood risk.
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Abstract
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Hurricane Irma impacted the entire Florida peninsula in September 2017. The combination of Irma’s strength, size, and track provided a unique opportunity to study hurricane effects on storm surge on both sides of a peninsula. Storm surge characteristics on the west coast of Florida were markedly different from those on the east coast. On the west coast, the maximum storm surge was 1.6 m at Naples, which was attributed to onshore winds and an atmospheric pressure of 970 hPa. A stunning negative surge of -2.7 m appeared at Cedar Key, in the peninsula’s northwestern quarter, after ~10 hr of oblique offshore and divergent winds. On the east coast, the maximum surge was 2.4 m at Fernandina Beach, where wind velocity displayed horizontal convergence. A revealing finding of this investigation was that wind divergence is an essential component for predicting storm surge.
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1 Introduction
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Storm surge, taken as the difference between observed and predicted tides (ValleLevinson et al., 2013), depends on storm size, atmospheric pressure, wind velocity, wind fetch and duration, the angle relative to the coast, and bathymetry (Hall and Sobel, 2013; Resio et al., 2009). Storm surge caused by hurricanes can devastate densely populated coastal regions. Moreover, the combination of storm surge and heavy precipitation exacerbates flooding in lowlying coastal areas (Wahl et al., 2015). The response of storm surge to atmospheric forcing needs improved understanding as its destructive effects increase with sea level rise, coastal development and building construction (Muis et al., 2016; Hinkel et al., 2014; Kemp and Horton, 2013).
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Numerical models have been used to simulate storm surge (e.g. Weisberg and Zheng, 2008; Bilskie et al, 2016). A study investigated the sensitivity of coastal inundation to hurricane attributes: track, intensity, size, and translation speed (Foster et al., 2017). They simulated the coastal inundation with three different hurricanes: Charly, Ike, and the hypothetical “Charike”. The results showed that surge inundation is more sensitive to storm size and landfall location than storm speed. Some efforts have explored surges with unexpected behavior. Morey et al. (2006) studied an unanticipated 2-3 m surge along Apalachee Bay, Florida, during Hurricane Dennis. They demonstrated that along-shore winds translated northwestward along the bay to generate a storm surge similar to a topographic Rossby wave. They also showed that storm surge models could be improved for a storm translating along a similar track. Two- and threedimensional simulations described the vulnerability of Tampa Bay to storm surge and the advantage of three-dimensional over two-dimensional models (Weisberg and Zheng, 2008). Other simulations in the northern Gulf of Mexico have shown that geometry and bathymetry affected the timing and height of the storm surges related to hurricanes Ivan, Dennis, Katrina, and Issac (Bilskie et al., 2016). Also in the northern Gulf, Hurricane Ike caused a ‘forerunner’ surge before the hurricane-forced surge (Kennedy et al., 2011). This forerunner was attributed to Ekman setup and was proposed as a potential mechanism of inundation in low-lying coastal areas. Previous studies on hurricane-related surges have focused on the generation by onshore winds and low barometric pressure. However, as shown in this study, other mechanisms can also be influential.
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Each hurricane generates a unique storm surge, which is mainly associated with meteorological conditions and coastline topography (Irish et al., 2008; Lin et al, 2010).
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Hurricane Irma in 2017 provided a rare combination of positive and negative surges along the east and west coast of Florida. The negative surge observed in west Florida was not described by forecasts. Additionally, semi-diurnal perturbations to the storm surge appeared within bights on both northern coasts of Florida. The goal of this investigation was to describe the effect of Hurricane Irma on the west and east coasts of the Florida Peninsula and to identify the forcing associated with the peculiar surge behavior along the peninsula. The effect of Hurricane Irma was analyzed with water level and atmospheric observations on Florida’s west coast and on the US southeastern coast. This study indicated that wind divergence is critical for determining storm surge of a hurricane translating along a peninsula.
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2 Storm Trajectory
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Hurricane Irma developed near the Cape Verde islands, off the northwestern coast of Africa, at 15:00 GMT on 30 August 2017. After steadily gaining strength and size under favorable conditions (Atlantic-wide track and ocean surface temperatures >28°C), Irma attained Category 5 status on 5 September in the Caribbean. As a Category 5 hurricane, Irma fringed northern Puerto Rico, the Dominican Republic, and Haiti, where it was then downgraded to Category 4. Irma regained Category 5 status as it made landfall in Cuba, at 3:00 GMT on 9 September with maximum sustained winds of ~72m/s and a barometric pressure of 924 hPa. On 9 September, Irma weakened to a Category 3 hurricane as it passed over northern Cuba. Irma’s path between 10 and 12 September was north-northwestward toward south Florida (Figure 1a). Irma strengthened to Category 4 at 6:00 GMT on 10 September over the Straits of Florida. It crossed the Florida Keys ~32 km east of Key West with maximum sustained winds of ~58 m/s (Figure 1c) and a central barometric pressure of 929 hPa (Figure 1d). Irma continued northward with an average translation speed of ~6 m/s (Figure 1b) and then arrived near Naples, Florida, at 20:00 GMT on 10 September with maximum sustained winds of ~51 m/s and a barometric pressure of 940 hPa. The hurricane moved northward on land, skirting the west coast of Florida with an average speed of ~7.5 m/s. Irma became a tropical storm as it passed north of Tampa Bay at 12:00 GMT on 11 September. According to the National Weather Service, Irma’s wind field extended up to ~650 km radially from the center of the storm on 11 September.
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Figure 1. a) Track of Hurricane Irma between 10 and 12 September 2017. Each label appears at the beginning and noon of the day (GMT). Colored circles denote the Category of the Hurricane. Red stars indicate NOAA weather stations with barometric pressure, wind, and water level data. Blue lines are the 10, 50 and 100 m isobaths. b) Translation speed (m/s) calculated by the Hurricane locations. Blue line presents five-point moving average of the data points. c) Maximum sustained speed (m/s). d) Barometric pressure (hPa).
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3 Methods
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Water level data were obtained from 11 stations along the west coast of Florida and 8 stations along the US east coast (Figure 1a) maintained by the National Oceanic and
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Atmospheric Administration (NOAA). Data were available from NOAA’s Tides & Currents portal (https://tidesandcurrents.noaa.gov). Compiled water level data included verified observations and predicted values related to astronomical tide. Depending on availability, barometric pressure and wind velocities were retrieved from most, but not all, water level stations. Barometric pressures were unavailable at Lake Worth Pier. Wind data were unavailable at Port Manatee, FL, Pensacola, FL and Springmaid Pier, SC. The data from NOAA were compiled at 6-minute intervals from 9 through 12 September 2017.
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Hovmöller diagrams are widely used in atmospheric sciences to describe spatial and temporal variability of a scalar or vector. This study presents a series of Hovmöller diagrams, describing the evolution of several variables along the east and west coast of the Florida peninsula. The variables include de-tided water level (observed minus predicted), wind velocity, barometric pressure, and wind stress divergence ( / + / in N/m3). Also represented in a Hovmöller diagram is the detided water level obtained from an analytical solution of storm surges. In this application, the axes of the Hovmöller diagrams represent time (x-axis) and distance from Key West (y-axis) with the value of the variables displayed in colored contours. For the diagrams on the west coast of Florida, time increases to the left in order to describe simultaneously the storm-related signals as they propagated from their reference origin, Key West, along both sides of the peninsula. All times are represented in Greenwich Mean Time (GMT) for the period studied.
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Wind stress divergence was included as a study parameter because of its prominence in representing pulses generated by a moving atmospheric disturbance (Thiebaut and Vennell, 2011). The analytical representation, also used here, consists of a two-dimensional analytical barotropic model, implemented for transient shallow-water waves. The transient shallow-water wave ( ) is expressed in terms of a) wave celerity ( = ℎ, where is gravity acceleration and ℎ is constant water depth), b) Coriolis frequency ( ), and c) the combined forcing ( ) of atmospheric pressure and wind-stress. The model’s momentum balance, combined with continuity, is given by (Thiebaut and Vennell, 2011):
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− 119
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∂
∇
=
=− ∇
,
(1)
∇
−
1
∇· +
,
(2)
where is the water level related to the inverse barometer effect, is wind stress, and (∇ × )/( ) is Ekman pumping, proportional to wind stress curl. The combined forcing, expressed as: " exp&'()*
= is
+ +, − - ./. (3)
With eq. (3) the steady-state forced wave solution to Equation (1) is: ,
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+
The forcing term of the analytical model (rhs of eq 1) is given by:
= 123
∇
=
," exp&'()*
+ +, − - ./ ,
(4)
where ," = " /(1 − 3 + 45 ) in which 3 = -/( 6, ) is the Froude number and 45 = 4/(2748 ) is the dimensionless disturbance width, which compares the disturbance width, L, to
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the Rossby radius of deformation 48 = / , 6, = ), + +, is the wave number magnitude, ' = √−1; )* and +, are the and -components of the atmospheric disturbance’s wave number, respectively; - is the angular frequency of the atmospheric disturbance; and " is the sum of atmospheric pressure and wind forcing. "
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=
"
+
": ,
(5)
The dominance of wind forcing in Equation (5) was described by Gill (1982). When atmospheric pressure effects can be neglected, the wind forcing, " can be approximated as ": (see Thiebaut and Vennell, 2011): ":
=
1 <(), 6,
"
+ +,
".
−'
-
(),
"
− +,
" .= ,
(6)
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The ratio between and - in (6) shows the significance between the wind stress divergence (first term on the rhs of (6)) and the curl of the wind stress (second term). The divergence, (), " + +, " ., becomes more important than the curl, (), " − +, " ., for high frequency forcing (f <ω).
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Details on the steady-state wave solution of Equation (1) are given by Thiebaut and Vennell (2011). The storm surge , was estimated using Equation (4) by including wind stress divergence and Ekman pumping, as shown in section 5, after describing hurricane Irma’s surge and forcing agents. The amplitude of the forced wave in equation (4) depends on the wind stress, wave number, Earth’s rotation, disturbance angular frequency, and wave celerity. In turn, wave celerity depends on the water depth that was the only parameter to define. Depth variability modified the surge amplitudes but did not change the location of relative maximum and minimum surges that related to the wind field distribution. Thus, a constant water depth of 7 m is used in this study because is representative of all stations (Fig. 1) and reproduced the observed surge well.
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The model results along the coast are compared with observations using three indices: the Root mean square error (RMSE); squared correlation coefficient (R2 see Thomson and Emery (2014); and Skill (see Warner et al., 2005)
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H 1 ?@AB = < D ( C IJK
? =M 150 151 152 153
H ( 1 D C−1 IJK
EFG
K/
EFG − , ) =
,
(7)
− NNNNNN EFG )( , − NNN ,) Q , OPEFG OP,
(8)
where N is the total number of observation points in time, EFG represents the observed surge, , is the modeled surge obtained with equation 4, OPEFG and OP, are the standard deviation of the observed and modeled surge respectively, and the overbar denotes a time mean. In addition, the model skill was calculated as (Warner et al., 2005): A)'++ = 1 −
∑H IJK(| ,
∑H IJK|
− − NNNNNN| EFG + | ,
EFG | EFG
− NNNNNN| EFG )
,
(8)
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Skill equals to one indicates a perfect agreement between the modeled and observed surge, and a disagreement is indicated by a skill close to zero.
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4 Results
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4.1 Storm Surge
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The track of Irma along the Florida Peninsula provided a unique scenario of simultaneous storm surge on the west and east coasts of Florida. Hovmöller diagrams in Figure 2 show the time evolution of storm surge and wind vectors at NOAA stations and at 6-min intervals. Florida’s west coast (Figure 2a) displayed both negative and positive storm surges, while storm surges were all positive along the Atlantic coast (Figure 2b). Storm surge at Key West was 1 m at 14:24 on 10 September when Hurricane Irma passed over the Florida Keys. The highest storm surge on the west coast was 1.6 m at 23:06 on 10 September at Naples. The greatest negative storm surge, an astounding -2.7 m, occurred at 8:12 on 11 September at Cedar Key. Negative surges occurred over the entire west coast of the peninsula. This negative surge allowed people, mainly around the Tampa area, to walk offshore previous to the subsequent positive surge. North of Naples, the surge reached values around 1 m, which contrasted to the anticipated 5 m announced in municipality and state advisories. Along the Atlantic Coast, Fernandina Beach recorded the highest storm surge (2.4 m) at 10:24 on 11 September. The storm surge exhibited a unique behavior in the sense that it appeared simultaneously on both sides of a peninsula. One of the revealing aspects of the storm surge was its negative values on the west coast of Florida despite the low (<990 hPa) barometric pressures recorded.
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Semidiurnal perturbations to the surge appeared in the South Atlantic Bight, between Trident Pier and Springmaid Pier (Figure 2b). These perturbations were related to tide-storm interactions (Valle-Levinson et al., 2013; Feng et al., 2016). For the first time, semidiurnal perturbations were also observed on the west coast of Florida, between Clearwater Beach and Apalachicola Bay, in a region known as the Florida Big Bend. These perturbations developed within a bight and in the region of dominant semidiurnal tide in the Southeastern US and in the Gulf of Mexico. This prominence of semidiurnal perturbations is because the intensity of tidesurge interactions is proportional to tidal amplitude (i.e. Proudman, 1955; Prandle and Wolf, 1978; Horsburgh and Wilson, 2007). Along the US Atlantic coast, Feng et al. (2016) demonstrated the evidence of tide-surge interactions. They indicated that the largest semidiurnal perturbation mostly occurred near the South Atlantic Bight apex during the passage of Hurricane Floyd in 1999. In addition, 93% of events described in that study were characterized by a phase delay of the observed tide relative to the predicted tide (Feng et al., 2016). During Irma, intense perturbations generated by tide-storm interactions (Valle-Levinson et al., 2013; Feng et al., 2016) were again observed near the apex (Fort Pulaski, Figure 2b). Further studies should explore the persistence of semidiurnal perturbations in the Florida Big Bend during storms. The next section explores the effects of barometric pressure and wind forcing on storm surge.
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Figure 2. Hovmöller diagrams of wind velocities (vectors, m/s) and storm surge (color contours, m) at 6-min intervals, during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. White dots indicate the time and locations of the lowest barometric pressure. Storm surge and winds were interpolated to the grid points (50 km in distance, 6 min in time) by a Delaunay triangulation (Matlab’s default). For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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4.2 Barometric Pressure and Winds
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Among Florida’s west coast stations, Naples, on the southwest coast of the peninsula, showed the lowest barometric pressure (~939 hPa) at 20:54 on 10 September (Figure 3a). In contrast, the lowest barometric pressure on the east coast was almost 50 hPa higher and ~13 h later at Trident Pier (~988 hPa), in the middle of the peninsula, at 12:18 on 11 September (Figure 3b). The lowest barometric pressure was observed on the west coast of Florida because Irma made landfall near Naples and its trajectory fringed Florida’s west coast. At each station on the east coast, the lowest barometric pressure roughly corresponded to the time of greatest storm surge. However, the same was not the case for the west coast. This indicated that barometric pressure had a limited effect on storm surge along the west coast. As an example, the storm surge at Cedar key was -2.7 m, even though the barometric pressure was 979 hPa at 8:12, 11 September. Hovmöller diagrams of barometric pressure show a cone-shaped distribution along both coasts of Florida. The lowest local pressure propagated quasi-linearly in the time-space domain.
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Figure 3. Hovmöller diagrams of wind velocities (vectors, m/s) and barometric pressure (color
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contours, hPa) in a 6-min interval, during the period influenced by Irma a) along the west coast of Florida and b) along the US Atlantic Coast. White dots indicate the time and locations of the lowest barometric pressure. Barometric pressure and winds were interpolated as in Figure 2. Hovmöller diagrams of wind velocities (vectors) and the divergence of the wind shear stresses (color contours, N/m3) during the period influenced by Irma c) along the west coast of Florida and d) along the Southeastern US Atlantic Coast. Positive contours denote divergence of wind stress. Hovmöller diagrams of wind velocities (vectors) and the curl of the wind shear stresses (color contours, N/m3) during the period influenced by Irma e) along the west coast of Florida and f) along the Southeastern US Atlantic Coast. Positive contours denote wave setup. For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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Wind directions were predominantly southwestward along both Florida coasts before Irma. After the storm, wind directions became primarily northeastward at both coasts. Key West, the first site of Irma’s impact, recorded the highest wind magnitude (~31m/s southeastward) along the west coast at 12:24 on 10 September. Counterclockwise wind rotation during the hurricane induced differences in the surge pattern at both coasts. On the east coast, the highest wind magnitude (~28m/s northwestward) was recorded at Lake Worth Pier. Because barometric pressure had no apparent effect on the west coast’s storm surge, wind forcing was more influential. For local variations of PV , the response Δη of sea level (Pugh, 1987, p195) is given as Δη = −ΔPV /( ). Taking = 1026 kg/m3 and = 9.8 m/s2, the mean sea level increases ~1 cm with 1 hPa decrease. Persistent off-shore winds, with a marked southward component at Cedar Key for two days, triggered the negative storm surge. As the hurricane moved northward, the wind direction switched to onshore following its counterclockwise rotation. This direction change induced a positive surge on the west coast. The highest storm surge on the west coast (~1.6 m), at Naples, was excited by those of onshore winds. Along the east coast, onshore winds combined with low barometric pressure to generate the highest storm surges at each station.
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The wind stress was interpolated by inverse distance weighting, in the middle of the rectangular grid line between a pair of stations. The divergence of the wind stress ( / + / in N/m3) was computed between pairs of stations to relate it to the storm surge (Figure 3c and 3d). The timing of negative storm surge coincided with increased wind stress divergence (positive values in Figure 3c and d). Southward wind stresses off Clearwater Beach were stronger than those off Cedar Key, to the north. This wind divergence favored the appearance of decreased water level at the coast, similar to upwelling events, with the greatest negative storm surge. Moreover, the negative surge off Clearwater Beach was less prominent than that off Cedar Key. The average of the negative storm surges at Cedar Key and Clearwater Beach were -0.8 m and -0.4 m, respectively. The difference in negative surge between the two sites was related to the geometry of the coastline and the fetch of wind stress action. Cedar Key is in the middle of the Florida Big Bend region (Figure 1a) where there is essentially no water fetch for southward winds. Clearwater Beach is at the southernmost end of the Florida Big Bend region (Figure 1a) where the coastline protrudes onto the gulf. From Cedar Key to Clearwater Beach, the water fetch is nearly 130 km. The shoreline at Cedar Key is aligned northwestward and at Clearwater it changes to northeastward. This coastline protrusion allows water to be transported from the north toward Clearwater and partially pile up, thus diminishing the negative surge magnitude.
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Still on the west coast of Florida, the wind convergence between Port Manatee and Fort Myers (negative values in Figure 3c and d) generated a positive surge, even though there was a phase delay between the positive storm surge and the wind stress convergence. Before Irma’s eye arrived, offshore wind (southwestward winds) transported water away from the west coast. After relaxation of southwestward winds and reversal to northeastward with the passage of the hurricane’s eye, the surge at Naples became positive. At 5:48 on 11 September, the convergence (Figure 3c) near Naples was 0.6 times smaller than near Fort Myers or Port Manatee. However, the northeastward winds ~20 m/s near Naples actually caused convergence on the west coast. The effects of the strongest northeastward winds and convergence at Naples corresponded to the highest storm surge along the west coast.
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Along the east coast, the storm surge was primarily associated with wind stress convergence (Figure 3d). The wind directions at Mayport were northwestward and at Fort Pulaski were southwestward at the time of greatest surge. Thus, the effects of onshore and converging winds combined with low barometric pressure to exacerbate the storm surge near Fernandina Beach, Florida. However, wind divergences (positive values in Figure 3c and d) did not generate negative storm surge along the east coast. Color contours in Figure 3d indicated divergence at Fernandina Beach and Mayport from September 9th to 11th. However, southwestward winds at the two locations, in fact denoted that the winds were onshore. This wind convergence to the coast, thus generated only positive surge along the east coast as shown in Figure 2. The most revealing findings caused by hurricane Irma around Florida’s coast are discussed in the next section.
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5 Discussion
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This section explores the relationship between storm surge and atmospheric forcing (i.e., barometric pressure and wind stresses). Storm surge on the west coast of the Florida peninsula related more to wind divergence than wind stress and barometric pressure. Scatter plots (Figure 4) show the relationship between atmospheric forcing and storm surge. On the west coast, barometric pressure seems to have had no effect on storm surge (Figure 4a). Storm surge at Cedar Key became increasingly negative, regardless of the low barometric pressure. At Key West, storm surge increased to ~1 m as barometric pressure decreased to ~960 hPa but the influence was relatively weak. On the east coast, the response was better defined: surges were inversely proportional to the barometric pressure (Figure 4b).
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Possible relationships between storm surge and wind stress are explored in Figure 4c through 4f. The only station, Naples on the west coast showed linkage between storm surge and east wind stress, . Positive , which denotes onshore winds, coincided with positive storm surge. Consistently, offshore winds at Naples contributed to negative storm surge. The combination of low barometric pressure and onshore winds generated positive storm surge at Key West. As mentioned in the previous section, all stations of the east coast displayed positive storm surges. Scatter plots in Figure 4d show storm surge associated with . The wind direction along the east coast was predominantly onshore (westward) over the entire period. Lake Worth Pier had the strongest onshore wind stresses but Fernandina Beach, ~500 km to the north, recorded the highest storm surge. This, and the results of Figure 3, suggested that the wind stress divergence was also influential to the storm surge on the east coast.
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The storm surge relation to the north component of the wind stress, , was tentative. Cedar Key had the greatest negative storm surge despite the relatively weak northward
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component of wind stresses. Instead, the negative surge was linked to the wind stress divergence between Clearwater Beach and Cedar Key (Figure 3c). Standard deviation of at Mayport and Fernandina Beach was 0.19 and 0.07 N/m , respectively. This indicated that the wind stress was greater at Mayport than Fernandina Beach. Yet, the highest storm surges were observed at Fernandina Beach. This study proposes that the wind stress divergence could have as much an effect on the storm surge as barometric pressure and wind stress, as explained next with the analytical solution.
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Figure 4. Scatter plots showing the relationship between storm surges (m) and barometric pressures (hPa) during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. c) and d) show the relationship between storm surge and the east-west wind stress (N/m2). e) and f) show the relationship between storm surge and the north-south wind stress. In the legend on the left, colored circles represent the west coast
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stations. In the legend on the right, colored asterisks represent the east coast stations. The vertical axes represent storm surge and the horizontal axes represent each atmospheric forcing.
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The relationship between surge and a) wind stress divergence and b) wind stress curl was explored using scatter plots in Figure 5. Along the west coast, the negative storm surges at Naples and Cedar Key were associated with a positive wind stress divergence (Fig. 5a) as suggested in section 4.2. Along the east coast, negative wind divergence was related to maximum surge levels. Wind divergence was most effective when wind blew offshore, and contributed to the negative surge along the west coast. In contrast, the positive surge was mainly dominated by onshore winds as observed in Fig. 4d and 4f. Wind curl effects along the west coast (Fig. 5c) had no clear relationship with the storm surge because positive and negative surges coincided with a positive curl. Along the east coast, before hurricane arrival at the stations the curl was negative (Fig. 3). When Irma landed, the maximum surge was associated with a positive wind curl (Fig. 5d). This indicated that the effect of the wind divergence was relevant for both coasts. Wind stress curl showed a better relationship with the observed storm surge at the east coast than at the west coast.
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Figure 5. Scatter plots showing the relationship between storm surges (m) and the divergence of the wind stress during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. c) and d) show the relationship between storm surge and the curl of the wind stress. In the legend on the left, colored circles represent the west coast stations. In the legend on the right, colored asterisks represent the east coast stations.
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Figure 6. Hovmöller diagrams of wind velocities (vectors, m/s) and computed water level variation (color contours, m) in a 6-min interval, during the period influenced by Irma a) along the west coast of Florida and b) along the US Atlantic Coast. For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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The storm surge from the analytical model indicated the greatest negative storm surge, ~2.1 m, near Clearwater Beach (Figure 6a). The greatest observed negative storm surge (Figure 2a) appeared at Cedar Key. Because the model neglects effects of coastline geometry and bathymetry, it did not resolve the fetch of wind stress. In the analytical model, the greatest negative storm surge thus appeared near Clearwater Beach, where the wind divergence was strongest. The greatest positive storm surge, ~2.0 m, was estimated at Naples, as observed along the west coast (Figure 2a).
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Along the east coast, the model predicted positive storm surges at all stations as westward winds converged on the east coast (Figure 6b). In contrast with observations, the greatest storm surge was predicted at Lake Worth Pier, because the wind stresses were strongest and onshore. The discrepancy between observations and theory was attributed to the absence of a detailed coastline boundary and bathymetry in the model. A numerical model simulation, based on storm size, water fetch, shoreline orientation, and water depth, would explicitly determine the importance of the wind stress divergence and curl. However, the analytical model pointed out to the sensitivity of the surge to wind stress divergence and curl.
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Figure 7. Model validation indices. Root mean squared error (RMSE, solid line), squared correlation coefficient (R2, dashed line) and model skill (dotted line) for the a) west (black) and b) east (red) coast of Florida Peninsula.
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The error analysis was performed with Equations (7), (8), and (9) under the assumptions of the analytical model (constant depth and infinite domain). Along the west coast (Figure 7a), the highest error was 0.72 m around Cedar Key. That error coincided with the location of the greatest observed negative surge (Figure 2a). The model performed well from Vaca Key to Clearwater Beach, where the correlation coefficient was around 0.5 and the skill was around 0.7. Errors may be related to the coastline orientation changing just before the Florida Bight at Cedar Key. Along the east coast (Figure 7b), the highest error of 0.78 m coincided with the highest positive storm surge observed around Fernandina Beach. In addition, correlation coefficients and the model skill decreased northward from Vaca Key. Between Virginia Key and Key West the error was lowest, < 0.2 m, and the skill, > 0.9, and squared correlation, ~0.8, were the highest.
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Neglecting atmospheric pressure and changes in coastline orientation yielded increased errors and decreased model skill. The importance of the analytical results in this application is that, at both coasts, the effects of changing coastline orientation and of atmospheric pressure are not negligible. The model with atmospheric pressure effects would represent better the positive surge observed along the east coast because the scatter plot at Fig.4b showed a well-defined relationship between the surge and the barometric pressure.
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6. Conclusion
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A hurricane that translated along a peninsula caused simultaneous positive and negative surges on both sides of the peninsula. Positive surges were observed on the right side of the hurricane, while both positive and negative surges appeared on the left side. This behavior was unforeseen in hazard advisories. On the coast affected by the right side of the hurricane, surges were related to onshore winds and decreased barometric pressures. On the coast affected by the left side, barometric pressure was unrelated to the surge. Observational and analytical model results showed that the wind stress divergence and curl are essential to simulate the storm surge reliably. On the west coast, the wind stress positive divergence influenced the negative storm
391 392 393 394 395
surge; meanwhile the effect of wind stress curl was negligible. In contrast, on the east coast, the direct effect of the onshore wind dominated over the divergence to generate the positive surge influenced by a negative wind-stress curl. The analytical model indices illustrated the importance of considering changes in the coastline orientation as the skill and error of the model decreased and increased, respectively, at locations where the coastline orientation changed.
396
Acknowledgments
397 398 399
Atmospheric forcing data were obtained from the NOAA Tides and Currents (https://tidesandcurrents.noaa.gov/). This study was funded by the Gulf of Mexico Research Initiative through the CARTHE Research Consortium.
400
References
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Bilskie, M. V., S. C. Hagen, S. C. Medeiros, A. T. Cox, M. Salisbury, and D. Coggin (2016), Data and numerical analysis of astronomic tides, wind-waves, and hurricane storm surge along the northern Gulf of Mexico, JGR: Oceans, 121(5), 3625-3658.
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Feng, X., M. Olabarrieta, and A. Valle-Levinson (2016), Storm-induced semidiurnal perturbations to surges on the US Eastern Seaboard. Cont. Shelf Res. 114, 54-71.
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Fossell, K. R., Ahijevych, D., Morss, R. E., Snyder, C., & Davis, C. (2017). The practical predictability of storm tide from tropical cyclones in the Gulf of Mexico. Monthly Weather Review, 145(12), 5103-5121.
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Gill, A. E. (1982), Atmosphere-Ocean Dynamics. Academic Press, 30. 662 pp.
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Hall, T. M., and A. H. Sobel (2013), On the impact angle of Hurricane Sandy’s New Jersey landfall. Geophys. Res. Lett. 40, 2312-2315.
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Hinkel, J., D. Lincke, A. T. Vafeidis, M. Perrette, R. J. Nicholls, R. S.J. Tol, B. Marzeion, X. Fettweis, C. Lonescu, and A. Levermann (2014), Coastal flood damage and adaptation costs under 21st century sea-level rise. Proc. Natl. Acad. Sci. USA, 111, 3292-3297.
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Horsburgh, K. J., and C. Wilson (2007), Tide-surge interaction and its role in the distribution of surge residuals in the North Sea. JGR: Oceans, 112(C8).
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Irish, J. L., D. T. Resio, and J. J. Ratcliff (2008), The influence of storm size on hurricane surge. J. Phys. Oceanogr. 38, 2003-2013.
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Kemp, A. C., and B. P. Horton (2013), Contribution of relative sea-level rise to historical hurricane flooding in New York City. J. Quat. Sci. 28, 537-541.
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Kennedy, A. B., U. Gravois, B. C. Zachry, J. J. Westerink, M. E. Hope, R. A. Luettich, and R. G. Dean (2011), Origin of the Hurricane Ike forerunner surge, Geophys. Res. Lett. 38(L08608).
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Lin, N., K. A. Emanuel, J. A. Smith, and E. Vanmarcke (2010), Risk assessment of hurricane storm surge for New York City. JGR: Atmospheres, 115, D18121.
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Morey, S. L., S. Baig, M. A. Bourassa, D. S. Dukhovskoy, and J. J. O'Brien (2006), Remote forcing contribution to storm-induced sea level rise during Hurricane Dennis, Geophys. Res. Lett. L19603.
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Muis, S., M. Verlaan, H. C. Winsemius, J. C.J.H. Aerts, and P. J. Ward (2016), A global reanalysis of storm surges and extreme sea levels. Nat. Comm. 7 (11969).
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Prandle, D., and J. Wolf (1978), The interaction of surge and tide in the North Sea and River Thames. Geophys. J. Int. 55(1), 203-216.
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Proudman, J. (1955), The propagation of tide and surge in an estuary. Proc. R. Soc. Lond. Ser. A. Math. Phys. Sci. 231 (1184), 8-24.
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Pugh, D. T. (1987), Tides, surges and mean sea-level: A handbook for engineers and scientist. John Wiley & Sons, 472 pp.
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Resio, D. T., Irish, J., & Cialone, M. (2009). A surge response function approach to coastal hazard assessment–part 1: basic concepts. Natural Hazards, 51(1), 163-182.
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Thiebaut, S., R. Vennell (2011), Resonance of long waves generated by storms obliquely crossing shelf topography in a rotating ocean. J. Fluid Mech. 682. 261-288.
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Thomson, R. E., & Emery, W. J. (2014). Data analysis methods in physical oceanography. Newnes.
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Valle-Levinson, A., M. Olabarrieta, and A. Valle (2013), Semidiurnal perturbations to the surge of Hurricane Sandy. Geophys. Res. Lett. 40.
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Wahl, T., S. Jain, J. Bender, S. D. Meyers, and M. E. Luther (2015), Increasing risk of compound flooding from storm surge and rainfall for major US cities. Nat. Clim. Chang. 5, 1093–1097.
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Warner, J. C., Geyer, W. R., & Lerczak, J. A. (2005). Numerical modeling of an estuary: A comprehensive skill assessment. Journal of Geophysical Research: Oceans, 110(C5).
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Weisberg, R. H., and L. Zheng (2008), Hurricane storm surge simulations comparing threedimensional with two-dimensional formulations based on an Ivan-like storm over the Tampa Bay, Florida region, JGR: Oceans, 113(C12).
Highlights
• • •
Effects of Hurricane Irma on Florida Peninsula were analyzed with water level and atmospheric forcing records. Storm surges on the west coast of Florida were markedly different from those on the east coast. Wind stress divergence is critical for determining storm surge and flood risk.
S0272-7714(19)30291-4
DOI:
https://doi.org/10.1016/j.ecss.2019.106402
Reference:
YECSS 106402
To appear in:
Estuarine, Coastal and Shelf Science
Received Date: 26 March 2019 Revised Date:
19 August 2019
Accepted Date: 2 October 2019
Please cite this article as: So, S., Juarez, B., Valle-Levinson, A., Gillin, M.E., Storm surge from Hurricane Irma along the Florida Peninsula, Estuarine, Coastal and Shelf Science (2019), doi: https:// doi.org/10.1016/j.ecss.2019.106402. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
1
Storm surge from Hurricane Irma along the Florida Peninsula
2
Sangdon So1, Braulio Juarez1, Arnoldo Valle-Levinson1, and Matlack E. Gillin1
3
1
Civil and Coastal Engineering Department, University of Florida, Gainesville, Florida, USA.
4
Corresponding author: Braulio Juarez ([email protected])
5
Key Points:
6 7 8 9 10 11
•
Effects of Hurricane Irma on Florida Peninsula were analyzed with water level and atmospheric forcing records.
•
Storm surges on the west coast of Florida were markedly different from those on the east coast.
•
Wind stress divergence is critical for determining storm surge and flood risk.
12
Abstract
13 14 15 16 17 18 19 20 21 22
Hurricane Irma impacted the entire Florida peninsula in September 2017. The combination of Irma’s strength, size, and track provided a unique opportunity to study hurricane effects on storm surge on both sides of a peninsula. Storm surge characteristics on the west coast of Florida were markedly different from those on the east coast. On the west coast, the maximum storm surge was 1.6 m at Naples, which was attributed to onshore winds and an atmospheric pressure of 970 hPa. A stunning negative surge of -2.7 m appeared at Cedar Key, in the peninsula’s northwestern quarter, after ~10 hr of oblique offshore and divergent winds. On the east coast, the maximum surge was 2.4 m at Fernandina Beach, where wind velocity displayed horizontal convergence. A revealing finding of this investigation was that wind divergence is an essential component for predicting storm surge.
23
1 Introduction
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Storm surge, taken as the difference between observed and predicted tides (ValleLevinson et al., 2013), depends on storm size, atmospheric pressure, wind velocity, wind fetch and duration, the angle relative to the coast, and bathymetry (Hall and Sobel, 2013; Resio et al., 2009). Storm surge caused by hurricanes can devastate densely populated coastal regions. Moreover, the combination of storm surge and heavy precipitation exacerbates flooding in lowlying coastal areas (Wahl et al., 2015). The response of storm surge to atmospheric forcing needs improved understanding as its destructive effects increase with sea level rise, coastal development and building construction (Muis et al., 2016; Hinkel et al., 2014; Kemp and Horton, 2013).
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Numerical models have been used to simulate storm surge (e.g. Weisberg and Zheng, 2008; Bilskie et al, 2016). A study investigated the sensitivity of coastal inundation to hurricane attributes: track, intensity, size, and translation speed (Foster et al., 2017). They simulated the coastal inundation with three different hurricanes: Charly, Ike, and the hypothetical “Charike”. The results showed that surge inundation is more sensitive to storm size and landfall location than storm speed. Some efforts have explored surges with unexpected behavior. Morey et al. (2006) studied an unanticipated 2-3 m surge along Apalachee Bay, Florida, during Hurricane Dennis. They demonstrated that along-shore winds translated northwestward along the bay to generate a storm surge similar to a topographic Rossby wave. They also showed that storm surge models could be improved for a storm translating along a similar track. Two- and threedimensional simulations described the vulnerability of Tampa Bay to storm surge and the advantage of three-dimensional over two-dimensional models (Weisberg and Zheng, 2008). Other simulations in the northern Gulf of Mexico have shown that geometry and bathymetry affected the timing and height of the storm surges related to hurricanes Ivan, Dennis, Katrina, and Issac (Bilskie et al., 2016). Also in the northern Gulf, Hurricane Ike caused a ‘forerunner’ surge before the hurricane-forced surge (Kennedy et al., 2011). This forerunner was attributed to Ekman setup and was proposed as a potential mechanism of inundation in low-lying coastal areas. Previous studies on hurricane-related surges have focused on the generation by onshore winds and low barometric pressure. However, as shown in this study, other mechanisms can also be influential.
53 54
Each hurricane generates a unique storm surge, which is mainly associated with meteorological conditions and coastline topography (Irish et al., 2008; Lin et al, 2010).
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Hurricane Irma in 2017 provided a rare combination of positive and negative surges along the east and west coast of Florida. The negative surge observed in west Florida was not described by forecasts. Additionally, semi-diurnal perturbations to the storm surge appeared within bights on both northern coasts of Florida. The goal of this investigation was to describe the effect of Hurricane Irma on the west and east coasts of the Florida Peninsula and to identify the forcing associated with the peculiar surge behavior along the peninsula. The effect of Hurricane Irma was analyzed with water level and atmospheric observations on Florida’s west coast and on the US southeastern coast. This study indicated that wind divergence is critical for determining storm surge of a hurricane translating along a peninsula.
64
2 Storm Trajectory
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Hurricane Irma developed near the Cape Verde islands, off the northwestern coast of Africa, at 15:00 GMT on 30 August 2017. After steadily gaining strength and size under favorable conditions (Atlantic-wide track and ocean surface temperatures >28°C), Irma attained Category 5 status on 5 September in the Caribbean. As a Category 5 hurricane, Irma fringed northern Puerto Rico, the Dominican Republic, and Haiti, where it was then downgraded to Category 4. Irma regained Category 5 status as it made landfall in Cuba, at 3:00 GMT on 9 September with maximum sustained winds of ~72m/s and a barometric pressure of 924 hPa. On 9 September, Irma weakened to a Category 3 hurricane as it passed over northern Cuba. Irma’s path between 10 and 12 September was north-northwestward toward south Florida (Figure 1a). Irma strengthened to Category 4 at 6:00 GMT on 10 September over the Straits of Florida. It crossed the Florida Keys ~32 km east of Key West with maximum sustained winds of ~58 m/s (Figure 1c) and a central barometric pressure of 929 hPa (Figure 1d). Irma continued northward with an average translation speed of ~6 m/s (Figure 1b) and then arrived near Naples, Florida, at 20:00 GMT on 10 September with maximum sustained winds of ~51 m/s and a barometric pressure of 940 hPa. The hurricane moved northward on land, skirting the west coast of Florida with an average speed of ~7.5 m/s. Irma became a tropical storm as it passed north of Tampa Bay at 12:00 GMT on 11 September. According to the National Weather Service, Irma’s wind field extended up to ~650 km radially from the center of the storm on 11 September.
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Figure 1. a) Track of Hurricane Irma between 10 and 12 September 2017. Each label appears at the beginning and noon of the day (GMT). Colored circles denote the Category of the Hurricane. Red stars indicate NOAA weather stations with barometric pressure, wind, and water level data. Blue lines are the 10, 50 and 100 m isobaths. b) Translation speed (m/s) calculated by the Hurricane locations. Blue line presents five-point moving average of the data points. c) Maximum sustained speed (m/s). d) Barometric pressure (hPa).
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3 Methods
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Water level data were obtained from 11 stations along the west coast of Florida and 8 stations along the US east coast (Figure 1a) maintained by the National Oceanic and
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Atmospheric Administration (NOAA). Data were available from NOAA’s Tides & Currents portal (https://tidesandcurrents.noaa.gov). Compiled water level data included verified observations and predicted values related to astronomical tide. Depending on availability, barometric pressure and wind velocities were retrieved from most, but not all, water level stations. Barometric pressures were unavailable at Lake Worth Pier. Wind data were unavailable at Port Manatee, FL, Pensacola, FL and Springmaid Pier, SC. The data from NOAA were compiled at 6-minute intervals from 9 through 12 September 2017.
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Hovmöller diagrams are widely used in atmospheric sciences to describe spatial and temporal variability of a scalar or vector. This study presents a series of Hovmöller diagrams, describing the evolution of several variables along the east and west coast of the Florida peninsula. The variables include de-tided water level (observed minus predicted), wind velocity, barometric pressure, and wind stress divergence ( / + / in N/m3). Also represented in a Hovmöller diagram is the detided water level obtained from an analytical solution of storm surges. In this application, the axes of the Hovmöller diagrams represent time (x-axis) and distance from Key West (y-axis) with the value of the variables displayed in colored contours. For the diagrams on the west coast of Florida, time increases to the left in order to describe simultaneously the storm-related signals as they propagated from their reference origin, Key West, along both sides of the peninsula. All times are represented in Greenwich Mean Time (GMT) for the period studied.
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Wind stress divergence was included as a study parameter because of its prominence in representing pulses generated by a moving atmospheric disturbance (Thiebaut and Vennell, 2011). The analytical representation, also used here, consists of a two-dimensional analytical barotropic model, implemented for transient shallow-water waves. The transient shallow-water wave ( ) is expressed in terms of a) wave celerity ( = ℎ, where is gravity acceleration and ℎ is constant water depth), b) Coriolis frequency ( ), and c) the combined forcing ( ) of atmospheric pressure and wind-stress. The model’s momentum balance, combined with continuity, is given by (Thiebaut and Vennell, 2011):
115 116 117 118
− 119
120 121 122
∂
∇
=
=− ∇
,
(1)
∇
−
1
∇· +
,
(2)
where is the water level related to the inverse barometer effect, is wind stress, and (∇ × )/( ) is Ekman pumping, proportional to wind stress curl. The combined forcing, expressed as: " exp&'()*
= is
+ +, − - ./. (3)
With eq. (3) the steady-state forced wave solution to Equation (1) is: ,
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+
The forcing term of the analytical model (rhs of eq 1) is given by:
= 123
∇
=
," exp&'()*
+ +, − - ./ ,
(4)
where ," = " /(1 − 3 + 45 ) in which 3 = -/( 6, ) is the Froude number and 45 = 4/(2748 ) is the dimensionless disturbance width, which compares the disturbance width, L, to
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the Rossby radius of deformation 48 = / , 6, = ), + +, is the wave number magnitude, ' = √−1; )* and +, are the and -components of the atmospheric disturbance’s wave number, respectively; - is the angular frequency of the atmospheric disturbance; and " is the sum of atmospheric pressure and wind forcing. "
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=
"
+
": ,
(5)
The dominance of wind forcing in Equation (5) was described by Gill (1982). When atmospheric pressure effects can be neglected, the wind forcing, " can be approximated as ": (see Thiebaut and Vennell, 2011): ":
=
1 <(), 6,
"
+ +,
".
−'
-
(),
"
− +,
" .= ,
(6)
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The ratio between and - in (6) shows the significance between the wind stress divergence (first term on the rhs of (6)) and the curl of the wind stress (second term). The divergence, (), " + +, " ., becomes more important than the curl, (), " − +, " ., for high frequency forcing (f <ω).
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Details on the steady-state wave solution of Equation (1) are given by Thiebaut and Vennell (2011). The storm surge , was estimated using Equation (4) by including wind stress divergence and Ekman pumping, as shown in section 5, after describing hurricane Irma’s surge and forcing agents. The amplitude of the forced wave in equation (4) depends on the wind stress, wave number, Earth’s rotation, disturbance angular frequency, and wave celerity. In turn, wave celerity depends on the water depth that was the only parameter to define. Depth variability modified the surge amplitudes but did not change the location of relative maximum and minimum surges that related to the wind field distribution. Thus, a constant water depth of 7 m is used in this study because is representative of all stations (Fig. 1) and reproduced the observed surge well.
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The model results along the coast are compared with observations using three indices: the Root mean square error (RMSE); squared correlation coefficient (R2 see Thomson and Emery (2014); and Skill (see Warner et al., 2005)
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H 1 ?@AB = < D ( C IJK
? =M 150 151 152 153
H ( 1 D C−1 IJK
EFG
K/
EFG − , ) =
,
(7)
− NNNNNN EFG )( , − NNN ,) Q , OPEFG OP,
(8)
where N is the total number of observation points in time, EFG represents the observed surge, , is the modeled surge obtained with equation 4, OPEFG and OP, are the standard deviation of the observed and modeled surge respectively, and the overbar denotes a time mean. In addition, the model skill was calculated as (Warner et al., 2005): A)'++ = 1 −
∑H IJK(| ,
∑H IJK|
− − NNNNNN| EFG + | ,
EFG | EFG
− NNNNNN| EFG )
,
(8)
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Skill equals to one indicates a perfect agreement between the modeled and observed surge, and a disagreement is indicated by a skill close to zero.
156
4 Results
157
4.1 Storm Surge
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The track of Irma along the Florida Peninsula provided a unique scenario of simultaneous storm surge on the west and east coasts of Florida. Hovmöller diagrams in Figure 2 show the time evolution of storm surge and wind vectors at NOAA stations and at 6-min intervals. Florida’s west coast (Figure 2a) displayed both negative and positive storm surges, while storm surges were all positive along the Atlantic coast (Figure 2b). Storm surge at Key West was 1 m at 14:24 on 10 September when Hurricane Irma passed over the Florida Keys. The highest storm surge on the west coast was 1.6 m at 23:06 on 10 September at Naples. The greatest negative storm surge, an astounding -2.7 m, occurred at 8:12 on 11 September at Cedar Key. Negative surges occurred over the entire west coast of the peninsula. This negative surge allowed people, mainly around the Tampa area, to walk offshore previous to the subsequent positive surge. North of Naples, the surge reached values around 1 m, which contrasted to the anticipated 5 m announced in municipality and state advisories. Along the Atlantic Coast, Fernandina Beach recorded the highest storm surge (2.4 m) at 10:24 on 11 September. The storm surge exhibited a unique behavior in the sense that it appeared simultaneously on both sides of a peninsula. One of the revealing aspects of the storm surge was its negative values on the west coast of Florida despite the low (<990 hPa) barometric pressures recorded.
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Semidiurnal perturbations to the surge appeared in the South Atlantic Bight, between Trident Pier and Springmaid Pier (Figure 2b). These perturbations were related to tide-storm interactions (Valle-Levinson et al., 2013; Feng et al., 2016). For the first time, semidiurnal perturbations were also observed on the west coast of Florida, between Clearwater Beach and Apalachicola Bay, in a region known as the Florida Big Bend. These perturbations developed within a bight and in the region of dominant semidiurnal tide in the Southeastern US and in the Gulf of Mexico. This prominence of semidiurnal perturbations is because the intensity of tidesurge interactions is proportional to tidal amplitude (i.e. Proudman, 1955; Prandle and Wolf, 1978; Horsburgh and Wilson, 2007). Along the US Atlantic coast, Feng et al. (2016) demonstrated the evidence of tide-surge interactions. They indicated that the largest semidiurnal perturbation mostly occurred near the South Atlantic Bight apex during the passage of Hurricane Floyd in 1999. In addition, 93% of events described in that study were characterized by a phase delay of the observed tide relative to the predicted tide (Feng et al., 2016). During Irma, intense perturbations generated by tide-storm interactions (Valle-Levinson et al., 2013; Feng et al., 2016) were again observed near the apex (Fort Pulaski, Figure 2b). Further studies should explore the persistence of semidiurnal perturbations in the Florida Big Bend during storms. The next section explores the effects of barometric pressure and wind forcing on storm surge.
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Figure 2. Hovmöller diagrams of wind velocities (vectors, m/s) and storm surge (color contours, m) at 6-min intervals, during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. White dots indicate the time and locations of the lowest barometric pressure. Storm surge and winds were interpolated to the grid points (50 km in distance, 6 min in time) by a Delaunay triangulation (Matlab’s default). For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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4.2 Barometric Pressure and Winds
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Among Florida’s west coast stations, Naples, on the southwest coast of the peninsula, showed the lowest barometric pressure (~939 hPa) at 20:54 on 10 September (Figure 3a). In contrast, the lowest barometric pressure on the east coast was almost 50 hPa higher and ~13 h later at Trident Pier (~988 hPa), in the middle of the peninsula, at 12:18 on 11 September (Figure 3b). The lowest barometric pressure was observed on the west coast of Florida because Irma made landfall near Naples and its trajectory fringed Florida’s west coast. At each station on the east coast, the lowest barometric pressure roughly corresponded to the time of greatest storm surge. However, the same was not the case for the west coast. This indicated that barometric pressure had a limited effect on storm surge along the west coast. As an example, the storm surge at Cedar key was -2.7 m, even though the barometric pressure was 979 hPa at 8:12, 11 September. Hovmöller diagrams of barometric pressure show a cone-shaped distribution along both coasts of Florida. The lowest local pressure propagated quasi-linearly in the time-space domain.
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Figure 3. Hovmöller diagrams of wind velocities (vectors, m/s) and barometric pressure (color
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contours, hPa) in a 6-min interval, during the period influenced by Irma a) along the west coast of Florida and b) along the US Atlantic Coast. White dots indicate the time and locations of the lowest barometric pressure. Barometric pressure and winds were interpolated as in Figure 2. Hovmöller diagrams of wind velocities (vectors) and the divergence of the wind shear stresses (color contours, N/m3) during the period influenced by Irma c) along the west coast of Florida and d) along the Southeastern US Atlantic Coast. Positive contours denote divergence of wind stress. Hovmöller diagrams of wind velocities (vectors) and the curl of the wind shear stresses (color contours, N/m3) during the period influenced by Irma e) along the west coast of Florida and f) along the Southeastern US Atlantic Coast. Positive contours denote wave setup. For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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Wind directions were predominantly southwestward along both Florida coasts before Irma. After the storm, wind directions became primarily northeastward at both coasts. Key West, the first site of Irma’s impact, recorded the highest wind magnitude (~31m/s southeastward) along the west coast at 12:24 on 10 September. Counterclockwise wind rotation during the hurricane induced differences in the surge pattern at both coasts. On the east coast, the highest wind magnitude (~28m/s northwestward) was recorded at Lake Worth Pier. Because barometric pressure had no apparent effect on the west coast’s storm surge, wind forcing was more influential. For local variations of PV , the response Δη of sea level (Pugh, 1987, p195) is given as Δη = −ΔPV /( ). Taking = 1026 kg/m3 and = 9.8 m/s2, the mean sea level increases ~1 cm with 1 hPa decrease. Persistent off-shore winds, with a marked southward component at Cedar Key for two days, triggered the negative storm surge. As the hurricane moved northward, the wind direction switched to onshore following its counterclockwise rotation. This direction change induced a positive surge on the west coast. The highest storm surge on the west coast (~1.6 m), at Naples, was excited by those of onshore winds. Along the east coast, onshore winds combined with low barometric pressure to generate the highest storm surges at each station.
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The wind stress was interpolated by inverse distance weighting, in the middle of the rectangular grid line between a pair of stations. The divergence of the wind stress ( / + / in N/m3) was computed between pairs of stations to relate it to the storm surge (Figure 3c and 3d). The timing of negative storm surge coincided with increased wind stress divergence (positive values in Figure 3c and d). Southward wind stresses off Clearwater Beach were stronger than those off Cedar Key, to the north. This wind divergence favored the appearance of decreased water level at the coast, similar to upwelling events, with the greatest negative storm surge. Moreover, the negative surge off Clearwater Beach was less prominent than that off Cedar Key. The average of the negative storm surges at Cedar Key and Clearwater Beach were -0.8 m and -0.4 m, respectively. The difference in negative surge between the two sites was related to the geometry of the coastline and the fetch of wind stress action. Cedar Key is in the middle of the Florida Big Bend region (Figure 1a) where there is essentially no water fetch for southward winds. Clearwater Beach is at the southernmost end of the Florida Big Bend region (Figure 1a) where the coastline protrudes onto the gulf. From Cedar Key to Clearwater Beach, the water fetch is nearly 130 km. The shoreline at Cedar Key is aligned northwestward and at Clearwater it changes to northeastward. This coastline protrusion allows water to be transported from the north toward Clearwater and partially pile up, thus diminishing the negative surge magnitude.
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Still on the west coast of Florida, the wind convergence between Port Manatee and Fort Myers (negative values in Figure 3c and d) generated a positive surge, even though there was a phase delay between the positive storm surge and the wind stress convergence. Before Irma’s eye arrived, offshore wind (southwestward winds) transported water away from the west coast. After relaxation of southwestward winds and reversal to northeastward with the passage of the hurricane’s eye, the surge at Naples became positive. At 5:48 on 11 September, the convergence (Figure 3c) near Naples was 0.6 times smaller than near Fort Myers or Port Manatee. However, the northeastward winds ~20 m/s near Naples actually caused convergence on the west coast. The effects of the strongest northeastward winds and convergence at Naples corresponded to the highest storm surge along the west coast.
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Along the east coast, the storm surge was primarily associated with wind stress convergence (Figure 3d). The wind directions at Mayport were northwestward and at Fort Pulaski were southwestward at the time of greatest surge. Thus, the effects of onshore and converging winds combined with low barometric pressure to exacerbate the storm surge near Fernandina Beach, Florida. However, wind divergences (positive values in Figure 3c and d) did not generate negative storm surge along the east coast. Color contours in Figure 3d indicated divergence at Fernandina Beach and Mayport from September 9th to 11th. However, southwestward winds at the two locations, in fact denoted that the winds were onshore. This wind convergence to the coast, thus generated only positive surge along the east coast as shown in Figure 2. The most revealing findings caused by hurricane Irma around Florida’s coast are discussed in the next section.
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5 Discussion
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This section explores the relationship between storm surge and atmospheric forcing (i.e., barometric pressure and wind stresses). Storm surge on the west coast of the Florida peninsula related more to wind divergence than wind stress and barometric pressure. Scatter plots (Figure 4) show the relationship between atmospheric forcing and storm surge. On the west coast, barometric pressure seems to have had no effect on storm surge (Figure 4a). Storm surge at Cedar Key became increasingly negative, regardless of the low barometric pressure. At Key West, storm surge increased to ~1 m as barometric pressure decreased to ~960 hPa but the influence was relatively weak. On the east coast, the response was better defined: surges were inversely proportional to the barometric pressure (Figure 4b).
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Possible relationships between storm surge and wind stress are explored in Figure 4c through 4f. The only station, Naples on the west coast showed linkage between storm surge and east wind stress, . Positive , which denotes onshore winds, coincided with positive storm surge. Consistently, offshore winds at Naples contributed to negative storm surge. The combination of low barometric pressure and onshore winds generated positive storm surge at Key West. As mentioned in the previous section, all stations of the east coast displayed positive storm surges. Scatter plots in Figure 4d show storm surge associated with . The wind direction along the east coast was predominantly onshore (westward) over the entire period. Lake Worth Pier had the strongest onshore wind stresses but Fernandina Beach, ~500 km to the north, recorded the highest storm surge. This, and the results of Figure 3, suggested that the wind stress divergence was also influential to the storm surge on the east coast.
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The storm surge relation to the north component of the wind stress, , was tentative. Cedar Key had the greatest negative storm surge despite the relatively weak northward
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component of wind stresses. Instead, the negative surge was linked to the wind stress divergence between Clearwater Beach and Cedar Key (Figure 3c). Standard deviation of at Mayport and Fernandina Beach was 0.19 and 0.07 N/m , respectively. This indicated that the wind stress was greater at Mayport than Fernandina Beach. Yet, the highest storm surges were observed at Fernandina Beach. This study proposes that the wind stress divergence could have as much an effect on the storm surge as barometric pressure and wind stress, as explained next with the analytical solution.
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Figure 4. Scatter plots showing the relationship between storm surges (m) and barometric pressures (hPa) during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. c) and d) show the relationship between storm surge and the east-west wind stress (N/m2). e) and f) show the relationship between storm surge and the north-south wind stress. In the legend on the left, colored circles represent the west coast
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stations. In the legend on the right, colored asterisks represent the east coast stations. The vertical axes represent storm surge and the horizontal axes represent each atmospheric forcing.
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The relationship between surge and a) wind stress divergence and b) wind stress curl was explored using scatter plots in Figure 5. Along the west coast, the negative storm surges at Naples and Cedar Key were associated with a positive wind stress divergence (Fig. 5a) as suggested in section 4.2. Along the east coast, negative wind divergence was related to maximum surge levels. Wind divergence was most effective when wind blew offshore, and contributed to the negative surge along the west coast. In contrast, the positive surge was mainly dominated by onshore winds as observed in Fig. 4d and 4f. Wind curl effects along the west coast (Fig. 5c) had no clear relationship with the storm surge because positive and negative surges coincided with a positive curl. Along the east coast, before hurricane arrival at the stations the curl was negative (Fig. 3). When Irma landed, the maximum surge was associated with a positive wind curl (Fig. 5d). This indicated that the effect of the wind divergence was relevant for both coasts. Wind stress curl showed a better relationship with the observed storm surge at the east coast than at the west coast.
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Figure 5. Scatter plots showing the relationship between storm surges (m) and the divergence of the wind stress during the period influenced by Irma a) along the west coast of Florida and b) along the southeastern US Atlantic Coast. c) and d) show the relationship between storm surge and the curl of the wind stress. In the legend on the left, colored circles represent the west coast stations. In the legend on the right, colored asterisks represent the east coast stations.
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Figure 6. Hovmöller diagrams of wind velocities (vectors, m/s) and computed water level variation (color contours, m) in a 6-min interval, during the period influenced by Irma a) along the west coast of Florida and b) along the US Atlantic Coast. For the west coast of Florida, time increases to the left in order to simultaneously describe the propagation of the storm-related signals on both sides of the peninsula. The distance (km) from Key West station is marked with numbers on the outside y-axis, while the station names are labeled on the inside.
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The storm surge from the analytical model indicated the greatest negative storm surge, ~2.1 m, near Clearwater Beach (Figure 6a). The greatest observed negative storm surge (Figure 2a) appeared at Cedar Key. Because the model neglects effects of coastline geometry and bathymetry, it did not resolve the fetch of wind stress. In the analytical model, the greatest negative storm surge thus appeared near Clearwater Beach, where the wind divergence was strongest. The greatest positive storm surge, ~2.0 m, was estimated at Naples, as observed along the west coast (Figure 2a).
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Along the east coast, the model predicted positive storm surges at all stations as westward winds converged on the east coast (Figure 6b). In contrast with observations, the greatest storm surge was predicted at Lake Worth Pier, because the wind stresses were strongest and onshore. The discrepancy between observations and theory was attributed to the absence of a detailed coastline boundary and bathymetry in the model. A numerical model simulation, based on storm size, water fetch, shoreline orientation, and water depth, would explicitly determine the importance of the wind stress divergence and curl. However, the analytical model pointed out to the sensitivity of the surge to wind stress divergence and curl.
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Figure 7. Model validation indices. Root mean squared error (RMSE, solid line), squared correlation coefficient (R2, dashed line) and model skill (dotted line) for the a) west (black) and b) east (red) coast of Florida Peninsula.
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The error analysis was performed with Equations (7), (8), and (9) under the assumptions of the analytical model (constant depth and infinite domain). Along the west coast (Figure 7a), the highest error was 0.72 m around Cedar Key. That error coincided with the location of the greatest observed negative surge (Figure 2a). The model performed well from Vaca Key to Clearwater Beach, where the correlation coefficient was around 0.5 and the skill was around 0.7. Errors may be related to the coastline orientation changing just before the Florida Bight at Cedar Key. Along the east coast (Figure 7b), the highest error of 0.78 m coincided with the highest positive storm surge observed around Fernandina Beach. In addition, correlation coefficients and the model skill decreased northward from Vaca Key. Between Virginia Key and Key West the error was lowest, < 0.2 m, and the skill, > 0.9, and squared correlation, ~0.8, were the highest.
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Neglecting atmospheric pressure and changes in coastline orientation yielded increased errors and decreased model skill. The importance of the analytical results in this application is that, at both coasts, the effects of changing coastline orientation and of atmospheric pressure are not negligible. The model with atmospheric pressure effects would represent better the positive surge observed along the east coast because the scatter plot at Fig.4b showed a well-defined relationship between the surge and the barometric pressure.
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6. Conclusion
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A hurricane that translated along a peninsula caused simultaneous positive and negative surges on both sides of the peninsula. Positive surges were observed on the right side of the hurricane, while both positive and negative surges appeared on the left side. This behavior was unforeseen in hazard advisories. On the coast affected by the right side of the hurricane, surges were related to onshore winds and decreased barometric pressures. On the coast affected by the left side, barometric pressure was unrelated to the surge. Observational and analytical model results showed that the wind stress divergence and curl are essential to simulate the storm surge reliably. On the west coast, the wind stress positive divergence influenced the negative storm
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surge; meanwhile the effect of wind stress curl was negligible. In contrast, on the east coast, the direct effect of the onshore wind dominated over the divergence to generate the positive surge influenced by a negative wind-stress curl. The analytical model indices illustrated the importance of considering changes in the coastline orientation as the skill and error of the model decreased and increased, respectively, at locations where the coastline orientation changed.
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Acknowledgments
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Atmospheric forcing data were obtained from the NOAA Tides and Currents (https://tidesandcurrents.noaa.gov/). This study was funded by the Gulf of Mexico Research Initiative through the CARTHE Research Consortium.
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Highlights
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Effects of Hurricane Irma on Florida Peninsula were analyzed with water level and atmospheric forcing records. Storm surges on the west coast of Florida were markedly different from those on the east coast. Wind stress divergence is critical for determining storm surge and flood risk.