Sea level acceleration and variability in the Chesapeake Bay: past trends,future projections,and spatial variations within the Bay

Ocean Dynamics - Fast sea level rise (SLR) is causing a growing risk of flooding to coastal communities around the Chesapeake Bay (hereafter, CB or “the Bay”), but there are also...     

Silicones in Chesapeake Bay sediments

Sediment samples from the upper reaches to the mouth of the Chesapeake Bay were analysed for extractable organic silicon (silicone) content. Organic silicon in the sediments ranged from less than 0.2 to some 36 ppm, w/w. In general, silicone tended to accumulate in high depositional areas: the northern bay, and along the shores to the south. While present, anthropogenic inputs in terms of defined source were not clear. It appears that processes in the bay act to rapidly remove silicone from the water column, probably on a function of the flocculation/precipitation of seston, especially in the northern area.     

Wave measurement and modeling in Chesapeake Bay

Three recently measured wind and wave data sets in the northern part of Chesapeake Bay (CB) are presented. Two of the three data sets were collected in late 1995. The third one was collected in July of 1998. The analyzed wind and wave data show that waves were dominated by locally generated, fetch limited young wind seas. Significant wave heights were highly correlated to the local driving wind speeds and the response time of the waves to the winds was about 1 h. We also tested two very different numerical wave models, Simulation of WAves Nearshore (SWAN) and Great Lakes Environmental Research Laboratory (GLERL), to hind-cast the wave conditions against the data sets. Time series model–data comparisons made using SWAN and GLERL showed that both models behaved well in response to a suddenly changing wind. In general, both SWAN and GLERL over-predicted significant wave height; SWAN over-predicted more than GLERL did. SWAN had a larger scatter index and a smaller correlation coefficient for wave height than GLERL had. In addition, both models slightly under-predicted the peak period with a fairly large scatter and low correlation coefficient. SWAN predicted mean wave direction better than GLERL did. Directional wave spectral comparisons between SWAN predictions and the data support these statistical comparisons. The GLERL model was much more computationally efficient for wind wave forecasts in CB. SWAN and GLERL predicted different wave height field distributions for the same winds in deeper water areas of the Bay where data were not available, however. These differences are as yet unresolved.     

Bimodal wave spectra in lower Chesapeake Bay, sea bed energetics and sediment transport during winter storms

The transition zone separating estuarine environments from the coastal ocean is characterized not only by distinctive morphological and sedimentary trends but by unique hydrodynamic forces as well. Lower Chesapeake Bay, a large coastal estuary within the Mid-Atlantic Bight of the U.S. East Coast, experiences complex wave and current-induced forces produced during winter storms. Wave and current measurements made near Thimble Shoal Light over five winter seasons show that most storms simultaneously produce both ocean and bay-generated wave trains that appear as distinct bimodal peaks in directional spectra. Analysis of selected storm wave records reveal that lower-frequency ocean waves, although nominally lower in amplitude than higher-frequency bay waves, are roughly equivalent to bay waves in terms of energy expended on beds of fine- to medium-grained sand at either end of the Thimble Shoal Channel. Grain-friction energy dissipation estimates calculated for waves and currents suggest that waves provide more net energy capable of transporting bottom sediment than currents, although strong barotropic flows briefly encountered during a major storm on 13–14 March 1993, exceeded wave energy expended at the bed by almost an order of magnitude. From analyses of wave orbital velocity spectra, it is shown that dual wave trains characterized by differences in peak frequency and direction may assist each other through interactions that increase their combined contribution to frictional energy dissipation and inferred sediment transport at the bed.     

北太平洋海表面高度的年际变化及其机制

利用15年（1993～2007年）月平均的海表面高度（SSH）异常资料,分析了北太平洋海表面高度的年际变化的时空结构,并研究了热通量和风应力两个因子对其的强迫作用.结果表明,北太平洋年际时间尺度SSH变化的大值区在黑潮延伸区和西太平洋暖池区.EOF分解第一模态的空间结构沿纬向呈带状分布,第二模态为沿经向呈带状分布.热通量强迫作用在中纬度的东北太平洋可以解释SSH年际变化40%以上.风应力对SSH的作用包括正压和斜压两个方面.正压Sverdrup平衡模型模拟的SSH年际变化较弱,仅能解释高纬度副极地环流西部的20%~40%.由大尺度风应力强迫的第一阶斜压Rossby波模型可以解释热带地区的20%~60%,中纬度中部的20%~40%,以及阿拉斯加环流东部和副极地环流西部的20%~60%.风应力强迫的一阶斜压Rossby波模型对SSH的强迫机理又可分为局地风应力强迫和西传Rossby波作用.其中,风应力的局地强迫作用（Ekman抽吸）在东北太平洋、白令海以及热带中部有显著的预报技巧,可以解释SSH年际变异的40%以上.Rossby波的传播作用在中纬度海域的副热带环流中西部和夏威夷岛以东起着重要作用,可解释20%~60%.     

Low-frequency sea level variability and impact of recent sea ice decline on the sea level trend in the Arctic Ocean from a high-resolution simulation

Ocean Dynamics - The Arctic Ocean is undergoing significant changes, with rapid sea ice decline, unprecedented freshwater accumulation, and pronounced regional sea level rise. In this paper, we...     

Phytoplankton Kinetics in the Chesapeake Bay Eutrophication Model

The CE-Qual-ICM model computes phytoplankton biomass and production as a function of temperature, light, and nutrients. Biomass is computed as carbon while inorganic nitrogen, phosphorus, and silica are considered as nutrients. Model formulations for production, metabolism, predation, nutrient limitation, and light limitation are detailed. Methods of parameter determination and parameter values are presented. Results of model application to a ten-year period in Chesapeake Bay indicate the model provides reasonable representations of observed biomass, nutrient concentrations, and limiting factors. Computed primary production agrees with observed under light-limited conditions. Under strongly nutrient-limited conditions, computed product is less than observed. The production characteristics of the model are similar to behavior reported for several similar models. Process omitted from the model that may account for production shortfalls include variable algal stoichiometry, use of urea as nutrient, and vertical migration by phytoplankton.     

Flow patterns at the Chesapeake Bay entrance

The spatial and temporal variability of water entering and leaving the Chesapeake Bay estuary was determined with a spatial resolution of 75 m. The four cruises during which the observations were made took place under different conditions of freshwater discharge, tidal phase, and wind forcing. The tidal variability of the flows was dominated by the semidiurnal constituents that displayed greatest amplitudes and phase lags near the surface and in the channels that lie at the north and south sides of the entrance. The subtidal variability of the flows was classified into two general scenarios. The first scenario occurred during variable or persistently non-southwesterly winds. Under these conditions there was surface outflow and bottom inflow in the two channels, inflow over the shoal between the two channels, and possible anticyclonic gyre formation over the shoal. The flow pattern in the channels was produced by gravitational circulation and wind forcing. Over the shoal it was caused by tidal rectification and wind forcing. The second scenario occurred during persistently southwesterly winds. The anticyclonic gyre over the shoal vanished suggesting that wind forcing dominated the tidal rectification mechanism over the shoal, while gravitational circulation and wind forcing continued to cause the flows in the channels. In both scenarios, most of the volume exchange took place in the channels.     

The relationships between tropical Atlantic sea level variability and major climate indices

Relationships were examined between variability in tropical Atlantic sea level and major climate indices with the use of TOPEX/POSEIDON altimeter and island tide gauge data with the aim of learning more about the external influences on the variability of the tropical Atlantic ocean. Possible important connections were found between indices related to the El Niño–Southern Oscillation (ENSO) and the sea levels in all three tropical regions (north, equatorial, and south), although the existence of only one major ENSO event within the decade of available altimetry means that a more complete investigation of the ENSO-dependence of Atlantic sea level changes has to await for the compilation of longer data sets. An additional link was found with the Indian Ocean Dipole (IOD) in the equatorial region, this perhaps surprising observation is probably an artifact of the similarity between IOD and ENSO time series in the 1990s. No evidence was obtained for significant correlations between tropical Atlantic sea level and North Atlantic Oscillation or Antarctic Oscillation Index. The most intriguing relationship observed was between the Quasi-Biennial Oscillation and sea level in a band centered approximately on 10°S. A plausible explanation for the relationship is lacking, but possibilities for further research are suggested.     

Cross-Media Models of the Chesapeake Bay Watershed and Airshed

A continuous, deterministic watershed model of the Chesapeake Bay watershed, linked to an atmospheric deposition model is used to examine nutrient loads to the Chesapeake Bay under different management scenarios. The Hydrologic Simulation Program - Fortran, Version 11 simulation code is used at an hourly time-step for ten years of simulation in the watershed. The Regional Acid Deposition Model simulates management options in reducing atmospheric deposition of nitrogen. Nutrient loads are summed over daily periods and used for loading a simulation of the Chesapeake estuary employing the Chesapeake Bay Estuary Model Package. Averaged over the ten-year simulation, loads are compared for scenarios under 1985 conditions, forecasted conditions in the year 2000, and estimated conditions under a limit of technology scenario. Limit of technology loads are a 50%, 64%, and 42% reduction from the 1985 loads in total nitrogen, total phosphorus, and total suspended solids, respectively. Urban loads, which include point source, on-site wastewater disposal systems, combined sewer overflows, and nonpoint source loads have the highest flux of nutrient loads to the Chesapeake, followed by crop land uses.on assignment from NOAA Air Resources Laboratory     

Pressure effects on past regional sea level trends and variability in the German Bight

The impact on a large-scale sea level pressure field to the regional mean sea level changes of the German Bight is analysed. A multiple linear regression together with an empirical orthogonal function analysis is used to describe the relationship between the sea level pressure and the regional mean sea level considering the time period 1924–2001. Both, the part of the variability and of the long-term trend that can be associated with changes in the sea level pressure, are investigated. Considering the whole time period, this regression explains 58?% of the variance and 33?% of the long-term trend of the regional mean sea level. The index of agreement between the regression result and the observed time series is 0.82. As a proxy for large-scale mean sea level changes, the mean sea level of the North East Atlantic is subsequently introduced as an additional predictor. This further improves the results. For that case, the regression explains 74?% of the variance and 87?% of the linear trend. The index of agreement rises to 0.92. These results suggest that the sea level pressure mainly accounts for the inter-annual variability and parts of the long-term trend of regional mean sea level in the German Bight while large-scale sea level changes in the North East Atlantic account for another considerable fraction of the observed long-term trend. Sea level pressure effects and the mean sea level of the North East Atlantic provide thus significant contributions to regional sea level rise and variability. When future developments are considered, scenarios for their future long-term trends thus need to be comprised in order to provide reliable estimates of potential future long-term changes of mean sea level in the German Bight.     

Predicting dissolved oxygen in the Chesapeake Bay: applications and implications

Eutrophic depletion of dissolved oxygen (DO) and its consequences for ecosystem dynamics have been a central theme of research, assessment and management policies for several decades in the Chesapeake Bay. Ongoing forecast efforts predict the extent of the summer hypoxic/anoxic area due to nutrient loads from the watershed. However, these models neither predict DO levels nor address the intricate interactions among various ecological processes. The prediction of spatially explicit DO levels in the Chesapeake Bay can eventually lead to a reliable depiction of the comprehensive ecological structure and functioning, and can also allow the quantification of the role of nutrient reduction strategies in water quality management. In this paper, we describe a three dimensional empirical model to predict DO levels in the Chesapeake Bay as a function of water temperature, salinity and dissolved nutrient concentrations (TDN and TDP). The residual analysis shows that predicted DO values compare well with observations. Nash–Sutcliffe efficiency (NSE) and root mean square error-observations standard deviation ratio (RSR) are used to evaluate the performance of the empirical model; the scores demonstrate the usability of model predictions (NSE, surface layer = 0.82–0.86; middle layer = 0.65–0.82; bottom layer = 0.70–0.82; RSR surface layer = 0.37–0.44; middle layer = 0.43–0.58 and bottom layer = 0.43–0.54). The predicted DO values and other physical outputs from downscaling of regional weather and climate predictions, or forecasts from hydrodynamic models, can be used to forecast various ecological components. Such forecasts would be useful for both recreational and commercial users of the Chesapeake Bay.     

Evaluation of butyltin compounds in Maryland waters of Chesapeake Bay

A monthly sampling programme for dibutyltin (DBT), tributyltin (TBT) and tetrabutyltin (TTBT) was initiated for a period of one year (July 1985–June 1986) in the Maryland waters of Chesapeake Bay. Concentrations of the above butyltin species were evaluated in the microlayer and water column of eight sampling stations representing two small and two large marinas, a large harbour, two major river systems and a heavily used shipping channel. DBT concentrations in the microlayer were generally higher in the four marinas when compared with the other stations. The highest DBT concentration reported in the microlayer was 1156 ng l⁻¹. Mean microlayer TBT concentrations ranged from 54–310 ng l⁻¹ in the four marinas. Three TBT concentrations ranging from 1049–1171 ng l⁻¹ were reported in the microlayer of the marinas. TBT concentrations of 41 and 29 mg l⁻¹ were detected in the microlayer of a heavily used shipping channel (C & D Canal) during May and June. TTBT concentrations were not detected in the microlayer at most stations during the 12 month sampling period.Mean DBT concentrations in the water column ranged from 23–145 ng l⁻¹ in the four marinas. DBT concentrations in the water column of the other stations were < 35 ng l⁻¹. Mean water column concentrations of TBT ranged from 51–408 ng l⁻¹ in all four marinas. Peak concentrations of TBT were reported in May and June for the various marinas. The highest TBT concentration reported in the water column was 998 ng l⁻¹. TBT concentrations of 20–24 ng l⁻¹ were reported in one of the river systems (Potomac River). TTBT concentrations were not detected in the water column at most of the stations.     

Coupling Suspension Feeders to the Chesapeake Bay Eutrophication Model

A model predicting suspension-feeding bivalve biomass and its interactions with water quality has been developed and coupled with the Chesapeake Bay Eutrophication Model. This coupling included deposition of filtered particulate matter to the sediments and the recycling of inorganic nutrients back to the water column. Because individual size is a crucial determinant of bivalve filtration and respiration rates, an empirical function, was developed from data, relating computed areal biomass to size, which was then used to adjust these rates during the simulation. Biomass was strongly related to the eutrophication model's predictions of organic and total solids distributions, as well as to bottom water dissolved oxygen. The tight coupling between seasonal organic matter concentration and biomass suggested that food, or the ability of suspension feeders to ingest it given present total solids loadings, is a limiting factor baywide. Hypoxia and anoxia also reduced benthic biomass in affected locations. High site-specific temporal variability observed in the data may contain a large component of spatial patchiness, on scales below which the present estuarine eutrophication model could resolve. Further insights will be needed to incorporate the effects of patchiness, as well as other important spatial and temporal signals, such as predation and recruitment.