Tuesday, 14 January 2020: 9:15 AM
158 (Boston Convention and Exhibition Center)
Dongming Yang, IMSG at NOAA/NWS/NCEP, College Park, MD; and A. Van der Westhuysen, J. R. Rhome, and C. Fritz
With the purpose of building up a surge and inundation forecasting capability in vulnerable developing countries, the National Weather Service has participated in the USAID/WMO Coastal Inundation and Flooding Demonstration Project (CIFDP) for the Island of Hispaniola (Dominican Republic and Haiti). Wind waves have a significant impact on storm surge levels in reef-fringed islands environments. However, third-generation wave models such as WAVEWATCH III and SWAN are computationally expensive, and thus not feasible for operational coupling to the computationally-efficient surge model SLOSH, currently used at the National Hurricane Center (NHC). This constraint is even greater in developing countries with modest computational resources, such as the Dominican Republic and Haiti. This has limited the use of coupled wave-surge modeling in the generation of NHC’s surge hazard databases such as the Maximum Envelope of Water (MEOW) and Maximum of Maximum (MOM). It is also prohibitively expensive to apply in probabilistic storm surge forecasting, which requires an ensemble of hundreds of model runs.
This modeling gap was addressed by incorporating an efficient parametric wind wave model as a subroutine into SLOSH. This imbedded wave model receives wind stresses and water levels from SLOSH, and in turn exports wave radiation stress gradients to the surge model. It features a parameterization of the frequency evolution during wind-wave growth, and is reduced to only two carrier frequencies (one for the wind sea, the other for the swell), distributed over only eight directions. As a result, the model has a computational cost on par with that of SLOSH, and two orders of magnitude lower than that of SWAN. In this paper, we present the validation of this coupled model for laboratory and idealized and cases, as well a collection of recent hurricanes that passed over Hispaniola, including Maria (2017), Matthew (2016), Isaac (2012) and Irene (2011). Results show realistic surge response and favorable comparison against observations. This model was subsequently applied to compute the first-ever MEOW and MOM surge hazard databases for the island of Hispaniola that include the effect of wind waves, which will be reviewed.
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