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Toward High-Resolution, Rapid, Probabilistic Forecasting of the Inundation Threat from Landfalling Hurricanes

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Toward High-Resolution, Rapid, Probabilistic Forecasting of the Inundation Threat from Landfalling Hurricanes 1304 MONTHLY WEATHER REVIEW VOLUME 141 Toward High-Resolution, Rapid, Probabilistic Forecasting of the Inundation Threat from Landfalling Hurricanes ANDREW J. CONDON,Y.PETER SHENG, AND VLADIMIR A. PARAMYGIN Department of Civil and Coastal Engineering, University of Florida, Gainesville, Florida (Manuscript received 16 May 2012, in final form 28 September 2012) ABSTRACT State-of-the-art coupled hydrodynamic and wave models can predict the inundation threat from an approaching hurricane with high resolution and accuracy. However, these models are not highly efficient and often cannot be run sufficiently fast to provide results 2 h prior to advisory issuance within a 6-h forecast cycle. Therefore, to produce a timely inundation forecast, coarser grid models, without wave setup contributions, are typically used, which sacrifices resolution and physics. This paper introduces an efficient forecast method by applying a multidimensional interpolation technique to a predefined optimal storm database to generate the surge response for any storm based on its landfall characteristics. This technique, which provides a ‘‘digital lookup table’’ to predict the inundation throughout the region, is applied to the southwest Florida coast for Hurricanes Charley (2004) and Wilma (2005) and compares well with deterministic results but is obtained in a fraction of the time. Because of the quick generation of the inundation response for a single storm, the response of thousands of possible storm parameter combinations can be determined within a forecast cycle. The thousands of parameter combinations are assigned a probability based on historic forecast errors to give a probabilistic estimate of the inundation forecast, which compare well with ob- servations. 1. Introduction constraints of a 6-h forecast cycle. Typically the NHC has roughly an hour at most from the time the most The extent of coastal inundation from a given hurri- recent track–intensity information is received to com- cane has proven to be difficult to forecast in an efficient plete storm surge forecasts for the next 36–120 h for manner. High-resolution, physics-based models such as inclusion in the latest advisory (J. R. Rhome 2011, Advanced Circulation (ADCIRC; Luettich et al. 1992; personal communication). Dietrich et al. (2012) show Weaver and Slinn 2006), Curvilinear-grid Hydrody- that coupled Simulating Waves Nearshore (SWAN) and namics in 3D–Storm Surge Modeling System (CH3D- ADCIRC simulations for Hurricane Katrina can take SSMS; Sheng et al. 2006, 2010a,b; Sheng and Paramygin between 10 and 2000 min of wall clock time per day of 2010), Princeton Ocean Model (POM; Peng et al. 2004; simulation depending on the computing resources (8192 Oey et al. 2006), and Finite Volume Coastal Ocean to 256 computational cores) and solver (implicit or ex- Model (FVCOM; Rego and Li 2009; Weisberg and plicit). For similar simulations of Hurricane Katrina, Zheng 2008) have all been proven to accurately simulate CH3D-SSMS runs at about 900 min of wall clock time coastal inundation from hurricanes. However, these per day of simulation on eight computational cores. Both models are all computationally expensive to run com- these examples demonstrate that either enormous com- pared to the Sea, Lake, and Overland Surges from putational resources or too much wall clock time are Hurricanes (SLOSH; Jelesnianski et al. 1992) model needed to develop inundation forecasts in a timely man- of the National Hurricane Center (NHC), which makes ner. In addition the National Research Council (NRC) forecasting much more difficult given the tight time report ‘‘Completing the Forecast’’ emphasizes the need for more probabilistic forecasts that involve an ensemble of storm simulations using a storm surge modeling system Corresponding author address: Y. Peter Sheng, Department of Civil and Coastal Engineering, University of Florida, 365 Weil (National Research Council 2006). Given the 1-h time Hall, P.O. Box 116580, Gainesville, FL 32607. window available to produce a hurricane storm surge E-mail: [email protected]fl.edu forecast, it is currently not possible to run an ensemble DOI: 10.1175/MWR-D-12-00149.1 Ó 2013 American Meteorological Society Unauthenticated | Downloaded 10/04/21 01:29 PM UTC APRIL 2013 C O N D O N E T A L . 1305 of thousands of storms with a high-resolution modeling core, and is typically accurate within 20% (Jelesnianski system. Other attempts to generate a timely estimate of et al. 1992). The model does not account for dynamic the inundation response have been made. effects of tides and waves, which other forecasting sys- The Saffir–Simpson hurricane scale (SSHS; Simpson tems incorporate. The largest drawback to the SLOSH 1974) was used by NHC to relate the storm surge hazard forecasts is the coarse resolution [Fort Myers, Florida, to hurricane intensity. Following the active Atlantic grid (efmy2) has an average resolution of 2 km] of the hurricane seasons of 2004 and 2005, it became obvious model domains compared to the other models mentioned. that storm surge hazard depends on other hurricane With a coarse grid many of the important small-scale characteristics (e.g., size and forward speed) in addition topographic and bathymetric features are not captured to intensity. Irish et al. (2008) showed that storm size can in the model, and the effects of waves may not be ac- cause variations of up to 30% in storm surge for a given curate even if a wave model were coupled to SLOSH. storm intensity. Kantha (2006) and Powell and Reinhold Despite these drawbacks, SLOSH is used in the gener- (2007) developed storm surge classification schemes ation of forecasts and probabilistic products (P-Surge; that look at hurricane characteristics beyond intensity to Glahn et al. 2009; Taylor and Glahn 2008). estimate the storm surge hazard posed by a particular Irish et al. (2011) recently produced probabilistic hurricane. These scales represented an improvement maximum hurricane surge forecasts based on surge re- over the SSHS as they accounted for storm size. How- sponse functions (Irish et al. 2009; Resio et al. 2009), ever, storm surge is also dependent on the landfall lo- hurricane characteristics, and joint probability statistics. cation, track heading, and translational speed of the This approach uses high-resolution simulation results to hurricane among other things for which these scales do generate surge response functions for a given region that not account (Jordan and Clayson 2008). Recently the can determine the surge response for a set of meteoro- NHC has officially removed storm surge information logical parameters. This approach is very promising but from the SSHS (NOAA/National Hurricane Center has underlying assumptions that the influence of the 2011a) because of the large differences that can develop storm angle and forward speed can be neglected when in the surge response and inundation for storms with the compared to the storm intensity, size, and landfall lo- same intensity but different other characteristics, and cation. While their work shows that in most cases this is a identical storms making landfall along different portions fair assumption based on model results, there are outliers of the coast. The offshore bathymetry, coastline config- which can be important. As pointed out by Rego and Li uration, and topography of the affected area play a large (2009) and Jelesnianski (1972), neglecting the forward role in dictating the extent of the inundation. Mildly speed and angle of approach may not be appropriate as sloping bathymetry has been shown to generate a larger there is a ‘‘critical motion relative to a coast that gives the surge response at the coast than steeper slopes (Irish et al. highest possible surge.’’ Additionally the technique does 2008). Likewise the landfall location can be important not account for tides and wave setup, which can con- as demonstrated by Weisberg and Zheng (2008) for tribute significantly to the surge and inundation. idealized storm surge simulations in the Tampa Bay, This paper addresses the rapid generation of high- Florida, area. The topography of the area and rough- resolution probabilistic inundation forecasts. The opti- ness of the terrain will dictate the extent of the coastal mal storm generation and multivariate interpolation inundation (Fletcher et al. 1995). Irish and Resio (2010) technique of Condon and Sheng (2012a,b) is applied to accounted for the local bathymetry in their hydrody- a single storm to generate an estimate of the inundation namics based scale, which gives the best quantitative hazard for southwest Florida from Hurricanes Charley results for the potential surge at the coast for 28 historical (2004) and Wilma (2005). This is accomplished in an hurricanes compared to SSHS, Powell and Reinhold adaptive manner to improve accuracy with each forecast. (2007), and Kantha (2006). However this scale lacks in- The technique considers the effect of storm intensity, size, formation regarding coastline configuration and topog- landfall location, forward speed, and approach angle on raphy, which is essential in determining the hazard from the surge response. The optimal storm database, which inundation. includes wave effects on surge and inundation, is pro- In addition to the classification schemes described duced and can be combined with a simple tidal model to above to qualitatively estimate inundation hazard, more account for tidal effects. Analysis of the official NHC quantitative measures have been developed. The NHC forecast errors for the past five years
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