A Real-Time Forecasting System for Hurricane Induced Storm Surge and Coastal Flooding

Author(s):  
Y. Peter. Sheng ◽  
Vladimir A. Paramygin ◽  
Vadim Alymov ◽  
Justin R. Davis
Author(s):  
Jason G. Fleming ◽  
Crystal W. Fulcher ◽  
Richard A. Luettich ◽  
Brett D. Estrade ◽  
Gabrielle D. Allen ◽  
...  

2021 ◽  
Vol 21 (8) ◽  
pp. 2523-2541
Author(s):  
Md. Jamal Uddin Khan ◽  
Fabien Durand ◽  
Xavier Bertin ◽  
Laurent Testut ◽  
Yann Krien ◽  
...  

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.


2020 ◽  
Author(s):  
Md Jamal Uddin Khan ◽  
Fabien Durand ◽  
Xavier Bertin ◽  
Laurent Testut ◽  
Yann Krien ◽  
...  

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.


2008 ◽  
Vol 52 ◽  
pp. 1393-1398
Author(s):  
Seiji AMOU ◽  
Susumu NAKANO ◽  
Takeshi KIMURA ◽  
Shigeru TSUGAWA

2003 ◽  
Author(s):  
Hans C. Graber ◽  
Mark A. Donelan ◽  
Michael G. Brown ◽  
Donald N. Slinn ◽  
Scott C. Hagen ◽  
...  

2001 ◽  
Author(s):  
Joo Heon Lee ◽  
Do Hun Lee ◽  
Sang Man Jeong ◽  
Eun Tae Lee

2017 ◽  
Author(s):  
James A. Coller ◽  
Andrew Silver ◽  
Okey Nwogu ◽  
Benjamin S.H. Connell

The US Nav has developed a real-time multi-ship ship motion forecasting system which combines forecast wave conditions with ship motion simulations to produce a prediction of the relative motions between two ships operating in a skin-to-skin configuration. The system utilizes two different simulation methods for predicting ship motions: MotionSim and Reduced Order Model (ROM) based on AEGIR. MotionSim is a fast three-dimensional panel method that is used to estimate the Response Amplitude Operators (RAOs) necessary for multi-ship motion predictions. The ROM works to maximize the accuracy of high fidelity ship motion prediction methods while maintaining the computational speed required for real-time forecasting. A model scale experiment was performed in 2015 on two Navy ships conventionally moored together. The predicted relative ship motions from MotionSim and ROM were compared to the model data using three different metrics: RMS (root mean square) ratio, correlation coefficient, and average angle measurement (AAM).This paper provides an overview of the two methods for predicting the multi-ship motions, a description of the model test, challenges faced during testing, and a discussion on the methodology of the evaluation and the results of each code correlation.


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