LAUV: The Man-Portable Autonomous Underwater Vehicle

Sousa, Alexandre; Madureira, L.; Coelho, Jorge F. J.; Pinto, José; Pereira, João; Sousa, João Borges de; Dias, Paulo Sousa

doi:10.3182/20120410-3-pt-4028.00045

Cited by 40 publications

(17 citation statements)

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“…Both front detection and sampling location were decided by a state‐based autonomous agent running onboard the AUV, optimizing data collection across and along the front. The sampling platform was a light AUV (Sousa et al, ) equipped with an active pumping 16 Hz SBE 49 FastCAT CTD, an Anderaa Optode 4831 sensor (measuring the dissolved oxygen), and a WetLabs Triple‐Measurement Meter EcoPuck (measuring color dissolved organic matter at 370/460 nm, chlorophyll a fluorescence at 470/695 nm, and optical backscatter). The accuracy of the CTD instrument is ±3 ×10 −4 S m −1 (conductivity), ±2 × 10 −3 °C (temperature) and of the dissolved oxygen sensor less than 8 μmol L −1 .…”

Section: Datamentioning

confidence: 99%

Observations of Turbulence at a Near‐Surface Temperature Front in the Arctic Ocean

et al. 2020

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High-resolution ocean temperature, salinity, current, and turbulence data were collected at an Arctic thermohaline front in the Nansen Basin. The front was close to the sea ice edge and separated the cold and fresh surface melt water from the warm and saline mixed layer. Measurements were made on 18 September 2018, in the upper 100 m, from a research vessel and an autonomous underwater vehicle. Destabilizing surface buoyancy fluxes from a combination of heat loss to the atmosphere and cross-front Ekman transport by down-front winds reduced the potential vorticity in the upper ocean. Turbulence structure in the mixed layer was generally consistent with turbulence production through convection by heat loss to atmosphere and mechanical forcing by moderate winds. Conditions at the front were favorable for forced symmetric instability, a mechanism drawing energy from the frontal geostrophic current. A clear signature of increased dissipation from symmetric instability could not be identified; however, this instability could potentially account for the increased dissipation rates at the front location down to 40 m depth that could not be explained by the atmospheric forcing. This turbulence was associated with turbulent heat fluxes of up to 10 W m −2 , eroding the warm and cold intrusions observed between 30 and 60 m depth. A Seaglider sampled across a similar frontal structure in the same region 10 days after our survey. The submesoscale-to-turbulence-scale transitions and resulting mixing can be widespread and important in the Atlantic sector of the Arctic Ocean. Plain Language SummaryOn 18 September 2018, high-resolution temperature, salinity, current, and turbulence data were collected near a surface temperature and salinity front in the Nansen Basin north of Svalbard, within the framework of the Nansen Legacy Project. Measurements were performed from the research icebreaker Kronprins Haakon and using an autonomous underwater vehicle. The front separates warm and salty Atlantic-origin waters from cold and fresh Arctic-origin waters. Energetic turbulence in the upper 30 m was consistent with convection by heat loss to the atmosphere and mechanical forcing by moderate winds at the surface of the ocean. At the front, the conditions were favorable for forced symmetric instability, a mechanism drawing energy from the large-scale current. The contribution to turbulence from this instability could not be clearly identified but can be potentially important. Such observations linking 1-3 km scales to turbulence in the Arctic Ocean are rare. Turbulence at a front in the Arctic has consequences on the heat and nutrient transport from the slope to the deep Arctic Basin. A Seaglider sampled across a similar frontal structure in the same region end of September 2018. Observed frontal structure and mixing processes can be common in the Atlantic sector of the Arctic Ocean.

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Section: Datamentioning

confidence: 99%

Observations of Turbulence at a Near‐Surface Temperature Front in the Arctic Ocean

et al. 2020

View full text Add to dashboard Cite

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“…Both front detection and sampling location were decided by a state-based autonomous agent running onboard the AUV, optimizing data collection across and along the front. The sampling platform was a light AUV (Sousa et al, 2012) equipped with an active pumping 16 Hz SBE 49 FastCAT CTD, an Anderaa Optode 4831 sensor (measuring the dissolved oxygen), and a WetLabs Triple-Measurement Meter EcoPuck (measuring color dissolved organic matter at 370/460 nm, chlorophyll a fluorescence at 470/695 nm, and optical backscatter). The accuracy of the CTD instrument is ±3 ×10 −4 S m −1 (conductivity), ±2 × 10 −3 • C (temperature) and of the dissolved oxygen sensor less than 8 μmol L −1 .…”

Section: Autonomous Underwater Vehiclementioning

confidence: 99%

Observations of turbulence at a near-surface temperature front in the Arctic Ocean

Koenig

Fer

Kolås

et al. 2020

Preprint

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Measurements made at an Arctic thermohaline front show turbulence production through convection and forced symmetric instability, a mechanism drawing energy from the frontal geostrophic current. Destabilizing surface buoyancy fluxes from a combination of heat loss to the atmosphere and cross-front Ekman transport by down-front winds reduce the potential vorticity in the upper ocean. The front, located in the Nansen Basin close to the sea ice edge, separates the cold and fresh surface melt water from the warm and saline mixed layer. High resolution temperature, salinity, current and turbulence data were collected in the upper 100 m, on 18 September 2018 across the front from a research vessel and an autonomous underwater vehicle. The AUV was deployed to autonomously collect high resolution data across the front using adaptive sampling. Both front detection and sampling location were decided by a state-based autonomous agent running onboard the AUV, optimizing data collection across and along the front.In addition to convection by heat loss to atmosphere and mechanical forcing by moderate wind in the mixed layer, forced symmetric instability contributed with comparable magnitude in generation of turbulence at the front location down to 40 m depth. This turbulence was associated with turbulent heat fluxes of up to 10 W.m-2, eroding the warm and cold intrusions observed at respectively 35 and 55 m depth. A similar frontal structure has been crossed by a Seaglider in the same region 10 days after our survey. The submesoscale-to-turbulence scale transitions and resulting mixing can be widespread and important in the Atlantic sector of the Arctic Ocean.

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“…Our robotic platform consisted of a light AUV (Sousa et al., ) equipped with a 16 Hz Seabird “Fastcat 49” active conductivity, temperature, and depth (CTD) sensor providing temperature and salinity measurements, see Figure . The CTD is active as it continuously pumps water, ensuring that a fresh sample is observed.…”

Section: Field Experimentsmentioning

confidence: 99%

Information‐driven robotic sampling in the coastal ocean

Fossum

Eidsvik

Ellingsen

et al. 2018

Journal of Field Robotics

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Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such features. We present methods that capitalize on information from ocean models and in situ measurements, using Gaussian process modeling and objective functions, allowing sampling efforts to be concentrated to regions with high scientific interest. We demonstrate how to combine and correlate marine data from autonomous underwater vehicles, model forecasts, remote sensing satellite, buoy, and ship‐based measurements, as a means to cross‐validate and improve ocean model accuracy, in addition to resolving upper water‐column interactions. Our work is focused on the west coast of Mid‐Norway where significant influx of Atlantic Water produces a rich and complex physical–biological coupling, which is hard to measure and characterize due to the harsh environmental conditions. Results from both simulation and full‐scale sea trials are presented.

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LAUV: The Man-Portable Autonomous Underwater Vehicle

Cited by 40 publications

References 1 publication

Observations of Turbulence at a Near‐Surface Temperature Front in the Arctic Ocean

Observations of Turbulence at a Near‐Surface Temperature Front in the Arctic Ocean

Observations of turbulence at a near-surface temperature front in the Arctic Ocean

Information‐driven robotic sampling in the coastal ocean

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