Thesis (Ph. D.)--Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2010. / "June 2010." Cataloged from PDF version of thesis. / Includes bibliographical references (p. 151-159). / The Labrador Sea, as one of a few places of deep water formation, plays an important role in the Meridional Overturning Circulation. While the interior of the Labrador Sea, where the deepest convection takes place, is known to experience variability on time scales ranging from days to decades, little is known about the variability of the other components of the Labrador Sea circulation - the boundary current system and the eddies that connect it with the interior. Using various types of in situ data combined with the surface flux and satellite altimetry data products, I studied the variability of both the boundary current system and the eddies on different time scales as well as their influence on the post-convective re-stratification of the Labrador Sea interior. The analysis presented in the thesis supports the result of the previous theoretical studies that argue that lateral fluxes, driven by the boundary current/interior gradients, play an important role in the post-convective restratification of the Labrador Sea. I found that both components of the boundary current, the surface West Greenland Current and the subsurface Irminger Current, have a strong seasonal cycle. In the spring both the West Greenland and Irminger Currents are colder and fresher than in the fall. However, the West Greenland Current is faster and thicker in the spring while the Irminger Current is the fastest and thickest in the fall. My analysis suggests that the observed seasonal changes in the velocity are primarily due to the baroclinic component of the current while the barotropic component remains nearly unchanged. The Subpolar Gyre, and the Labrador Sea in particular, have experienced a decline in the circulation accompanied by the warming of the water column over the last decades. I found that a similar trend is seen in the West Greenland Current system which slowed down from 1992 to 2004, primarily due to a decrease in the barotropic flow. At the same time, the subsurface Irminger Current has become warmer, saltier, and lighter, something that is also reflected in the properties of the eddies. Two years exhibited pronounced anomalies: in 1997 and 2003 the velocity, temperature and salinity of the Irminger Current abruptly increase with respect to the overall trend. Finally, I discuss the impacts of the boundary current changes on the lateral fluxes that are responsible for the restratification of the Labrador Sea and the properties of the interior. / by Tatiana Rykova. / Ph.D.

Thesis (Ph. D.)--Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 1999. / Includes bibliographical references (leaves 129-139). / Observations of diapycnal mixing rates are examined and related to diapycnal advection for both double-diffusive and turbulent regimes. The role of double-diffusive mixing at the site of the North Atlantic Tracer Release Experiment is considered. The strength of salt-finger mixing is analyzed in terms of the stability parameters for shear and double-diffusive convection, and a nondimensional ratio of the thermal and energy dissipation rates. While the model for turbulence describes most dissipation occurring in high shear, dissipation in low shear is better described by the salt-finger model, and a method for estimating the salt-finger enhancement of the diapycnal haline diffusivity over the thermal diffusivity is proposed. Best agreement between tracer-inferred mixing rates and microstructure based estimates is achieved when the salt-finger enhancement of haline flux is taken into account. The role of turbulence occurring above rough bathymetry in the abyssal Brazil Basin is also considered. The mixing levels along sloping bathymetry exceed the levels observed on ridge crests and canyon floors. Additionally, mixing levels modulate in phase with the spring-neap tidal cycle. A model of the dissipation rate is derived and used to specify the turbulent mixing rate and constrain the diapycnal advection in an inverse model for the steady circulation. The inverse model solution reveals the presence of a secondary circulation with zonal character. These results suggest that mixing in abyssal canyons plays an important role in the mass budget of Antarctic Bottom Water. / by Louis Christopher St. Laurent. / Ph.D.

Thesis (S.M.)--Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2008. / Includes bibliographical references (p. 64-67). / Coupled ocean/atmosphere simulations exhibit systematic warm biases over the South West African (SWA) coastal region. Recent investigations indicate that coastal ocean dynamics may play an important role in determining the SST patterns, but none of them provide a detailed analysis. In this study, I analyze simulations produced both by coupled models and by idealized models. Then results are interpreted on the basis of a theoretical framework. Finally the conclusion is reached that the insufficient resolution of the ocean component in the coupled model is responsible for the warm biases over the SWA coastal region. The coarse resolution used in the ocean model has an artificially stretched coastal side-wall boundary layer, which induces a smaller upwelling velocity in the boundary layer. The vertical heat transport decreases even when the volume transport is unchanged because of its nonlinear relationship with the magnitude of the upwelling velocity. Based on the scaling of the idealized model simulations, a simplified calculation shows that the vertical heat transport is inversely proportional to the zonal resolution over the coastal region. Therefore, increasing the horizontal resolution can considerably improve the coastal SST simulation, and better resolve the coastal dynamics. / by Jinbo Wang. / S.M.

Thesis (S.M.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Biology; and the Woods Hole Oceanographic Institution), 2011. / Cataloged from PDF version of thesis. "February 2011." / Includes bibliographical references (leaves 44-48). / Trichodesmium, a genus of diazotrophic cyanobacteria, is an important contributor to the marine nitrogen (N) and carbon (C) cycles. The extent to which Trichodesmium dinitrogen (N2) fixation contributes to the marine N cycle has been modeled based on abundance data and rate estimates from surface populations. However, recent data show that Trichodesmium populations have a broad vertical distribution. The presence of previously unaccounted for subsurface populations suggests that past estimates of the contribution of new N by Trichodesmium to the North Atlantic may be artificially low. Herein, culture and field studies were combined to examine trends in N2 fixation in discrete surface and subsurface Trichodesmium populations in the western North Atlantic. Surface populations were dominated by the raft colony morphology of Trichodesmium and surface N2 fixation rates ranged from (33 to 156 μmol h-1 mol C-1). Subsurface populations were dominated by the puff colony morphology. Subsurface N2 fixation was typically detectable, but consistently lower than surface population rates (9 to 88 μmol h-1 mol C-1). In an analysis of the entire field dataset, N2 fixation rates varied non-linearly as a function of in situ irradiance. This trend in N2 fixation versus in situ irradiance is consistent with field and culture observations in the literature (Bell et al., 2005; Capone et al., 2005), however other models that predict N2 fixation based on light predict higher subsurface N2 fixation than what was detected in this study. In culture, N2 fixation in Trichodesmium was proportional to light level over the range of irradiances tested (10 to 70 μmol quanta m-2 s-1) and over long and short time scales, suggesting subtle changes in the light field could depress subsurface N2 fixation. Since the subsurface samples were dominated by the puff colony morphology, it is unclear if the subsurface N2 fixation rates are the result of the in / by Abigail Heithoff. / S.M.

Thesis (S.M.)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2006. / Includes bibliographical references (leaves 94-96). / Recent studies have shown that the presence of sand ripples on the seabed improves sonar detection of buried mines at sub-critical angles. Sidescan sonar data of ripples off on the west Florida shelf were collected as part of ONR's Ripples Departmental Research Initiative (DRI) September 26-29th and November 7-9th, 2004. Hurricane Ivan, the strongest storm of the 2004 hurricane season, passed over the experiment site a week before the first data collection. This study focuses on the ripples created by Ivan. Average relict ripple wavelengths left after the storm were found to increase with water depth (50 cm, 62 cm, and 83 cm in 20, 30, and 50 meter water depths) despite the fact that orbital diameter decreases with water depth. Ripple prediction requires information about surface gravity waves and sediment grain size. The most reliable offshore wave field available was created with Wavewatch III by Naval Postgraduate School scientists. These waves were inputted into Delft3D WAVE, incorporating the nearshore wave model SWAN to predict waves at the locations where ripples were measured. Orbital motions at the seabed and grain size were inputted into a time-dependent ripple model with varying dissipation parameters to estimate sand ripples created by Hurricane Ivan. Ripple wavelength was found to be more strongly dependent on grain size than wave dissipation. / by Colleen Marie Bowers. / S.M.

Thesis (Ph. D.)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2007. / Includes bibliographical references (p. 124-126). / This thesis introduces an algorithm for inverting for the geoacoustic properties of the seafloor in shallow water. The input data required by the algorithm are estimates of the amplitudes of the normal modes excited by a low-frequency pure-tone sound source, and estimates of the water column sound speed profiles at the source and receiver positions. The algorithm makes use of perturbation results, and computes the small correction to an estimated background profile that is necessary to reproduce the measured mode amplitudes. Range-dependent waveguide properties can be inverted for so long as they vary slowly enough in range that the adiabatic approximation is valid. The thesis also presents an estimator which can be used to obtain the input data for the inversion algorithm from pressure measurements made on a vertical line array (VLA). The estimator is an Extended Kalman Filter (EKF), which treats the mode amplitudes and eigenvalues as state variables. Numerous synthetic and real-data examples of both the inversion algorithm and the EKF estimator are provided. The inversion algorithm is similar to eigenvalue perturbation methods, and the thesis also presents a combination mode amplitude/eigenvalue inversion algorithm, which combines the advantages of the two techniques. / by Travis L. Poole. / Ph.D.

Thesis (Elec.E. and S.M. in Electrical Engineering)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2003. / "February 2003." / Includes bibliographical references (leaves 139-141). / by Andrea L. Kraay. / Elec.E.and S.M.in Electrical Engineering

Thesis: Ph. D., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 153-156). / One of the long term goals of Autonomous Underwater Vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and expert image interpretation. This thesis proposes a vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target for lower cost-per-vehicle sensing and onboard, fully autonomous classification. The contributions of this thesis include the collection of novel high-quality bistatic data sets around spherical and cylindrical targets in situ during the BayEx'14 and Massachusetts Bay 2014 scattering experiments and the development of a machine learning methodology for classifying target shape and estimating orientation using bistatic amplitude data collected by an AUV. To achieve the high quality, densely sampled 3D bistatic scattering data required by this research, vehicle broadside sampling behaviors and an acoustic payload with precision timed data acquisition were developed. Classification was successfully demonstrated for spherical versus cylindrical targets using bistatic scattered field data collected by the AUV Unicorn as a part of the BayEx'14 scattering experiment and compared to simulated scattering models. The same machine learning methodology was applied to the estimation of orientation of aspect-dependent targets, and was demonstrated by training a model on data from simulation then successfully estimating the orientations of a steel pipe in the Massachusetts Bay 2014 experiment. The final models produced from real and simulated data sets were used for classification and parameter estimation of simulated targets in real time in the LAMSS MOOS-IvP simulation environment. / by Erin Marie Fischell. / Ph. D.

Thesis: Ph. D., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 335-357). / This thesis presents a sum-product inference algorithm for in-situ, nonparametric platform navigation called Multi-modal iSAM (incremental smoothing and mapping), for problems of thousands of variables. Our method tracks dominant modes in the marginal posteriors of all variables with minimal approximation error, while suppressing almost all low likelihood modes (in a non-permanent manner) to save computation. The joint probability is described by a non-Gaussian factor graph model. Existing inference algorithms in simultaneous localization and mapping assume Gaussian measurement uncertainty, resulting in complex front-end processes that attempt to deal with non-Gaussian measurements. Existing robustness approaches work to remove "outlier" measurements, resulting heuristics and the loss of valuable information. Track different hypotheses in the system has prohibitive computational cost and and low likelihood hypotheses are permanently pruned. Our approach relaxes the Gaussian only restriction allowing the frontend to defer ambiguities (such as data association) until inference. Probabilistic consensus ensures dominant modes across all measurement information. Our approach propagates continuous beliefs on the Bayes (Junction) tree, which is an efficient symbolic refactorization of the nonparametric factor graph, and approximates the underlying Chapman-Kolmogorov equations. Like the predecessor iSAM2 max-product algorithm [Kaess et al., IJRR 2012], we retain the Bayes tree incremental update property, which allows for tractable recycling of previous computations. Several non-Gaussian measurement likelihood models are introduced, such as ambiguous data association or highly non-Gaussian measurement modalities. In addition, keeping with existing inertial navigation for dynamic platforms, we present a novel continuous-time inertial odometry residual function. Inertial odometry uses preintegration to seamlessly incorporate pure inertial sensor measurements into a factor graph, while supporting retroactive (dynamic) calibration of sensor biases. By centralizing our approach around a factor graph, with the aid of modern starved graph database techniques, concerns from different elements of the navigation ecosystem can be separated. We illustrate with practical examples how various sensing modalities can be combined into a common factor graph framework, such as: ambiguous loop closures; raw beam-formed acoustic measurements; inertial odometry; or conventional Gaussian-only likelihoods (parametric) to infer multi-modal marginal posterior belief estimates of system variables. / by Dehann Fourie. / Ph. D.

Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 177-187). / This dissertation presents three separate-but related-contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field-some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current-the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework-without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation. / by Michael Jordan Stanway. / Ph.D.