Utilizing Extended Continental Shelf (ECS) and Ocean Exploration Mapping Data for Standardized Marine Ecological Classification of the U.S. Atlantic Margin

Accurate maps of ocean bathymetry and seafloor habitats are needed to support effective marine ecosystem-based management (EBM) approaches. The central premise of this thesis was to synthesize geomorphological elements of large regions of the deep ocean seafloor to establish standards of characterization for ecosystem-based classification. The approach was to apply semi-automated characterization techniques on seafloor bathymetric data that were originally collected for other purposes. The purpose of generating these maps is ultimately to apply to informing ecosystem-based management for large marine regions. While seafloor classification techniques for habitat classification have been applied in shallow water and generally over more local regions, these techniques have never before been applied at continental-margin scales in such deep water. Over the past decade, the United States has made a substantial investment in seafloor mapping efforts covering over 2.5 million square kilometers of the nation’s potential extended continental shelf (ECS) regions, which extend into deep ocean areas beyond 200 nautical miles from the nation’s shoreline. The entire potential ECS region off the U.S. Atlantic margin has been mapped by researchers at the University of New Hampshire’s Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). Extensive complimentary mapping datasets collected by the National Oceanic and Atmospheric Administration’s Office of Ocean Exploration and Research (NOAA OER) have been acquired in adjacent U.S. waters off the East Coast covering the continental slope submarine canyons region and a majority of the Blake Plateau. The focus of this thesis is on demonstrating that data gathered with the initial purpose of establishing a potential extended continental shelf claim can further be used to support EBM efforts and sound marine spatial planning. The approaches developed here could be effectively applied to ECS and ocean exploration data sets collected world-wide to leverage substantial additional value from broad-scale ocean mapping efforts. This thesis posited and tested three hypotheses: 1) Broad-scale bathymetric data of the U.S. Atlantic margin collected for ECS and deep sea exploration purposes are useful to consistently classify ecological marine units of the seafloor and generate value-added characterization maps of large regions. 2) Transparent, repeatable, and efficient semi-automated geomorphic analysis methods employing the Coastal and Marine Ecological Classification Standard (CMECS) as an organizational framework produce useful habitat characterization maps of the U.S. Atlantic margin. 3) Vulnerable cold-water coral (CWC) habitats are identifiable and able to be inventoried and characterized using geomorphic analysis and CMECS classification of bathymetric data. These three research hypotheses were tested through classification and characterization studies of three distinct regions of the U.S. Atlantic margin at different scales (an individual seamount feature, the continental slope and abyssal plains, and a continental margin borderland) ranging across a diversity of marine habitats. An automatic segmentation approach to initially identify landform features from the bathymetry of these study areas was completed and then translated into CMECS classification terminology. Geomorphic terrain classification methods were applied to the continental slope and the abyssal plain of the U.S. Atlantic margin ECS region covering a 959,875 km2 area. Landform features derived from the bathymetry were then translated into complete coverage geomorphology maps of the region utilizing CMECS to define geoforms. Abyssal flats made up more than half of the area (53%), with the continental slope flat class making up another 30% of the total area. Flats of any geoform class (including continental shelf flats and guyot flats) made up 83.06% of the study area. Slopes of any geoform classes make up a cumulative total of 13.26% of the study region (8.27% abyssal slopes, 3.73% continental slopes, 1.25% seamount slopes), while ridge features comprise only 1.82% of the total study area (1.03% abyssal ridges, 0.63 continental slope ridge, and 0.16% seamount ridges). Using methods developed to classify the ECS dataset, bathymetric data from twenty multibeam sonar mapping surveys of the Blake Plateau region were used to derive a standardized geomorphic classification capable of quantifying cold-water coral (CWC) mound habitats. Results documented the most extensive CWC mound province thus far discovered and reported in the literature. Nearly continuous CWC mound features span an area up to 472 km long and 88 km wide, with a core area of high density mounds up to 248 km long by 35 km wide. A total of 59,760 individual peak features were delineated, providing the first estimate of the overall number of potential CWC mounds mapped in the Blake Plateau region to date. Five geomorphic landform classes were mapped and quantified: peaks (342 km2), valleys (2,883 km2), ridges (2,952 km2), slopes (15,227 km2), and flats (49,003 km2). The complex geomorphology of eight subregions was described qualitatively with geomorphic “fingerprints” and quantitatively by measurements of mound density and vertical relief. Ground-truth from 23 submersible dive videos revealed coral rubble to be the dominant substrate component within the peak, ridge, and slope landforms explored, thereby validating the interpretation of these bathymetric features as CWC mounds. Results indicated that the Blake Plateau supports a globally exceptional CWC mound province of heretofore unprecedented scale (at least for now) and diverse morphological complexity. This dissertation has successfully characterized the geomorphology of vast regions of the deep ocean floor off the U.S. Atlantic margin for ecosystem-based management purposes. It has applied techniques and established standards of classification that can be applied to other regions throughout the World. This latter point is critical as there are ongoing international efforts today to map the entirety of the World\u27s oceans at meaningful scales and these techniques can synthesize this information in meaningful ways. Furthermore, the need for such syntheses is paramount in order to successful manage (conserve and preserve) the living and non-living resources of the ocean. This thesis shows a way forward for such endeavors, and emphasizes 1) the applicability of data acquired for other purposes to be applied to this purpose, and 2) the need for standards to define and describe marine habitats so that all governments, managers, biologists, geoscientists, and other ocean stakeholders communicate using the same language

Climate in Earth history

Complex atmosphere-ocean-land interactions govern the climate system and its variations. During the course of Earth history, nature has performed a large number of experiments involving climatic change; the geologic record contains much information regarding these experiments. This information should result in an increased understanding of the climate system, including climatic stability and factors that perturb climate. In addition, the paleoclimatic record has been demonstrated to be useful in interpreting the origin of important resources-petroleum, natural gas, coal, phosphate deposits, and many others

Intra- and supra-salt strain during gravity-driven salt tectonics on passive margins

Ductile salt units have a profound influence on the subsequent tectono-stratigraphic evolution of sedimentary basins. The development of thin-skinned, kinematic zones of updip extension and downdip contraction, driven by the interplay between gravity gliding and gravity spreading, is well established. In detail, however, there is great complexity in the range of structural styles observed on salt-influenced passive margins, and their key controls are still not fully understood. I use 3D seismic reflection data from two salt-influenced passive margin settings (the Kwanza Basin, offshore Angola and the Levantine Basin, offshore Lebanon) to interpret their post-salt tectono-stratigraphic evolutions. I assess the relationship between sub-, intra-, and supra-salt structures, with a particular emphasis on the influence of base-salt relief and intra-salt lithological heterogeneity. A number of different tools are employed to perform this analysis, including structural restorations, strain calculations and translation measurements. Ramp syncline basins develop due to salt flow over base-salt relief and provide a record of horizontal overburden translation during gravity gliding. This record can be used to calculate rates of translation, revealing spatial and temporal variations at the basin scale in both study areas, which are linked to thick- and thin-skinned processes. On the Angolan margin, the interaction of salt flow with base-salt relief is inferred to generate local stress fields that allow synchronous extension and contraction despite closely spaced positions on the margin. On the Lebanese margin, the salt flow over large sub-salt anticlines modulates the rate of basinward translation. In both cases I show that the geometry of the base-salt surface can have an important influence on the orientation and distribution of supra-salt structures. The seismic-based interpretations are tested using physical analogue models, designed to investigate the effect of salt thickness and heterogeneity on the degree of coupling between sub- and supra-salt structures in experiments with controlled boundary conditions. These results support and integrate the seismic case studies, showing how thinner and more heterogeneous evaporite sequences are more strongly influenced by the base-salt geometry. I conclude that the interaction between salt flow and base-salt relief is a primary control on the structural development of the salt and overburden in gravity-driven systems, and this may explain some of the observed contrast in structural styles between different salt basins.Open Acces

Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Technical ReportThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Numerical modeling of submarine hydrothermal fluid flow

Mid-ocean ridges and volcanic passive continental margins are prime regions to explore active and extinct hydrothermal systems. In both settings, a large number of hydrothermal vents have already been discovered by direct observations and/or geophysical surveys. The growing interest in these systems results from their relevance for different fields of marine sciences. For example, commercially interesting ore deposits form as a byproduct of hydrothermal venting at the seafloor, unique ecosystems evolve around submarine vent sites, and hydrothermal systems driven by sill intrusions into organic sediments are related to hydrocarbon maturation and even venting of greenhouse gases into the atmosphere. Numerical simulations of hydrothermal fluid flow can help to gain a quantitative understanding of the subsurface physicochemical processes that control these systems. This thesis contributes to a better understanding of hydrothermalism in oceanic and continental settings by presenting a newly developed hydrothermal flow model and two case studies of hydrothermal flow at mid-ocean ridges and volcanic passive margins. To explore the effects of bathymetric relief on hydrothermal fluid flow in submarine settings, a systematic study has been carried out using 375 simulations. These simulations show that temperature-induced pressure variations in the subsurface result in the deviation of hydrothermal plumes towards bathymetric highs in submarine settings. The plume deviation from its origin is directly related to the surface slope and depth of the heat source. A case study for the fast-spreading East Pacific Rise at 9° 30’N shows that bathymetric effects help to focus venting directly onto the ridge axis – only if bathymetry is taken into account can across axis fluid flow be reconciled with exclusive on-axis venting. A second case study for the slow-spreading Lucky Strike segment of the Mid-Atlantic Ridge shows that also here venting is likely to occur at local bathymetric highs. The effects of hydrothermal convection triggered by sill intrusions in continental settings have been explored in a case-study for the Gjallar Ridge area on the Norwegian margin. This area is affected by a swarm of sill intrusions originated from North-Atlantic continental break-up during the Paleocene-Eocene transition as well as pre-break-up faults resulting from extensional tectonics. The structures are interpreted using 3D multichannel seismic data in combination with a structural and thermal reconstruction of the margin using TECMOD software. The reconstructed temperature is used as initial condition for sediments prior to sill injection and the detailed thermal history of sediments is modeled by a 2D fluid flow simulation. The simulation results show that high-temperature venting (>200°C) occurs less than 1000 years following sill emplacement. The faults play strong roles for transferring the fluids to far-off regions. As a result of circulating hot fluids, the maturity of sedimentary rocks is greatly enhanced, especially where the hot fluids are trapped below impermeable sills during their ascent, thereby suggesting potential zones for future hydrocarbon explorations. Furthermore, solution strategies for modeling hydrothermal fluid flow by finite element, finite volume and semi-Lagrangian methods are explained in particular in order to find out how the temperature equation is solved. Different schemes of fully-implicit, Crank-Nicolson and exponential for temperature diffusion and finite volume and semi-Lagrangian for temperature advection are evaluated. The results suggest that the most accurate method for solving temperature diffusion is Crank-Nicolson. However, other methods such as fully implicit and exponential are still valid. The mass conserving finite volume method is the most accurate method for solving temperature advection; however, limited time-stepping is its major drawback and thus semi-Lagrangian method is usually preferred. Therefore, the definition of optimum method is linked to the accuracy of interest and complexity of the media

Ranked Similarity Search of Scientific Datasets: An Information Retrieval Approach

In the past decade, the amount of scientific data collected and generated by scientists has grown dramatically. This growth has intensified an existing problem: in large archives consisting of datasets stored in many files, formats and locations, how can scientists find data relevant to their research interests? We approach this problem in a new way: by adapting Information Retrieval techniques, developed for searching text documents, into the world of (primarily numeric) scientific data. We propose an approach that uses a blend of automated and curated methods to extract metadata from large repositories of scientific data. We then perform searches over this metadata, returning results ranked by similarity to the search criteria. We present a model of this approach, and describe a specific implementation thereof performed at an ocean-observatory data archive and now running in production. Our prototype implements scanners that extract metadata from datasets that contain different kinds of environmental observations, and a search engine with a candidate similarity measure for comparing a set of search terms to the extracted metadata. We evaluate the utility of the prototype by performing two user studies; these studies show that the approach resonates with users, and that our proposed similarity measure performs well when analyzed using standard Information Retrieval evaluation methods. We performed performance tests to explore how continued archive growth will affect our goal of interactive response, developed and applied techniques that mitigate the effects of that growth, and show that the techniques are effective. Lastly, we describe some of the research needed to extend this initial work into a true Google for data

ICASE/LaRC Symposium on Visualizing Time-Varying Data

Time-varying datasets present difficult problems for both analysis and visualization. For example, the data may be terabytes in size, distributed across mass storage systems at several sites, with time scales ranging from femtoseconds to eons. In response to these challenges, ICASE and NASA Langley Research Center, in cooperation with ACM SIGGRAPH, organized the first symposium on visualizing time-varying data. The purpose was to bring the producers of time-varying data together with visualization specialists to assess open issues in the field, present new solutions, and encourage collaborative problem-solving. These proceedings contain the peer-reviewed papers which were presented at the symposium. They cover a broad range of topics, from methods for modeling and compressing data to systems for visualizing CFD simulations and World Wide Web traffic. Because the subject matter is inherently dynamic, a paper proceedings cannot adequately convey all aspects of the work. The accompanying video proceedings provide additional context for several of the papers

Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets