scholarly journals Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

2012 ◽  
Vol 140 (7) ◽  
pp. 2215-2231 ◽  
Author(s):  
T. Butler ◽  
M. U. Altaf ◽  
C. Dawson ◽  
I. Hoteit ◽  
X. Luo ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Storm Surge ◽  
Time Window ◽  
Function Analysis ◽  
High Water ◽  
Water Levels ◽  
Modeling Framework ◽  
Hurricane Storm Surge ◽  
Storm Surge Forecasting

Abstract Accurate, real-time forecasting of coastal inundation due to hurricanes and tropical storms is a challenging computational problem requiring high-fidelity forward models of currents and water levels driven by hurricane-force winds. Despite best efforts in computational modeling there will always be uncertainty in storm surge forecasts. In recent years, there has been significant instrumentation located along the coastal United States for the purpose of collecting data—specifically wind, water levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge forecasting based on the use of ensemble Kalman filters and the advanced circulation (ADCIRC) storm surge model is described. The singular evolutive interpolated Kalman (SEIK) filter has been shown to be effective at producing accurate results for ocean models using small ensemble sizes initialized by an empirical orthogonal function analysis. The SEIK filter is applied to the ADCIRC model to improve storm surge forecasting, particularly in capturing maximum water levels (high water marks) and the timing of the surge. Two test cases of data obtained from hindcast studies of Hurricanes Ike and Katrina are presented. It is shown that a modified SEIK filter with an inflation factor improves the accuracy of coarse-resolution forecasts of storm surge resulting from hurricanes. Furthermore, the SEIK filter requires only modest computational resources to obtain more accurate forecasts of storm surge in a constrained time window where forecasters must interact with emergency responders.

scholarly journals STORM SURGE FORECASTING METHODS IN ENCLOSED SEAS

1978 ◽  
Vol 1 (16) ◽  
pp. 58
Author(s):  
P.F. Hamblin
Keyword(s):  
Water Level ◽  
Storm Surge ◽  
Storm Surges ◽  
High Water ◽  
Computational Effort ◽  
Water Levels ◽  
Large Lakes ◽  
Forecasting Methods ◽  
The Stability ◽  
Storm Surge Forecasting

Storm surges in enclosed seas although generally not as large in amplitude as their oceanic counterparts are nonetheless of considerable importance when low lying shoreline profiles, shallow water depth, and favourable geographical orientation to storm winds occur together. High water may result in shoreline innundation and in enhanced shoreline erosion. Conversely low water levels are hazardous to navigation. The purpose of this paper is to discuss the problem of storm surge forecasting in enclosed basins with emphasis on automated operational procedures. In general, operational forecasting methods must be based on standard forecast parameters, require a minimum of computational effort in the preparation of the forecast, must be applicable to lakes of different geometry and to any point on the shore, and to be able to resolve water level changes on an hourly basis to 10 cm in the case of high water level excursions associated with large lakes and less than that for smaller lakes. Particular physical effects arising in lakes which make these constraints difficult to fulfill are the reflections of resurgences of water levels arising from lateral boundaries, the stability of the atmospheric boundary layer and the presence of such subsynoptic disturbances as squall lines and travelling pressure jumps.

scholarly journals Adjusting the Wind Stress Drag Coefficient in Storm Surge Forecasting Using an Adjoint Technique

2013 ◽  
Vol 30 (3) ◽  
pp. 590-608 ◽  
Author(s):  
Shiqiu Peng ◽  
Yineng Li ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Drag Coefficient ◽  
Storm Surge ◽  
Wind Stress ◽  
Weather Prediction ◽  
Ocean Model ◽  
Error Sources ◽  
Empirical Parameter ◽  
Forecasting Errors ◽  
Storm Surge Forecasting

Abstract A three-dimensional ocean model and its adjoint model are used to adjust the drag coefficient in the calculation of wind stress for storm surge forecasting. A number of identical twin experiments (ITEs) with different error sources imposed are designed and performed. The results indicate that when the errors come from the wind speed, the drag coefficient is adjusted to an “optimal value” to compensate for the wind errors, resulting in significant improvements of the specific storm surge forecasting. In practice, the “true” drag coefficient is unknown and the wind field, which is usually calculated by an empirical parameter model or a numerical weather prediction model, may contain large errors. In addition, forecasting errors may also come from imperfect model physics and numerics, such as insufficient resolution and inaccurate physical parameterizations. The results demonstrate that storm surge forecasting errors can be reduced through data assimilation by adjusting the drag coefficient regardless of the error sources. Therefore, although data assimilation may not fix model imperfection, it is effective in improving storm surge forecasting by adjusting the wind stress drag coefficient using the adjoint technique.

Uncertainty in coastal flooding: modelling and visualisation

2020 ◽  
Author(s):  
John Maskell
Keyword(s):  
Water Level ◽  
Storm Surge ◽  
Return Period ◽  
Flood Risk ◽  
High Water ◽  
Coastal Flooding ◽  
Water Levels ◽  
Tidal Range ◽  
The Uk ◽  
Flood Maps

<p>Two case studies are considered in the UK, where uncertainty and drivers of coastal flood risk are explored through modelling and visualisations. Visualising the impact of uncertainty is a useful way of explaining the potential range of predicted or simulated flood risk to both expert and non-expert stakeholders.</p><p>Significant flooding occurred in December 2013 and January 2017 at Hornsea on the UK East Coast, where storm surge levels and waves overtopped the town’s coastal defences. Uncertainty in the potential coastal flooding is visualised at Hornsea due to the range of uncertainty in the 100-year return period water level and in the calculated overtopping due to 3 m waves at the defences. The range of uncertainty in the simulated flooding is visualised through flood maps, where various combinations of the uncertainties decrease or increase the simulated inundated area by 58% and 82% respectively.</p><p>Located at the mouth of the Mersey Estuary and facing the Irish Sea, New Brighton is affected by a large tidal range with potential storm surge and large waves. Uncertainty in the coastal flooding at the 100-year return period due to the combination of water levels and waves is explored through Monte-Carlo analysis and hydrodynamic modelling. Visualisation through flood maps shows that the inundation extent at New Brighton varies significantly for combined wave and surge events with a joint probability of 100 years, where the total flooded area ranges from 0 m<sup>2</sup> to 10,300 m<sup>2</sup>. Waves are an important flood mechanism at New Brighton but are dependent on high water levels to impact the coastal defences and reduce the effective freeboard. The combination of waves and high-water levels at this return level not only determine the magnitude of the flood extent but also the spatial characteristics of the risk, whereby flooding of residential properties is dominated by overflow from high water levels, and commercial and leisure properties are affected by large waves that occur when the water level is relatively high at the defences.</p>

scholarly journals A Real Time Storm Surge Forecasting System Using ADCIRC

2008 ◽  
Author(s):  
Jason G. Fleming ◽  
Crystal W. Fulcher ◽  
Richard A. Luettich ◽  
Brett D. Estrade ◽  
Gabrielle D. Allen ◽  
...  
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Forecasting System ◽  
Storm Surge Forecasting

scholarly journals NUMERICAL MODELLING OF TROPICAL CYCLONE STORM SURGE

1980 ◽  
Vol 1 (17) ◽  
pp. 44
Author(s):  
Rodney J. Sobey ◽  
Bruce A. Harper ◽  
George M. Mitchell
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
Wave Equations ◽  
Surface Wind ◽  
Water Levels ◽  
Open Boundary ◽  
Deformation Analysis ◽  
Linear Effects ◽  
Explicit Finite Difference ◽  
Hurricane Storm Surge

Details are presented of a general numerical hydrodynamic model for the generation and propagation of tropical cyclone or hurricane storm surge. The model, known as SURGE, solves the two-dimensional depth-integrated form of the Long Wave Equations using an explicit finite difference procedure, with tropical cyclone surface wind and pressure forcing estimated from an adaption of available models based on U.S. hurricanes. Variations in tropical cyclone parameters as well as the physical characteristics of a coastal location such as bathymetry and details of capes, bays, reefs and islands are accommodated by the model. The accuracy and stability of the numerical solution have been confirmed by a comprehensive wave deformation analysis including quasi-non-linear effects and the open boundary problem has been overcome by the use of a Bathystrophic Storm Tide approximation to boundary water levels. A detailed sensitivity analysis has identified the principal surge generating parameters and the model has been checked against an historical tropical cyclone storm surge. SURGE has been used extensively in the northern Australian region and examples are presented.

scholarly journals Towards an efficient storm surge and inundation forecasting system over the Bengal delta: chasing the Supercyclone Amphan

2021 ◽  
Vol 21 (8) ◽  
pp. 2523-2541
Author(s):  
Md. Jamal Uddin Khan ◽  
Fabien Durand ◽  
Xavier Bertin ◽  
Laurent Testut ◽  
Yann Krien ◽  
...  
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Coastal Region ◽  
Computationally Efficient ◽  
Bengal Delta ◽  
Modelling Framework ◽  
Forecasting System ◽  
Effective Decision Making ◽  
Storm Surge Forecasting

Abstract. The Bay of Bengal is a well-known breeding ground to some of the deadliest cyclones in history. Despite recent advancements, the complex morphology and hydrodynamics of this large delta and the associated modelling complexity impede accurate storm surge forecasting in this highly vulnerable region. Here we present a proof of concept of a physically consistent and computationally efficient storm surge forecasting system tractable in real time with limited resources. With a state-of-the-art wave-coupled hydrodynamic numerical modelling system, we forecast the recent Supercyclone Amphan in real time. From the available observations, we assessed the quality of our modelling framework. We affirmed the evidence of the key ingredients needed for an efficient, real-time surge and inundation forecast along this active and complex coastal region. This article shows the proof of the maturity of our framework for operational implementation, which can particularly improve the quality of localized forecast for effective decision-making over the Bengal delta shorelines as well as over other similar cyclone-prone regions.

scholarly journals Towards an efficient storm surge and inundation forecasting system over the Bengal delta: Chasing the super-cyclone Amphan

2020 ◽  
Author(s):  
Md Jamal Uddin Khan ◽  
Fabien Durand ◽  
Xavier Bertin ◽  
Laurent Testut ◽  
Yann Krien ◽  
...  
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Coastal Region ◽  
Computationally Efficient ◽  
Bengal Delta ◽  
Modelling Framework ◽  
Forecasting System ◽  
Super Cyclone ◽  
Storm Surge Forecasting

Abstract. The Bay of Bengal is a well-known breeding ground to some of the deadliest cyclones in history. Despite recent advancements, the complex morphology and hydrodynamics of this large delta and the associated modelling computational costs impede the storm surge forecasting in this highly vulnerable region. Here we present a proof of concept of a physically consistent and computationally efficient storm surge forecasting system tractable in real-time with limited resources. With a state-of-the-art wave-coupled hydrodynamic numerical modelling system, we forecast the recent super cyclone Amphan in real-time. From the available observations, we assessed the quality of our modelling framework. We affirmed the evidence of the key ingredients needed for an efficient, real-time surge and inundation forecast along this active and complex coastal region. This article shows the proof of the maturity of our framework for operational implementation, which can particularly improve the quality of localized forecast for effective decision-making.

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