On hurricane parametric wind and applications in storm surge modeling

Lin, Ning; Chavas, Daniel R.

doi:10.1029/2011jd017126

Cited by 164 publications

(170 citation statements)

References 57 publications

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“…As noted in previous studies (Ling and Chavas, 2012;Resio et al, 2013;Taflanidis et al, 2011;Zhong et al, 2010), the recreation of hurricane wind and pressure fields from hurricane parameterizations can have a significant impact on model simulation results. Wind and pressure fields were developed for hurricane Bob using the NWS 23 (NOAA, 1979), the modified Rankine wind field as described in Cheung et al (2007), and the Holland wind field (Holland, 1980).…”

Section: Hurricane Bob Simulationmentioning

confidence: 99%

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Bastidas¹,

Knighton

Kline³

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991) utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland). The sensitive model parameters (of 11 total considered) include wind drag, the depth-induced breaking γ B , and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking α B ) and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

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Section: Hurricane Bob Simulationmentioning

confidence: 99%

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Bastidas¹,

Knighton

Kline³

2016

Nat. Hazards Earth Syst. Sci.

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“…20. In particular, the surface wind is estimated by fitting the wind velocity at the gradient height to an analytical hurricane wind profile (45), translating the gradient wind to the surface level with a velocity reduction factor (0.85) and an empirical formula for inflow angles (46), and adding a fraction (0.55 at 20 degrees cyclonically) of the storm translation velocity to account for the asymmetry of the wind field induced by the surface background wind (47). The surface pressure is also estimated from a simple parametric model (48).…”

Section: Methodsmentioning

confidence: 99%

Increased threat of tropical cyclones and coastal flooding to New York City during the anthropogenic era

Reed

Mann

Emanuel

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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In a changing climate, future inundation of the United States' Atlantic coast will depend on both storm surges during tropical cyclones and the rising relative sea levels on which those surges occur. However, the observational record of tropical cyclones in the North Atlantic basin is too short (A.D. 1851 to present) to accurately assess long-term trends in storm activity. To overcome this limitation, we use proxy sea level records, and downscale three CMIP5 models to generate large synthetic tropical cyclone data sets for the North Atlantic basin; driving climate conditions span from A.D. 850 to A.D. 2005. We compare pre-anthropogenic era (A.D. 850-1800) and anthropogenic era (A.D.1970-2005) storm surge model results for New York City, exposing links between increased rates of sea level rise and storm flood heights. We find that mean flood heights increased by ∼1.24 m (due mainly to sea level rise) from ∼A.D. 850 to the anthropogenic era, a result that is significant at the 99% confidence level. Additionally, changes in tropical cyclone characteristics have led to increases in the extremes of the types of storms that create the largest storm surges for New York City. As a result, flood risk has greatly increased for the region; for example, the 500-y return period for a ∼2.25-m flood height during the preanthropogenic era has decreased to ∼24.4 y in the anthropogenic era. Our results indicate the impacts of climate change on coastal inundation, and call for advanced risk management strategies. T ropical cyclones (TCs) and their associated storm surges are the costliest natural hazards to impact the U.S. Atlantic coast (1-3). For example, Hurricane Sandy caused an estimated $50 billion of damage and destroyed at least 650,000 houses in 2012, largely because of flooding from a 3-to 4-m storm surge and large waves (4). A storm surge is the anomalous rise of water above predicted astronomical tides, and its height is driven primarily by wind patterns, storm track, and coastal geomorphology forcing water onshore, with a smaller contribution from reduced atmospheric pressure allowing the ocean surface to rise. The financial cost and human impact of future storm surges will be controlled by the TC climate (frequency, intensity, size, duration, and location) and the rate of relative sea level rise (RSLR), which is the base water level upon which storm surges occur (5, 6). The flood height attained during a given storm is determined by combining storm surge, tides, and relative sea level. Therefore, as sea level rises through time, coastal inundation risk from storm surges rises as well. Thus, it is useful to conduct a longterm analysis of the impact of changing TC climates and RSLR on flood heights (7).The observational record of TCs in the North Atlantic Ocean basin spans A.D. 1851 to the present, but is too short (8) and potentially unreliable (9) to accurately assess long-term trends in TC frequency, intensity, and storm surge height, particularly for the largest events and for locations that rarely experience land...

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“…Although the local wind and surge estimates are less sensitive to inflow angle [50], the inflow angle θ 3 was considered in the present study, and can be described as a function of r [54]: …”

Section: Parametric Cyclone Modelmentioning

confidence: 99%

“…The wind field was modified from gradient height to 10 m above sea surface with a wind-reducing coefficient of 0.85 following [50]. The formula of B = 1.5 + (980 − P c )/120 presented by Hubbert et al [51] was adopted.…”

Section: Parametric Cyclone Modelmentioning

confidence: 99%

Simulation of Typhoon-Induced Storm Tides and Wind Waves for the Northeastern Coast of Taiwan Using a Tide–Surge–Wave Coupled Model

Chen

Lin

Jang

et al. 2017

Water

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Abstract:The storm tide is a combination of the astronomical tide and storm surge, which is the actual sea water level leading to flooding in low-lying coastal areas. A full coupled modeling system (Semi-implicit Eulerian-Lagrangian Finite-Element model coupled with Wind Wave Model II, SELFE-WWM-II) for simulating the interaction of tide, surge and waves based on an unstructured grid is applied to simulate the storm tide and wind waves for the northeastern coast of Taiwan. The coupled model was driven by the astronomical tide and consisted of main eight tidal constituents and the meteorological forcings (air pressure and wind stress) of typhoons. SELFE computes the depth-averaged current and water surface elevation passed to WWM-II, while WWM-II passes the radiation stress to SELFE by solving the wave action equation. Hindcasts of wind waves and storm tides for five typhoon events were developed to validate the coupled model. The detailed comparisons generally show good agreement between the simulations and measurements. The contributions of surge induced by wave and meteorological forcings to the storm tide were investigated for Typhoon Soudelor (2015) at three tide gauge stations. The results reveal that the surge contributed by wave radiation stress was 0.55 m at Suao Port due to the giant offshore wind wave (exceeding 16.0 m) caused by Typhoon Soudelor (2015) and the steep sea-bottom slope. The air pressure resulted in a 0.6 m surge at Hualien Port because of an inverted barometer effect. The wind stress effect was only slightly significant at Keelung Port, contributing 0.22 m to the storm tide. We conclude that wind waves should not be neglected when modeling typhoon-induced storm tides, especially in regions with steep sea-bottom slopes. In addition, accurate tidal and meteorological forces are also required for storm tide modeling.

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On hurricane parametric wind and applications in storm surge modeling

Cited by 164 publications

References 57 publications

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Increased threat of tropical cyclones and coastal flooding to New York City during the anthropogenic era

Simulation of Typhoon-Induced Storm Tides and Wind Waves for the Northeastern Coast of Taiwan Using a Tide–Surge–Wave Coupled Model

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