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The localized scale of most fisheries management does not account for potential regional connectivity, particularly for fish species with prolonged planktonic larval durations (PLD). Although bonefish (Albula vulpes) inhabits shallow coastal habitats from juvenile through adult life stages, it is a strong candidate for population connectivity via larval dispersal with a PLD of 41–71 days. To address this knowledge gap, surface trajectories of particles (“virtual larvae”) released from 26 known and predicted spawning sites of bonefish around the Caribbean Sea, Florida, and Bahamas were simulated for 2009–2015 using a realistic ocean circulation hindcast model coupled with an online particle tracking simulator to study larval transport variations. At each site, 100 surface particles were released twice per month (at full and new moons) from October to April in each year and tracked for 53 days. We then estimated the likelihood that management regions would rely upon larval retention versus larval dispersal from other management zones. Overall, separately managed areas are likely to be connected via larval dispersal rather than entirely self-recruiting. Significant temporal differences in particle dispersal found for new and full moon phases, and between winter and spring, highlight that it is vital to resolve multiscale temporal and spatial variability in circulation transport when studying larval transport and connectivity. Results underscore the need to include the likelihood of population connectivity in fisheries management and conservation strategies, and to ensure that the ontogenetic habitat requirements of bonefish are properly managed at a regional scale.

Local governments in China regularly implement short-term emission control measures to improve air quality during important sporting events. As a condition for hosting the 2014 Youth Olympic Games (YOG), the Nanjing government agreed to temporarily and substantially improve air quality. Regression analysis, Spearman correlation analysis, χ2 test, and the contingent valuation method were used to explore the effects of robust, short-term air pollution control measures on risk perception, daily exposure to PM2.5, risk acceptance levels, and willingness to pay/accept (WTP/WTA) for reductions in air pollution for the benefit of reducing health risks. Postimplementation, the respondents' risk perception levels presented the following changes: during the YOG, the respondents perceived the lowest effects of haze pollution while after the YOG, they perceived the highest effects. The changes in risk acceptance levels showed the same tendency. Furthermore, after the YOG, the respondents asked for the most economic compensation, and their willingness to pay for risk reduction also reached the highest level. This study reveals the need to increase the public's understanding of the health risks of air pollution, protect those populations most exposed to high levels of PM2.5, and take more effective long-term measures to meet local residents' demands for improved air quality.

Gradual recovery of Chinese nuclear power industry and its increasingly important position in the world have created a need to understand how public attitudes towards nuclear power changed after the Fukushima nuclear accident in Japan (FNAJ). To address this need, we augment our previous work to include data from a new survey conducted three years after the FNAJ in the same study area. The results showed that three years after the FNAJ, factor knowledge continued to increase, whereas the other four perception factors acceptance, risk, benefit, and trust had recovered from their post-FNAJ changes to different degrees. The sensitive groups whose acceptance declined more after the FNAJ showed a greater increase as time passed. It was also found that median acceptable frequency for level 1 nuclear events (anomaly) showed little change from Survey 2 to Survey 3, while tolerance of more severe events (incidents and serious incidents) has decreased substantially. The overall recovery of public acceptance shown in our study was in line with the nuclear development trend of China. But more efforts still need to be made to improve nuclear safety and risk communication.

Right-side bias in both sea surface cooling and phytoplankton blooms is often observed in the wake of hurricanes in the Northern Hemisphere. This idealized hurricane modeling study uses a coupled biological-physical model to understand the underlying mechanisms behind hurricane-induced cooling and phytoplankton bloom asymmetry. Both a deep ocean case and a continental shelf sea case are considered and contrasted. Model analyses show that while right-side asymmetric mixing due to inertial oscillations and restratification from strong right-side recirculation cells contributes to bloom asymmetry in the open ocean, the well-mixed condition in the continental shelf sea inhibits formation of recirculation cells, and the convergence of water onto the shelf is a more important process for bloom asymmetry.

An autonomous underwater glider was deployed in March 2014 to sample the Gulf Stream and its adjacent shelf waters in the South Atlantic Bight, providing a new look at cross-shelf exchange associated with Gulf Stream dynamics. Observations collected over 4 weeks reveal significant cross-shelf exchange (up to 0.5 Sv) at the shoreward edge of the Gulf Stream, which was 2 orders of magnitude larger than estimates from long-term mean hydrographic conditions. Gulf Stream frontal eddies may have contributed to some of the largest fluxes of heat (0.5°C Sv) and salt (0.03 Sv g/kg) onto the shelf. We estimate that the largest upwelling event during the mission could have brought nitrate concentrations over 20 μM to within 125 m of the surface. This study demonstrates clear capabilities of autonomous underwater gliders for sampling in and near fast moving boundary currents to obtain unique and critical in situ observations effectively.

Satellite approaches for estimation of the partial pressure of CO2 (pCO2) and air-sea flux of CO2 in coastal regions offer the potential to reduce uncertainties in coastal carbon budgets and improve understanding of spatial and temporal patterns and the factors influencing them. We used satellite-derived products in combination with an extensive data set of ship-based observations to develop an unprecedented multi-year time-series of pCO2 and air-sea flux of CO2 in the northern Gulf of Mexico for the period 2006–2010. A regression tree algorithm was used to relate satellite-derived products for chlorophyll, sea surface temperature, and dissolved and detrital organic matter to ship observations of pCO2. The resulting relationship had an r2 of 0.827 and a prediction error of 31.7 μatm pCO2 (root mean-squared error of the relationship was 28.8 μatm). Using a wind speed and gas exchange relationship along with satellite winds, estimates of air-sea flux of CO2 were derived yielding an average annual flux over the period 2006–2010 of − 0.8 to − 1.5 (annual mean = − 1.1 ± 0.3) mol C m− 2 y− 1, where the negative value indicates net ocean uptake. The estimated total annual CO2 flux for the study region was − 4.3 + 1.1 Tg C y− 1. Relationships of satellite-derived pCO2 with salinity were consistent with shipboard observations and exhibited a concave relationship with low values at mid- and low salinities attributed to strong biological drawdown of CO2 in the high productivity river-mixing zone. The time-series of satellite-derived pCO2 was characterized by a seasonal pattern with values lower during winter and spring, low to intermediate values during fall, and higher and more variable values during summer. These findings were similar to simulations from a coupled physical-biogeochemical model. A seasonal pattern was also evident in the air-sea flux of CO2 with generally more negative fluxes (i.e., ocean uptake) during winter and spring, and positive fluxes during summer months with fall being a period of transition. Interannual variations in annual means of both air-sea flux of CO2 and DIN loading were significant, with higher DIN loading coinciding in some cases with more negative air-sea flux of CO2 (i.e., net ocean uptake). Spatial patterns of pCO2 reflected regional environmental forcing including effects of river discharge, wind forcing, and shelf-slope circulation. Our study also illustrates the utility of satellite extrapolation for highlighting areas that may contribute significantly to regional signals and for guiding prioritization of locations for acquiring further observations. The approach should be readily applicable to other regions given adequate availability of in situ observations for algorithm development.

Air-sea interactions have significant impacts on coastal convection and surface fluxes exchange. They are important for the spatial and vertical distributions of air pollutants that affect public health, particularly in densely populated coastal areas. To understand the impacts of air-sea interactions on coastal air quality predictions, sensitivity simulations with different atmosphere-ocean coupling are conducted in this work over southeastern U.S. in July 2010 using the Weather Research and Forecasting Model with Chemistry (WRF/Chem). The results show that comparing to WRF/Chem without air-sea interactions, WRF/Chem with a 1-D ocean mixed layer model (WRF/Chem-OML) and WRF/Chem coupled with a 3-D Regional Ocean Modeling System (WRF/Chem-ROMS) predict the domain averaged changes in the sea surface temperature of 0.06°C and 0.94°C, respectively for July average. The simulated differences in the surface concentrations of O3 and PM2.5 between WRF/Chem-ROMS and WRF/Chem can be as large as 17.3 ppb and 7.9 µg m–3, respectively, with the largest changes occurring not only along coast and remote ocean, but also over some inland areas. Extensive validations against observations show that WRF/Chem-ROMS improves the predictions of most cloud and radiative variables, and surface concentrations of some chemical species such as SO2, NO2, maximum 1-h and 8-h O3, SO42–, NH4+, NO3–, and PM10. This illustrates the benefits and needs of using coupled atmosphere-ocean model with advanced model representations of air-sea interactions for regional air quality modeling.

Commercial cooking has higher intensity and more severe instantaneous cooking pollution from volatile organic chemicals compared to home cooking, making health risk assessment of occupational exposure for chefs a priority. In this study, chefs from three cooking styles of kitchens, including steaming, frying, and grilling, were selected to investigate the external and internal exposures, health risks and effects of several typical aromatic hydrocarbons (benzene, toluene and naphthalene). Naphthalene was found to be the most concentrated contaminant in air samples among the different kitchens, while benzene had the lowest concentration. The concentration of toluene in frying kitchens was significantly higher than that in steaming kitchens. Air concentrations of toluene in frying kitchens, as well as benzene concentrations in grilling kitchens exceeded the standard level according to indoor air quality standard (GB/T18883-2002). Regarding the metabolites of pollutants in urine, the content of S-benzylmercapturic acids (S-BMA) for frying chefs was significantly higher than that for other cooking styles of chefs, which was consistent with the relatively higher air concentrations of toluene. There was a good correlation between internal and external exposure of the pollutants. The level of oxidative stress was influenced by 2-hydroxynaphthalene (2-OHN) and S-BMA, indicating the potential health risks of these occupational exposed chefs. This study indicates the need to improve the monitoring of typical aromatic hydrocarbons, as well as to investigate their potential health effects in large-scale groups, and improve the ventilation in kitchens.

The intensity, frequency, and duration of heat waves are expected to increase with climate change. In this study, we found a significant difference of public perceived effects of heat waves and trust in government among urban, suburban, and rural districts. Rural residents had a significant higher effect perception than urbanites and also showed stronger willingness to have medical insurance or regular physical examinations. Meanwhile, suburban residents had the lowest trust perception in government among these three districts, which may be due to suburban districts' unique social structure and complex social issues. Besides, we assessed the relationship between the factor effect and demographic variables. The results showed that urban respondents' effect perception was significantly related to heat wave experiences. Suburban respondents' effect perception was significantly related to age, income, and heat wave experiences. And rural respondents' effect perception was significantly related to income and chronic diseases. Based on our results, much more attention needs to be paid to rural districts. The government should strengthen infrastructure construction such as cooling centers, improve emergency response plans and mechanisms, and increase reserves of emergency supplies in rural districts. Also, targeted risk communication is of the equal importance to aid the policy-makers improving the relationship with the public and regaining the public's trust and support.

A high-resolution, unstructured Simulating WAves Nearshore (SWAN) model with a resolution of 200 m within 20 km of the coast was developed to provide a reliable setting for a long-term wave energy characterization of the Gulf of Mexico, Puerto Rico, and the U.S. Virgin Islands. A thorough model parameter sensitivity analysis, as well as a calibration process for selecting the whitecapping dissipation formulation, were conducted. Sensitivity analyses for the simulation timestep and number of iterations highlighted the less-studied interplay between these parameters in SWAN, which can substantially affect simulation accuracy and cost and is vital for the next step long-term simulation of the wave energy resources. For the present study, a 3 min timestep and three iterations are optimum. The “Garden Sprinkling” effect and the cut-off frequency were also investigated. Using 36 directional bins and a larger cut-off frequency (1.0 Hz) enable the best agreement between the model simulation and the in situ wave observations. This subsequently leads to improved model skill and performance in resolving the observed International Electrotechnical Commission (IEC) wave energy resource parameters that are highly non-linear functions of wave spectral moments.

Nutrients are typically the most important determinant of the productivity of marine ecosystems. Hence, nutrients have been an essential variable of ocean observations in the modern oceanography era. Understanding of marine ecosystems and biogeochemistry, however, is largely limited by the spatiotemporal coverage of nutrient data. Herein, we developed a novel algorithm based on a large observational dataset of nutrients and their relationship with water masses indexed by temperature and salinity in the South China Sea (SCS). The algorithm yielded errors of ≤ 1.3, ≤ 0.10 and ≤ 3.5 μmol L−1 for NO3– + NO2– (N + N), phosphate and silicate, respectively. It is then applied to reconstruct nutrient concentrations primarily using temperature and salinity data archived in the World Ocean Database and Argo database during 1940–2018. It increases the nutrient data to ~ 5 million, by ca. three orders of magnitude compared to direct measurements in the SCS. This allows for a full examination of the seasonal climatology of nutrients in the SCS. In summer, in the upper 200 m, nutrient concentrations in the northwest and southernmost SCS are higher than in the rest of the SCS. An overall reversed pattern is revealed in winter, when higher nutrient concentrations are found in the central basin rather than basin margins. The Kuroshio intrusion and the vertical displacement of the nutricline, driven by upwelling/downwelling induced by horizontal convergences/divergences at both meso- and basin scales, determine the spatial and seasonal variation of nutrients. Seasonally, the Kuroshio intrusion and vertical displacements of the nutricline tend to offset the spatial variation of nutrient concentrations in spring, while they show an additive effect in the fall.

Many fundamental questions in marine ecology require an understanding of larval dispersal and connectivity, yet direct observations of larval trajectories are difficult or impossible to obtain. Although biophysical models provide an alternative approach, in the deep sea, essential biological parameters for these models have seldom been measured empirically. In this study, we used a biophysical model to explore the role of behaviorally mediated migration from two methane seep sites in the Gulf of Mexico on potential larval dispersal patterns and population connectivity of the deep-sea mussel “ Bathymodiolus” childressi , a species for which some biological information is available. Three possible larval dispersal strategies were evaluated for larvae with a Planktonic Larval Duration (PLD) of 395 days: (1) demersal drift, (2) dispersal near the surface early in larval life followed by an extended demersal period before settlement, and (3) dispersal near the surface until just before settlement. Upward swimming speeds varied in the model based on the best data available. Average dispersal distances for simulated larvae varied between 16 km and 1488 km. Dispersal in the upper water column resulted in the greatest dispersal distance (1173 km ± 2.00), followed by mixed dispersal depth (921 km ± 2.00). Larvae originating in the Gulf of Mexico can potentially seed most known seep metapopulations on the Atlantic continental margin, whereas larvae drifting demersally cannot (237 km ± 1.43). Depth of dispersal is therefore shown to be a critical parameter for models of deep-sea connectivity.

Hydrokinetic turbines harnessing energy from ocean currents represent a potential low carbon electricity source. This study provides a detailed techno-economic assessment of ocean turbines operating in the Gulf Stream off the North Carolina coast. Using hindcast data from a high-resolution ocean circulation model in conjunction with the US Department of Energy's reference model 4 (RM4) for ocean turbines, we examine resource quality and apply portfolio optimization to identify the best candidate sites for ocean turbine deployment. We find that the lowest average levelized cost of electricity (LCOE) from a single site can reach 400 $/MWh. By optimally selecting geographically dispersed sites and taking advantage of economies of scale, the variations in total energy output can be reduced by an order of magnitude while keeping the LCOE below 300 $/MWh. Power take-off and transmission infrastructure are the largest cost drivers, and variation in resource quality can have a significant influence on the project LCOE. While this study focuses on a limited spatial domain, it provides a framework to assess the techno-economic feasibility of ocean current energy in other western boundary currents.

Based on long-term realistic ocean circulation hindcast for in the Bohai, Yellow, and East China Seas, 45 years (1961–2005) of sea surface salinity data were analyzed using Self-Organizing Maps (SOM) to have a better understanding of the Changjiang Diluted Water (CDW) variation. Three spatial patterns were revealed by the SOM: normal, transition, and extension. The normal pattern mainly occurs from December to May while the CDW hugs China's east coast closely and flows southward. The extension pattern is dominant from June to October when the CDW extends northwestward toward Jeju Island in an omega shape. The transition pattern prevails for the rest of the year. Pattern-averaged temperature, circulation, and chlorophyll-a concentration show significant differences. CDW area and its eastern most extension were explored as a function of the Changjiang runoff and regional upwelling index. We found that Changjiang runoff and upwelling index can be reasonable predictors for the overall CDW area, while ambient circulation determines the distribution and structure of the CDW, and thus the CDW eastern most extension.

This paper outlines strategies that would advance coastal ocean modeling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the U.S. Integrated Ocean Observing System (IOOS��) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of U.S. based researchers with a cross-section of coastal oceanography and ocean modeling expertise and community representation drawn from Regional and U.S. Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modeling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3-8 year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, U.S. Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal-academic partnerships benefiting IOOS stakeholders and end users.

Abundant mesoscale eddies propagate to the east of Taiwan and affect the Kuroshio Current and its onshore intrusion northeast of Taiwan. But the dynamical process of how eddy activities modulate the Kuroshio intrusion is still unclear. In this study, in situ ocean velocity observations, drifter trajectories, tide gauge measurements, satellite sea surface height data, and assimilative Hybrid Coordinate Ocean Model (HYCOM) reanalysis outputs were used to analyze a cyclonic eddy-induced large Kuroshio onshore intrusion during late autumn 2008. Along with nine anticyclonic eddy events and seven cyclonic eddy events extracted from long-term HYCOM reanalysis outputs, the variability of the eddy-induced intrusion were quantified. The impacts of the cyclonic eddy and the anticyclonic eddy were opposite. Under the impact of cyclonic (anticyclonic) eddy, the total onshore intrusion between 122°E and 124°E across the 200 m isobaths was decreased (increased) by 15.7% (7.3%), while the onshore intrusion west of 122.6°E and the northeastward current on the outer shelf was increased (decreased) by 30.6% (4.7%) and 31% (10.1%), respectively. The arrival of cyclonic (anticyclonic) eddy brought positive (negative) potential vorticity (PV) flux and modulated the local ocean vertical stratification, which weakened (enhanced) the cross-slope PV gradient and the shelf slope constraint on the upper layer current, therefore, favored (inhibited) the Kuroshio onshore intrusion. This article is protected by copyright. All rights reserved.

Variability in along-shelf and cross-shelf circulation in the South Atlantic Bight (SAB) is investigated using altimetry observations. Satellite-derived along-shelf velocity anomalies are in good agreement with independent near-surface current measurements from moored acoustic Doppler current profilers and surface velocities from high frequency radar at adjacent locations. This is especially true if wind-driven Ekman velocities are added to the geostrophic velocities, suggesting that the influence of Ekman dynamics to surface along-shelf flow in the SAB is unusually large. The decade-long time series reveals substantial seasonal variability in surface velocities, with peak poleward anomalies during late spring and summer and strong equatorward flow during autumn. Convergences and divergences in the along-shelf transport between two cross-sections are compared with three-dimensional numerical model results and used to estimate cross-shelf transport across the 50 m isobath in the SAB. The calculation suggests a pattern of weak offshore flow during spring followed by prolonged and relatively stronger offshore flow during summer and early autumn, while cross-shelf velocity anomalies during winter are weak and slightly onshore. Prolonged offshore flow following the peak in river discharge that generally occurs in spring indicates the potential for the establishment of a conduit for offshore export of riverine material. The long-term time series also reveals several large events of interannual variability, including the 2003 cold event observed in the SAB.

The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

In July 2009, an unusually intense bloom of the toxic dinoflagellate Alexandrium catenella occurred in the Gulf of Maine. The bloom reached high concentrations (from hundreds of thousands to one million cells L−1) that discolored the water and exceeded normal bloom concentrations by a factor of 1000. Using Medium Resolution Imaging Spectrometer (MERIS) imagery processed to target chlorophyll concentrations (>2 µg L−1), patches of intense A. catenella concentration were identified that were consistent with the highly localized cell concentrations observed from ship surveys. The bloom patches were generally aligned with the edge of coastal waters with high-absorption. Dense bloom patches moved onshore in response to a downwelling event, persisted for approximately one week, then dispersed rapidly over a few days and did not reappear. Coupled physical-biological model simulations showed that wind forcing was an important factor in transporting cells onshore. Upward swimming behavior facilitated the horizontal cell aggregation, increasing the simulated maximum depth-integrated cell concentration by up to a factor of 40. Vertical convergence of cells, due to active swimming of A. catenella from the subsurface to the top layer, could explain the additional 25-fold intensification (25 × 40=1000-fold) needed to reach the bloom concentrations that discolored the water. A model simulation that considered upward swimming overestimated cell concentrations downstream of the intense aggregation. This discrepancy between model and observed concentrations suggested a loss of cells from the water column at a time that corresponded to the start of encystment. These results indicated that the joint effect of upward swimming, horizontal convergence, and wind-driven flow contributed to the red water event, which might have promoted the sexual reproduction event that preceded the encystment process.

There has been considerable debate as to how natural forcing and anthropogenic activities alter the timing and magnitude of the delivery of dissolved organic carbon (DOC) to the coastal ocean, which has ramifications for the ocean carbon budget, land-ocean interactions, and coastal life. Here we present an analysis of DOC export from the Mississippi River to the Gulf of Mexico during 1901–2010 as influenced by changes in climate, land use and management practices, atmospheric CO2, and nitrogen deposition, through the integration of observational data with a coupled hydrologic/biogeochemical land model. Model simulations show that DOC export in the 2000s increased more than 40% since the 1900s. For the recent three decades (1981–2010), however, our simulated DOC export did not show a significant increasing trend, which is consistent with observations by U.S. Geological Survey. Our factorial analyses suggest that land use and land cover change, including land management practices (LMPs: i.e., fertilization, irrigation, tillage, etc.), were the dominant contributors to the century-scale trend of rising total riverine DOC export, followed by changes in atmospheric CO2, nitrogen deposition, and climate. Decadal and interannual variations of DOC export were largely attributed to year-to-year climatic variability and extreme flooding events, which have been exacerbated by human activity. LMPs show incremental contributions to DOC increase since the 1960s, indicating the importance of sustainable agricultural practices in coping with future environmental changes such as extreme flooding events. Compared to the observational-based estimate, the modeled DOC export was 20% higher, while DOC concentrations were slightly lower. Further refinements in model structure and input data sets should enable reductions in uncertainties in our prediction of century-long trends in DOC.

A three-dimensional coupled physical–biogeochemical model was used to simulate and examine temporal and spatial variability of sea surface pCO2 in the Gulf of Mexico (GoM). The model was driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A 7-year model hindcast (2004–2010) was performed and validated against ship measurements. Model results revealed clear seasonality in surface pCO2 and were used to estimate carbon budgets in the Gulf. Based on the average of model simulations, the GoM was a net CO2 sink with a flux of 1.11 ± 0.84 × 1012 mol C yr−1, which, together with the enormous fluvial inorganic carbon input, was comparable to the inorganic carbon export through the Loop Current. Two model sensitivity experiments were performed: one without biological sources and sinks and the other using river input from the 1904–1910 period as simulated by the Dynamic Land Ecosystem Model (DLEM). It was found that biological uptake was the primary driver making GoM an overall CO2 sink and that the carbon flux in the northern GoM was very susceptible to changes in river forcing. Large uncertainties in model simulations warrant further process-based investigations.

A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexico (GOM), and the Caribbean Sea. The statistical relationship is built upon linear regressions between the empirical orthogonal function (EOF) spaces of a cross- calibrated, multi-platform, multi-instrument ocean surface wind velocity dataset (predictand) and the global NCEP wind reanalysis (predictor) over a 10 year period from 2000 to 2009. The statistical relationship is validated before applications and its effectiveness is confirmed by the good agreement between downscaled wind fields based on the NCEP reanalysis and in-situ surface wind measured at 16 National Data Buoy Center (NDBC) buoys in the U.S. east coastal ocean and the GOM during 1992–1999. The predictand-predictor relationship is applied to IPCC GFDL model output (2.0°×2.5°) of downscaled coastal wind at 0.25°×0.25° resolution. The temporal and spatial variability of future predicted wind speeds and wind energy potential over the study region are further quantified. It is shown that wind speed and power would significantly be reduced in the high CO2 climate scenario offshore of the mid-Atlantic and northeast U.S., with the speed falling to one quarter of its original value.

A 25 km streak of CF3SF5 was released on an isopycnal surface approximately 1100 m deep, and 150 m above the bottom, along the continental slope of the northern Gulf of Mexico, to study stirring and mixing of a passive tracer. The location and depth of the release were near those of the deep hydrocarbon plume resulting from the 2010 Deepwater Horizon oil well rupture. The tracer was sampled between 5 and 12 days after release, and again 4 and 12 months after release. The tracer moved along the slope at first but gradually moved into the interior of the Gulf. Diapycnal spreading of the patch during the first 4 months was much faster than it was between 4 and 12 months, indicating that mixing was greatly enhanced over the slope. The rate of lateral homogenization of the tracer was much greater than observed in similar experiments in the open ocean, again possibly enhanced near the slope. Maximum concentrations found in the surveys had fallen by factors of 104, 107, and 108, at 1 week, 4 months, and 12 months, respectively, compared with those estimated for the initial tracer streak. A regional ocean model was used to simulate the tracer field and help interpret its dispersion and temporal evolution. Model-data comparisons show that the model simulation was able to replicate statistics of the observed tracer distribution that would be important in assessing the impact of oil releases in the middepth Gulf.

This paper summarizes the findings of a workshop convened in the United States in 2018 to discuss methods in coastal and estuarine modeling and to propose key areas of research and development needed to improve their accuracy and reliability. The focus of this paper is on physical processes, and we provide an overview of the current state-of-the-art based on presentations and discussions at the meeting, which revolved around the four primary themes of parameterizations, numerical methods, in-situ and remote-sensing measurements, and high-performance computing. A primary outcome of the workshop was agreement on the need to reduce subjectivity and improve reproducibility in modeling of physical processes in the coastal ocean. Reduction of subjectivity can be accomplished through development of standards for benchmarks, grid generation, and validation, and reproducibility can be improved through development of standards for input/output, coupling and model nesting, and reporting. Subjectivity can also be reduced through more engagement with the applied mathematics and computer science communities to develop methods for robust parameter estimation and uncertainty quantification. Such engagement could be encouraged through more collaboration between the forward and inverse modeling communities and integration of more applied math and computer science into oceanography curricula. Another outcome of the workshop was agreement on the need to develop high-resolution models that scale on advanced HPC systems to resolve, rather than parameterize, processes with horizontal scales that range between the depth and the internal Rossby deformation scale. Unsurprisingly, more research is needed on parameterizations of processes at scales smaller than the depth, including parameterizations for drag (including bottom roughness, bedforms, vegetation and corals), wave breaking, and air–sea interactions under strong wind conditions. Other topics that require significantly more work to better parameterize include nearshore wave modeling, sediment transport modeling, and morphodynamics. Finally, it was agreed that coastal models should be considered as key infrastructure needed to support research, just like laboratory facilities, field instrumentation, and research vessels. This will require a shift in the way proposals related to coastal ocean modeling are reviewed and funded.

Despite the recent success achieved by the unstructured-grid SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model) in multi-resolution studies, its skill in simulating the baroclinic eddying ocean needs to be further improved. In particular, the classical 2nd-order transport schemes for estuaries and coastal zones are too dissipative to resolve the baroclinic dynamics associated with strong boundary currents, such as meso-scale meanders and eddies. To close this gap, this paper presents a newly designed 3rd-order finite volume transport scheme, based on the Weighted Essentially Non-Oscillatory (WENO) formalism. This new scheme strikes a delicate balance among accuracy, efficiency, and monotonicity for the transport in the eddying regime. Idealized numerical benchmark experiments demonstrate that the WENO scheme is very effective in limiting numerical diffusion. The scheme is then applied in a realistic simulation of the Gulf Stream and the surrounding circulation, further confirming its capability of resolving baroclinic meso-scale eddies and meanders. This new high-order transport scheme is therefore ideal for extending the ability of SCHISM to study cross-scale baroclinic applications that range from the river dynamics to the eddying ocean processes.

A regional-scale ocean model was used to hindcast the coastal circulation over the Middle Atlantic Bight (MAB) and Gulf of Maine (GOM) from 2004 to 2013. The model was nested inside a data assimilative global ocean model that provided initial and open boundary conditions. Realistic atmospheric forcing, tides and observed river runoff were also used to drive the model. Hindcast solutions were compared against observations, which included coastal sea levels, satellite altimetry sea surface height, temperature and salinity time series in the GOM, glider transects in the MAB, and observed mean depth-averaged velocities by Lentz (2008a). Good agreements with observations suggest that the hindcast model is capable of capturing the major circulation variability in the MAB and GOM. Time- and space-continuous hindcast fields were used to depict the mean circulation, along- and cross-shelf transport and the associated momentum balances. The hindcast confirms the presence of the equatorward mean shelf circulation, which varies from 2.33 Sv at Scotian Shelf to 0.22 Sv near Cape Hatteras. Using the 200 m isobath as the shelf/slope boundary, the mean cross-shelf transport calculations indicate that the shelfbreak segments off the Gulf of Maine (including the southern flank of Georges Bank and the Northeast Channel) and Cape Hatteras are the major sites for shelf water export. The momentum analysis reveals that the along-shelf sea level difference from Nova Scotia to Cape Hatteras is about 0.36 m. The nonlinear advection, stress, and horizontal viscosity terms all contribute to the ageostrophic circulation in the along-isobath direction, whereas the nonlinear advection plays a dominant role in determining the ageostrophic current in the cross-isobath direction.

There has been global interest in renewable energy for meeting energy demands, and as these demands increase, it will become of greater importance to utilize low-carbon energy sources to mitigate anthropogenic impact on the environment. Onshore hydropower is responsible for half of the electricity generated by a renewable source in the USA. In the ocean, marine hydrokinetic (MHK) energy in western boundary currents (WBCs) can be considered for electricity generation by submarine turbines. WBCs are a continuous and sustainable source of energy that could be transmitted to shore to support coastal communities in future years. The Gulf Stream is the WBC of the North Atlantic subtropical gyre, and it flows for part of its course along the upper continental slope off the southeastern USA. This large-scale current has maximum flow speeds exceeding 2 m s−1, and this together with its proximity to the coastline distinguishes it as a potential source of MHK energy. Using current data from a moored acoustic Doppler current profiler (ADCP) and a regional ocean circulation model, MHK power densities offshore of North Carolina were found to average 798 W m−2 for the ADCP and 641 W m−2 for the model during a nine-month period at a potential turbine site, a difference of about 20%. The model was shown to have similar current speeds to the ADCP for slowly varying currents (fluctuations of weeks to months due to Gulf Stream path shifts), and lower speeds for higher frequency current variations (fluctuations of several days to a couple of weeks due to wavelike Gulf Stream meanders). This article considers the Gulf Stream as a prospective renewable energy source and assesses the power density of this WBC at multiple locations offshore of North Carolina. Understanding the Stream’s power density character, including its spatial and temporal variations along the North Carolina coast, is essential in considering the Gulf Stream as a future alternative energy resource.

Upper ocean responses to tropical storms/hurricanes have been extensively studied using satellite observations. However, resolving concurrent sea surface temperature (SST) and chlorophyll a (chl a) responses along storm tracks remains a major challenge due to extensive cloud coverage in satellite images. Here we produce daily cloud-free SST and chl a reconstructions based on the Data INterpolating Empirical Orthogonal Function method over a 10 year period (2003–2012) for the Gulf of Mexico and Sargasso Sea regions. Daily reconstructions allow us to characterize and contrast previously obscured subweekly SST and chl a responses to storms in the two main storm-impacted regions of the Atlantic Ocean. Statistical analyses of daily SST and chl a responses revealed regional differences in the response time as well as the response sensitivity to maximum sustained wind speed and translation speed. This study demonstrates that SST and chl a responses clearly depend on regional ocean conditions and are not as universal as might have been previously suggested.

High-resolution, physical-biological models of coastal and shelf regions typically use a single functional phytoplankton group, which limits their ability to represent ecological gradients (e.g. highly productive shelf systems adjacent to oligotrophic regions), as these are dominated by different functional phytoplankton groups. We implemented a size-structured ecosystem model in a high-resolution, regional circulation model of the northeast North American shelf and adjacent deep ocean in order to assess whether the added functional complexity of two functional phytoplankton groups improves the model's ability to represent surface chlorophyll concentrations along an ecological gradient encompassing five distinct regions. We used satellite-derived SST and sea-surface chlorophyll for our model assessment, as these allow investigation of spatial variability and temporal variations from monthly to interannual, and analyzed three complimentary statistical measures of model-data agreement: model bias, root-mean-squared error and model efficiency (or skill). All three measures were integrated for the whole domain, for distinct subregions and were calculated in a spatially explicit manner. Comparison with a previously published simulation that used a model with a single phytoplankton functional group indicates that the inclusion of an additional phytoplankton group representing picoplankton markedly improves the model's skill.