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Influence of Hurricane Wind Field Variability on Real‐Time Forecast Simulations of the Coastal Environment
... This one-way nesting approach has been successfully used in other coastal areas. Most recently, a configuration of Delft3D Flow [45,46] and SWAN [47] was implemented by [48], in a similar application to this study, to assess the influence of varying wind fields on forecasts of coastal dynamics near North Carolina, USA. Boundary and atmospheric forcing from various global models were used to provide appropriately downscaled wave, current and water level estimates. ...
... Delft3D Flow has been extensively used in ocean and coastal domains [56] and the reliability of its code variously established [57][58][59]. The model has been successfully applied in cases similar to the one in this study (e.g., [48,50,53,60,61]). ...
A coupled numerical hydrodynamic model is presented for the Cape Peninsula region of South Africa. The model is intended to support a range of interdisciplinary coastal management and research applications, given the multifaceted socioeconomic and ecological value of the study area. Calibration and validation are presented, with the model reproducing the mean circulation well. Maximum differences between modelled and measured mean surface current speeds and directions of 3.9 × 10 −2 m s −1 and 20.7°, respectively, were produced near Cape Town, where current velocities are moderate. At other measurement sites, the model closely reproduces mean surface and near-bed current speeds and directions and outperforms a global model. In simulating sub-daily velocity variability, the model's skill is moderate, and similar to that of a global model, where comparison is possible. It offers the distinct advantage of producing information where the global model cannot, however. Validation for temperature and salinity is provided, indicating promising performance. The model produces a range of expected dynamical features for the domain including upwelling and vertical current shear. Nuances in circulation patterns are revealed; specifically, the development of rotational flow patterns within False Bay is qualified and an eddy in Table Bay is identified.
... The study site (Figure 1), which is located on Pea Island in the Outer Banks of North Carolina, United States (approximately 170 km east of Greenville), was chosen to evaluate methods for extracting dune vegetation (DuneVeg) metrics, develop an automated workflow for remote extraction techniques, and perform a trend analysis using the derived vegetation metrics. The site is part of the US Coastal Research Program's DUring Nearshore Event eXperiment (DUNEX), which is a multi-agency, academia, and stakeholder collaboration to study nearshore processes during coastal storm events [19,21,22]. The Pea Island site is part of the Pea Island National Wildlife Refuge and is approximately 19 km in length and 2.4 km wide. ...
Monitoring and modeling of coastal vegetation and wetland systems are considered major challenges, especially when considering environmental response to hazards, disturbances, and management activities. Remote sensing applications can provide alternatives and complementary approaches to the often costly and laborious field-based collection methods traditionally used for coastal ecosystem monitoring. New and improved sensors and data analysis techniques have become available, making remote sensing applications attractive for evaluation and potential use in monitoring coastal vegetation properties and ecosystem conditions and change. This study involves the extraction of vegetation metrics from airborne LiDAR (Light Detection and Ranging) and hyperspectral imagery (HSI) to quantify coastal dune vegetation characteristics and assesses landscape-level trends from those derived metrics. HSI- and LiDAR-derived elevation (digital elevation model) and vegetation metrics (canopy height model, leaf area index, and normalized difference vegetation index) were used in conjunction with per-pixel linear regression and hot spot analyses to evaluate hurricane-induced spatial and temporal changes in elevation and vegetation properties. These assessments showed areas with greatest decreases in vegetation metric values were associated with direct tropical storm energies and processes (i.e., overwashing events eroding beach and dune features), while those with the greatest increases in vegetation metric values were in areas where overwashed sediments were distributed. This study narrows existing gaps in dune vegetation data by advancing new methodologies to classify, quantify, and estimate critical coastal vegetation metrics. The tools and methods developed in this study will ultimately improve future estimates and predictions of nearshore dynamics and impacts from disturbance events.
... In addition to bay-side storms, hurricanes with tracks over the nearby ocean and winds circulating over the sound can create a similar water level rebound effect. Rey and Mulligan (2021) reported water level gradients of 2 m along the Pamlico Sound during Hurricane Dorian in 2019, with low water levels (− 0.5 m) in the back barrier region as wind was blowing to the west and high water levels (1.5 m) as the wind was blowing to the southeast. These examples provide evidence of the significant water level gradients that can develop in large bays as storms travel along them. ...
Bay-side storms, defined here as storms with tracks on the landward side of barrier islands, may disturb the hydrodynamics of inner bays to a larger extent than on the ocean side. These storms are common in large-scale O(>100,000 m) estuarine systems and have the potential to modify the circulation in bays and within tidal inlets. Here, we provide an overview of the hydrodynamic response of a tidal inlet under forcings caused by bay-side storms and explore the role of waves in modulating the release of storm surge from the back-barrier regions into the ocean. A two-dimensional horizontal numerical model including wave-current interactions is calibrated and validated against field observations of water levels and depth-averaged velocities at Oregon Inlet, NC. The model is then used to investigate the effect of synthetic bay-side storms with varying wave conditions and water levels based on those generated by Hurricane Irene (2011), which is the strongest bay-side storm to hit the Outer Banks of North Carolina in the last two decades. Effect of timing of the peak storm surge during the ebb and flood phases of the tide is also explored.
Results from synthetic storms indicate that, during bay-side storms, the water level gradient along the inlet favors ebbing flows regardless of the timing of the storms relative to tidal phase. These results suggest that waves might be responsible for any influx of volume to the bay during high bay-side surge events. Wave blocking effects were found to be stronger along the ebb shoal and only reached the flood delta when bay water levels were nearly the same as the ocean water levels. Reduction of currents by waves in the inlet have the potential to extend the duration of the inundation period in the back barrier region. Bay-side storms also caused flux enhancement over inlet shoals and channels in the flood delta, which could have implications for circulation patterns as well as the morphodynamics of the system.
... The geographic configuration surrounding Oregon Inlet, combined with prevailing winds from the southwest and northeast, maximizes fetch length over the Pamlico Sound and enhances wind induced setup/setdown (Mulligan et al., 2015;Safak et al., 2016). Previous observations and numerical simulations have shown that winds may alter water levels in the sound by more than 2 m, a magnitude that surpasses the tidal range within the sound by at least an order of magnitude (Clunies et al., 2017;Mulligan et al., 2015;Rey & Mulligan, 2021;Safak et al., 2016). ...
Wind influence on tidal inlet hydrodynamics is examined using 40 days of wind, water level, and current observations collected in Spring 2019 at Oregon Inlet, NC, a large (1 km wide, 1–13 m deep) meso‐tidal inlet with complex delta systems. Wind velocities through the inlet (ranging 0–18 m/s) are modulated at subtidal timescales and are well correlated (R = 0.87) to a subtidal component of the water level slope through the inlet. The subtidal wind and water level slope are also well correlated to the subtidal current along the principal flow axis in the main inlet channel (R = 0.92 and 0.96, respectively). In combination with findings from previous studies, these findings suggest that regional winds induce the subtidal water level slope through the inlet by causing opposing setup/setdown to either side of the inlet. A force balance at the inlet demonstrates that the wind‐induced pressure gradient forces the subtidal currents, with wave forcing and local wind shear acting as lower‐order influences. The magnitude of the subtidal current is substantial, exceeding that of the tidal currents 45% of the time. Cumulatively, these findings indicate that regional winds exert a first‐order control on the currents at Oregon Inlet and cause irregular hydrodynamic patterns not well described by the traditional inlet classification scheme. Regional geographic characteristics may contribute to the high level of wind influence at Oregon Inlet, but similar processes are likely to be important to net flow dynamics at other inlets with large, shallow inland water bodies.
... These wind fields were obtained from the Rapid Refresh Model (RAP), an hourly updating assimilation system using in-situ data sources (observation stations, satellite imagery) to generate winds on a grid with 13 km resolution at the 10 m elevation above the sea surface (Benjamin et al. 2016). The RAP wind field resolution allows for an accurate representation of the spatial variability and asymmetry of the hurricane (Rey and Mulligan 2021). The winds are shown at selected times with a time interval of 6 hours in Figure 3. ...
Large waves and storm surge generated by powerful storms can have detrimental impacts on coastal areas. The Gulf of Maine and Bay of Fundy system in the Atlantic Ocean is a particularly dynamic environment where storm surge can synergistically combine with the large tides to yield serious impacts on low-lying coastal areas. In this study, impacts from Hurricane Arthur in 2014 were investigated with observations and numerical simulations using a coupled hydrodynamic-wave model. The results indicate that the storm generated significant wave heights up to 5 m in the Gulf of Maine and a storm surge of over 0.5 m in coastal areas in the Upper Bay of Fundy, however this surge occurred during the neap tide with no associated flooding. Additional simulations, including a historically important event called the Saxby Gale of 1869, were also simulated. This powerful storm occurred during a perigean spring tide, and the model results indicate wave heights of over 10 m and storm surge of over 0.7 m that caused significant flooding. The results indicate that a well-timed tropical cyclone during a high spring tide has the potential to create a storm surge that could overtop existing dyke systems, causing extensive flooding and damage.
Table Bay, located in the Cape Peninsula region of South Africa, supports a variety of human and ecological interests. Notably it hosts a major port, with significant shipping and smaller maritime activity in and near the bay. Despite this, knowledge of its circulation dynamics remains cursory. In this study, surface gravity waves, particularly those with longer periods and higher wave heights such as swells, are shown to be important in driving near surface currents and establishing circulation patterns within Table Bay. A surface circulation feature, linked to large wave conditions and established by strong wave-driven flows near Robben Island, is identified and described by means of two coastal ocean model simulations. One simulation is dynamically coupled to a wave model and includes current forcing due to waves, whereas the other neglects waves. The influence of these wave-driven currents is relevant at the event scale, but also affects the monthly means of the simulation periods. Finally, the importance of including accurate surface gravity wave forcing in simulations of coastal currents, for applications of coastal models, is elucidated. This is achieved by analysing differences in the drift of a series of drogues deployed in the coupled and uncoupled simulations. Trajectories, drift speeds and drogue fates differed materially between the two configurations, underscoring the implications of wave-driven currents for common use cases.
The wind-driven nature of large lakes suggests that the accuracy of meteorological inputs is essential for hydrodynamic modelling. Moreover, coupling between the meteorological inputs and density stratification may also influence the simulated lake behavior. To investigate wind-driven large lake processes, a high-resolution coupled Delft3D-SWAN model was applied to Lake Ontario to simulate storm surges, surface waves, and circulation during two recent storm events. In both events, the sustained wind speeds approached 20 m s⁻¹; however, variations in wind direction and duration altered the lake's surface wave and storm surge responses. The influence of different atmospheric inputs was investigated by comparing results from two spatially varied atmospheric models: the Rapid Refresh (RAP) and the High-Resolution Deterministic Prediction System (HRDPS). Hydrodynamic simulations using HRDPS were marginally better, with maximum root mean squared errors (RMSE) between modelled and observed water levels of 0.07 m, compared to 0.08 m with RAP. Predictions of the magnitude and timing of the maximum wave heights varied based on wind fields, with differences between predicted peak wave heights of up to 0.4 m. Both events occurred during a stratified period, allowing for a comparative evaluation of the influence of baroclinic and barotropic processes on the simulated surface wave and storm surge results. Simulations including the vertical density gradient gave a better representation of current velocities with depth and resulted in an improved prediction of peak storm surge magnitudes and surface water level behavior following the storms, reducing the RMSE by up to 12%.
Storm surge caused by tropical cyclones can cause overland flooding and lead to loss of life while damaging homes, businesses, and critical infrastructure. In 2018, Hurricane Michael made landfall near Mexico Beach, FL, on 10 October with peak wind speeds near 71.9 m s ⁻¹ (161 mph) and storm surge over 4.5 m NAVD88. During Hurricane Michael, water levels and waves were predicted near real-time using a deterministic, depth-averaged, high-resolution ADCIRC+SWAN model of the northern Gulf of Mexico. The model was forced with an asymmetrical parametric vortex model (GAHM) based on Michael's National Hurricane Center (NHC) forecast track and strength. The authors report errors between simulated and observed water level time-series, peak water level, and timing of peak for NHC Advisories. Forecasts of water levels were within 0.5 m of observations, and the timing of peak water levels was within 1 hr as early as 48 hr before Michaels eventual landfall. We also examined the effect of adding far-field meteorology in our TC vortex model for use in real-time forecasts. In general, we found that including far-field meteorology by blending the TC vortex with a basin-scale NWP product improved water level forecasts. However, we note that divergence between the NHC forecast track and the forecast track of the meteorological model supplying the far-field winds represents a potential limitation to operationalizing a blended wind field surge product. The approaches and data reported herein provide a transparent assessment of water level forecasts during Hurricane Michael and highlight potential future improvements for more accurate predictions.
Tropical cyclones, including hurricanes, have high winds that can generate strong ocean surface circulation and large surface waves and numerous hurricanes that form and propagate over the Atlantic Ocean interact with the continental shelf. Hurricane Frey et al. (2012) impacted the east coast of North America after moving across the narrow shelf and made landfall in Onslow Bay, North Carolina, USA. In contrast, Hurricane Isaias (2020) moved generally parallel to the continental shelf, making landfall in Onslow Bay along a very different track compared to Hurricane Florence. These hurricanes provide an opportunity to understand the waves generated by large storms that move across the open ocean to the coastal environment on the shelf. In this study, the coupled Delft3D-SWAN modelling system is applied to numerically simulate the wind and wave conditions during both Hurricane Florence and Hurricane Isaias. The simulations are analyzed to understand the source terms that control the generated and dissipation of the surface wave field. The model results for Hurricane Florence, indicated that the deep water terms (wind input, whitecapping and quadruplet wave interactions) governed wave action balance on the shelf and in Onslow Bay (10–100 m depths), with negligible contributions from the shallow water dissipation terms such as bottom friction. Hurricane Isaias followed the same trend, but with lower values corresponding to lower wind speeds and smaller wave heights. In addition, Hurricane Florence crossed the shelf and approached the bay from the open ocean with larger waves that were not limited by fetch. In contrast, since Hurricane Isaias followed the coast along the shelf, the wave conditions were fetch-limited on the west side of the track near the coast and not limited by fetch on the east side on the open shelf. The results of this study underscore how hurricanes with different tracks with respect to the orientation of the shelf and coast generate different wave fields and impact coastal environments in different ways.
For enhanced public safety and water resource management, a
three-dimensional operational lake hydrodynamic forecasting system,
COASTLINES (Canadian cOASTal and Lake forecastINg modEl System), was
developed. The modeling system is built upon the three-dimensional Aquatic Ecosystem Model
(AEM3D) model, with predictive simulation capabilities developed and tested
for a large lake (i.e., Lake Erie). The open-access workflow derives model
forcing, code execution, post-processing, and web-based visualization of the
model outputs, including water level elevations and temperatures, in near-real time. COASTLINES also generates 240 h predictions using atmospheric
forcing from 15 and 25 km horizontal-resolution operational
meteorological products from the Environment Canada Global Deterministic
Forecast System (GDPS). Simulated water levels were validated against
observations from six gauge stations, with model error increasing with
forecast horizon. Satellite images and lake buoys were used to validate
forecast lake surface temperature and the water column thermal
stratification. The forecast lake surface temperature is as accurate as
hindcasts, with a root-mean-square deviation <2 ∘C.
COASTLINES predicted storm surges and up-/downwelling events that are
important for coastal flooding and drinking water/fishery management,
respectively. Model forecasts are available in real time at https://coastlines.engineering.queensu.ca/ (last access: January 2022 ). This study provides an example
of the successful development of an operational forecasting workflow,
entirely driven by open-access data, that may be easily adapted to simulate
aquatic systems or to drive other computational models, as required for
management and public safety.
Under excitation by hurricanes, previously quiescent wave fields and their properties can rapidly evolve as they absorb energy from the turbulent atmosphere. Significant wave height (Hs) is one of the primary variables scrutinized during extreme events. Thus, using Hurricane Dorian (2019) as a case study, an empirical wind-wave model for forecasting hurricane-induced wind seas is proposed for the Caribbean Sea (CS). Results are compared with the current South China Sea (SCS) state-of-the-art using 10 other hurricanes that passed through the CS from 2011–2019. Results illustrate that the proposed CS model can achieve similar correlation coefficients between observed and simulated Hs as the SCS model, but crucially, the CS model produces approximately half the root mean square error
generated by the SCS model. Mean average percentage errors were also significantly lower using the CS model for Hs predictions compared to the SCS model. These results illustrate a comprehensive improvement in regional Hs predictions under hurricane conditions. However, due to the single predictor of wind speed for either model, they both fail under swell conditions and modulation of the wave field by surface currents, leaving room for future improvement by the inclusion of additional variables.
Pamlico Sound, a large back-barrier estuary in North Carolina, is under threat of climate change due to increased storm activity and sea-level rise. The response of this system is investigated by considering what has already happened during changes in sea-level over the late Holocene epoch. The hydrodynamic changes that occurred in response to geomorphic evolution are simulated using a 3D numerical model for four distinct ‘time-slice’ scenarios. To accomplish this, the present-day bathymetry was obtained from a high resolution digital elevation model, and paleo-bathymetric grids were developed from sediment cores and seismic observations. Using the same hydrodynamic forcing for each geomorphic scenario, the models are compared to assess the combined response to: different inlets connecting the back-barrier estuary to the ocean; changes in basin geomorphology due to sedimentation; and sea-level rise. The results indicate that these factors have a considerable effect on hydrodynamics, waves, and salinity in the estuary. The time-averaged tidal ranges were up to three times as high for the past environments in comparison with present day water level elevations, and maximum current velocities were over three times higher in regions close to paleo-inlets. The simulations for each time-slice suggest that the salinity distribution in Pamlico Sound is strongly influenced by the hydraulic connectivity with other estuaries, and the number and size of tidal inlets through the barrier island system. The results indicate that changes to barrier systems induce strong, non-uniform and complex responses in back-barrier estuaries with regime-shifts in hydrodynamic energy and water mass properties.
Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 m3s−1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.
A nowcasting and forecasting system for storm surge, inundation, waves, and baroclinic flow for the Florida coast has been developed. The system is based on dynamically coupled CH3D and SWAN models and can use a variety of modules to provide different input forcing, boundary and initial conditions. The system is completely automated and operates unattended at pre-scheduled intervals as well as in event-triggered mode in response to Atlantic-basin tropical cyclone advisories issued by the National Hurricane Center. The system provides up to 72-h forecasts forward depending on the input dataset duration. Spatially, the system spans the entire Florida coastline by employing four high-resolution domains with resolutions as fine as 10–30 m in the near-shore and overland to allow the system to resolve fine estuarine details such as in the Intracoastal Waterway and minor tributaries. The system has been validated in both hindcast and nowcast/forecast modes using water level and salinity data from a variety of sources and has been found to run robustly during the test periods. Low level products (e.g., raw output datasets) are disseminated using THREDDS while a custom defined web-based graphical user interface (GUI) was developed for high level access.
The Rapid Refresh (RAP), an hourly-updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly-updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the previous RUC in three primary aspects: a larger geographical domain (covering North America); use of the community-based WRF-ARW (Weather Research and Forecasting – Advanced Research WRF) model replacing the RUC forecast model; and use of the Gridpoint Statistical Interpolation (GSI) assimilation instead of the RUC three-dimensional variational (3DVar) assimilation. As part of the RAP development, modifications have been made to the community WRF-ARW model (especially in model physics) and GSI assimilation systems, some based on previous model and assimilation design innovations developed initially with the RUC. Upper-air comparison is included for forecast verification against both rawinsondes and aircraft reports, the latter allowing hourly verification. In general, the RAP produces superior forecasts to those from the RUC, and its skill has continued to increase from 2012 up to RAP version 3 as of 2015. In addition, the RAP can improve on persistence forecasts for the 1-3h forecast range for surface, upper-air, and ceiling forecasts.
Wind-wave contributions to tropical cyclone (TC)-induced extreme sea levels are known to be significant in areas with narrow littoral zones, particularly at oceanic islands. Despite this, little information exists in many of these locations to assess the likelihood of inundation, the relative contribution of wind and wave setup to this inundation, and how it may change with sea level rise (SLR), particularly at scales relevant to coastal infrastructure. In this study, we explore TC-induced extreme sea levels at spatial scales on the order of tens of meters at Apia, the capitol of Samoa, a nation in the tropical South Pacific with typical high-island fringing reef morphology. Ensembles of stochastically generated TCs (based on historical information) are combined with numerical simulations of wind waves, storm-surge, and wave setup to develop high-resolution statistical information on extreme sea levels and local contributions of wind setup and wave setup. The results indicate that storm track and local morphological details lead to local differences in extreme sea levels on the order of 1 m at spatial scales of less than 1 km. Wave setup is the overall largest contributor at most locations; however, wind setup may exceed wave setup in some sheltered bays. When an arbitrary SLR scenario (+1 m) is introduced, overall extreme sea levels are found to modestly decrease relative to SLR, but wave energy near the shoreline greatly increases, consistent with a number of other recent studies. These differences have implications for coastal adaptation strategies.
The modifications to the data assimilation component of the Regional Deterministic Prediction System (RDPS) implemented at Environment Canada operations during the fall of 2014 are described. The main change is the replacement of the limited-area four-dimensional variational data assimilation (4DVar) algorithm for the limited-area analysis and the associated three-dimensional variational data assimilation (3DVar) scheme for the synchronous global driver analysis by the four-dimensional ensemble-variational data assimilation (4DEnVar) scheme presented in the first part of this study. It is shown that a 4DEnVar scheme using global background-error covariances can provide RDPS forecasts that are slightly improved compared to the previous operational approach, particularly during the first 24 h of the forecasts and in the summertime convective regime. Further forecast improvements were also made possible by upgrades in the assimilated observational data and by introducing the improved global analysis presented in the first part of this study in the RDPS intermittent cycling strategy. The computational savings brought by the 4DEnVar approach are also discussed.
A new operational wave forecasting system has been implemented at the National Centers for Environmental Prediction (NCEP) using the third public release ofWAVEWATCH III. The new system uses a mosaic of grids with two-way nesting in a single model. This global system replaces a previous operational wave modeling suite (based on the second release ofWAVEWATCH III). The new forecast system consists of nine grids at different resolutions to provide the NationalWeather Service (NWS) and NCEP centers with model guidance of suitable resolution for all areas where they have the responsibility of providing gridded forecast products. New features introduced in WAVEWATCH III, such as two-way nesting between grids and carving out selected areas of the computational domain, have allowed the operational model to increase spatial resolution and extend the global domain closer to the North Pole, while at the same time optimizing the computational cost.Aspectral partitioning algorithm has been implemented to separate individual sea states from the overall spectrum, thus providing additional products for multiple sea states. Field output data are now packed in version 2 of the gridded binary (GRIB2) format and apart from the standard mean wave parameters, they also include parameters of partitioned wave spectra. The partitioning is currently limited to three fields: the wind-wave component, and primary and secondary swells. The modeling system has been validated against data using a multiyear hindcast database as well as archived forecasts.Anew software tool developed by the U.S. Army Corps ofEngineers (USACE) is used to extend the analysis from overall error estimates to separate skill scores for wind seas and swells.
Forecasting and prediction of natural events, such as tropical and extra-tropical cyclones, inland flooding, and severe winter weather, provide critical guidance to emergency managers and decision-makers from the local to the national level, with the goal of minimizing both human and economic losses. This guidance is used to facilitate evacuation route planning, post-disaster response and resource deployment, and critical infrastructure protection and securing, and it must be available within a time window in which decision makers can take appropriate action. This latter element is that which induces the need for urgency in this area. In this paper, we outline the North Carolina Forecasting System (NCFS) for storm surge and waves for coastal North Carolina, which is threatened by tropical cyclones about once every three years. We initially used advanced cyberinfrastructure techniques (e. g., opportunistic grid computing) in an effort to provide timely guidance for storm surge and wave impacts. However, our experience has been that a distributed computing approach is not robust enough to consistently produce the real-time results that end users expect. As a result, our technical approach has shifted so that the reliable and timely delivery of forecast products has been guaranteed by provisioning dedicated computational resources as opposed to relying on opportunistic availability of external resources. Our experiences with this forecasting effort is discussed in this paper, with a focus on Hurricane Irene (2011) that impacted a substantial portion of the US east coast from North Carolina, up along the eastern seaboard, and into New England.
The reanalysis at National Centers for Environmental Prediction (NCEP) focuses on atmospheric states reports generated by a constant model and a constant data assimilation system. The datasets have been exchanged among national and international partners and used in several more reanalyses. The new data assimilation techniques have been introduced including three-dimensional variational data assimilation (3DVAR), 4DVAR, and ensembles of analyses such as ensemble Kalman filter (EnKF), which produce not only an ensemble mean analysis but also a measure of the uncertainty. The new climate forecast system reanalysis (CFSR) was executed to create initial states for the atmosphere, ocean, land, and sea ice that are consistent as possible with the next version of the climate forecast system (CFS) version 2, which is to be implemented operationally at NCEP in 2010. Several graphical plots were generated automatically at the end of each reanalyzed month and were displayed on the CFSR Web site in real time.
Weather forecasts are inherently uncertain, and meteorologists have information about weather forecast uncertainty that is not readily available to most forecast users. Yet effectively communicating forecast uncertainty to nonmeteorologists remains challenging. Improving forecast uncertainty communication requires research-based knowledge that can inform decisions on what uncertainty information to communicate, when, and how to do so. To help build such knowledge, this article explores the public’s perspectives on everyday weather forecast uncertainty and uncertainty information using results from a nationwide survey. By contributing to the fundamental understanding of laypeople’s views on forecast uncertainty, the findings can inform both uncertainty communication and related research.
The article uses empirical data from a nationwide survey of the U.S. public to investigate beliefs commonly held among meteorologists and to explore new topics. The results show that when given a deterministic temperature forecast, most respondents expected the temperature to fall within a range around the predicted value. In other words, most people inferred uncertainty into the deterministic forecast. People’s preferences for deterministic versus nondeterministic forecasts were examined in two situations; in both, a significant majority of respondents liked weather forecasts that expressed uncertainty, and many preferred such forecasts to single-valued forecasts. The article also discusses people’s confidence in different types of forecasts, their interpretations of the probability of precipitation forecasts, and their preferences for how forecast uncertainty is conveyed. Further empirical research is needed to study the article’s findings in other contexts and to continue exploring perception, interpretation, communication, and use of weather forecast uncertainty.
This paper investigates the effects of waves on storm surge, currents,
and inundation in the Outer Banks and Chesapeake Bay during Hurricane
Isabel in 2003 through detailed comparison between observed wind, wave,
surge, and inundation data and results from an integrated storm surge
modeling system, CH3D-SSMS. CH3D-SSMS, which includes coupled coastal
and basin-scale storm surge and wave models, successfully simulated
measured winds, waves, storm surge, currents, and inundation during
Isabel. Comprehensive modeling and data analysis revealed noticeable
effects of waves on storm surge, currents, and inundation. Among the
processes that represent wave effects, radiation stress (outside the
estuaries) and wave-induced stress (outside and inside the estuaries)
are more important than wave-induced bottom stress in affecting the
water level. Maximum surge was 3 m, while maximum wave height was 20 m
offshore and 2.5 m inside the Chesapeake Bay, where the maximum
wave-induced water level reached 1 m. Significant waves reached 3.5 m
and 16 s at Duck Pier, North Carolina, and 1.6 m and 5 s at Gloucester,
Virginia. At Duck, wave effects accounted for ˜36 cm or 20% of the
peak surge elevation of 1.71 m. Inside the Chesapeake Bay, wave effects
account for 5-10% of observed peak surge level. A two-layer flow is
found at Kitty Hawk, North Carolina, during the peak of storm surge
owing to the combined effects of wind and wave breaking. Higher surge
elevations result when the 3-D surge model, instead of the 2-D surge
model, is coupled with the 2-D wave model owing to its relatively lower
bottom friction. Wave heights obtained with 3- and 2-D surge models show
little difference.
A coupled system of wind, wind wave, and coastal circulation models has been implemented for southern Louisiana and Mississippi to simulate riverine flows, tides. wind waves. and hurricane storm surge in the region. The system combines the NOAA Hurricane Research Division Wind Analysis System (H*WIND) and the Interactive Objective Kinematic Analysis (IOKA) kinematic wind analyses, the Wave Model (WAM) offshore and Steady-State Irregular Wave (STWAVE) nearshore wind wave models, and the Advanced Circulation (ADCIRC) basin to channel-scale unstructured grid circulation model. The system emphasizes a high-resolution (down to 50 m) representation of the geometry. bathymetry, and topography nonlinear coupling of all processes including wind wave radiation stress-induced set up; and objective specification of frictional parameters based on land-cover databases and commonly used parameters. Riverine flows and tides are validated for no storm conditions, while winds, wind waves, hydrographs, and high water marks are validated for Hurricanes Katrina and Rita.
This article reviews the evolution, communication, and differing interpretations of the National Hurricane Center's "cone of uncertainty" hurricane forecast graphic. it concludes with a discussion of this graphic from the perspective of risk communication theory. The 2004 hurricane season, in which five named storms struck Florida, demonstrated that hurricane forecast graphics, despite admirable attempts by the forecast community to make user-friendly products, are still subject to misinterpretation by many members of the public. This exploratory analysis draws upon interviews with key government officials and media figures, archival research of Florida newspapers, analysis of 962 public comments on the National Hurricane Center's cone of uncertainty graphic, a separate multiagency study of 2004 hurricane behavior, and relevant risk communication literature, to identify several characteristics of this graphic that likely contribute to public misinterpretation. Forecast providers should consider more formal, rigorous pretesting of forecast graphics, using standard social science techniques, in order to minimize the probability of misinterpretation.
This paper describes the importance of wave-current interaction in an inlet-estuary system. The three-dimensional, fully coupled, Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system was applied in Willapa Bay (Washington State) from 22 to 29 October 1998 that included a large storm event. To represent the interaction between waves and currents, the vortex-force method was used. Model results were compared with water elevations, currents, and wave measurements obtained by the U.S. Army Corp of Engineers. In general, a good agreement between field data and computed results was achieved, although some discrepancies were also observed in regard to wave peak directions in the most upstream station. Several numerical experiments that considered different forcing terms were run in order to identify the effects of each wind, tide, and wave-current interaction process. Comparison of the horizontal momentum balances results identified that wave-breaking-induced acceleration is one of the leading terms in the inlet area. The enhancement of the apparent bed roughness caused by waves also affected the values and distribution of the bottom shear stress. The pressure gradient showed significant changes with respect to the pure tidal case. During storm conditions the momentum balance in the inlet shares the characteristics of tidal-dominated and wave-dominated surf zone environments. The changes in the momentum balance caused by waves were manifested both in water level and current variations. The most relevant effect on hydrodynamics was a wave-induced setup in the inner part of the estuary.
The results from a numerical modelling system are presented for wave prediction inside Lunenburg Bay. The Bay, typical of the coast in Atlantic Canada, is an environment where ocean swell enters only from selected directions; wind-sea dominates the wave spectrum from other directions, and shallow water physics are important. The modelling system consisted of wave models for both the present time (nowcasts) and forecasts using the Simulating Waves Nearshore (SWAN) model inside the Bay. Nowcasts (stationary computations of the wave field that ran every 30 minutes) were driven by real-time observations of the directional wave boundary conditions, winds and water levels. Forecasts (48 hourly non-stationary computations) were driven by boundary conditions from the WAVEWATCH III ocean wave model (implemented on a larger domain) and winds from the Global Environmental Multiscale (GEM) atmospheric model. The results were compared with wave observations inside the Bay and provided in real-time. Model performance was assessed for a storm event with 2.8 m significant wave heights that occurred in October 2007, by comparing nowcast predictions, forecast predictions and observations. The nowcasts provided the best correlation, R 2 = 0.75, with observations inside the Bay, since they were driven by observations made at the model boundary. The forecasts tended to underpredict the significant wave height and peak period, but overall the model results compared well with the data over a wide range of wind and wave conditions.
An automated storm surge forecasting system was created around AD-CIRC to predict the storm surge from tropical cyclones in real time as a storm approaches. This system was then applied to Lake Pontchartrain in Southern Louisiana as a case study in order to assist the US Army Corps of Engineers with planning decisions that must be made as storms approach and make landfall. Surge forecasts are generated following each tropical storm advisory update issued by the National Hurricane Center. The gen-eral procedure is to create an ensemble of five ADCIRC storm surge runs based on the consensus storm forecast from the National Hurricane Center and perturbations to this forecast. Winds and pressure fields are generated using a parametric wind model (based on the Holland wind model) that has been coded as an ADCIRC subroutine to maximize execution speed. Initial outputs are water level and wind speed time series plots along the southern shore of Lake Pontchartrain near critical infrastructure. Results will be presented based on the forecasts for historical storms, as well as a summary of the system's performance on the case study site during the 2007 hurricane season.
1] A coupled wave/flow model was used to simulate the currents in a coastal bay during the landfall of a hurricane with large waves. Extensive wave breaking along the shoreline and over a midbay shoal induced the development of a strong mean circulation in the bay, in combination with currents forced by wind, tide, and storm surge. The general circulation pattern consisted of inflows along the shoreline and over the shoal region that were driven by radiation stress gradients, and outflows due to mass balance of the wave-driven inflow that were observed in deeper channels. The predicted currents agreed with observations only when wave forcing was included in the circulation model. Wave-driven flows accounted for over 50% of the high flushing rates during the storm and induced strong horizontal velocity gradients over short ($200 m) length scales. (2008), Wave-driven circulation in a coastal bay during the landfall of a hurricane, J. Geophys. Res., 113, C05026, doi:10.1029/2007JC004500.
In 2017, Hurricanes Harvey, Irma, and Maria caused more than $200 billion dollars of damage in the United States, as well as the incalculable cost of the loss of life and mental trauma associated with these disasters (Sullivan 2017). In a changing climate, sea level rise and the potential for increasing tropical cyclone intensity can result in even more devastating damages (IPCC 2013; Knutson et al. 2010). Therefore, engineers, community planners, and coastal residents need accurate, timely, and accessible forecasting of storm processes and their impact on coastal communities to bolster national resilience and reduce risk to life and property during these events. However, along with uncertainties in understanding and modeling of storm processes, there are complex challenges associated with determining and meeting the needs of end users who rely on these forecasts for emergency management decisions.
To determine needed advancements in storm forecasting, the U.S. Coastal Research Program (USCRP) hosted a Storm Processes and Impacts workshop for coastal stakeholders 16-18 April 2018, in St. Petersburg, Florida. The attendees included local coastal managers, emergency managers, state and regional agencies, federal agency scientists and engineers, academics, and private industry scientists and engineers. Workshop objectives were to synthesize present capabilities for modeling storm processes and forecasting impacts and to prioritize advancements. In addition, the workshop provided an opportunity to bridge the apparent gap between the research of coastal scientists and engineers and the information being distributed publicly and to emergency managers before, during, and after storm events. Finally, plans for a large-scale, extreme-event field experiment, DUNEX (During Nearshore Event eXperiment), anticipated in 2020-2021, were presented to encourage continued engagement of coastal researchers across disciplines.
This paper represents a synthesis of the forecasting challenges, research needs, infrastructure improvements, and communication challenges presented and discussed during the workshop. Each section includes a table of prioritized challenges or needs based on the workshop participants’ feedback.
A previously developed research-grade (e.g. high-resolution) unstructured mesh of the northern Gulf of Mexico (named NGOM3) is optimized to produce a computationally efficient forecast-grade mesh for deployment in a real-time hurricane storm surge early warning system. The real-time mesh is developed from a mesh decimation scheme with focus on the coastal floodplain. The mesh decimation scheme reduces mesh nodes and elements from the research-grade mesh while preserving the representation of the bare-earth topography. The resulting real-time unstructured mesh (named NGOM-RT) contains 64% less mesh nodes than the research-grade mesh. Comparison of (ADCIRC + SWAN) simulated times-series and peak water levels to observations between the research-grade and real-time-grade meshes for Hurricanes Ivan (2004), Dennis (2005), Katrina (2005), and Isaac (2012) show virtually no difference. Model simulations with the NGOM-RT mesh are 1.5–2.0 times faster than using NGOM3 on the same number of compute cores.
Natural processes driving the dynamics of tidal inlets have been studied in length, however, as humaninfluence in the coastal environment persists, there is a need to comprehend how both natural andhuman-induced processes drive different aspects of tidal inlet morphological evolution. An effort tounderstand the combined effects of natural and anthropogenic-induced processes in a tidal inlet is pur-sued by studying Oregon Inlet, considered one of the most dynamic inlets in the Outer Banks of NorthCarolina, USA. The temporal and spatial scales of the anthropogenic processes driving the morpholog-ical evolution of this tidal inlet are studied by means of remotely sensed data and in-situ observationsgathered from 2005 until 2015. Effects of natural process that cannot be gathered from observations arestudied via a morphological model based on Delft3D. Evolutional trends include the cyclical response ofthe main channel of the inlet to dredging, a 13◦northward rotation of the main channel, and frequentsediment transport reversal in the southern shoulder. Simulations indicate a net sediment transport rateinto the inlet of 205,000 m3/yr. Tidal currents are responsible for 55% of such transport, while wavesaccount for the remaining 45%. After a 2-year non-dredging modeling scenario, sediments from the sub-aqueous spit form a detached shoal in the north side of the flood delta and the main channel remainsopen branching into two dominant channels. Observations and model results indicate that Oregon Inlethas been in a state of stable equilibrium in the past decade. Natural and human-induced processes con-tribute to such equilibrium. This study exemplifies the decadal behavior of a tidal inlet influenced bynatural processes, infrastructure, and dredging.
Significance
We present an approach to normalize hurricane damage, where damage is framed in terms of an equivalent area of total destruction. This has some advantages over customary normalization schemes, and we demonstrate that our record has reduced variance and correlates marginally better with wind speeds and pressure. That is, it allows us to better address climatic trends. We find that hurricanes are indeed becoming more damaging. The frequency of the very most damaging hurricanes has increased at a rate of 330% per century.
The first free-of-charge archive of Canada’s operational numerical weather predictions. The archive allows for individual spatial and temporal sub-setting of all data enhancing modeling in Canada and globally.
The Canadian Surface Prediction Archive (CaSPAr) is an archive of numerical weather predictions issued by Environment and Climate Change Canada. Amongst the products archived on a daily basis are five operational numerical weather forecasts, three operational analyses, and one reanalysis product. The products have an hourly to daily temporal resolution and 2.5 km to 50 km spatial resolution. To date the archive contains 301 TB of data while 185 GB of new data are added every night. The data is archived in CF-1.6 compliant NetCDF4 format. The archive is available online (https://caspar-data.ca) since June 2017 and allows users to precisely request data according to their needs, i.e. spatial cropping based on a standard shape or uploaded shapefile of the domain of interest, selection of forecast horizons, variables as well as issue dates. The degree of customization in CaSPAr is a unique feature relative to other publically accessible numerical weather prediction archives and it minimizes user download requirements and local processing time. We benchmark the processing time and required storage of such requests based on 216 test scenarios. We also demonstrate how CaSPAr data can be employed to analyze extreme rainfall events. CaSPAr provides access to data that is fundamental for evaluating numerical weather prediction models and demonstrating the improvement in products such as flood and energy demand forecasting systems.
The amount and extent of coastal flooding caused by hurricanes can be sensitive to the timing or speed of the storm. For storms moving parallel to the coast, the hazards can be stretched over a larger area. Hurricane Matthew was a powerful storm that impacted the southeastern U.S. during October 2016, moving mostly parallel to the coastline from Florida through North Carolina. In this study, three sources for atmospheric forcing are considered for a simulation of Matthew's water levels, which are validated against extensive observations, and then the storm's effects are explored on this long coastline. It is hypothesized that the spatial variability of Matthew's effects on total water levels is partly due to the surge interacting nonlinearly with tides. By changing the time of occurrence of the storm, differences in storm surge are observed in different regions due to the storm coinciding with other periods in the tidal cycles. These differences are found to be as large as 1 m and comparable to the tidal amplitude. A change in forward speed of the storm also should alter its associated flooding due to differences in the duration over which the storm impacts the coastal waters. With respect to the forward speed, the present study contributes to established results by considering the scenario of a shore-parallel hurricane. A faster storm caused an increase in peak water levels along the coast but a decrease in the overall volume of inundation. On the other hand, a slower storm pushed more water into the estuaries and bays and flooded a larger section of the coast. Implications for short-term forecasting and long-term design studies for storms moving parallel to long coastlines are discussed herein.
Satellite remote sensing shows two hot spots of high suspended sediment concentration during the passage of Hurricane Irene (2011) over Chesapeake Bay: the shallow shoals in the mid Bay and the area around the mouth of the estuary. A coupled ocean wave sediment transport model is used to investigate mechanisms driving sediment resuspension and transport during the storm. The model reproduces the observed spatial variations of suspended sediment concentration and surface wave heights in the estuary and shows that both wave- and current-induced shear stresses are important in stirring bottom sediment. In the mid-Bay region, large wave-induced shear stress causes sediment resuspension on the shallow shoals, while wind-driven currents advect the suspended sediment downstream. Around the mouth of the estuary, the combined action of large waves and strong outflows produces high suspended sediment concentration, resulting in the export of ~0.8 Mt of estuarine sediments to the shelf. The storm-induced sediment resuspension and export could be an important term in the sedimentary budget of an estuary.
Storm surge prediction models rely on an accurate representation of the wind conditions. In this paper, we examine the sensitivity of surge predictions to forecast uncertainties in the track and strength of a storm (storm strength is quantified by the power dissipation of the associated wind field). This analysis is performed using Hurricane Arthur (2014), a Category 2 hurricane, which made landfall along the North Carolina (NC) coast in early July 2014. Hindcast simulations of a coupled hydrodynamic-wave model are performed on a large unstructured mesh to analyze the surge impact of Arthur along the NC coastline. The effects of Arthur are best represented by a post-storm data assimilated wind product with parametric vortex winds providing a close approximation. Surge predictions driven by forecast advisories issued by the National Hurricane Center (NHC) during Arthur are analyzed. The storm track predictions from the NHC improve over time. However, successive advisories predict an unrealistic increase in the storm's strength. Due to these forecast errors, the global root mean square errors of the predicted wind speeds and water levels increase as the storm approaches landfall. The relative impacts of the track and strength errors on the surge predictions are assessed by replacing forecast storm parameters with the best known post-storm information about Arthur. In a “constant track” analysis, Arthur's post storm determined track is used in place of the track predictions of the different advisories but each advisory retains its size and intensity predictions. In a “constant storm strength” analysis, forecast wind and pressure parameters are replaced by corresponding parameters extracted from the post storm analysis while each advisory retains its forecast storm track. We observe a strong correlation between the forecast errors and the wind speed predictions. However, the correlation between these errors and the forecast water levels is weak signifying a non-linear response of the shallow coastal waters to meteorological forcing.
Storm surge and overland flooding can be predicted with computational models at high levels of resolution. To improve efficiency in forecasting applications, surge models often use atmospheric forcing from parametric vortex models, which represent the surface pressures and wind fields with a few storm parameters. The future of storm surge prediction could involve real-time coupling of surge and full-physics atmospheric models; thus, their accuracies must be understood in a real hurricane scenario. The authors compare predictions from a parametric vortex model (using forecast tracks from the National Hurricane Center) and a full-physics coupled atmosphere-wave-ocean model during Hurricane Isaac (2012). The predictions are then applied within a tightly coupled, wave and surge modeling system describing the northern Gulf of Mexico and the floodplains of southwest Louisiana. It is shown that, in a hindcast scenario, a parametric vortex model can outperform a data-assimilated wind product, and given reasonable forecast advisories, a parametric vortex model gives reasonable surge forecasts. However, forecasts using a full-physics coupled model outperformed the forecast advisories and improved surge forecasts. Both approaches are valuable for forecasting the coastal impacts associated with tropical cyclones.
Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.
Weather-related research often requires synthesizing vast amounts of data that need archival solutions that are both economical and viable during and past the lifetime of the project. Public cloud computing services (e.g., from Amazon, Microsoft, or Google) or private clouds managed by research institutions are providing object data storage systems potentially appropriate for long-term archives of such large geophysical data sets. We illustrate the use of a private cloud object store developed by the Center for High Performance Computing (CHPC) at the University of Utah. Since early 2015, we have been archiving thousands of two-dimensional gridded fields (each one containing over 1.9 million values over the contiguous United States) from the High-Resolution Rapid Refresh (HRRR) data assimilation and forecast modeling system. The archive is being used for retrospective analyses of meteorological conditions during high-impact weather events, assessing the accuracy of the HRRR forecasts, and providing initial and boundary conditions for research simulations. The archive is accessible interactively and through automated download procedures for researchers at other institutions that can be tailored by the user to extract individual two-dimensional grids from within the highly compressed files. Characteristics of the CHPC object storage system are summarized relative to network file system storage or tape storage solutions. The CHPC storage system is proving to be a scalable, reliable, extensible, affordable, and usable archive solution for our research.
Hurricane Sandy was the largest storm on historical record in the Atlantic Ocean basin with extensive coastal damage caused by large waves and high storm surge. In this study, three different spatially-varying surface wind and atmospheric pressure fields that are used for forecasting or hindcasting hurricane waves on the continental shelf are investigated. These wind fields include two 2D parametric wind models (Holland model, H80; Generalized Asymmetric Holland Model, GAHM), and a 3D atmospheric model with data assimilation (WeatherFlow Regional Atmospheric Modelling System, WRAMS). These wind fields are used to drive wave hindcasts using coupled Delft3D-SWAN hydrodynamic and ocean wave models on a regional grid, and the bulk wave statistics and the directional wave spectra are compared to observations at offshore wave buoys to investigate the impact of differences between the complex wind fields on predictions of the sea surface evolution.
The numerical wave model SWAN (Simulating WAves Nearshore) and historical wave buoy observations were used to investigate the response of surface wave fields to tropical cyclone (TC) wind forcing on the Australian North West Shelf (NWS). Analysis of historical wave data during TC events at a key location on the NWS showed that an average of 1.7 large TCs impacted the region each year, albeit with high variability in TC track, intensity and size, and also in the surface wave field response. An accurately modelled TC wind field resulted in a good prediction of the observed extreme wave conditions by SWAN. Results showed that the presence of the background winds during a TC and a long TC lifetime with large variations in translation speed can provide additional energy input. This potentially enhances the generated swell waves and increases the spatial extent of the TC generated surface wave fields. For the TC translation speeds in this study, a positive relationship between TC translation speed and the resulting maximum significant wave height and wave field asymmetry was observed. Bottom friction across the wide NWS limited the amount of wave energy reaching the coastal region; consistently reducing wave energy in depths below 50 m, and in the case of the most extreme conditions, in depths up to 100 m that comprise much of the shelf. Nevertheless, whitecapping was still the dominant dissipation mechanism on the broader shelf region. Shelf-scale refraction had little effect on the amount of wave energy reaching the nearshore zone; however, refraction locally enhanced or reduced wave energy depending on the orientation of the isobaths with respect to the dominant wave direction during the TC.
Large estuaries are influenced by winds over adjacent coastal ocean and land areas causing significant spatial variations in water levels, currents and surface waves. In this study we apply a numerical model to simulate hydrodynamics and waves in the Albemarle-Pamlico Estuarine System, a large and shallow back-barrier basin in eastern North Carolina, over a one-month study period (September, 2008) with observations from several storm wind events of differing time scales and directions. Model performance is evaluated for a spatially varying wind field from the North American Regional Reanalysis (NARR) dataset in comparison to spatially uniform forcing from wind observations at offshore, coastal and land-based sites across the region. A spatially uniform wind field from offshore winds observations results in statistically better hydrodynamic simulations of water levels (R = 0.88) in the estuaries than NARR (R = 0.48) after comparison with measurements and indicates the importance of strong marine winds over most of the estuary surface area.
Wave and current measurements from a cross-shore array of nearshore sensors in Duck, NC, are used to elucidate the balance of alongshore momentum under energetic wave conditions with wide surf zones, generated by passing hurricanes that are close to and far from to the coast. The observations indicate that a distant storm (Hurricane Bill, 2009) with large waves has low variability in directional wave characteristics resulting in alongshore currents that are driven mainly by the changes in wave energy. A storm close to the coast (Hurricane Earl, 2010), with strong local wind stress and combined sea and swell components in wave energy spectra, has high variability in wave direction and wave period that influence wave breaking and nearshore circulation as the storm passes. During both large wave events, the horizontal current shear is strong and radiation stress gradients, bottom stress, wind stress, horizontal mixing, and cross-shore advection contribute to alongshore momentum at different spatial locations across the nearshore region. Horizontal mixing during Hurricane Earl, estimated from rotational velocities, was particularly strong suggesting that intense eddies were generated by the high horizontal shear from opposing wind-driven and wave-driven currents. The results provide insight into the cross-shore distribution of the alongshore current and the connection between flows inside and outside the surf zone during major storms, indicating that the current shear and mixing at the interface between the surf zone and shallow inner shelf is strongly dependent on the distance from the storm center to the coast.
Uncertainty represented in visualizations is often ignored or
misunderstood by the non-expert user. The National Hurricane
Center displays hurricane forecasts using a track forecast cone,
depicting the expected track of the storm and the uncertainty in
the forecast. Our goal was to test whether different graphical
displays of a hurricane forecast containing uncertainty would
influence a decision about storm characteristics. Participants
viewed one of five different visualization types. Three varied
the currently used forecast cone, one presented a track with
no uncertainty, and one presented an ensemble of multiple
possible hurricane tracks. Results show that individuals make
different decisions using uncertainty visualizations with different
visual properties, demonstrating that basic visual properties
must be considered in visualization design and communication.
Best tracks are National Hurricane Center (NHC) poststorm analyses of the intensity, central pressure, position, and size of Atlantic and eastern North Pacific basin tropical and subtropical cyclones. This paper estimates the uncertainty (average error) for Atlantic basin best track parameters through a survey of the NHC Hurricane Specialists who maintain and update the Atlantic hurricane database. A comparison is then made with a survey conducted over a decade ago to qualitatively assess changes in the uncertainties. Finally, the implications of the uncertainty estimates for NHC analysis and forecast products as well as for the prediction goals of the Hurricane Forecast Improvement Program are discussed.
Tropical cyclones deliver intense winds that can generate some of the most severe surface wave and storm surge conditions in the coastal ocean. Hurricane Irene (2011) crossed a large, shallow lagoonal estuarine system in North Carolina, causing flooding and erosion of the adjacent low-lying coastal plain and barrier islands. This event provided an opportunity to improve understanding of the estuarine response to strong and rotating wind forcing. Observations from acoustic sensors in subestuaries and water-level elevation measurements from a network of pressure sensors across the system are presented. Data are examined with two modeling techniques: (1) a simple numerical approach using a momentum balance between the wind stress, flow acceleration, pressure gradient, and bottom friction that gives insight into temporal variability in water levels through the passage of the storm; and (2) an advanced hydrodynamic model based on the full shallow water fluid momentum equations, coupled to a spectral surface wave model that accounts for the spatially varying bathymetry and wind field. The results indicate that both wind-generated surface waves and the wind-driven storm surge are important contributors to the total water surface elevations that induce flooding along estuarine shorelines under strong hurricane forcing.
The Real Time Ocean Forecast System (RTOFS) for the North Atlantic is an ocean forecast system based on the HYbrid Coordinate Ocean Model (HYCOM). HYCOM is the result of a collaborative effort between the University of Miami, the Naval Research Laboratory (NRL), and the Los Alamos National Laboratory (LANL), as part of a multi-institutional HYCOM Consortium for Data-Assimilative Ocean Modeling funded by the National Ocean Partnership Program (NOPP) to develop and evaluate a data-assimilative hybrid isopycnal-sigma-pressure (generalized) coordinate ocean model. This paper describes the RTOFS-Atlantic, an operational real time ocean nowcast/forecast system for the North Atlantic running daily at National Centers for Environmental Prediction (NCEP).
The Coast Survey Development Laboratory (CSDL) of the National Ocean Service (NOS) and the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) have collaborated to establish an Extratropical Surge and Tide Operational Forecast System (ESTOFS) for the Western North Atlantic basin. The hydrodynamic model employed for ESTOFS is the ADvanced CIRCulation (ADCIRC) finite element model. The ESTOFS will be implemented operationally by NCEP Central Operations (NCO) to provide forecasts of surge with tides, astronomical tides, and sub-tidal water levels (the isolated surge) throughout the domain. The ESTOFS combines the surge with tides and utilizes unstructured grids, which can provide higher resolution at the coast. The ESTOFS is also designed to provide the surge with tides to WAVEWATCHIII (WW3) for coupling waves with coastal water levels. Therefore, ESTOFS set-up is designed to follow WW3: it uses the same Global Forecast System (GFS) surface forcing and has the same forecast cycle and length, and will run concurrently at NCO. The model results are compared with observations at 62 stations using NOS' standard skill assessment software. The skill assessment focuses on the performance of the model in simulating water levels in two model run scenarios: the hindcast, and the semi-operational forecast. As for the results of skill assessment, the model's water level forecasts are of sufficient accuracy for operational implementation.
Acting on the perception that they perform better for longer, most property owners in the United States choose hard engineered structures, such as bulkheads or riprap revetments, to protect estuarine shorelines from erosion. Less intrusive alternatives, specifically marsh plantings with and without sills, have the potential to better sustain marsh habitat and support its ecosystem services, yet their shoreline protection capabilities during storms have not been evaluated. In this study, the performances of alternative shoreline protection approaches during Hurricane Irene (Category 1 storm) were compared by 1) classifying resultant damage to shorelines with different types of shoreline protection in three NC coastal regions after Irene; and 2) quantifying shoreline erosion at marshes with and without sills in one NC region by using repeated measurements of marsh surface elevation and marsh vegetation stem density before and after Irene. In the central Outer Banks, NC, where the strongest sustained winds blew across the longest fetch; Irene damaged 76% of bulkheads surveyed, while no damage to other shoreline protection options was detected. Across marsh sites within 25 km of its landfall, Hurricane Irene had no effect on marsh surface elevations behind sills or along marsh shorelines without sills. Although Irene temporarily reduced marsh vegetation density at sites with and without sills, vegetation recovered to pre-hurricane levels within a year. Storm responses suggest that marshes with and without sills are more durable and may protect shorelines from erosion better than the bulkheads in a Category 1 storm. This study is the first to provide data on the shoreline protection capabilities of marshes with and without sills relative to bulkheads during a substantial storm event, and to articulate a research framework to assist in the development of comprehensive policies for climate change adaptation and sustainable management of estuarine shorelines and resources in U.S. and globally.
Due to the devastating effects of recent hurricanes in the Gulf of Mexico (e.g., Katrina, Rita, Ike and Gustav), the development of a high-resolution, real-time, total water level prototype system has been accelerated. The fully coupled model system that includes hydrology is an extension of the ADCIRC Surge Guidance System (ASGS), and will henceforth be referred to as ASGS-STORM (Scalable, Terrestrial, Ocean, River, Meteorological) to emphasize the major processes that are represented by the system.The ASGS-STORM system incorporates tides, waves, winds, rivers and surge to produce a total water level, which provides a holistic representation of coastal flooding. ASGS-STORM was rigorously tested during Hurricane Irene, which made landfall in late August 2011 in North Carolina. All results from ASGS-STORM for the advisories were produced in real-time, forced by forecast wind and pressure fields computed using a parametric tropical cyclone model, and made available via the web. Herein, a skill assessment, analyzing wind speed and direction, significant wave heights, and total water levels, is used to evaluate ASGS-STORM's performance during Irene for three advisories and the best track from the National Hurricane Center (NHC). ASGS-STORM showed slight over-prediction for two advisories (Advisory 23 and 25) due to the over-estimation of the storm intensity. However, ASGS-STORM shows notable skill in capturing total water levels, wind speed and direction, and significant wave heights in North Carolina when utilizing Advisory 28, which had a slight shift in the track but provided a more accurate estimation of the storm intensity, along with the best track from the NHC. Results from ASGS-STORM have shown that as the forecast of the advisories improves, so does the accuracy of the models used in the study; therefore, accurate input from the weather forecast is a necessary, but not sufficient, condition to ensure the accuracy of the guidance provided by the system. While Irene provided a real-time test of the viability of a total water level system, the relatively insignificant freshwater discharges precludes definitive conclusions about the role of freshwater discharges on total water levels in estuarine zones. Now that the system has been developed, on-going work will examine storms (e.g., Floyd) for which the freshwater discharge played a more meaningful role.
Despite recent advances in numerical weather prediction, major errors in short-range forecasts still occur. To gain insight into the origin and nature of model forecast errors, error frequencies and magnitudes need to be documented for different models and different regions. This study examines errors in sea level pressure for four operational forecast models at observation sites along the east and west coasts of the United States for three 5-month cold seasons. Considering several metrics of forecast accuracy, the European Centre for Medium-Range Weather Forecasts (ECMWF) model outperformed the other models, while the North American Mesoscale (NAM) model was least skillful. Sea level pressure errors on the West Coast are greater than those on the East Coast. The operational switch from the Eta to the Weather Research and Forecasting Nonhydrostatic Mesoscale Model (WRF-NMM) at the National Centers for Environmental Prediction (NCEP) did not improve forecasts of sea level pressure. The results also suggest that the accuracy of the Canadian Meteorological Centre's Global Environmental Mesoscale model (CMC-GEM) improved between the first and second cold seasons, that the ECMWF experienced improvement on both coasts during the 3-yr period, and that the NCEP Global Forecast System (GFS) improved during the third cold season on the West Coast.
A third-generation numerical wave model to compute random, short-crested waves in coastal regions with shallow water and ambient currents (Simulating Waves Nearshore (SWAN)) has been developed, implemented, and validated. The model is based on a Eulerian formulation of the discrete spectral balance of action density that accounts for refractive propagation over arbitrary bathymetry and current fields. It is driven by boundary conditions and local winds. As in other third-generation wave models, the processes of wind generation, whitecapping, quadruplet wave-wave interactions, and bottom dissipation are represented explicitly. In SWAN, triad wave-wave interactions and depth-induced wave breaking are added. In contrast to other third-generation wave models, the numerical propagation scheme is implicit, which implies that the computations are more economic in shallow water. The model results agree well with analytical solutions, laboratory observations, and (generalized) field observations.
This study evaluates the performance of the National Centers for Environmental Prediction Global Forecast System (GFS) against observations made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program at the southern Great Plains site for the years 2001-04. The spatial and temporal scales of the observations are examined to search for an optimum approach for comparing grid-mean model forecasts with single-point observations. A single-column model (SCM) based upon the GFS was also used to aid in understanding certain forecast errors. The investigation is focused on the surface energy fluxes and clouds. Results show that the overall performance of the GFS model has been improving, although certain forecast errors remain. The model overestimated the daily maximum latent heat flux by 76 W m-2 and the daily maximum surface downward solar flux by 44 W m-2, and underestimated the daily maximum sensible heat flux by 44 W m-2. The model's surface energy balance was reached by a cancellation of errors. For clouds, the GFS was able to capture the observed evolutions of cloud systems during major synoptic events. However, on average, the model largely underestimated cloud fraction in the lower and midtroposphere, especially for daytime nonprecipitating low clouds because shallow convection in the GFS does not produce clouds. Analyses of surface radiative fluxes revealed that the diurnal cycle of the model's surface downward longwave flux (SDLW) was not in phase with that of the ARM-observed SDLW. SCM experiments showed that this error was caused by an inaccurate scaling factor, which was a function of ground skin temperature and was used to adjust the SDLW at each model time step to that computed by the model's longwave radiative transfer routine once every 3 h. A method has been proposed to correct this error in the operational forecast model. It was also noticed that the SDLW biases changed from mostly negative in 2003 to slightly positive in 2004. This change was traced back to errors in the near-surface air temperature. In addition, the SDLW simulated with the newly implemented Rapid Radiative Transfer Model longwave routine in the GFS is usually 5-10 W m-2 larger than that simulated with the previous routine. The forecasts of surface downward shortwave flux (SDSW) were relatively accurate under clear-sky conditions. The errors in SDSW were primarily caused by inaccurate forecasts of cloud properties. Results from this study can be used as guidance for the further development of the GFS.
A method is proposed for rapidly determining probabilistic maximum hurricane surge forecasts based on surge response functions, available meteorological information, and joint probability statistics. In using this method for Hurricane Ike, surge forecasts prior to landfall were computed in a matter of seconds. From a theoretical standpoint, surge response functions are scaling laws derived from high-resolution numerical simulations. Surge response functions allow rapid algebraic surge calculation while guaranteeing accuracy and detail by incorporating high-resolution computational results into their formulation. The Hurricane Ike example presented here shows that this method has the potential to improve evacuation planning and public early warning of hurricane flooding by providing rapid and accurate probabilistic projections of maximum surge.
Following the extreme flooding caused by Hurricane Katrina, the Federal Emergency Management Agency (FEMA) commissioned a study to update the Mississippi coastal flood hazard maps. The project included development and application of new methods incorporating the most recent advances in numerical modeling of storms and coastal hydrodynamics, analysis of the storm climatology, and flood hazard evaluation. This paper discusses the methods that were used and how they were applied to the coast of the State of Mississippi.
An observational network, dynamical models and data assimilation schemes are the three components of an ocean prediction system. Its configuration for a regional real-time forecasting system proceeds in three phases, based on previous knowledge and experience of the area. In the initial (exploratory) phase, identification of dominant scales (synoptic, mesoscale and submesoscale), processes and interactions is obtained. In the intermediate (dynamical) phase, a clear resolution of the important dynamics and events must be reflected in the nowcasts and forecasts. This is carried out via energy and vorticity analysis (EVA). The third phase is designed to validate the predictive capability of the forecasts. Both qualitative verification and quantitative skill are utilized. At each stage, high quality data sets are required. Observing System Simulation Experiments are essential to the development of the regional ocean prediction system. Initializations and updates are obtained by the fusion of multiple data streams, i.e., the melding of feature models, previous data driven simulations and observations. Nowcasts and forecasts are generated via sequential assimilation combining ship-acquired and sensed remote data. Nested models and nested observations are employed for adequate resolution. The approach is illustrated with recent real-time experiences at sea in the Iceland-Faeroe frontal region, the Straits of Sicily and the Eastern Mediterranean basin.
Computer modeling of sediment transport patterns is generally recognized as a valuable tool for understanding and predicting morphological developments. In practice, state-of-the-art computer models are one- or two-dimensional (depth-averaged) and have a limited ability to model many of the important three-dimensional flow phenomena found in nature. This paper presents the implementation and validation of sediment transport formulations within the proven DELFT3D three-dimensional (hydrostatic, free surface) flow solver. The paper briefly discusses the operation of the DELFT3D-FLOW module, presents the key features of the formulations used to model both suspended and bedload transport of noncohesive sediment, and describes the implemented morphological updating scheme. The modeling of the three-dimensional effects of waves is also discussed. Following the details of the implementation, the results of a number of validation studies are presented. The model is shown to perform well in several theoretical, laboratory, and real-life situations.
As the most costly US natural disaster in history, Hurricane Katrina fostered the IPET forensic study to better understand the event. All available observations from several hundred space-, land-, sea-, and aircraft-based measurement platforms were gathered and processed to a common framework for height, exposure, and averaging time, to produce a series of wind field snapshots at 3 h intervals to depict the wind structure of Katrina when in the Gulf of Mexico. The stepped-frequency microwave radiometer was calibrated against GPS sondes to establish the upper range of the instrument and then used to determine the wind field in the storm's core region in concert with airborne Doppler radar winds adjusted to the surface from near the top of the PBL (500 m). The SFMR data were used to develop a method to estimate surface winds from 3 km level reconnaissance aircraft observations, taking into consideration the observed azimuthal variation of the reduction factor. The “SFMR method” was used to adjust reconnaissance flight-level measurements to the surface in the core region when SFMR and Doppler winds were not available. A variety of coastal and inland mesonet data were employed, including portable towers deployed by Texas Tech University, University of Louisiana at Monroe, and the Florida Coastal Monitoring Program, as well as fixed mesonet stations from Louisiana State Universities Marine Consortium, University of Southern Mississippi, and Agricultural Networks from Louisiana, Mississippi, and Alabama, and the Coastal Estuarine Network of Alabama and Mississippi. Also included were land- (WSR-88D VAD and GBVTD, ASOS, Metar, LLWAS, HANDAR), space- (QuikScat, GOES cloud drift winds, WindSat), and marine- (GPS sondes, Buoys, C-MAN, ships) platforms. The wind fields serve as an analysis of record and were used to provide forcing for wave and storm surge models to produce hindcasts of water levels in the vicinity of flood control structures.