Predicting the Storm Surge Threat of Hurricane Sandy with the National Weather Service SLOSH Model

Abstract

Numerical simulations of the storm tide that flooded the US Atlantic coastline during Hurricane Sandy (2012) are carried out using the National Weather Service (NWS) Sea Lakes and Overland Surges from Hurricanes (SLOSH) storm surge prediction model to quantify its ability to replicate the height, timing, evolution and extent of the water that was driven ashore by this large, destructive storm. Recent upgrades to the numerical model, including the incorporation of astronomical tides, are described and simulations with and without these upgrades are contrasted to assess their contributions to the increase in forecast accuracy. It is shown, through comprehensive verifications of SLOSH simulation results against peak water surface elevations measured at the National Oceanic and Atmospheric Administration (NOAA) tide gauge stations, by storm surge sensors deployed and hundreds of high water marks collected by the U.S. Geological Survey (USGS), that the SLOSH-simulated water levels at 71% (89%) of the data measurement locations have less than 20% (30%) relative error. The RMS error between observed and modeled peak water levels is 0.47 m. In addition, the model's extreme computational efficiency enables it to OPEN ACCESS J. Mar. Sci. Eng. 2014, 2 438 run large, automated ensembles of predictions in real-time to account for the high variability that can occur in tropical cyclone forecasts, thus furnishing a range of values for the predicted storm surge and inundation threat.

Tropical Cyclone Storm Surge Risk

“…Both of these comparisons used different wind field models than used operationally in SLOSH. Forbes et al, 7 using standard operational wind fields, obtained relatively unbiased results with a standard deviation of about 25% in peak surge. For this magnitude of error, SLOSH increases surge uncertainty, over that inherent in the storm track forecast, by 3-12% in 24 h forecasts and 2 to 17% in 48-h forecasts.…”

Tropical Cyclone Storm Surge Risk

“…Both of these comparisons used different wind field models than used operationally in SLOSH. Forbes et al [20], using standard operational wind fields, obtained relatively unbiased results with a standard deviation of about 25 % in peak surge. For this magnitude of error, SLOSH increases surge uncertainty, over that inherent in the storm track forecast, by 3-12 % in 24-h forecasts and 2-17 % in 48-h forecasts.…”

“…On one hand, it can be argued uncertainties in realtime and forecast storm characteristics justify the use of relatively crude resolution and neglect of some physical terms in Fig. 1 Concept of information needs for decision-making over a range of time scales (modified from [9]) forecast surge simulations, e.g., the application of the SLOSH model [20] in the US. On the other hand, accurate prediction of storm surges in coastal areas, particularly inland inundation, requires high resolution and inclusion of all contributing physical processes in the simulations, such as waves along coasts typical of many Caribbean and Pacific regions [68] and the coupled influence of river flow and surges during landfall [41,42].…”

Exploring Water Level Sensitivity for Metropolitan New York during Sandy (2012) Using Ensemble Storm Surge Simulations

“…Forbes et al (2014) [13] showed a large ensemble spread of surge predictions using SLOSH for Sandy around NYC, but did not discuss the origin of that water level spread. Wind and pressure forcing for SLOSH are geometrically circular, thus unrepresentative of the large asymmetries observed during Sandy.…”

“…Forbes et al [13] showed that the NWS Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model [14] could realistically simulate the Sandy water levels using an ensemble of tracks and intensities from the National Hurricane Center. Both Forbes et al [13] and Georgas et al [12] illustrated that Sandy's observed flooding was not a worst-case scenario for this event given the variations in Sandy's track and phase of the tide landfall that might have occurred.…”