Abstract-An integrated ocean observatory has been developed and operated in the coastal waters off the central coast of New Jersey, USA. One major goal for the Long-term Ecosystem Observatory (LEO) is to develop a real-time capability for rapid environmental assessment and physical/biological forecasting in coastal waters. To this end, observational data are collected from satellites, aircrafts, ships, fixed/relocatable moorings and autonomous underwater vehicles. The majority of the data are available in real-time allowing for adaptive sampling of episodic events and are assimilated into ocean forecast models. In this observationally rich environment, model forecast errors are dom inated by uncertainties in the model physics or future boundary conditions rather than initial conditions. Therefore, ensemble forecasts with differing model parameterizations provide a unique opportunity for model refinement and validation. The system has been operated during three annual coastal predictive skill experiments from 1998 through 2000. To illustrate the capabilities of the system, case studies on coastal upwelling and small-scale biological slicks will be discussed. This observatory is one part of the expanding network of ocean observatories that will form the basis of a national observation network. These regional efforts should be linked through satellite remote sensing and surface current radar systems. Data on the ocean interior will be provided from subsurface AUVs and moorings. The combined data should be available through a network of virtual labs capable of rapid data visualization and dissemination.

The alternative hypothesis that observed regions of recurrent hypoxia on the New Jersey inner shelf are more related to coastal upwelling than riverine inputs of nutrients was investigated through a series of multidisciplinary research programs beginning in 1993. The largest variations in ocean temperatures along the New Jersey coast, other than seasonal, are found to be caused by episodic summertime upwelling events driven by southwesterly winds associated with the atmospheric Bermuda High. Off the southern coast of New Jersey, topographic variations associated with ancient river deltas cause upwelled water to evolve into an alongshore line of recurrent upwelling centers that are colocated with historical regions of low dissolved oxygen. Recurrent upwelling centers are observed every summer in a 9-year data set. The most significant upwelling events occur in summers following colder than usual falls and winters. Size and duration of individual events are correlated and are found to depend on the wind forcing history that effects the inner side of the Middle Atlantic Cold Pool, the precipitation history that effects the strength of the Hudson River plume, and the mixing storm frequency. Upwelling results in a significant enhancement of particulate organic carbon. The typical carbon enhancement associated with the upwelling is sufficient to deplete 75% of the oxygen in the bottom water, making it borderline hypoxic. This indicates that topographically controlled coastal upwelling, rather than riverine inputs, is the more probable mechanism for generating the historical regions of recurrent hypoxia observed along the New Jersey coast.

[1] A recurrent coastal sediment plume (RCP) is an episodic event in the southern basin of Lake Michigan that typically coincides with the spring diatom bloom. Strong winter storm activity during El Niño conditions in 1998 resulted in a large and intense RCP event. Consistently higher values of the light-saturated rate of photosynthesis, P max B , were observed in spring 1998 compared to 1999 and 2000. Higher values of P max B in 1998 appeared to be related to increased availability of phosphorus, as evidenced by significant correlations of P max B with soluble reactive phosphorus (SRP). Light-saturated growth rates were also significantly correlated with SRP concentrations. These findings were consistent the view that the RCP was a source of enrichment. However, incubation experiments involving lake water enriched with sediments showed relatively small increases in growth and photosynthetic parameters, while enrichments with river water exhibited elevated rates. This result, along with increased levels of river discharge in 1998 and high levels of dissolved phosphorus in river water, supported the view that riverine inputs rather than the RCP were responsible for the higher photosynthetic parameters and growth seen for coastal margin assemblages. Despite the higher levels of P max B in 1998, model analyses revealed that reduced light availability resulting from the intense RCP event constrained phytoplankton growth rates and primary production during this season and apparently suppressed the development of a typical spring bloom. These findings indicate a potential for reduced ecosystem productivity in response to extreme storm events, the frequency of which may increase with projected long-term climate changes.

[1] In order to characterize the impact of turbidity plumes on optical and biological dynamics, a suite of environmental parameters were measured in southern Lake Michigan during the springtime recurrent sediment plume. In-water measurements of inherent optical properties (IOPs) were entered into the Hydrolight 4.2 radiative transfer model and the output was compared with measured apparent optical properties (AOPs) across a wide range of optical conditions. Hydrolight output and measured underwater light fields were then used to clarify the effects of the sediment plume on primary production, phytoplankton community composition, and nearshore remote sensing ocean color algorithms. Our results show that the sediment plume had a negligible effect on the spectral light environment and phytoplankton physiology. The plume did not significantly alter the spectral quality of available light and did not lead to light limited phytoplankton populations compared to non-plume conditions. Further, the suspended sediment in the plume did not seriously impact the performance of ocean color algorithms. We evaluated several currently employed chlorophyll algorithms and demonstrated that the main factor compromising the efficacy of these algorithms was the composition of phytoplankton populations. As phycobilin-containing algae became the dominant species, chlorophyll algorithms that use traditional blue/green reflectance ratios were compromised due to the high absorption of green light by phycobilin pigments. This is a notable difficulty in coastal areas, which have highly variable phytoplankton composition and are often dominated by sharp fronts of phycobilin and non-phycobilin containing algae.

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