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  • 1
    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 Geophysical Research: Oceans 120 (2015): 5932–5944, doi:10.1002/2015JC010914.
    Description: The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance using the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-ice light field on small scales (〈1000 m2), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.
    Description: U.S. National Science Foundation Office of Polar Programs NSF OPP ANT-1126311, National Oceanic and Atmospheric Administration Office of Exploration and Research NOAA OER NA14OAR4320158, European Research Council Advanced Investigator Grant Number: 294757
    Keywords: Melt ponds ; Light transmittance ; Albedo ; ROV ; Spatial variability ; Shortwave radiation
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2022-10-20
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Barker, L. D. L., Jakuba, M., V., Bowen, A. D., German, C. R., Maksym, T., Mayer, L., Boetius, A., Dutrieux, P., & Whitcomb, L. L. Scientific challenges and present capabilities in underwater robotic vehicle design and navigation for oceanographic exploration under-ice. Remote Sensing, 12(16), (2020): 2588, doi:10.3390/rs12162588.
    Description: This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice).
    Description: Barker and Whitcomb gratefully acknowledge the support of the National Science Foundation under Award 1319667 and 1909182, and support of the first author under a Graduate Fellowship from the Johns Hopkins Department of Mechanical Engineering. Jakuba, Bowen, and German gratefully acknowledge the support of the National Aeronautics and Space Administration under Planetary Science and Technology through Analog Research (PSTAR) award NNX16AL04G. Maksym was supported by National Science Foundation Award CMMI-1839063. Dutrieux was supported by his Center for Climate and Life Fellowship from the Earth Institute of Columbia University. Boetius acknowledges funding from the Helmholtz Association for the FRAM infrastructure, and from her ERC Adv. Grant ABYSS (294757). Mayer’s work is supported by NOAA Grant NA15NOS4000200.
    Keywords: Underwater robotic vehicles ; Under-ice navigation ; Tethered vehicles ; Hybrid vehicles ; Gliders ; Ocean science ; Ocean exploration
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-05-26
    Description: May also be cited as: WHOI-00-01
    Description: Two classes of sample recovery devices have been fabricated for use with the Jason deep diving remotely operated vehicle (ROV). One class includes custom-built, autonomous vertical transporters (AVTs) that are capable of raising numerous benthic samples and other payloads to the ocean's surface independent of the sampling RAOV. AVTs are more commonly referred to as sample "elevators". Elevators are inexpensive to construct and can be deployed and recovered many times during the course of a single ROV dive in order to reduce wear and tear on the more expensive ROV. A second class includes a range of custom-built end effectors and articulated scoops that ROV operators mount onto the vehicle's manipulator and sampling cradle according to required sampling tasks. This report describes the design, fabrication, operation, and navigational tracking of these various non-destructive sampling devices. A ballast and flotation spreadsheeet is provided, which allows operators to customize each elevator deployment and sample recovery scenario while the ROV continues its work on the benthos.
    Keywords: ROV ; Sampling ; Autonomous
    Repository Name: Woods Hole Open Access Server
    Type: Technical Report
    Format: 6639707 bytes
    Format: application/pdf
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