Nickitas Georgas

The Impact of Tidal Phase on Hurricane Sandy's Flooding Around New York City and Long Island Sound

How do the local impacts of Hurricane Sandy’s devastating storm surge differ because of the phase of the normal astronomical tide, given the spatiotemporal variability of tides around New York? In the weeks and months after Hurricane Sandy’s peak surge came ashore at the time of local high tide at the southern tip of Manhattan and caused recordsetting flooding along the New York and New Jersey coastline, this was one question that government officials and critical infrastructure managers were asking. For example, a simple superposition of the observed peak storm surge during Sandy on top of high tide in Western Long Island Sound comes within 29cm (less than a foot) of the top elevation of the Stamford Hurricane barrier system which would have been overtopped by 60cm surface waves riding over that storm tide. Here, a hydrodynamic model study of how shifts in storm surge timing could have influenced flood heights is presented. Multiple flood scenarios were evaluated with Stevens Institute of Technology’s New York Harbor Observing and Prediction System model (NYHOPS) having Hurricane Sandy arriving any hour within the previous or next tidal cycle (any hour within a 26-hour period around Sandy’s actual landfall). The simulated scenarios of Sandy coming between 7 and 10 hours earlier than it did were found to produce the worst coastal flooding in the Upper East River, Western and Central Long Island Sound among the evaluated cases. Flooding would have generally been worse compared to the real Sandy in Connecticut and the areas of New York City around the Upper East River between the boroughs of Queens and the Bronx,

Verification of a Multimodel Storm Surge Ensemble around New York City and Long Island for the Cool Season

AbstractThree real-time storm surge forecasting systems [the eight-member Stony Brook ensemble (SBSS), the Stevens Institute of Technology’s New York Harbor Observing and Prediction System (SIT-NYHOPS), and the NOAA Extratropical Storm Surge (NOAA-ET) model] are verified for 74 available days during the 2007–08 and 2008–09 cool seasons for five stations around the New York City–Long Island region. For the raw storm surge forecasts, the SIT-NYHOPS model has the lowest root-mean-square errors (RMSEs) on average, while the NOAA-ET has the largest RMSEs after hour 24 as a result of a relatively large negative surge bias. The SIT-NYHOPS and SBSS also have a slight negative surge bias after hour 24. Many of the underpredicted surges in the SBSS ensemble are associated with large waves at an offshore buoy, thus illustrating the potential importance of nearshore wave breaking (radiation stresses) on the surge predictions. A bias correction using the last 5 days of predictions (BC) removes most of the surge bias i...

A validated tropical‐extratropical flood hazard assessment for New York Harbor

Recent studies of flood risk at New York Harbor (NYH) have shown disparate results for the 100-year storm tide, providing an uncertain foundation for the flood mitigation response after Hurricane Sandy. Here, we present a flood hazard assessment that improves confidence in our understanding of the regions present-day potential for flooding, by separately including the contribution of tropical cyclones (TCs) and extratropical cyclones (ETCs), and validating our modeling study at multiple stages against historical observations. The TC assessment is based on a climatology of 606 synthetic storms developed from a statistical-stochastic model of North Atlantic TCs. The ETC assessment is based on simulations of historical storms with many random tide scenarios. Synthetic TC landfall rates and the final TC and ETC flood exceedance curves are all shown to be consistent with curves computed using historical data, within 95% confidence ranges. Combining the ETC and TC results together, the 100-year return period storm tide at NYH is 2.70 m (2.51-2.92 at 95% confidence), and Hurricane Sandys storm tide of 3.38 m was a 260-year (170-420) storm tide. Deeper analyses of historical flood reports from estimated Category-3 hurricanes in 1788 and 1821 lead to new estimates and reduced uncertainties for their floods, and show that Sandys storm tide was the largest at NYH back to at least 1700. The flood exceedance curves for ETCs and TCs have sharply different slopes due to their differing meteorology and frequency, warranting separate treatment in hazard assessments.

Street-Scale Modeling of Storm Surge Inundation along the New Jersey Hudson River Waterfront

AbstractA new, high-resolution, hydrodynamic model that encompasses the urban coastal waters of New Jersey along the Hudson River Waterfront opposite New York City, New York, has been developed and validated for simulating inundation during Hurricane Sandy. A 3.1-m-resolution square model grid combined with a high-resolution lidar elevation dataset permits a street-by-street focus to inundation modeling. The waterfront inundation model is a triple-nested Stevens Institute Estuarine and Coastal Ocean Hydrodynamic Model (sECOM) application; sECOM is a successor model to the Princeton Ocean Model family of models. Robust flooding and drying of land in the model physics provides for the dynamic prediction of flood elevations and velocities across land features during inundation events. The inundation model was forced by water levels from the extensively validated New York Harbor Observing and Prediction System (NYHOPS) hindcast of that hurricane.Validation against 56 watermarks and 16 edgemarks provided via t...

New York City Panel on Climate Change 2015 Report Chapter 4: Dynamic Coastal Flood Modeling

Philip Orton,1,a Sergey Vinogradov,2,a Nickitas Georgas,1,a Alan Blumberg,1,a Ning Lin,3 Vivien Gornitz,4 Christopher Little,5 Klaus Jacob,6 and Radley Horton4 1Stevens Institute of Technology, Hoboken, NJ. 2Earth Resources Technology/National Atmospheric and Oceanic Administration, Silver Spring, MD. 3Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ. 4Columbia University Center for Climate Systems Research, New York, NY. 5Atmospheric and Environmental Research, Lexington, MA. 6Lamont-Doherty Earth Observatory, Palisades, NY.

Bottom Topography Mapping via Nonlinear Data Assimilation

AbstractA variational data assimilation method is described for bottom topography mapping in rivers and estuaries using remotely sensed observations of water surface currents. The velocity field and bottom topography are related by the vertically integrated momentum and continuity equations, leading to a nonlinear inverse problem for bottom topography, which is solved using a Picard iteration strategy combined with a nonlinear line search. An illustration of the method is shown for Haverstraw Bay, in the Hudson River, where the known bottom topography is well reconstructed. Once the topography has been estimated, currents and water levels may be forecast. The method makes feasible 1) the estimation of bottom topography in regions where in situ data collection may be impossible, dangerous, or expensive, and 2) the calibration of barotropic shallow-water models via control of the bottom topography.

Assessing the fidelity of surface currents from a coastal ocean model and HF radar using drifting buoys in the Middle Atlantic Bight

The rapid expansion of urbanization along the world’s coastal areas requires a more comprehensive and accurate understanding of the coastal ocean. Over the past several decades, numerical ocean circulation models have tried to provide such insight, based on our developing understanding of physical ocean processes. The systematic establishment of coastal ocean observation systems adopting cutting-edge technology, such as high frequency (HF) radar, satellite sensing, and gliders, has put such ocean model predictions to the test, by providing comprehensive observational datasets for the validation of numerical model forecasts. The New York Harbor Observing and Prediction System (NYHOPS) is a comprehensive system for understanding coastal ocean processes on the continental shelf waters of New York and New Jersey. To increase confidence in the system’s ocean circulation predictions in that area, a detailed validation exercise was carried out using HF radar and Lagrangian drifter-derived surface currents from three drifters obtained between March and October 2010. During that period, the root mean square (RMS) differences of both the east–west and north–south currents between NYHOPS and HF radar were approximately 15 cm s−1. Harmonic analysis of NYHOPS and HF radar surface currents shows similar tidal ellipse parameters for the dominant M2 tide, with a mean difference of 2.4 cm s−1 in the semi-major axis and 1.4 cm s−1 in the semi-minor axis and 3° in orientation and 10° in phase. Surface currents derived independently from drifters along their trajectories showed that NYHOPS and HF radar yielded similarly accurate results. RMS errors when compared to currents derived along the trajectory of the three drifters were approximately 10 cm s−1. Overall, the analysis suggests that NYHOPS and HF radar had similar skill in estimating the currents over the continental shelf waters of the Middle Atlantic Bight during this time period. An ensemble-based set of particle tracking simulations using one drifter which was tracked for 11 days showed that the ensemble mean separation generally increases with time in a linear fashion. The separation distance is not dominated by high frequency or short spatial scale wavelengths suggesting that both the NYHOPS and HF radar currents are representing tidal and inertial time scales correctly and resolving some of the smaller scale eddies. The growing ensemble mean separation distance is dominated by errors in the mean flow causing the drifters to slowly diverge from their observed positions. The separation distance for both HF radar and NYHOPS stays below 30 km after 5 days, and the two technologies have similar tracking skill at the 95 % level. For comparison, the ensemble mean distance of a drifter from its initial release location (persistence assumption) is estimated to be greater than 70 km in 5 days.

THE STEVENS FLOOD ADVISORY SYSTEM: OPERATIONAL H3E FLOOD FORECASTS FOR THE GREATER NEW YORK / NEW JERSEY METROPOLITAN REGION

This paper presents the automation, website interface, and verification of the Stevens Flood Advisory System (SFAS, http://stevens.edu/SFAS). The fully-automated, ensemble-based flood advisory system dynamically integrates real-time observations and river and coastal flood models forced by an ensemble of meteorological models at various scales to produce and serve street scale flood forecasts over urban terrain. SFAS is applied to the Greater NY/NJ Metropolitan region, and is used routinely by multiple forecast offices and departments within the US National Weather Service (NWS), regional and municipal Offices of Emergency Management, as well as the general public. Every six hours, the underlying H3E (Hydrologic–Hydraulic–Hydrodynamic Ensemble) modelling framework, prepares, runs, data-assimilates, and integrates results from 375 dynamic model simulations to produce actionable, probabilistic ensemble forecasts of upland and coastal (storm surge) flooding conditions with an 81-h forecast horizon. Meteorological forcing to the H3E models is provided by 125 weather model ensemble members as well as deterministic weather models from major weather agencies (NCEP, ECMWF, CMC) and academia. The state-of-the-art SFAS, a replacement of the well-known, but deterministic, Storm Surge Warning System (SSWS) that was highlighted during Hurricanes Irene and Sandy and more recently extratropical cyclone Jonas, has been operational since the end of 2015.

Comparison of NYHOPS hydrodynamic model SST predictions with satellite observations in the Hudson River tidal, estuarine, and coastal plume region

The New York Harbor Observation and Prediction System, now in its 3 rd generation (NYHOPS v3), combines a network of real time sensors and a hydrodynamic forecasting computer model to assess prevailing ocean, environmental and meteorological conditions and to provide long and short term forecasts of the mentioned conditions. The older NYHOPS v2 model used spatially uniform surface heat flux forcing. Barometric pressure gradient forcing has also been neglected. The scope of this work was to assess sensitivity of the NYHOPS Sea Surface Temperature (SST) predictions to the spatial variability of the surface boundary condition. We compared two runs using different meteorological forcing: 1) Spatially varying wind stress and air pressure forcing, but spatially uniform heat flux forcing for the entire NYHOPS region (NYHOPS v2 surface boundary conditions with air pressure). 2) Spatially varying wind stress, air pressure, and heat flux forcing (NYHOPS v3 surface boundary conditions with air pressure). The SST modeled with NYHOPS was then compared against the validated GOES 12 satellite SST mapped on the NYHOPS grid nodes. A remarkable improvement (error reduction to the extent of 60%) in the prediction of SST by NYHOPS v3 was observed compared to NYHOPS v2. Similar error ranges were observed on comparison of NYHOPS v3 modeled SST and the satellite SST against in-situ observations, indicating that NYHOPS provides an effective SST prediction tool.

A Coupled Circulation–Wave Model for Numerical Simulation of Storm Tides and Waves

AbstractThe Stevens Institute of Technology Estuarine and Coastal Ocean Model (sECOM) is coupled here with the Mellor–Donelan–Oey (MDO) wave model to simulate coastal flooding due to storm tides and waves. sECOM is the three-dimensional (3D) circulation model used in the New York Harbor Observing and Prediction System (NYHOPS). The MDO wave model is a computationally cost-effective spectral wave model suitable for coupling with 3D circulation models. The coupled sECOM–MDO model takes into account wave–current interactions through wave-enhanced water surface roughness and wind stress, wave–current bottom stress, and depth-dependent wave radiation stress. The model results are compared with existing laboratory measurements and the field data collected in New York–New Jersey (NY–NJ) harbor during Hurricane Sandy. Comparisons between the model results and laboratory measurements demonstrate the capabilities of the model to accurately simulate wave characteristics, wave-induced water elevation, and undertow cu...