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

AbstractAccurate, 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 ...

[1]  D. Pham Stochastic Methods for Sequential Data Assimilation in Strongly Nonlinear Systems , 2001 .

[2]  J. C. Dietrich,et al.  Hurricane Gustav (2008) Waves and Storm Surge: Hindcast, Synoptic Analysis, and Validation in Southern Louisiana , 2011 .

[3]  M. Verlaan,et al.  Tidal flow forecasting using reduced rank square root filters , 1997 .

[4]  D. Dee Simplification of the Kalman filter for meteorological data assimilation , 1991 .

[5]  J. C. Dietrich,et al.  A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part I: Model Development and Validation , 2010 .

[6]  C. Guard,et al.  Tropical Cyclone Report , 1989 .

[7]  J. Feyen,et al.  A Basin to Channel-Scale Unstructured Grid Hurricane Storm Surge Model Applied to Southern Louisiana , 2008 .

[8]  G. Holland An Analytic Model of the Wind and Pressure Profiles in Hurricanes , 1980 .

[9]  Arnold W. Heemink Storm surge prediction using Kalman filtering , 1986 .

[10]  Henrik Madsen,et al.  Parameter sensitivity of three Kalman filter schemes for assimilation of water levels in shelf sea models , 2006 .

[11]  J. Whitaker,et al.  Ensemble Square Root Filters , 2003, Statistical Methods for Climate Scientists.

[12]  Harley S. Winer,et al.  A real time storm surge forecasting system using ADCIRC , 2008 .

[13]  William G. Gray,et al.  A wave equation model for finite element tidal computations , 1979 .

[14]  Jacques Verron,et al.  A singular evolutive extended Kalman filter for data assimilation in oceanography , 1998 .

[15]  Alexey Kaplan,et al.  Mapping tropical Pacific sea level : Data assimilation via a reduced state space Kalman filter , 1996 .

[16]  P. Houtekamer,et al.  An Adaptive Ensemble Kalman Filter , 2000 .

[17]  Herman Gerritsen,et al.  The Dutch Continental Shelf Model , 2013 .

[18]  Arnold W. Heemink,et al.  Data assimilation for non‐linear tidal models , 1990 .

[19]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[20]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[21]  G. Evensen Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[22]  Craig H. Bishop,et al.  Adaptive sampling with the ensemble transform Kalman filter , 2001 .

[23]  J. C. Dietrich,et al.  Origin of the Hurricane Ike forerunner surge , 2011 .

[24]  Jeffrey L. Anderson,et al.  Comments on “Sigma-Point Kalman Filter Data Assimilation Methods for Strongly Nonlinear Systems” , 2009 .

[25]  Peter S. Maybeck,et al.  Stochastic Models, Estimation And Control , 2012 .

[26]  N. Heaps,et al.  Storm surges, 1967–1982 , 1983 .

[27]  James D. Brown,et al.  Modeling storm surge flooding of an urban area with particular reference to modeling uncertainties: A case study of Canvey Island, United Kingdom , 2007 .

[28]  Peter R. Oke,et al.  A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters , 2008 .

[29]  J. Whitaker,et al.  Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter , 2001 .

[30]  Arthur E. Mynett,et al.  Improving the operational forecasting system of the stratified flow in Osaka Bay using an ensemble Kalman filter–based steady state Kalman filter , 2008 .

[31]  Allan McRobie,et al.  The Big Flood: North Sea storm surge , 2005, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[32]  Michael Ghil,et al.  Meteorological data assimilation for oceanographers. Part I: Description and theoretical framework☆ , 1989 .

[33]  Ingemar Kinnmark,et al.  The Shallow Water Wave Equations: Formulation, Analysis and Application , 1985 .

[34]  Ibrahim Hoteit,et al.  Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter , 2011, 1108.0158.

[35]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[36]  Edward N. Rappaport,et al.  THE DEADLIEST, COSTLIEST, AND MOST INTENSE UNITED STATES TROPICAL CYCLONES FROM 1851 TO 2004 (AND OTHER FREQUENTLY REQUESTED HURRICANE FACTS) , 2005 .

[37]  R. E. Young,et al.  Initialization and data assimilation experiments with a primitive equation model , 1989 .

[38]  P. Malanotte‐Rizzoli,et al.  An approximate Kaiman filter for ocean data assimilation: An example with an idealized Gulf Stream model , 1995 .

[39]  J. C. Dietrich,et al.  A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part II: Synoptic Description and Analysis of Hurricanes Katrina and Rita , 2010 .

[40]  Ibrahim Hoteit,et al.  Comparison of extended and ensemble based Kalman filters with low and high resolution primitive equation ocean models , 2005 .

[41]  Dinh-Tuan Pham,et al.  A simplified reduced order Kalman filtering and application to altimetric data assimilation in Tropical Pacific , 2002 .

[42]  C. Vreugdenhil Numerical methods for shallow-water flow , 1994 .

[43]  O. Talagrand,et al.  Adaptive filtering: application to satellite data assimilation in oceanography , 1998 .

[44]  R. F. Henry,et al.  The storm surge problem in the bay of Bengal , 1986 .

[45]  Henrik Madsen,et al.  Efficient Kalman filter techniques for the assimilation of tide gauge data in three‐dimensional modeling of the North Sea and Baltic Sea system , 2004 .

[46]  Clint Dawson,et al.  Scalability of an Unstructured Grid Continuous Galerkin Based Hurricane Storm Surge Model , 2011, J. Sci. Comput..