As part of a U.S. Integrated Ocean Observing System (IOOS) funded Coastal and Ocean Modeling Testbed (COMT), hindcasts of waves and storm surge for 2017 Hurricanes Irma and Maria are examined and compared to wave and water level gauge data in the vicinity of Puerto Rico and the U.S. Virgin Islands. The region is characterized by adjacent deep ocean water, narrow shelves, and coral reef systems providing coastal protection. The storm physics are analyzed using an unstructured grid third‐generation wave circulation coupled modeling system (ADCIRC+SWAN) with respect to tides, winds, atmospheric pressure, waves, and wave radiation stress‐induced setup. The water level response is generally dominated by the pressure deficit of the hurricanes. Wind‐driven surge is important over the shallow shelf to the east of Puerto Rico and wave‐induced setup becomes significant at locations in close proximity to the coastline. Contrary to conditions along the Gulf of Mexico shelf, geostrophically induced setup is negligible. Characteristics from a range of meteorological forcing models are assessed, and the associated errors in the hydrodynamic response are quantified. A data‐assimilated tropical planetary boundary model leads to the smallest atmospheric pressure, water level and wave property errors across both storms. Through comparisons between ADCIRC+SWAN and SLOSH‐FW (a structured grid first‐generation wave circulation coupled model), it is shown that the response to atmospheric forcing is similar; however, nearshore wave setup is smaller in SLOSH‐FW due to its coarser resolution here. Further, in addition to erroneous wind‐driven surge through depth limiting over the open ocean, numerical oscillations in the water level time series develop in SLOSH‐FW likely due to its small domain size.

Hurricane events combine ocean storm surge penetration with inland runoff flooding. This article presents a new methodology to determine coastal flood levels caused by the combination of storm surge and surface runoff. The proposed approach couples the Simulating Waves Nearshore model and the Advanced Circulation (ADCIRC) model with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) two-dimensional hydrologic model. Radar precipitation data in a 2D hydrologic model with a circulation model allows simulation of time and spatially varied conditions. The method was applied to study flooding scenarios occurring during the passage of Hurricane Georges (1998) on the east coast of Puerto Rico. The combination of storm surge and surface runoff produced a critical scenario, in terms of flood depth, at this location. The paper describes the data collection process, circulation and hydrologic models, their assemblage and simulation scenarios. Results show that peak flow from inland runoff and peak flow due to storm surge did not coincide in the coastal zone; however, the interaction of both discharges causes an aggravated hazardous condition by increasing flood levels beyond those obtained with storm surge penetration only. Linking of storm surge and hydrologic models are necessary when storm surge conditions occur simultaneously with high precipitation over steep and small coastal watersheds.

This study applies a baroclinic‐coupled depth‐integrated modeling system to the North Atlantic Ocean, where an unstructured mesh is used to focus resolution down to ∼30 m along the coasts of Puerto Rico and the U.S. Virgin Islands. Ocean baroclinicity is incorporated through one‐way coupling from operational data‐assimilated Global Ocean Forecasting System 3.1 temperature and salinity fields at just 12% additional computational time. The main objectives are to provide a comprehensive analysis of observed and modeled coastal sea levels (spanning from seasonal to supertidal variations) in Puerto Rico and the U.S. Virgin Islands during 2017 and to evaluate the associated model performance with and without baroclinic coupling at 14 National Oceanic and Atmospheric Administration/National Ocean Service tide gauges deployed in the region. It is found that baroclinic coupling increases modeled energy across the entire frequency spectrum, which is more commensurate with observations. In particular, density‐driven effects such as the seasonal cycle and sea level setdown due to trailing cold wakes from passing hurricanes are largely reproduced. Supertidal shelf‐resonant seiching at one to two cycles per hour is observed and modeled at a number of locations, where excitation of these modes is often promoted by the baroclinic coupling. Baroclinicity improves the yearlong model skill at every tide gauge, where the mean total skill is increased from 87% to 93% accuracy (54% to 85% for the nontidal residual). In September 2017 during Hurricanes Irma and Maria, baroclinicity increases model skill at 10 out of 14 tide gauges even when the barotropic mode is adjusted to have no mean offset from the observations.

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