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  • 1
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    Evolution of a physical and biological front from upwelling to relaxation (2015)
    Elsevier
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Continental Shelf Research 108 (2015): 55-64, doi:10.1016/j.csr.2015.08.005.
    Description: Fronts influence the structure and function of coastal marine ecosystems. Due to the complexity and dynamic nature of coastal environments and the small scales of frontal gradient zones, frontal research is difficult. To advance this challenging research we developed a method enabling an autonomous underwater vehicle (AUV) to detect and track fronts, thereby providing high-resolution observations in the moving reference frame of the front itself. This novel method was applied to studying the evolution of a frontal zone in the coastal upwelling environment of Monterey Bay, California, through a period of variability in upwelling intensity. Through 23 frontal crossings in four days, the AUV detected the front using real-time analysis of vertical thermal stratification to identify water types and the front between them, and the vehicle tracked the front as it moved more than 10 km offshore. The physical front coincided with a biological front between strongly stratified phytoplankton-enriched water inshore of the front, and weakly stratified phytoplankton-poor water offshore of the front. While stratification remained a consistent identifier, conditions on both sides of the front changed rapidly as regional circulation responded to relaxation of upwelling winds. The offshore water type transitioned from relatively cold and saline upwelled water to relatively warm and fresh coastal transition zone water. The inshore water type exhibited an order of magnitude increase in chlorophyll concentrations and an associated increase in oxygen and decrease in nitrate. It also warmed and freshened near the front, consistent with the cross-frontal exchange that was detected in the high-resolution AUV data. AUV-observed cross-frontal exchanges beneath the surface manifestation of the front emphasize the importance of AUV synoptic water column surveys in the frontal zone.
    Description: This work was supported by the David and Lucile Packard Foundation.
    Keywords: Fronts ; Upwelling ; Relaxation ; Autonomous underwater vehicle
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
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    Autonomous four-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle (2016)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Field Robotics 33 (2016): 67-81, doi:10.1002/rob.21617
    Description: Coastal upwelling is a wind-driven ocean process that brings cooler, saltier, and nutrient-rich deep water upward to the surface. The boundary between the upwelling water and the normally stratified water is called the “upwelling front.” Upwelling fronts support enriched phytoplankton and zooplankton populations, thus they have great influences on ocean ecosystems. Traditional ship-based methods for detecting and sampling ocean fronts are often laborious and very difficult, and long-term tracking of such dynamic features is practically impossible. In our prior work, we developed a method of using an autonomous underwater vehicle (AUV) to autonomously detect an upwelling front and track the front's movement on a fixed latitude, and we applied the method in scientific experiments. In this paper, we present an extension of the method. Each time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to recross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzag tracks alternate in northward and southward sweeps, so as to track the front as it moves over time. This way, the AUV maps and tracks the front in four dimensions—vertical, cross-front, along-front, and time. From May 29 to June 4, 2013, the Tethys long-range AUV ran the algorithm to map and track an upwelling front in Monterey Bay, CA, over five and one-half days. The tracking revealed spatial and temporal variabilities of the upwelling front.
    Description: This work was supported by the David and Lucile Packard Foundation.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
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    Pump it Up workshop report (2017)
    Woods Hole Oceanographic Institution
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    Publication Date: 2022-05-25
    Description: Workshop held 28-29 September 2017, Cape Cod, MA
    Description: A two-day workshop was conducted to trade ideas and brainstorm about how to advance our understanding of the ocean’s biological pump. The goal was to identify the most important scientific issues that are unresolved but might be addressed with new and future technological advances.
    Keywords: Biological pump
    Repository Name: Woods Hole Open Access Server
    Type: Working Paper
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  • 4
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    Detection of unanticipated faults for autonomous underwater vehicles using online topic models (2018)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Field Robotics 35 (2018): 705-716, doi:10.1002/rob.21771.
    Description: For robots to succeed in complex missions, they must be reliable in the face of subsystem failures and environmental challenges. In this paper, we focus on autonomous underwater vehicle (AUV) autonomy as it pertains to self‐perception and health monitoring, and we argue that automatic classification of state‐sensor data represents an important enabling capability. We apply an online Bayesian nonparametric topic modeling technique to AUV sensor data in order to automatically characterize its performance patterns, then demonstrate how in combination with operator‐supplied semantic labels these patterns can be used for fault detection and diagnosis by means of a nearest‐neighbor classifier. The method is evaluated using data collected by the Monterey Bay Aquarium Research Institute's Tethys long‐range AUV in three separate field deployments. Our results show that the proposed method is able to accurately identify and characterize patterns that correspond to various states of the AUV, and classify faults at a high rate of correct detection with a very low false detection rate.
    Description: Office of Naval Research Grant Number: N00014‐14‐1‐0199; David and Lucile Packard Foundation
    Keywords: Autonomous underwater vehicle (AUV) ; Autonomy ; Fault detection and diagnosis ; Topic modeling
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
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    Targeted sampling by autonomous underwater vehicles (2019)
    Frontiers Media
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    Publication Date: 2022-10-20
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, Y., Ryan, J. P., Kieft, B., Hobson, B. W., McEwen, R. S., Godin, M. A., Harvey, J. B., Barone, B., Bellingham, J. G., Birch, J. M., Scholin, C. A., & Chavez, F. P. Targeted sampling by autonomous underwater vehicles. Frontiers in Marine Science, 6 (2019): 415, doi:10.3389/fmars.2019.00415.
    Description: In the vast ocean, many ecologically important phenomena are temporally episodic, localized in space, and move according to local currents. To effectively study these complex and evolving phenomena, methods that enable autonomous platforms to detect and respond to targeted phenomena are required. Such capabilities allow for directed sensing and water sample acquisition in the most relevant and informative locations, as compared against static grid surveys. To meet this need, we have designed algorithms for autonomous underwater vehicles that detect oceanic features in real time and direct vehicle and sampling behaviors as dictated by research objectives. These methods have successfully been applied in a series of field programs to study a range of phenomena such as harmful algal blooms, coastal upwelling fronts, and microbial processes in open-ocean eddies. In this review we highlight these applications and discuss future directions.
    Description: This work was supported by the David and Lucile Packard Foundation. The 2015 experiment in Monterey Bay was partially supported by NOAA Ecology and Oceanography of Harmful Algal Blooms (ECOHAB) Grant NA11NOS4780030. The 2018 SCOPE Hawaiian Eddy Experiment was partially supported by the National Science Foundation (OCE-0962032 and OCE-1337601), Simons Foundation Grant #329108, the Gordon and Betty Moore Foundation (Grant #3777, #3794, and #2728), and the Schmidt Ocean Institute for R/V Falkor Cruise FK180310. Publication of this paper was funded by the Schmidt Ocean Institute.
    Keywords: Targeted sampling ; Autonomous underwater vehicle (AUV) ; Environmental Sample Processor (ESP) ; Phytoplankton patch ; Upwelling front ; Open-ocean eddy
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
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    Autonomous tracking and sampling of the deep chlorophyll maximum layer in an open-ocean eddy by a long-range autonomous underwater vehicle (2020)
    Institute of Electrical and Electronics Engineers
    Details
    Publication Date: 2022-05-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, Y., Kieft, B., Hobson, B. W., Ryan, J. P., Barone, B., Preston, C. M., Roman, B., Raanan, B., Marin,Roman,,III, O'Reilly, T. C., Rueda, C. A., Pargett, D., Yamahara, K. M., Poulos, S., Romano, A., Foreman, G., Ramm, H., Wilson, S. T., DeLong, E. F., Karl, D. M., Birch, J. M., Bellingham, J. G., & Scholin, C. A. Autonomous tracking and sampling of the deep chlorophyll maximum layer in an open-ocean eddy by a long-range autonomous underwater vehicle. IEEE Journal of Oceanic Engineering, 45(4), (2020): 1308-1321, doi:10.1109/JOE.2019.2920217.
    Description: Phytoplankton communities residing in the open ocean, the largest habitat on Earth, play a key role in global primary production. Through their influence on nutrient supply to the euphotic zone, open-ocean eddies impact the magnitude of primary production and its spatial and temporal distributions. It is important to gain a deeper understanding of the microbial ecology of marine ecosystems under the influence of eddy physics with the aid of advanced technologies. In March and April 2018, we deployed autonomous underwater and surface vehicles in a cyclonic eddy in the North Pacific Subtropical Gyre to investigate the variability of the microbial community in the deep chlorophyll maximum (DCM) layer. One long-range autonomous underwater vehicle (LRAUV) carrying a third-generation Environmental Sample Processor (3G-ESP) autonomously tracked and sampled the DCM layer for four days without surfacing. The sampling LRAUV's vertical position in the DCM layer was maintained by locking onto the isotherm corresponding to the chlorophyll peak. The vehicle ran on tight circles while drifting with the eddy current. This mode of operation enabled a quasi-Lagrangian time series focused on sampling the temporal variation of the DCM population. A companion LRAUV surveyed a cylindrical volume around the sampling LRAUV to monitor spatial and temporal variation in contextual water column properties. The simultaneous sampling and mapping enabled observation of DCM microbial community in its natural frame of reference.
    Description: 10.13039/501100008982 - National Science Foundation 10.13039/100000936 - Gordon and Betty Moore Foundation 10.13039/100000008 - David and Lucile Packard Foundation 10.13039/100016377 - Schmidt Ocean Institute 10.13039/100000893 - Simons Foundation
    Keywords: Autonomous underwater vehicle (AUV) ; eddy ; Environmental Sample Processor (ESP) ; phytoplankton ; sampling ; tracking
    Repository Name: Woods Hole Open Access Server
    Type: Article
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