- Award ID(s):
- NSF-PAR ID:
- Date Published:
- Journal Name:
- Coastal Engineering Proceedings
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- Medium: X
- Sponsoring Org:
- National Science Foundation
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Two sessions were organized during the 2018 Fall AGU Meeting entitled, (1) Coastal Response to Extreme Events: Fidelity of Model Predictions of Surge, Inundation, and Morphodynamics and (2) Improved Observational and Modeling Skills to Understand the Hurricane and Winter Storm Induced Surge and Meteotsunami. The focus of these sessions was on examining the impact of natural disasters on estuarine and coastal regions worldwide, including the islands and mainland in the northwestern Atlantic and the northwestern Pacific. The key research interests are the investigations on the regional dynamics of storm surges, coastal inundations, waves, tides, currents, sea surface temperatures, storm inundations and coastal morphology using both numerical models and observations during tropical and extratropical cyclones. This Special Issue (SI) ‘Estuarine and coastal natural hazards’ in Estuarine Coastal and Shelf Science is an outcome of the talks presented at these two sessions. Five themes are considered (effects of storms of wave dynamics; tide and storm surge simulations; wave-current interaction during typhoons; wave effects on storm surges and hydrodynamics; hydrodynamic and morphodynamic responses to typhoons), arguably reflecting areas of greatest interest to researchers and policy makers. This synopsis of the articles published in the SI allows us to obtain a better understanding of the dynamics of natural hazards (e.g., storm surges, extreme waves, and storm induced inundation) from various physical aspects. The discussion in the SI explores future dimensions to comprehend numerical models with fully coupled windwave- current-morphology interactions at high spatial resolutions in the nearshore and surf zone during extreme wind events. In addition, it would be worthwhile to design numerical models incorporating climate change projections (sea level rise and global warming temperatures) for storm surges and coastal inundations to allow more precisely informed coastal zone management plans.more » « less
Physical processes driving barrier island change during storms are important to understand to mitigate coastal hazards and to evaluate conceptual models for barrier evolution. Spatial variations in barrier island topography, landcover characteristics, and nearshore and back‐barrier hydrodynamics can yield complex morphological change that requires models of increasing resolution and physical complexity to predict. Using the Coupled Ocean‐Atmosphere‐Wave‐Sediment Transport (COAWST) modeling system, we investigated two barrier island breaches that occurred on Fire Island, NY during Hurricane Sandy (2012) and at Matanzas, FL during Hurricane Matthew (2016). The model employed a recently implemented infragravity (IG) wave driver to represent the important effects of IG waves on nearshore water levels and sediment transport. The model simulated breaching and other changes with good skill at both locations, resolving differences in the processes and evolution. The breach simulated at Fire Island was 250 m west of the observed breach, whereas the breach simulated at Matanzas was within 100 m of the observed breach. Implementation of the vegetation module of COAWST to allow three‐dimensional drag over dune vegetation at Fire Island improved model skill by decreasing flows across the back‐barrier, as opposed to varying bottom roughness that did not positively alter model response. Analysis of breach processes at Matanzas indicated that both far‐field and local hydrodynamics influenced breach creation and evolution, including remotely generated waves and surge, but also surge propagation through back‐barrier waterways. This work underscores the importance of resolving the complexity of nearshore and back‐barrier systems when predicting barrier island change during extreme events.
Meteotsunami waves can be triggered by atmospheric disturbances accompanying tropical cyclone rainbands (TCRs) before, during, and long after a tropical cyclone (TC) makes landfall. Due to a paucity of high‐resolution field data along open coasts during TCs, relatively little is known about the atmospheric forcing that generate and resonantly amplify these ocean waves, nor their coastal impact. This study links high‐resolution field measurements of sea level and air pressure from Hurricane Harvey (2017) with a numerical model to assess the potential for meteotsunami generation by sudden changes in air pressure accompanying TCRs. Previous studies, through the use of idealized models, have suggested that wind is the dominant forcing mechanism for TCR‐induced meteotsunami with negligible contributions from air pressure. Our model simulations show that large air pressure perturbations (∼1–3 mbar) can generate meteotsunamis that are similar in period (∼20 min) and amplitude (∼0.2 m) to surf zone observations. The measured air pressure disturbances were often short in wavelength, which necessitates a numerical model with high temporal and spatial resolution to simulate meteotsunami triggered by this mechanism. Sensitivity analysis indicates that air pressure forcing can produce meteotsunami with amplitudes
O(0.5 m)and large spatial extents, but model results are sensitive to atmospheric factors, including model uncertainties (length, forward translation speed, and trajectory of the air pressure disturbance), as well as oceanographic factors (storm surge). The present study provides observational and numerical evidence that suggest that air pressure perturbations likely play a larger role in meteotsunami generation by TCRs than previously identified.
Abstract. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers, such as oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse, for the first time, the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis data sets. We assess the overall dependence from observations by using Kendall's rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find the highest dependence between different drivers at locations in the Gulf of Mexico, southeastern, and southwestern coasts. Regarding different driver combinations, the highest dependence exists between surge–waves, followed by surge–precipitation, surge–discharge, waves–precipitation, and waves–discharge. We also perform a seasonal dependence analysis (tropical vs. extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East Coast and stronger dependence during the extra-tropical season on the West Coast. Finally, we compare the dependence structure of different combinations of flooding drivers, using observations and reanalysis data, and use the Kullback–Leibler (KL) divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tail dependence between surge–discharge on the East and West coasts and overestimate tail dependence between surge–precipitation on the East Coast, while they underestimate it on the West Coast. The comprehensive analysis presented here provides new insights on where the compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, duringwhich time of the year (tropical versus extra-tropical season) compoundflooding is more likely to occur, and how well reanalysis data capture thedependence structure between the different flooding drivers.more » « less
null (Ed.)Abstract Extreme sea levels (ESLs) due to typhoon-induced storm surge threaten the societal security of densely populated coastal China. Uncertainty in extreme value analysis (EVA) for ESL estimation has large implications for coastal communities’ adaptation to natural hazards. Here we evaluate uncertainties in ESL estimation and relevant driving factors based on hourly observations from 13 tide gauge stations and a complementary dataset derived from a hydrodynamic model. Results indicate significant uncertainties in ESL estimations stemming from using different EVA methods, which then propagate to the inundation assessment. Amplification factors due to sea-level rise (SLR) are highly sensitive to local relative SLR and the shape of the exceedance probability curve, which in turn depends on the selected EVA method. The hydrodynamic model hindcast indicates that high ESLs mainly occurred in eastern coastal China due to typhoon-induced storm surge. Larger uncertainties in the modelled ESLs are found for the coasts of the Yangtze River Delta, and particularly in the river mouth region. Future research and adaptation planning should prioritize these regions given expected future rising sea level, compound flood events, and human-induced factors (e.g. subsidence). This study provides theoretical and practical references for adaptation to ESL-related hazards along coastal China, with implications for coastal regions worldwide.more » « less