Keston W. Smith

Model simulations of the Bay of Fundy Gyre: 1. Climatological results

The characteristics of a persistent gyre in the mouth of the Bay of Fundy are studied using model simulations. A set of climatological runs are conducted to evaluate the relative importance of the different forcing mechanisms affecting the gyre. The main mechanisms are tidal rectification, and density-driven circulation. Stronger circulation of the gyre occurs during the later part of the stratified season (July-August and September-October). The density-driven flow around the gyre is set-up by weak tidal mixing in the deep basin in the central Bay of Fundy and strong tidal mixing on the shallow flanks around Grand Manan Island and western Nova Scotia. Retention of particles in the Gyre is controlled by the residual tidal circulation, increased frontal retention during stratified periods, wind stress, and interactions with the adjacent circulation of the Gulf of Maine. Residence times longer than 30 days are predicted for particles released in the proximity of the gyre.

Data assimilative hindcast of the Gulf of Maine coastal circulation

[1] A data assimilative model hindcast of the Gulf of Maine (GOM) coastal circulation during an 11 day field survey in early summer 2003 is presented. In situ observations include surface winds, coastal sea levels, and shelf hydrography as well as moored and shipboard acoustic Doppler D current profiler (ADCP) currents. The hindcast system consists of both forward and inverse models. The forward model is a three-dimensional, nonlinear finite element ocean circulation model, and the inverse models are its linearized frequency domain and time domain counterparts. The model hindcast assimilates both coastal sea levels and ADCP current measurements via the inversion for the unknown sea level open boundary conditions. Model skill is evaluated by the divergence of the observed and modeled drifter trajectories. A mean drifter divergence rate (1.78 km d � 1 ) is found, demonstrating the utility of the inverse data assimilation modeling system in the coastal ocean setting. Model hindcast also reveals complicated hydrodynamic structures and synoptic variability in the GOM coastal circulation and their influences on coastal water material property transport. The complex bottom bathymetric setting offshore of Penobscot and Casco bays is shown to be able to generate local upwelling and downwelling that may be important in local plankton dynamics.

Model simulations of the Bay of Fundy Gyre: 2. Hindcasts for 2005–2007 reveal interannual variability in retentiveness

A persistent gyre at the mouth of the Bay of Fundy results from a combination of tidal rectification and buoyancy forcing (Aretxabaleta et al., J. Geophys. Res., vol. 113, 2008). Here we assess interannual variability in the strength of the gyre using data assimilative model simulations. Realistic hindcast representations of the Gyre are considered over the course of cruise surveys in 2005, 2006 and 2007. Assimilation of shipboard and moored ADCP velocities are used to improve the skill of the simulations, as quantified by comparison with non-assimilated drifter trajectories. Our hindcast suggest a weakening of the Gyre system during May 2005. Retention of simulated passive particles in the Gyre during that period was highly reduced. A recovery of the dense water pool in the deep part of the basin by June 2006 resulted in a return to particle retention characteristics similar to climatology. Retention estimates reached a maximum during May 2007 (sub-surface) and June-July 2007 (near-surface). Interannual variability in the strength of the gyre was primarily modulated by the stratification of the dense water pool inside the Grand Manan Basin. These changes in stratification may be attributed to mixing conditions the preceding fall/winter and/or advectively-driven modification of water mass properties.

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight

Abstract This paper addresses shelf-scale simulation with dominant open-water boundary conditions obtained by inversion of interior data. Important, established operational data streams are located along the shore of the study area, in areas influenced strongly by the local geometry. Failure to properly resolve the modeled near field surrounding these data results in their incorrect interpretation, causing invalid inversions and erroneous field estimates far across the shelf. Specifically, improving the model fit to the unresolved data leads to skill degeneration farther offshore and generally unacceptable field estimates remarkably far from shore. Proper near-field resolution leads to valid interpretation and inversion of the same data, with high inverse skill apparent across the shelf. The resolution required is within reach of todays technology.

Plume source detection using a process query system

A Process Query System (PQS) has the capability of filtering large volumes of real time data originating from a field of networked Physical Sensors. Modern air quality monitoring techniques such as Fourier Transform Infra-Red (FTIR) spectroscopy will eventually provide massively distributed real time contamination data at high fidelity. As large networks of these sensors are deployed, improved techniques of data retrieval and assimilation will be required. The case of detecting a diffusion event such as a hazardous chemical plume is considered. In this scenario, a plume model based on an Ensemble Kalman Filter (EnKF)is submitted to the PQS which manages multiple hypotheses explaining the current observations. The feasibility of such an application is demonstrated and results from preliminary simulations are presented.

Wind‐induced, cross‐frontal exchange on Georges Bank: A mechanism for early summer on‐bank biological particle transport

Author Posting.

The use of Lagrangian particle methods to investigate ocean-estuary exchange in well-mixed estuaries

A Lagrangian particle method which has been parallelized and embedded within a 2-D finite element code is used to study the transport and fate of contaminant plumes and ocean-estuary exchange processes in a well-mixed Gulf of Maine estuary. The particle method has been extended to include a random walk model in the horizontal that simulates sub-grid scale turbulent transport processes. This module has been formulated to allow for spatial variability in the diffusivity. The 2-D finite element model includes a porous medium transport module to treat the effects of wetting and drying of estuarine tidal flats. Due to the highly-complex, spatially dependent nature of tidal mixing and shear dispersion, contaminant transport is most naturally addressed through the Lagrangian methodology. Our approach involves instantaneous, massive particle releases that enable the quantification of ocean-estuary and inter-bay exchange along with the associated residence time. The results show that estuary-ocean exchange is significantly enhanced, and hence residence times reduced, by the presence of turbulent mixing, which combines with the effects of the sheared tidal currents to drive strong interbay exchange, and/or river input, which drives a mean throughflow. The particle approach helps to uncover the strong spatial dependent nature of the residence time within the estuary which has important ramifications for local water quality. The interbay exchanges are considered as a Markov process as discussed by Thompson et al. [11] and this framework is found to be useful.

Model initialization in a tidally energetic regime: A dynamically adjusted objective analysis

A simple improvement to objective analysis of hydrographic data is proposed to eliminate spatial aliasing effects in tidally energetic regions. The proposed method consists of the evaluation of anomalies from observations with respect to circulation model fields. The procedure is run iteratively to achieve convergence. The method is applied in the Bay of Fundy and compared with traditional objective analysis procedures and dynamically adjusted climatological fields. The hydrographic skill (difference between observed and model temperature and salinity) of the dynamically adjusted objective analysis is significantly improved by reducing bias and correcting the vertical structure. Representation of the observed velocities is also improved. The resulting flow is consistent with the known circulation in the Bay.

Wind-based convolution in limited-area coastal ocean forecasting

Coastal ocean forecasting presents important practical constraints on the limits of the forecast domain, the available data, the missing data, and the means for estimating same. The domain must contain all the relevant dynamics; the data must force same; and the real-time forecast must be fast. Here we are concerned with limited-area forecasts of 3-D transient dynamics, with necessarily extensive open boundaries and concomitant boundary conditions. The importance of inferred wind-band barotropic pressure at the open boundary is discussed, and the necessity for its inference by fitting a hindeast simulation to observations. The twin problems of dimension of the inversion, and its persistence through the forecast, potentially limit the forecast skill. On the physical hypothesis that the missing boundary conditions are the import of nonlocal wind-band dynamics: we develop a procedure for deducing boundary pressure as a convolution of observed (local) wind. This significantly reduces the rank of the inversion. leading to accelerated convergence of the conjugate gradient method iterative inverse. Additionally, the persistence of the convolution into the forecast period is far superior to the persistence of the pressure itself, and consistent with the inversion hypothesis as stated. A test case is developed and studied to illustrate these ideas and their realization in software.