Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 119-126). / Developing accurate and computationally efficient models for ocean acoustics is inherently challenging due to several factors including the complex physical processes and the need to provide results on a large range of scales. Furthermore, the ocean itself is an inherently dynamic environment within the multiple scales. Even if we could measure the exact properties at a specific instant, the ocean will continue to change in the smallest temporal scales, ever increasing the uncertainty in the ocean prediction. In this work, we explore ocean acoustic prediction from the basics of the wave equation and its derivation. We then explain the deterministic implementations of the Parabolic Equation, Ray Theory, and Level Sets methods for ocean acoustic computation. We investigate methods for evolving stochastic fields using direct Monte Carlo, Empirical Orthogonal Functions, and adaptive Dynamically Orthogonal (DO) differential equations. / As we evaluate the potential of Reduced-Order Models for stochastic ocean acoustics prediction, for the first time, we derive and implement the stochastic DO differential equations for Ray Tracing (DO-Ray), starting from the differential equations of Ray theory. With a stochastic DO-Ray implementation, we can start from non-Gaussian environmental uncertainties and compute the stochastic acoustic ray fields in a reduced order fashion, all while preserving the complex statistics of the ocean environment and the nonlinear relations with stochastic ray tracing. We outline a deterministic Ray-Tracing model, validate our implementation, and perform Monte Carlo stochastic computation as a basis for comparison. We then present the stochastic DO-Ray methodology with detailed derivations. We develop varied algorithms and discuss implementation challenges and solutions, using again direct Monte Carlo for comparison. / We apply the stochastic DO-Ray methodology to three idealized cases of stochastic sound-speed profiles (SSPs): constant-gradients, uncertain deep-sound channel, and a varied sonic layer depth. Through this implementation with non-Gaussian examples, we observe the ability to represent the stochastic ray trace field in a reduced order fashion. / by Michael Jesus Humara. / S.M. / S.M. Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: S.M., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), September, 2020 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 97-102). / Robotic swarms are becoming increasingly complex on the surface and in air due to highspeed and reliable communication links, Global Positioning Satellites (GPS), and visual support to relative navigation. However, the limited propagation of these signals in the ocean has impacted similar advances in undersea robotics. Autonomous underwater vehicles (AUVs) often rely on acoustics to inform navigation solutions; however, this approach presents challenges for scalable robotic swarms. Acoustic navigation is a means to inform range and bearing to a target. Many methods for range and bearing estimation, including current low-cost solutions, rely on precision time synchronization or two-way communication to compute ranges as part of a full navigation solution. The high cost of reliable Chip-scale atomic clocks (CSACs) and acoustic modems relative to other vehicle components limits large-scale swarms due to the associated cost-per-vehicle and communications infrastructure. / We propose a single, high-cost vehicle with a reliable navigation solution as a "leader" for a scalable swarm of lower-cost vehicles that receive acoustic signals from a source onboard the lead vehicle using a single hydrophone. These lower-cost "followers" navigate relative to the leader according to the preferred behavioral pattern, but for simplicity, we will refer to a simple following behavior in this work. This thesis outlines a method to obtain range estimates to sound sources in which the signal content, including frequency and power at its origin, can be reasonably approximated. Total transmission loss is calculated based on empirical equations for the absorption of sound in seawater and combined with geometric spreading loss from environmental models to estimate range to a source based on the loss at differential frequencies. We refer to this calculation as the signal absorption-based range estimator (SABRE). / This method for obtaining range combines with Doppler-shift methods for target bearing based on the maximum frequency detected within a banded limit around a known source frequency. A primary objective for SABRE is to address techniques that support low-cost options for undersea swarming. This thesis's contributions include a novel method for range estimation onboard underwater autonomous vehicles that supports navigation relative to a known source when combined with Doppler-shift methods for target bearing. This thesis seeks to develop the theory, algorithms, and analytical tools required and apply those tools to real-world data sets to investigate the feasibility, sources of error, and accuracy of this new approach to range estimation for underwater swarms. / by Brendan O'Neill. / S.M. / S.M. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: Ph. D., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2020 / Cataloged from student-submitted PDF of thesis. "September 2020." / Includes bibliographical references. / Speleothems, or sedimentary rocks formed in caves, act as valuable archives of past climate change due to their suitability for U-series dating and high-resolution proxy analysis. These records can provide insights into water availability and controls on hydrology prior to the instrumental record. In this thesis, I present three records from newly-analyzed Mexican stalagmites using stable isotope (oxygen and carbon) and trace element to calcium (Mg/Ca and Sr/Ca) ratios as proxies for changing hydroclimate. Chapter 2 presents a precisely dated, mid- Holocene record of high rainfall and limited precipitation variability in the Yucatan Peninsula, Mexico. Chapters 3 and 4 present novel climate records from northeastern Mexico, an understudied region of North America. Both records come from cave sites within the Mexican arid zone, which is simultaneously experiencing increased water scarcity and a rapidly growing population. In Chapter 3, I examine a speleothem from the first millennium of the Common Era, which showed that there is a precipitation dipole between northern and southern Mexico. Chapter 4 highlights, for the first time at decadal resolution, the northeast Mexican response to the 8.2 ka event and the Younger Dryas. These chapters show that the San Luis Potosí region is vulnerable to droughts under multiple climate mean states, and is subject to drying as Atlantic Meridional Overturning Circulation weakens due to anthropogenic climate change. The climate records detailed in this thesis improve our understanding of controls on Mexican hydroclimate and can serve as benchmarks for climate models. / by Gabriela Serrato Marks. / Ph. D. / Ph.D. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution)

Thesis: Ph. D., Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Department of Aeronautics and Astronautics; and the Woods Hole Oceanographic Institution), 2020 / Cataloged from student-submitted PDF of thesis. / Includes bibliographical references (pages 181-198). / Sea ice thickness has long been an under-measured quantity, even in the satellite era. The snow surface elevation, which is far easier to measure, cannot be directly converted into sea ice thickness estimates without knowledge or assumption of what proportion of the snow surface consists of snow and ice. We do not fully understand how snow is distributed upon sea ice, in particular around areas with surface deformation. Here, we show that deep learning methods can be used to directly predict snow depth, as well as sea ice thickness, from measurements of surface topography obtained from laser altimetry. We also show that snow surfaces can be texturally distinguished, and that texturally-similar segments have similar snow depths. This can be used to predict snow depth at both local (sub-kilometer) and satellite (25 km) scales with much lower error and bias, and with greater ability to distinguish inter-annual and regional variability than current methods using linear regressions. We find that sea ice thickness can be estimated to <20% error at the kilometer scale. The success of deep learning methods to predict snow depth and sea ice thickness suggests that such methods may be also applied to temporally/spatially larger datasets like ICESat-2. / by M. Jeffrey Mei. / Ph. D. / Ph.D. Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Department of Aeronautics and Astronautics; and the Woods Hole Oceanographic Institution)

Thesis: S.M., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2020 / Cataloged from student-submitted PDF of thesis. / Includes bibliographical references (page 85). / Advances in the miniaturization of microelectronics has greatly contributed to the proliferation of small, low cost autonomous underwater vehicles (AUVs). These affordable vehicles offer organizations a flexible platform that can be adapted to support a multitude of research goals. The small size and low entry cost come with a trade off of simple navigation systems, typically dead reckoning (DR) using a speed determined via propeller counts and heading from a low cost micro-electromechanical system (MEMS) inertial measurement unit (IMU), whose error grows unbounded without the availability of a ground referenced fix source and is compounded by the bias present in the speed measurement due to the change in hydrodynamics from the addition of sensors to the hull form. Additionally, some capabilities such as water current velocity measurement traditionally requires the addition of equipment that is not only expensive, but also whose size and power consumption can adversely affect operating characteristics and deployment times. This thesis expands on previous research using one-way travel time inverted USBL (OWTT-iUSBL) to calculate the local current velocity without the addition of a Doppler velocity log (DVL) or acoustic Doppler current profiler (ADCP). A novel extended Kalman filter (EKF) is proposed that, in addition to calculating the current velocity, estimates and corrects for the bias present in the speed measurement as determined by the main vehicle computer. Using data collected on the Charles River at the Massachusetts Institute of Technology (MIT) Sailing Pavilion, it is shown that current velocities can be reasonably calculated using OWTT-iUSBL data as compared to the values calculated using long baseline (LBL) data. / by Christopher R. Dolan. / S.M. / S.M. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: S.M., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), September, 2020 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 73-74). / Underwater Vehicles generally have control fins located only near their aft end, for making controllable changes in directions. This design allows for stability of control; however, the turns are typically large in comparison to the vehicle body length. Some bony fish, such as tuna, on the other hand, have deployable ventral and dorsal fins located towards the front of their body, in addition to their other fins. Their deployable fins allow them to modulate their hydrodynamic behavior in response to their environment. Tunas keep these fins retracted during steady cruising, and then deploy them during rapid maneuvers. However, the details of these hydrodynamic effects are not well understood. To investigate this phenomena, using a REMUS 100 as a model, a pair of vertical fins was added at different hull positions, to investigate the effects of fin location on the horizontal plane hydrodynamics, through: stability parameters, nonlinear simulation, and towing tank experiments. Depending on the added fin location, the stability of the vehicle changed, thereby affecting the maneuverability. As fins were placed further forward on the vehicle, maneuverability increased, with effects tapering off at 0.2 BL ahead of the vehicle's center of buoyancy. This investigation explored how rigid underwater vehicles could benefit from added fins, without drastically changing the design of current vehicles. / by Nastasia Elizabeth Winey. / S.M. / S.M. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: S.M., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), September, 2020 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 103-107). / This thesis examines the transition of a vessel from the open ocean, where collisions are rare, to a high risk and heavy traffic area such as a Traffic Separation Scheme (TSS). Previous autonomy approaches generally view path planning and collision avoidance as two separate functions, i.e. a vessel will follow the planned path until conditions are met for collision avoidance algorithms to take over. Here an intermediate phase is proposed with the goal of adjusting the time of arrival to a high vessel density area so that the risk of collision is reduced. A general algorithm that calculates maximum future traffic density for all choices in the speed domain is proposed and implemented as a MOOS-IvP behavior. This behavior gives the vessel awareness of future collision risks and aids the collision avoidance process. This new approach improves the safety of the vessel by reducing the number of risky encounters that will likely require the vessel to maneuver for safety. / by John Zhang Li. / S.M. / S.M. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: Ph. D., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2020 / Cataloged from student-submitted PDF of thesis. / Includes bibliographical references (pages 211-226). / Atlantic hurricanes threaten growing coastal populations along the U.S. coastline and in the Caribbean islands. Unfortunately, little is known about the forces that alter hurricane activity on multi-decadal to centennial timescales. This thesis uses proxy development and proxy-model integration to constrain the spatiotemporal variability in hurricane activity in the Bahama Archipelago over the past millennium. I present annually-resolved archives of storm activity stretching over the past 1000 to 1500 years in sediment cores from blue holes on three islands in the Bahama Archipelago: South Andros Island, Long Island, and Middle Caicos Island. I explore the sensitivity of each site to coarse-grained sediment deposition for modern storms. I find that the local geomorphologic conditions and the angle of approach and size of passing storms play a more important role in inducing coarse-grained sediment transport than storm intensity. / All three paleorecords capture multi-decadal and longer periods of elevated hurricane activity over the past millennium. Dramatic differences between these records suggest localized controls on the hurricane patterns observed by each island. Thus, compiling the records from this thesis together more accurately captures regional variations in hurricane strikes. Integrating our new Bahama Archipelago compilation with compiled paleohurricane records from the U.S. coastline indicates shifting patterns of hurricane activity over the past millennium between the Gulf Coast and the Bahama Archipelago/New England. I attribute these shifting storm patterns to changes in local environmental conditions and/or large-scale variations in hurricane tracks. Finally, I address whether variability in hurricane strikes observed in Bahamian paleohurricane records is related to climate or random variability. / Using a large suite of synthetic storms run over past millennium climate, I generate 1000 pseudo paleohurricane records containing centennial-scale signal like our proxy reconstructions. However, the signal observed in any individual record of paleohurricane activity from the Bahama Archipelago is driven more by random variability in hurricane tracks than by climate. This thesis lays the groundwork for creating high-resolution paleohurricane records from coastal karst basins and using hurricane models to inform our interpretations of these records. / by Elizabeth Jane Wallace. / Ph. D. / Ph.D. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution)

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2019 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 129-132). / This thesis evaluates automated open-circuit scuba diver detection using low-cost passive sonar and machine learning. Previous automated passive sonar scuba diver detection systems required matching the frequency of diver breathing transients to that of an assumed diver breathing frequency. Earlier work required prior knowledge of both the number of divers and their breathing rate. Here an image processing approach is used for automated diver detection by implementing a deep convolutional neural network. Image processing was chosen because it is a proven method for sonar classification by trained human operators. The system described here is able to detect a scuba diver from a single acoustic emission from the diver. Twenty dives were conducted in support of this work at the WHOI pier from October 2018 to February 2019. The system, when compared to a trained human operator, correctly classified approximately 93% of the data. When sequential processing techniques were applied, system accuracy rose to 97%. This demonstrated that a combination of low-cost, passive sonar and a properly tuned convolutional neural network can detect divers in a noisy environment to a range of at least 12.49 m (50 feet). / by Andrew M. Cole. / S.M. / S.M. Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution)

Thesis: Ph. D., Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), May, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 161-183). / Highly productive marine microbial communities in the coastal Southern Ocean sustain the broader Antarctic ecosystem and play a key role in Earth's climate via the biological pump. Regional phytoplankton growth is primarily limited by iron and co-limited by cobalamin (vitamin B₁₂), a trace cobalt-containing organometallic compound only synthesized by some bacteria and archaea. These micronutrients impact primary production and the microbial ecology of the two keystone phytoplankton types: diatoms and Phaeocystis antarctica. This thesis investigates microbe-driven cobalamin cycling in Antarctic seas across multiple spatiotemporal scales. I conducted laboratory culture experiments with complementary proteomics and transcriptomics to investigate the B₁₂-ecophysiology of P. antarctica strain CCMP 1871 morphotypes under iron-B₁₂ co-limitation. / We observed colony formation under higher iron treatments, and a facultative use of B₁₂-dependent (MetH) and B₁₂-independent (MetE) methionine synthase isoforms in response to vitamin availability, demonstrating that this strain is not B₁₂-auxotrophic. Through comparative 'omics, we identified a putative MetE protein in P. antarctica abundant under low B₁₂, which is also found in other marine microbes. Across Antarctic seas, community-scale cobalt and B₁₂ uptake rates were measured by ⁵⁷Co radiotracer incubation experiments and integrated with hydrographic and phytoplankton pigment data. I observed significant correlations between uptake fluxes and environmental variables, providing evidence for predominantly diatom-driven uptake of these micronutrients in warmer, fresher surface waters with notable regional differences. / To date, this work is the most comprehensive attempt to elucidate the processes governing the co-cycling of cobalt and B₁₂ in any marine system. At the ecosystem-scale, I developed and tested a hypothesis of micronutrient-driven community dynamics through a trait-based model with cross-feeding interactions. The model demonstrates how the observed seasonal succession of springtime P. antarctica from solitary to colonial cells, bacterioplankton, and summertime diatoms may be explained by the microbial cycling of iron, dissolved organic carbon, and B₁₂. Overall, this dissertation provides new information about the micronutrient-driven ecology of Antarctic marine microbes and adds to our understanding of the interconnections between organismal life cycle, trace metals, and trace organics in marine environments. / by Deepa Rao. / Ph. D. / Ph.D. Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution)