Effect of Bottom Friction, Wind Drag Coefficient, and Meteorological Forcing in Hindcast of Hurricane Rita Storm Surge Using SWAN + ADCIRC Model

Abstract

An evaluation of the effect of bottom friction, wind drag coefficient, and meteorological forcing is conducted using a tightly coupled wave and circulation model, SWAN + ADCIRC (i.e., Simulating WAves Nearshore + ADvanced CIRCulation), to hindcast the storm surge of Hurricane Rita (2005). Wind drag coefficient formulations of Powell, Zijlema, and Peng & Li are used to calculate wind stresses. Bottom friction and wind drag coefficients are systematically increased and decreased to quantify their impacts on the hindcast. Different meteorological forcing options are applied to study the effect of wind fields on storm surge development and propagation. Simulated water levels are compared with observed data collected from about 150 locations. It is evident that a lower bottom friction causes higher and faster surge propagation, and earlier arrival of inundation peak at locations far from the land fall. Drag coefficients of Powell, with or without a cap of 0.002, and Zijlema produce similar results, while that of Peng & Li slightly overpredicted the surge. Wind fields may cause overprediction or underprediction of the surge, depending on the choice of the wind model. A good agreement is found between Zijlema's findings and this study; that simultaneously decreasing or increasing both bottom friction and wind drag essentially provides the same hindcast results.

Impact of Tropical Cyclone Landfall Angle on Storm Surge Along the Mid‐Atlantic Bight

“…Track-based data are implemented within parametric models, which allows for easy manipulation of storm characteristics to study the individual impact of storm parameters. Various studies have compared the use of parametric models with more realistic wind field representations (Akbar et al, 2017;Bennett & Mulligan, 2017;Ramos-Valle et al, 2018;Torres et al, 2018), including the use of the WRF model. Full physics atmospheric models have proven to be more accurate, albeit at a larger computational cost (Ramos-Valle et al, 2018).…”

The Effect of the Surface Wind Field Representation in the Operational Storm Surge Model of the National Hurricane Center

“…However, one of the primary sources of uncertainty in storm surge modeling is the atmospheric forcing, i.e., the hurricane itself. When storm surges are hindcasted using detailed hydrodynamic models and accurate representations of the surface wind field, the simulated hydrodynamics are effectively replicated (e.g., [10,[13][14][15][16]). However, for operational forecasting, measurements of the full surface wind field are unavailable [17], and hurricane wind fields are often represented parametrically, using a small number of storm characteristics that can be more readily obtained.…”

“…In general, parametric wind models approximate the surface wind field as the sum of the background wind speed of the atmosphere, V b , and the axisymmetric wind speed, V, of the storm. The definition used for each of these components differentiates various parametric wind field models that have been developed, e.g., [13,16,23,24]. In the SLOSH model, the background wind field is modeled as a radially variable fraction of the storm's translational speed, V s , and the axisymmetric wind profile is modeled as a radially variable fraction of the storm's maximum wind speed, V max .…”

Simulating Storm Surge Impacts with a Coupled Atmosphere-Inundation Model with Varying Meteorological Forcing

“…Some storm surge models such as the Sea, Lake and Overland Surges from Hurricanes (SLOSH) allow for the use of symmetric vortex models, with spatially constant radius of maximum wind (Rmax), to characterize the TC wind field for a given track dataset. However, a recent study comparing multiple meteorological forcing for the case of Hurricane Rita found that due to uncertainties in the wind field, an asymmetric model outperforms the symmetric model in forecasting storm surge [15].…”

“…Recent studies have researched the effect of using various meteorological forcing for storm surge or wave assessment. Akbar et al [15] performed a hindcast of Hurricane Rita to study the effect of varying wind fields on storm surge estimates, including meteorological forcing from the National Oceanic and Atmospheric Administration (NOAA)/Hurricane Research Division's (HRD) Real-time Hurricane Wind Analysis System (HWIND; [16]), the Dynamic Holland Model [12], and the Asymmetric Holland Model [14]. Results from the study indicate that HWIND performed better than both the Dynamic and Asymmetric Holland Models.…”