Impact of SST and surface waves on Hurricane Florence (2018): a coupled modeling investigation

Author Posting. © American Meteorological Society , 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Zambon, J. B., He, R., Warner, J. C., & Hegermiller, C. A. Impact of SST and surface waves on Hurricane Florence (2018): a coupled modeling investigation. Weather and Forecasting, 36(5), (2021): 1713–1734, https://doi.org/10.1175/WAF-D-20-0171.1.Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir–Simpson category 4 to category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere–ocean–wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by ocean waves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r = 0.89) and strength (r = 0.95) coming from the fully coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean and wave features to the model further modified the fluxes due to more realistic cooling beneath the storm, which in turn modified the precipitation field. Our experiments highlight significant differences in how air–sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.This work has been supported by the U.S. Geological Survey Coastal/Marine Hazards and Resources Program, and by Congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157). The authors also wish to acknowledge research support through NSF Grant OCE-1559178 and NOAA Grant NA16NOS0120028. We also wish to thank Chris Sherwood from the U.S. Geological Survey for his help in deriving wave length from WAVEWATCH III data

Time-Varying Emulator for Short and Long-Term Analysis of Coastal Flood Hazard Potential

Rising seas coupled with ever increasing coastal populations present the potential for significant social and economic loss in the 21st century. Relatively short records of the full multidimensional space contributing to total water level coastal flooding events (astronomic tides, sea level anomalies, storm surges, wave run‐up, etc.) result in historical observations of only a small fraction of the possible range of conditions that could produce severe flooding. The Time‐varying Emulator for Short‐ and Long‐Term analysis of coastal flood hazard potential is presented here as a methodology capable of producing new iterations of the sea‐state parameters associated with the present‐day Pacific Ocean climate to simulate many synthetic extreme compound events. The emulator utilizes weather typing of fundamental climate drivers (sea surface temperatures, sea level pressures, etc.) to reduce complexity and produces new daily synoptic weather chronologies with an auto‐regressive logistic model accounting for conditional dependencies on the El Niño Southern Oscillation, the Madden‐Julian Oscillation, seasonality, and the prior two days of weather progression. Joint probabilities of sea‐state parameters unique to simulated weather patterns are used to create new time series of the hypothetical components contributing to synthetic total water levels (swells from multiple directions coupled with water levels due to wind setup, temperature anomalies, and tides). The Time‐varying Emulator for Short‐ and Long‐Term analysis of coastal flood hazard potential reveals the importance of considering the multivariate nature of extreme coastal flooding, while progressing the ability to incorporate large‐scale climate variability into site specific studies assessing hazards within the context of predicted climate change in the 21st century

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.This work was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program. The authors thank Jorge Perez, IH Cantabria, for providing the GOW wave hindcast and for assistance with wave spectra, and Sean Vitousek, University of Chicago, for a helpful review. This material is based upon work supported by the U.S. Geological Survey under grant/cooperative agreement GI5AC00426. A. R., J. A. A. A., and F. J. M. acknowledge the support of the Spanish “Ministerio de Economía y Competitividad” under grant BIA2014-59643-R. J. A. A. A. was funded by the Spanish “Ministerio de Educación, Cultura y Deporte” FPU (Formación del Profesorado Universitario) studentship BOE-A-2013-12235. Reanalyses of ocean data are available for research purposes through IH Cantabria (contact [email protected]). Southern California Bight look-up table data are available at https://doi.org/10.1594/PANGAEA.880314. Related Southern California nearshore wave data can be found at http://dx.doi.org/10.5066/F7N29V2V

A Climate Index Optimized for Longshore Sediment Transport Reveals Interannual and Multidecadal Littoral Cell Rotations

A recent 35-year endpoint shoreline change analysis revealed significant counterclockwiserotations occurring in north-central Oregon, USA, littoral cells that extend 10s of kilometers in length.While the potential for severe El Niños to contribute to littoral cell rotations at seasonal to interannual scalewas previously recognized, the dynamics resulting in persistent (multidecadal) rotation were unknown,largely due to a lack of historical wave conditions extending back multiple decades and the difficulty ofseparating the timescales of shoreline variability in a high energy region. This study addresses this questionby (1) developing a statistical downscaling framework to characterize wave conditions relevant for longshoresediment transport during data-poor decades and (2) applying a one-line shoreline change model toquantitatively assess the potential for such large embayed beaches to rotate. A climateINdex was optimizedto capture variability in longshore wave power as a proxy for potentialLOngshore Sediment Transport(LOST_IN), and a procedure was developed to simulate many realizations of potential wave conditions fromthe index. Waves were transformed dynamically with Simulating Waves Nearshore to the nearshore asinputs to a one-line model that revealed shoreline rotations of embayed beaches at multiple time and spatialscales not previously discernible from infrequent observations. Model results indicate that littoral cellsrespond to both interannual and multidecadal oscillations, producing comparable shoreline excursions toextreme El Niño winters. The technique quantitatively relates morphodynamic forcing to specific climatepatterns and has the potential to better identify and quantify coastal variability on timescales relevant to achanging climate.This work would not have been possible without funding from the NSF Graduate Research Fellowship Program (GRFP) through NSF grant DGE-1314109, the Coastal and Ocean Climate Applications (COCA) program through NOAA grant NA15OAR4310243, NOAA’s Regional Integrated Sciences and Assessments Program (RISA), under NOAA grant NA15OAR4310145, and the Spanish Ministerio de Educación Cultura y Deporte FPU (Formación del Profesorado Universitario) studentship BOE-A-2013-12235. Beach survey data collection undertaken on the Oregon coast was made possible by the Northwest Association of Networked Ocean Observing Systems (NANOOS) through NOAA grant NA16NOS0120019

Modeling the morphodynamics of coastal responses to extreme events: what shape are we in?

This paper is not subject to U.S. copyright. The definitive version was published in Sherwood, C. R., van Dongeren, A., Doyle, J., Hegermiller, C. A., Hsu, T.-J., Kalra, T. S., Olabarrieta, M., Penko, A. M., Rafati, Y., Roelvink, D., van der Lugt, M., Veeramony, J., & Warner, J. C. Modeling the morphodynamics of coastal responses to extreme events: what shape are we in? Annual Review of Marine Science, 14, (2022): 457–492, https://doi.org/10.1146/annurev-marine-032221-090215.This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash,collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.All authors except D.R. were partially supported by the IFMSIP project, funded by US Office of Naval Research grant PE 0601153N under contracts N00014-17-1-2459 (Deltares), N00014-18-1-2785 (University of Delaware), N0001419WX00733 (US Naval Research Laboratory, Monterey), N0001418WX01447 (US Naval Research Laboratory, Stennis Space Center), and N0001418IP00016 (US Geological Survey). C.R.S., C.A.H., T.S.K., and J.C.W. were supported by the US Geological Survey Coastal/Marine Hazards and Resources Program. A.v.D. and M.v.d.L. were supported by the Deltares Strategic Research project Quantifying Flood Hazards and Impacts. M.O. acknowledges support from National Science Foundation project OCE-1554892

A Multimodal Wave Spectrum-Based Approach for Statistical Downscaling of Local Wave Climate

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g., Pacific Ocean). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, this study addresses these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in the statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into ?wave families,? defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.This work was supported by the U.S. Geological Survey Grant/Cooperative Agreement G15AC00426. AR, JAAA, and FJM were supported by the Spanish Ministerio de Economia y Competitividad Grant BIA2014-59643-R. PC was supported by the Spanish Ministerio de Economia y Competitividad Grant BIA2015-70644-R. JAAA was funded by the Spanish Ministerio de Educación, Cultura y Deporte FPU (Formación del Profesorado Universitario) studentship BOEA-2013-12235. Support was provided from the U.S. DOD Strategic Environmental Research and Development Program (SERDP Project RC-2644) through the NOAA National Centers for Environmental Information (NCEI). CFSR atmospheric data are available online (at https://climatedataguide.ucar.edu/climate-data/climate-forecastsystem-reanalysis-cfsr). Reanalyses of ocean data are available for research purposes through IH Cantabria (contact [email protected])

Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream

Author Posting. © American Meteorological Society, 2019. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 49(11), (2019): 2883-2900, doi: 10.1175/JPO-D-19-0124.1.Hurricanes interact with the Gulf Stream in the South Atlantic Bight (SAB) through a wide variety of processes, which are crucial to understand for prediction of open-ocean and coastal hazards during storms. However, it remains unclear how waves are modified by large-scale ocean currents under storm conditions, when waves are aligned with the storm-driven circulation and tightly coupled to the overlying wind field. Hurricane Matthew (2016) impacted the U.S. Southeast coast, causing extensive coastal change due to large waves and elevated water levels. The hurricane traveled on the continental shelf parallel to the SAB coastline, with the right side of the hurricane directly over the Gulf Stream. Using the Coupled Ocean–Atmosphere–Wave–Sediment Transport modeling system, we investigate wave–current interaction between Hurricane Matthew and the Gulf Stream. The model simulates ocean currents and waves over a grid encompassing the U.S. East Coast, with varied coupling of the hydrodynamic and wave components to isolate the effect of the currents on the waves, and the effect of the Gulf Stream relative to storm-driven circulation. The Gulf Stream modifies the direction of the storm-driven currents beneath the right side of the hurricane. Waves transitioned from following currents that result in wave lengthening, through negative current gradients that result in wave steepening and dissipation. Wave–current interaction over the Gulf Stream modified maximum coastal total water levels and changed incident wave directions at the coast by up to 20°, with strong implications for the morphodynamic response and stability of the coast to the hurricane.C.A. Hegermiller is grateful to the Woods Hole Oceanographic Institution (WHOI) Postdoctoral Scholarship program and the WHOI-U.S. Geological Survey (USGS) cooperative agreement for support. This project was supported by the USGS Coastal and Marine Hazards and Resources Program and by the Office of Naval Research, Increasing the Fidelity of Morphological Storm Impact Predictions Project. Thank you to the internal and external reviewers for improving the quality of this work, and to conversations within the Woods Hole community during the development of the experiment and analysis of the results. Model data can be found at http://geoport.whoi.edu/thredds/catalog/sand/usgs/users/chegermiller/projects/WCI_JPO_2019/catalog.html. Figure color maps are from Thyng et al. (2016).2020-05-0

Ocean Surface Gravity Wave Evolution during Three Along-Shelf Propagating Tropical Cyclones: Model’s Performance of Wind-Sea and Swell

Despite recent advancements in ocean–wave observations, how a tropical cyclone’s (TC’s) track, intensity, and translation speed affect the directional wave spectra evolution is poorly understood. Given the scarcity of available wave spectral observations during TCs, there are few studies about the performance of spectral wave models, such as Simulating Waves Nearshore (SWAN), under various TC scenarios. We combined the National Data Buoy Center observations and numerical model hindcasts to determine the linkages between wave spectrum evolution and TC characteristics during hurricanes Matthew 2016, Dorian 2019, and Isaias 2020. Five phases were identified in the wave spectrogram based on the normalized distance to the TC, the sea–swell separation frequency, and the peak wave frequency, indicating how the wave evolution relates to TC characteristics. The wave spectral structure and SWAN model’s performance for wave energy distribution within different phases were identified. The TC intensity and its normalized distance to a buoy were the dominant factors in the energy levels and peak wave frequencies. The TC heading direction and translation speed were more likely to impact the durations of the phases. TC translation speeds also influenced the model’s performance on swell energy. The knowledge gained in this work paves the way for improving model’s performance during severe weather events

Modeling of barrier breaching during hurricanes Sandy and Matthew

This paper is not subject to U.S. copyright. The definitive version was published in Hegermiller, C. A., Warner, J. C., Olabarrieta, M., Sherwood, C. R., & Kalra, T. S. Modeling of barrier breaching during hurricanes Sandy and Matthew. Journal of Geophysical Research: Earth Surface, 127(3), (2022): e2021JF006307, https://doi.org/10.1029/2021JF006307.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.C. A. Hegermiller is grateful to the U.S. Geological Survey (USGS) Mendenhall Research Fellowship Program for support. This project was supported by the USGS Coastal and Marine Geology Program and the Office of Naval Research, Increasing the Fidelity of Morphological Storm Impact Predictions Project. M. Olabarrieta acknowledges support from the NSF project OCE-1554892.2022-07-2