Linear frequency domain finite element model for tidal embayment analysis.

A frequency domain (harmonic) finite element model is developed for the numerical prediction of depth average circulation within small embayments. Such embayments are often characterized by irregular boundaries and bottom topography and large gradients in velocity. Previously developed finite element based time domain models require high eddy viscosity coefficients and small time steps to insure numerical stability, making application to small bays infeasible. Application of the harmonic method in conjunction with finite elements overcomes theseproblems. The model TEA, for Tidal Embayment Analysis, solves the linearized problem and is the core of a fully nonlinear code presently under development.This report discusses in detail both the theory behind TEA and program usage. Furthermore the versatility of TEA is demonstrated in several prototype examples

A Retrospective Evaluation of the Storm Surge Produced by Hurricane Gustav (2008): Forecast and Hindcast Results

The evolution and convergence of modeled storm surge were examined using a high-resolution implementation of the Advanced Circulation Coastal Ocean and Storm Surge (ADCIRC) model for Hurricane Gustav (2008). The storm surge forecasts were forced using an asymmetric gradient wind model (AWM), directly coupled to ADCIRC at every time step and at every grid node. A total of 20 forecast advisories and best-track data from the National Hurricane Center (NHC) were used as input parameters into the wind model. Differences in maximum surge elevations were evaluated for ensembles comprised of the final 20, 15, 10, and 5 forecast advisories plus the best track. For this particular storm, the final 10-12 forecast advisories, encompassing the last 2.5-3 days of the storm's lifetime, give a reasonable estimate of the final storm surge and inundation. The results provide a detailed perspective of the variability in the storm surge due to variability in the meteorological forecast and how this changes as the storm approaches landfall. This finding is closely tied to the consistency and accuracy of the NHC storm track forecasts and the predicted landfall location and, therefore, cannot be generalized to all storms in all locations. Nevertheless, this first attempt to translate variability in forecast meteorology into storm surge variability provides useful insights for guiding the potential use of storm surge models for forecast purposes. Model skill was also evaluated for Hurricane Gustav by comparing observed water levels with hindcast modeled water levels forced by river flow, tides, and several sources of wind data. The AWM (which ingested best-track information from NHC) generated winds that were slightly higher than those from NOAA's Hurricane Research Division (HRD) HWind analyses and substantially greater than the North American Mesoscale (NAM) model. Surge obtained using the AWM more closely matched the observed water levels than that computed using HWind; however, this may be due to the neglect of the contribution of wave setup to the surge, especially in exposed areas. Several geographically distinct storm surge response regimes, some characterized by multisurge pulses, were identified and described

Extratropical storm inundation testbed : intermodel comparisons in Scituate, Massachusetts

Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 5054–5073, doi:10.1002/jgrc.20397.The Integrated Ocean Observing System Super-regional Coastal Modeling Testbed had one objective to evaluate the capabilities of three unstructured-grid fully current-wave coupled ocean models (ADCIRC/SWAN, FVCOM/SWAVE, SELFE/WWM) to simulate extratropical storm-induced inundation in the US northeast coastal region. Scituate Harbor (MA) was chosen as the extratropical storm testbed site, and model simulations were made for the 24–27 May 2005 and 17–20 April 2007 (“Patriot's Day Storm”) nor'easters. For the same unstructured mesh, meteorological forcing, and initial/boundary conditions, intermodel comparisons were made for tidal elevation, surface waves, sea surface elevation, coastal inundation, currents, and volume transport. All three models showed similar accuracy in tidal simulation and consistency in dynamic responses to storm winds in experiments conducted without and with wave-current interaction. The three models also showed that wave-current interaction could (1) change the current direction from the along-shelf direction to the onshore direction over the northern shelf, enlarging the onshore water transport and (2) intensify an anticyclonic eddy in the harbor entrance and a cyclonic eddy in the harbor interior, which could increase the water transport toward the northern peninsula and the southern end and thus enhance flooding in those areas. The testbed intermodel comparisons suggest that major differences in the performance of the three models were caused primarily by (1) the inclusion of wave-current interaction, due to the different discrete algorithms used to solve the three wave models and compute water-current interaction, (2) the criterions used for the wet-dry point treatment of the flooding/drying process simulation, and (3) bottom friction parameterizations.This project was supported by NOAA via the U.S.IOOS Office (award: NA10NOS0120063 and NA11NOS0120141) and was managed by the Southeastern Universities Research Association. The Scituate FVCOM setup was supported by the NOAA-funded IOOS NERACOOS program for NECOFS and the MIT Sea Grant College Program through grant 2012-R/RC-127.2014-04-0

U.S. IOOS coastal and ocean modeling testbed : inter-model evaluation of tides, waves, and hurricane surge in the Gulf of Mexico

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 5129–5172, doi:10.1002/jgrc.20376.A Gulf of Mexico performance evaluation and comparison of coastal circulation and wave models was executed through harmonic analyses of tidal simulations, hindcasts of Hurricane Ike (2008) and Rita (2005), and a benchmarking study. Three unstructured coastal circulation models (ADCIRC, FVCOM, and SELFE) validated with similar skill on a new common Gulf scale mesh (ULLR) with identical frictional parameterization and forcing for the tidal validation and hurricane hindcasts. Coupled circulation and wave models, SWAN+ADCIRC and WWMII+SELFE, along with FVCOM loosely coupled with SWAN, also validated with similar skill. NOAA's official operational forecast storm surge model (SLOSH) was implemented on local and Gulf scale meshes with the same wind stress and pressure forcing used by the unstructured models for hindcasts of Ike and Rita. SLOSH's local meshes failed to capture regional processes such as Ike's forerunner and the results from the Gulf scale mesh further suggest shortcomings may be due to a combination of poor mesh resolution, missing internal physics such as tides and nonlinear advection, and SLOSH's internal frictional parameterization. In addition, these models were benchmarked to assess and compare execution speed and scalability for a prototypical operational simulation. It was apparent that a higher number of computational cores are needed for the unstructured models to meet similar operational implementation requirements to SLOSH, and that some of them could benefit from improved parallelization and faster execution speed.This project was supported by NOAA via the U.S. IOOS Office (award: NA10NOS0120063 and NA11NOS0120141

Tidal circulation, A frequency domain finite element model

A highly efficient finite element model has been developed for the numerical prediction of depth average circulation within small scale embayments which are often characterized by irregular boundaries and bottom topography.Traditional finite element models use time-stepping and have been plagued with requirements for high eddy viscosity coefficients and small time steps necessary to insure numerical stability, making application to small bays infeasible. These problems are overcome by operating in the frequency domain, an intrinsically more natural solution procedure for a highly periodic process such as tidal forcing. In order to handle non-linearities, an iterative scheme which updates non-linearities as right hand side force loadings must be implemented.Pioneering efforts with the harmonic approach have had shortcomings in either not modeling all physically relevant terms and/or in not gearing towards application to small scale regions. Small embayments are often quite shallow and have rapidly varying depth, making the nonlinear terms in the governing hydrodynamic equations much more significant. This requires that more frequencies be used in order to resolve the tide and account for the greater nonlinear coupling due to bottom friction, convective acceleration and finite amplitude effects. In order to make the process of handling this wide range of frequencies manageable, a hybrid frequency-time domain approach is applied. The iterative scheme revolves around a highly efficient linear core code which can handle a wide range of frequencies. Furthermore, instead of Fourier expanding the nonlinear terms, an efficient least squares error minimization algorithm is used for the discrete spectral analysis of the iteratively updated psuedo-force time history generated by the nonlinearities.With this highly efficient scheme it is now possible to efficiently study both short period and long term residual circulation within small scale embayments.Sponsored by Northeast Utilities Service Company and New England Power Service Company under the MIT Energy Laboratory Electric Utitility Program and by The Sea Grant Office of NOAA, U.S. Department of Commerce

The effect of uncertainty on estimates of hurricane surge hazards

It is shown here that uncertainty can significantly affect estimated surge levels over a wide range of annual exceedance probabilities (AEPs). For AEPs in the range of 1 × 10-2-5 × 10-2 in the New Orleans area, estimated surge values with and without consideration of uncertainty differ by about 0.5-1.0 m. Similarly, suppression of natural variability, such as using a single value for Mississippi River discharge in surge simulations, rather than allowing the discharge to vary probabilistically, is shown to produce deviations up to 1 m for the 1 × 10-2 AEP in locations within the mainline river levees in this area. It is also shown that uncertainty can play a critical role in the analysis of very low probability events in the AEP range 1 × 10-4-1 × 10-6. Such events are typically used in designs of structures with major societal impacts. It is shown here that, for this range of AEPs along the west coast of Florida, the neglect of uncertainty can under-predict design surge levels by about 20 % compared to estimated surge levels that include uncertainty. © 2012 Springer Science+Business Media B.V

Quantifying impacts of forecast uncertainties on predicted storm surges

In this paper, we propose a framework for quantifying risks, including (1) the effects of forecast errors, (2) the ability to resolve critical grid features that are important to accurate site-specific forecasts, and (3) a framework that can move us toward performance-based/cost-based decisions, within an extremely fast execution time. A key element presently lacking in previous studies is the interrelationship between the effects of combined random errors and bias in numerical weather prediction (NWP) models and bias and random errors in surge models. This approach examines the number of degrees of freedom in present forecasts and develops an equation for the quantification of these types of errors within a unified system, given the number of degrees of freedom in the NWP forecasts. It is shown that the methodology can be used to provide information on the forecasts and along with the combined uncertainty due to all of the individual contributions. A potential important benefit from studies using this approach would be the ability to estimate financial and other trade-offs between higher-cost “rapid” evacuation methods and lower-cost “slower” evacuation methods. Analyses here show that uncertainty inherent in these decisions depends strongly on forecast time and geographic location. Methods based on sets of surge maxima do not capture this uncertainty and would be difficult to use for this purpose. In particular, it is shown that surge model bias can play a dominant role in distorting the forecast probabilities

Probabilistic Storm Surge Estimation for Landfalling Hurricanes: Advancements in Computational Efficiency Using Quasi-Monte Carlo Techniques

During landfalling tropical storms, predictions of the expected storm surge are critical for guiding evacuation and emergency response/preparedness decisions, both at regional and national levels. Forecast errors related to storm track, intensity, and size impact these predictions and, thus, should be explicitly accounted for. The Probabilistic tropical storm Surge (P-Surge) model is the established approach from the National Weather Service (NWS) to achieve this objective. Historical forecast errors are utilized to specify probability distribution functions for different storm features, quantifying, ultimately, the uncertainty in the National Hurricane Center advisories. Surge statistics are estimated by using the predictions across a storm ensemble generated by sampling features from the aforementioned probability distribution functions. P-Surge relies, currently, on a full factorial sampling scheme to create this storm ensemble, combining representative values for each of the storm features. This work investigates an alternative formulation that can be viewed as a seamless extension to the current NHC framework, adopting a quasi-Monte Carlo (QMC) sampling implementation with ultimate goal to reduce the computational burden and provide surge predictions with the same degree of statistical reliability, while using a smaller number of sample storms. The definition of forecast errors adopted here directly follows published NWS practices, while different uncertainty levels are considered in the examined case studies, in order to offer a comprehensive validation. This validation, considering different historical storms, clearly demonstrates the advantages QMC can offer