Coupled Ocean Atmosphere Wave Sediment Research Articles

Development of a daily coastal ocean model for Mississippi Sound and Bight

The Mississippi Sound and Bight is a complex coastal system with shallow estuarine waters that are highly vulnerable to the effects of climate change and anthropogenic influences. In order to further our understanding of the system and provide natural resource managers and decision-makers with science-based guidance, a pre-operational coastal ocean forecast system has been developed using the Coupled Ocean Atmosphere Wave Sediment Transport Modeling System (COAWST). The COAWST application for Mississippi Bight (msbCOAWST) can be run in hindcast mode, pre-operational near real-time mode, or forecast mode and relies on other operational models including the National Water Model (NWM) for river forcing, the High Resolution Rapid Refresh model (HRRR) for atmospheric forcing, and the Navy Coastal Ocean Model (NCOM) for open ocean boundary forcing. msbCOAWST is being validated using data from a variety of in situ measurements that quantify coastal processes, including tides and water quality parameters (i.e. temperature and salinity). The highest model skill is obtained for temperature followed by water levels and salinity. msbCOAWST has been used to provide guidance for quantifying how freshwater influences derived from river diversion operations impact water quality in estuarine waters. While the model is initially developed to study water quality and circulation in pre-operational near real-time and forecast modes, it is currently being extended to include waves, sediment transport, and biogeochemistry and also linked with habitat suitability models and ecological models in hindcast mode so as to comprehensively reveal consequential environmental concerns due to the onset and persistence of hypoxia, seasonal and storm-induced waves with their associated impacts on the region’s fisheries and shellfisheries.

Coastal CUBEnet: an integrated observation and modeling system for sustainable Northern Gulf of Mexico coastal areas

The University of Southern Mississippi has developed the coastal CUBEnet environment. Coastal CUBEnet is a high-resolution, coastal ocean sensor, modeling, and data sharing web-based network that provides the environmental intelligence needed to support the complex modeling of the interlinked processes in the northern Gulf of Mexico. With near-real time data delivery via a common infrastructure, CUBEnet uses state of the art sensors to provide a set of networked measurements systems, visualization tools, and model developments to gain an understanding of the Gulf of Mexico’s marine environments. CUBEnet is also a mechanism for improved human engagement with Gulf of Mexico resources and provides stake holders with the data needed to make informed coastal, environmental, and economic decisions. The Coastal CUBEnet’s data environment utilizes both stationary and uncrewed mobile systems and high-resolution distributed sensors to create a networked platform across the northern coastal Gulf of Mexico. CUBEnet’s modeling environment has developed an implementation of The Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) Model for the Mississippi Bight region that has been applied to investigate shore to shelf advective exchange processes, and their influence on coastal water quality conditions that support the region’s prolific marine ecosystem. CUBEnet’s modeling environment provides prototype modeling applications that are supported by real-time observations of key coastal environmental variables. CUBEnet’s Web accessible visualization tools provide parameter fields and vertical profiles from hydrodynamic models and field observations. Nowcasts and forecast results are available for the Eastern LA coastline, MS coastline, Mobile Bay, and the West coast of Florida.

Development and Evaluation of a Short-Term Ensemble Forecasting Model on Sea Surface Wind and Waves across the Bohai and Yellow Sea

In this study, an ensemble forecasting model for in situ wind speed and wave height was developed using the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This model utilized four bias correction algorithms—Model Output Statistics (MOS), Back Propagation Neural Network (BPNN), Long Short-Term Memory (LSTM) neural network, and Convolutional Neural Network (CNN)—to construct ensemble forecasts. The training data were derived from the COAWST simulations of one year and observations from three buoy stations (Laohutan, Zhifudao, and Lianyungang) in the Yellow Sea and Bohai Sea. After the optimization of the bias correction model training, the subsequent evaluations on the ensemble forecasts showed that the in situ forecasting accuracy of wind speed and wave height was significantly improved. Although there were some uncertainties on bias correction performance levels for individual algorithms, the uncertainties were greatly reduced by the ensemble forecasts. Depending on the dynamic weight assignment, the ensemble forecasts presented a stable performance even when the corrected forecasts by three algorithms had an obvious negative bias. Specifically, the ensemble forecasting bias was found with a mean reduction of about 96%~99% and 91%~95% for wind speed and wave height, and a reduction of about 91%~98% and 16%~54% during the period of Typhoon “Muifa”. For the four correction algorithms, the performance of bias correction was not directly related to the algorithm complexity. However, the strategies with more complex algorithms (i.e., CNN) were more conservative, and simple algorithms (i.e., MOS) might have induced unstable performance levels despite their lower bias in some cases.

Development of a Numerical Prediction Model for Marine Lower Atmospheric Ducts and Its Evaluation across the South China Sea

The Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model serves as the foundation for creating a forecast model to detect lower atmospheric ducts in this study. A set of prediction tests with different forecasting times focusing on the South China Sea domain was conducted to evaluate the short-term forecasting effectiveness of lower atmospheric ducts. The assessment of sounding observation data revealed that the prediction model performed well in predicting the characteristics of all types of ducts. The mean values of the forecasting errors were slightly lower than the reanalysis data but had lower levels of correlation coefficients. At an altitude of about 2000 m, the forecasted error of modified atmospheric refractivity reached peak values and then decreased gradually with increasing altitude. The accuracy of forecasted surface ducts was higher than that of elevated ducts. Noticeable land–sea differences were identified for the spatial distributions of duct characteristics, and the occurrence rates of both the surface and elevated ducts were high at sea. As for the differences among the forecasts of 24, 48, and 72 h ahead, the differences primarily occurred at altitude levels below 20 m and 500 m~1500 m, which are consistent with the differences in the duct height.

Total water levels along the South Atlantic Bight during three along-shelf propagating tropical cyclones: relative contributions of storm surge and wave runup

Abstract. Total water levels (TWLs), including the contribution of wind waves, associated with tropical cyclones (TCs) are among the most damaging hazards faced by coastal communities. TC-induced economic losses are expected to increase because of stronger TC intensity, sea level rise, and increased populations along the coasts. TC intensity, translation speed, and distance to the coast affect the magnitude and duration of increased TWLs and wind waves. Under climate change, the proportion of high-intensity TCs is projected to increase globally, whereas the variation pattern of TC translation speed also depends on the ocean basin and latitude. There is an urgent need to improve our understanding of the linkages between TC characteristics and TWL components. In the past few years, hurricanes Matthew (2016), Dorian (2019), and Isaias (2020) propagated over the South Atlantic Bight (SAB) with similar paths but resulted in different coastal impacts. We combined in situ observations and numerical simulations with the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to analyze the extreme TWLs under the three TCs. Model verification showed that the TWL components were well reproduced by the present model setup. Our results showed that the peak storm surge and the peak wave runup depended mainly on the TC intensity, the distance to the TC eye, and the TC heading direction. A decrease in TC translation speed primarily led to longer exceedance durations of TWLs, which may result in more severe economic losses. Wave-dependent water level components (i.e., wave setup and wave swash) were found to dominate the peak TWL within the near-TC field. Our results also showed that in specific conditions, the prestorm wave runup associated with the TC-induced swell may lead to TWLs higher than at the peak of the storm. This was the case along the SAB during Hurricane Isaias. Isaias's fast TC translation speed and the fact that its swell was not blocked by any islands were the main factors contributing to these peak TWLs ahead of the storm peak.

EFFECTS OF WAVE SKEWNESS AND ASYMMETRY ON THE EVOLUTION OF FIRE ISLAND, NEW YORK

Bedload transport of sediment by waves and currents is one of the key physical processes that affect the evolution of coasts, nearshore areas, and the engineering practices there. Wave skewness and asymmetry, both of which increase as waves shoal, result in a net bedload sediment flux over a wave cycle. The impacts of this mechanism on large-scale coastal and shoreline change are investigated in this study, using field observations and Coupled Ocean Atmosphere Wave Sediment Transport (COAWST), a hydrodynamic process-based numerical modeling system (Warner et al., 2010). The study site is Fire Island, New York, located at the Atlantic Coast of the USA, with a focus on the persistent shoreline shape, at the western half of this 50-km-long barrier island, that has been hypothesized to be linked to the sand deposits at the shoreface.

Numerical Simulation of the Flood and Inundation Caused by Typhoon Noru Downstream from the Vu Gia-Thu Bon River Basin

Typhoon Noru (2022) was a historic storm that caused significant damage to the central region of Vietnam. Typhoon Noru has caused strong winds and torrential rainfall in Da Nang, Quang Nam, and Quang Ngai. Quang Nam Province saw many trees and power lines fall, and many areas were flooded. The Da Nang government has reported the typhoon toppled many trees, blew the rooftops of three houses, damaged the walls of several schools, and caused a power outage at some 3200 substations. It resulted in widespread flooding in coastal areas and downstream from the Vu Gia-Thu Bon River river basin. This study evaluates the impact of Typhoon Noru. The results show that: (1) The numerical simulation was applied to re-analyze the offshore meteorological field with the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model as an input for 2D wave propagation and hydraulic models; (2) The study couples the 1D and 2D models in MIKE FLOOD to simulate the flood and inundation caused by Typhoon Noru in the study area. The calibration and validation results of the 1D hydraulic model, the 2D wave propagation model, and the 2D hydrodynamic model were reasonably good, with a Nash coefficient ranging from 0.84 to 0.96 and a percent bias (BIAS) of −0.9% to 7.5%. The results of the simulation showed that the flood and inundation caused by Typhoon Noru resulted in significant damage in two districts: Thang Binh in Quang Nam province and Hoa Vang in Da Nang province. The practical significance of these results is that they provide valuable support for warning systems and troubleshooting efforts related to the impact of typhoons.

The Effect of Surface Oil on Ocean Wind Stress

This study provides, to the best of our knowledge, the first detailed analysis of how surface oil modifies air–sea interactions in a two-way coupled model, i.e., the coupled–ocean–atmosphere–wave–sediment–transport (COAWST) model, modified to account for oil-related changes in air–sea fluxes. This study investigates the effects of oil on surface roughness, surface wind, surface and near-surface temperature differences, and boundary-layer stability and how those conditions ultimately affect surface stress. We first conducted twin-coupled modeling simulations with and without the influence of oil over the Deepwater Horizon (DWH) oil spill period (20 April to 5 May 2010) in the Gulf of Mexico. Then, we compared the results by using a modularized flux model with parameterizations selected to match those selected in the coupled model adapted to either ignore or account for different atmospheric/oceanic processes in calculating surface stress. When non-oil inputs to the bulk formula were treated as being unchanged by oil, the surface stress changes were always negative because of oil-related dampening of the surface roughness alone. However, the oil-related changes to 10 m wind speeds and boundary-layer stability were found to play a dominant role in surface stress changes relative to those due to the oil-related surface roughness changes, highlighting that most of the changes in surface stress were due to oil-related changes in wind speed and boundary-layer stability. Finally, the oil-related changes in surface stress due to the combined oil-related changes in surface roughness, surface wind, and boundary-layer stability were not large enough to have a major impact on the surface current and surface oil transport, indicating that the feedback from the surface oil to the surface oil movement itself is insignificant in forecasting surface oil transport unless the fractional oil coverage is much larger than the value found in this study.

Investigating the precipitation features of monsoon deep depressions over the Bay of Bengal using high‐resolution stand‐alone and coupled simulations

AbstractA comprehensive attempt has been made to simulate the characteristics of monsoon deep depressions (MDD) originating over the Bay of Bengal (BoB) basin, with special emphasis on their rainfall using a coupled ocean–atmospheric model, that is, the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model, and a stand‐alone atmospheric model, that is, the Weather Research and Forecasting (WRF) model, with a lead time of up to 72 hr. It is to be noted that COAWST employs WRF as its atmospheric component, while the Regional Ocean Modeling System (ROMS) is used as the oceanic component. It is found that though the tracks of the four MDDs considered have been reasonably simulated, the intensity was overestimated in both sets of simulations compared to India Meteorological Department (IMD) best estimates. Decomposition of the contributors to rain rate for the composite of the storms in the deep depression (DD) phase revealed that the moisture sources/sinks (Qm) are the major component in modulating the rain rate compared to the cloud sources/sinks. Further analysis of Qm suggested that vertical and horizontal advection of moisture forms the leading contributors to Qm. Validation against Modern Era Retrospective‐Analysis for Research and Analysis (MERRA) reanalysis showed that COAWST captured a more realistic evolution of Qm (specifically vertical advection) compared to its stand‐alone counterpart. Investigation of the composite storm energetics in a vortex‐following control volume showed a scarcity of bulk kinetic energy (volume‐integrated kinetic energy over the control volume) in the later hours of the DD phase in COAWST which led to the dissipation of the storm core, unlike in WRF, where a re‐intensification took place through condensational heating. It is inferred that in spite of the stand‐alone atmospheric model capturing the moisture incursion from the lateral boundaries in the lower levels significantly, the better representation of the vertical structure in COAWST led to more realistic simulations of the storms, increasing the skill in rainfall prediction.

The second-generation real-time ecological environment prediction system for the Guangdong–Hong Kong–Marco Greater Bay Area: Model setup, validation, improvements, and online visualization

With the rapidly growing population and socioeconomic development of the Guangdong–Hong Kong–Marco Greater Bay Area of China, inputs of diverse contaminants have rapidly increased. This poses threats to the water quality of the Pearl River Estuary (PRE) and adjacent seas. To provide valuable information to assist the governors, stakeholders, and decision-makers in tracking changes in environmental conditions, daily nowcasts and two-day forecasts from the ecological prediction system, namely the Coupled Great Bay Ecological Environmental Prediction System (CGEEPS), has been setup. These forecast systems have been built on the Coupled Ocean–Atmosphere–Wave–Sediment Transport modelling system. This comprises an atmospheric Weather Research Forecasting module and an oceanic Regional Ocean Modelling System module. Daily real-time nowcasts and 2-day forecasts of temperature, salinity, NO2 + NO3, chlorophyll, and pH are continuously available. Visualizations of the forecasts are available on a local website (http://www.gbaycarbontest.xyz:8008/). This paper describes the setup of the environmental forecasting system, evaluates model hindcast simulations from 2014 to 2018, and investigates downscaling and two-way coupling with the regional atmospheric model. The results shown that though CGEEPS lacks accuracy in predicting the absolute value for biological and biogeochemical environmental variables. It is quite informative to predict the spatio-temporal variability of ecological environmental changes associated with extreme weather events. Our study will benefit of developing real-time marine biogeochemical and ecosystem forecast tool for oceanic regions heavily impact by extreme weathers.

Effects of swell waves on the dynamics of the estuarine turbidity maximum in an idealized convergent partially mixed estuary

The dynamics of estuarine sediments plays a key role in the morphological evolution, water quality, and ecosystem health of estuaries. Estuarine turbidity maxima (ETMs) are ubiquitous in estuaries worldwide and have drawn enormous attention from researchers. Here, we use a coupled ocean–atmosphere–wave–sediment transport modeling system to examine the effects of swell waves on the location, extent, and suspended sediment concentration (SSC) of ETMs in a convergent partially mixed estuary. Our results reveal that swell waves influence the residual circulation, mixing, and bottom stress in the estuary. The wave–current interaction increases the bottom stress in the estuary but reduces mixing in the lower to middle reaches of the estuary, owing to the enhanced landward salt transport, and the increased stratification. The reduced mixing enhances the estuarine circulation in the middle reach of the estuary. These changes cause a landward shift of the primary ETM and an increase in the SSC in the lower estuary. Moreover, the Coriolis force changes the ETM distribution and influences the wave effects. Overall, the findings of this study further elucidate ETM dynamics in an estuary. • Swell wave advects more saline water in the estuary and increases stratification. • Wave-current interaction increases the bottom stress in the lower estuary. • Swell wave causes a landward shift of the primary estuarine turbidity maxima (ETM).

Multi-instrument observations of microseisms generated by typhoon Kalmaegi (2014) over the Northwestern Pacific

The typhoon-generated microseisms, originating from the complex energy coupling and transferring among the Atmosphere-Ocean-Solid Earth spheres, can be detected remotely by seismometers as the strongest ambient seismic noise. The lack of in situ observations during the passage of typhoons has hampered numerical modeling of wind fields and ocean waves, and limited our understanding of the generation mechanisms of microseisms associated with typhoons. Here we present a comprehensive investigation of microseisms generated by typhoon Kalmaegi (September 2014) based on multiple-instrument constraints from observations including terrestrial and ocean-bottom seismic stations as well as ocean buoys. To understand the generation mechanisms, we apply an improved frequency-domain beamforming method to seismic array data leading to successful location of double-frequency (DF) microseism source regions. For comparison, we calculate the typhoon-induced ocean waves and theoretical source regions of the DF microseisms using the coupled ocean–atmosphere–wave–sediment transport modeling system with validation by ocean buoy observations. Both observations and numerical modeling results reveal two different generation mechanisms for typhoon-induced DF microseisms during the lifespan of Kalmaegi. When over the Philippine Sea, the DF microseisms were generated mainly by opposing ocean waves from two distinct storms. After Kalmaegi entered the South China Sea, the DF microseisms were generated mainly by the fast-moving typhoon with source regions just trailing behind, with the minimum frequencies determined by the typhoon translation speed. DF microseisms generated in coastal source regions were not detected by ocean bottom seismometers, suggesting that DF microseisms might not effectively propagate across the ocean-basin seafloor covered by thick sediments, owing to severe seismic attenuation and spreading losses. This information is crucial for the use of DF microseisms for future tracking and monitoring of typhoons.

Investigation of Ocean Sub-Surface Processes in Tropical Cyclone Phailin Using a Coupled Modeling Framework: Sensitivity to Ocean Conditions

The present study is aimed to investigate sub-surface ocean processes and their contribution to the intensification of a tropical cyclone (TC) from a coupled-modeling perspective. The Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model was employed to simulate TC Phailin, which originated over the Bay of Bengal and made landfall on the eastern coast of India in October 2013. Three sub-surface ocean condition datasets—viz., (a) the European Centre for Medium-Range Weather Forecast (ECMWF) Ocean Reanalysis, (b) the Climate Forecast System Version 2 (CFSV2) Operational Analysis, and (c) the Hybrid Coordinate Ocean Model (HYCOM) Reanalysis datasets—were used for the initial and boundary conditions for the oceanic component of the coupled model in three different simulations of TC Phailin. All the simulations showed a delay in intensification compared to the observation, and ECMWF simulated the most intensified TC. CFSV2 simulated a deeper mixed layer (ML) and higher mixing, which hindered the intensification. Furthermore, higher entrainment of cold water in the ML led to cold water reaching the surface and, consequently, decreased sea surface temperature, which acted as negative feedback in the intensification of the storm in the cases of CFSV2 and HYCOM. ECMWF realistically simulated the interactions of the TC with a cold-core eddy before landfall. A sudden increase in ML heat content, the addition of heat in the ML due to entrainment, and the prevention of cold water reaching the surface were indicative of the breaking of the barrier layer (BL) in ECMWF, which was further corroborated by the spatial distribution of BL thickness in the simulation. This acted as positive feedback in the intensification of the TC. The findings of this study strongly suggest that not only the incorporation of physical oceanic sub-surface processes in the modeling of TCs but also the proper representation of prevailing mesoscale features and ocean sub-surface temperature, salinity, and current profiles in datasets is essential for realistic simulations of TCs.

Impacts of wave feedbacks and planetary boundary layer parameterization schemes on air-sea coupled simulations: A case study for Typhoon Maria in 2018

Typhoon Maria was a devastating super typhoon hitting China in 2018. We conducted five numerical experiments based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport model system to explore the sensitivity of typhoon track, intensity, structure, and oceanic response to the feedbacks of ocean surface waves (particular attention was paid to wave-induced sea surface roughness [SSR]), and different planetary boundary layer (PBL) parameterization schemes. The model results were in good agreement with observations. It was found that Typhoon Maria's intensity and structure, especially the distribution of air-sea interface heat flux and the shape of the typhoon centre, were highly sensitive to the feedbacks of waves, the choices of PBL and wave-induced SSR parameterization schemes. Previous model results based only on atmospheric models have shown that typhoon simulation accuracy is very sensitive to the parameterization scheme of PBL. In this study, it was revealed that the effect of wave feedbacks on typhoon simulation results could be comparable to that of using different PBL parameterization schemes. The wave feedbacks include the modification of the SSR and the additional cooling induced by wave-enhanced ocean mixing. From the sensitivity experiments, the former was the most dominant, and its main mechanism lies in the correction of the SSR to affect the exchange coefficients of momentum and heat fluxes at the air-sea interface and ultimately the typhoon simulation results. A systematic analysis of sea temperature response during typhoon was conducted, and the response showed small difference in different experiments. This suggests that the difference in typhoon intensity and structure among the experimental simulations is not significantly related to the difference in simulated sea surface temperature, but is most likely related to the difference in momentum and heat fluxes caused by wave feedbacks and the choices of PBL and wave-induced SSR parameterization schemes. The difference of significant wave height (SWH) in experiments with different wave-induced SSR parameterization schemes reached 10% (1.5 m). The typhoon-induced sea surface height (SSH) reached 2.4 m, and the difference of SSH caused by wave feedbacks, different PBL and wave-induced SSR parameterization schemes reached 12.5%, 12.5% and 8.3%, respectively. This study has significant implication for improving the simulation accuracy of typhoon track, intensity, structure, and disasters caused by typhoons.

Assessing the Impact of Wave–Current Interactions on Storm Surges and Waves during Cold Air Outbreaks in the Northern East China Sea

Storm surges and disastrous waves induced by cold air outbreaks, a type of severe weather system, often impact the coastal economic development. Using the Climate Forecast System Reanalysis wind product and the Coupled Ocean–Atmosphere–Wave–Sediment Transport model, we developed a coupled numerical model and applied it to examine the interaction between surface gravity waves and ocean currents during cold air outbreaks in two case studies in the northern East China Sea. The results revealed that wave–current interactions improved the simulation accuracy, especially the water level, as verified by tidal station measurements. We conducted sensitivity experiments to explore the spatiotemporal variation of the impact of wave–current interactions on storm surges and waves in the northern East China Sea, away from the coastline. The wave-induced surge (up to 0.4 m) and the wave-induced current (up to 0.5 m/s) were found to be related to the difference between wave direction and current direction. The significant wave height difference (up to 0.5 m) was sensitive to the storm surge nearshore and sensitive to the current field offshore, while the mean wave direction change (up to 40°) was more sensitive to the current field than to the storm surge. Additionally, the wave–current interaction regulated the momentum balance and wave action balance, respectively. By comparison, the momentum residuals of pressure gradient, Coriolis force, Coriolis–Stokes force, and bottom stress, which were pronounced in different areas, were modulated more significantly by the wave effect than other terms. The dominant mechanisms of wave–current interactions on waves included the current-induced modification of energy generation caused by wind input, the current-induced modification of energy dissipation caused by whitecapping, and the current-induced wave advection.

Assessment of hurricane generated loads on offshore wind farms; a closer look at most extreme historical hurricanes in New England

We simulated and assessed the environmental forces including wave and wind loads generated by the most extreme historical hurricanes in the US northeast within the proposed offshore/planned wind farms: Hurricane Carol in 1954, and 1938 New England hurricane. Offshore wind energy industry is on the verge of rapid growth off the US east coast. Development of wind energy projects in this area requires a comprehensive assessment of hurricane risks in planning and operation stages. In this study, we used an ocean modeling system (COAWST: Coupled Ocean Atmosphere Wave Sediment Transport) to better understand and characterize hurricane-generated loads within the planned wind farm sites offshore Rhode Island and Massachusetts. The COAWST model was first validated using observed data and then applied to hurricanes with return periods of around 500-year (recommended by IEC 61400-3-1). Hurricane Carol and 1938 hurricane were simulated using a parametric model which generated the peak wind speeds of 49 m/s and 45 m/s, spatially averaged over the area, that led to significant wave heights of 11.90 m and 9.80 m, respectively. .Spatial variability of the wind and wave loads within the proposed sites were assessed. Further, the effects of these variabilities on the structural response of a typical monopile were demonstrated using the OpenFAST Model. Results showed up to 60% spatial variability of hurricane loads in the leased areas. Results demonstrated the need of using advanced ocean modeling systems for planning and operation of wind farms as opposed to traditional statistical methods such as measure and correlate for site characterization.

Wave Effects on Sediment Transport and Entrapment in a Channel‐Shoal Estuary: The Pearl River Estuary in the Dry Winter Season

AbstractSediment dynamics have great effects on the morphology of estuaries and deltas. As riverine sediment input has decreased in many estuaries in recent years, the removal and dispersion of sediments by currents and waves inside estuaries has assumed a more dominant role; however, the overall effects of waves are less well understood. In this study, we used the Coupled Ocean Atmosphere Wave Sediment Transport system to model the effects of waves on sediment transport in China's Pearl River Estuary. The results indicate that the presence of waves increased the landward current and sediment transport at the bottom of the channel and the seaward fluxes of water and sediment at the West Shoal, which is the main shallow area that accepts riverine sediment. Relative to the case without waves, the effects of waves increased the estuary's total sediment export by 45% to 9.14 megatons in one typical year, which even exceeded the annual riverine load in the year. The dry winter season shows the highest wave effects on sediment budget, and the sediment export was increased by 86% to 2.59 megatons with waves when compared with that without waves. This increase export was mainly concentrated at the surface near the western shore. Moreover, the waves increased lateral sediment entrapment in the Southwest Shoal, which explains the local geomorphologic evolution in recent decades. This study is of implication for the study on sediment exchange between shoal and channel in estuaries and on the fates of riverine sediment from source to sink.

Analysis of Ashobaa tropical cyclone-induced waves in the Northern Indian Ocean using coupled atmosphere–wave modeling

The Tropical Cyclones play a significant role in the world natural disasters. At the time of the cyclones, the atmosphere and the ocean are constantly exchanging energy. In this study, spectral and statistical analyses of the waves affected by the Cyclone Ashobaa in the northern Indian Ocean were investigated. For this purpose, a Coupled Atmosphere–Wave model as a subsystem of COAWST (Coupled Ocean–Atmosphere–Wave–Sediment Transport) was employed. In this modeling system, the Weather Research and Forecasting model (WRF) and the Simulating Waves Near-Shore model (SWAN), were used. Four monitoring points were considered to analyze the waves in the northern Indian Ocean in the offshores of Mumbai, Karachi, Chabahar and Muscat. The results of wave simulation showed that, the wave height on the northeastern offshore of the Arabian Sea is higher than the wave height on the offshore of the Gulf of Oman. As a result, the east and northeast coasts of the Arabian Sea are mostly affected than the coasts of the Gulf of Oman by the Cyclone Ashobaa-induced storm surges and swells.

Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model

AbstractThe importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.

Development of a submerged aquatic vegetation growth model in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST v3.4) model

Abstract. The coupled biophysical interactions between submerged aquatic vegetation (SAV), hydrodynamics (currents and waves), sediment dynamics, and nutrient cycling have long been of interest in estuarine environments. Recent observational studies have addressed feedbacks between SAV meadows and their role in modifying current velocity, sedimentation, and nutrient cycling. To represent these dynamic processes in a numerical model, the presence of SAV and its effect on hydrodynamics (currents and waves) and sediment dynamics was incorporated into the open-source Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. In this study, we extend the COAWST modeling framework to account for dynamic changes of SAV and associated epiphyte biomass. Modeled SAV biomass is represented as a function of temperature, light, and nutrient availability. The modeled SAV community exchanges nutrients, detritus, dissolved inorganic carbon, and dissolved oxygen with the water-column biogeochemistry model. The dynamic simulation of SAV biomass allows the plants to both respond to and cause changes in the water column and sediment bed properties, hydrodynamics, and sediment transport (i.e., a two-way feedback). We demonstrate the behavior of these modeled processes through application to an idealized domain and then apply the model to a eutrophic harbor where SAV dieback is a result of anthropogenic nitrate loading and eutrophication. These cases demonstrate an advance in the deterministic modeling of coupled biophysical processes and will further our understanding of future ecosystem change.