15 research outputs found

    Statistics of surface divergence and their relation to air-water gas transfer velocity

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    Air-sea gas fluxes are generally defined in terms of the air/water concentration difference of the gas and the gas transfer velocity,kL. Because it is difficult to measure kLin the ocean, it is often parameterized using more easily measured physical properties. Surface divergence theory suggests that infrared (IR) images of the water surface, which contain information concerning the movement of water very near the air-water interface, might be used to estimatekL. Therefore, a series of experiments testing whether IR imagery could provide a convenient means for estimating the surface divergence applicable to air-sea exchange were conducted in a synthetic jet array tank embedded in a wind tunnel. Gas transfer velocities were measured as a function of wind stress and mechanically generated turbulence; laser-induced fluorescence was used to measure the concentration of carbon dioxide in the top 300 ÎĽm of the water surface; IR imagery was used to measure the spatial and temporal distribution of the aqueous skin temperature; and particle image velocimetry was used to measure turbulence at a depth of 1 cm below the air-water interface. It is shown that an estimate of the surface divergence for both wind-shear driven turbulence and mechanically generated turbulence can be derived from the surface skin temperature. The estimates derived from the IR images are compared to velocity field divergences measured by the PIV and to independent estimates of the divergence made using the laser-induced fluorescence data. Divergence is shown to scale withkLvalues measured using gaseous tracers as predicted by conceptual models for both wind-driven and mechanically generated turbulence

    Near-Real-Time Acoustic Monitoring of Beaked Whales and Other Cetaceans Using a Seaglider™

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    In most areas, estimating the presence and distribution of cryptic marine mammal species, such as beaked whales, is extremely difficult using traditional observational techniques such as ship-based visual line transect surveys. Because acoustic methods permit detection of animals underwater, at night, and in poor weather conditions, passive acoustic observation has been used increasingly often over the last decade to study marine mammal distribution, abundance, and movements, as well as for mitigation of potentially harmful anthropogenic effects. However, there is demand for new, cost-effective tools that allow scientists to monitor areas of interest autonomously with high temporal and spatial resolution in near-real time. Here we describe an autonomous underwater vehicle – a glider – equipped with an acoustic sensor and onboard data processing capabilities to passively scan an area for marine mammals in near-real time. The glider was tested extensively off the west coast of the Island of Hawai'i, USA. The instrument covered approximately 390 km during three weeks at sea and collected a total of 194 h of acoustic data. Detections of beaked whales were successfully reported to shore in near-real time. Manual analysis of the recorded data revealed a high number of vocalizations of delphinids and sperm whales. Furthermore, the glider collected vocalizations of unknown origin very similar to those made by known species of beaked whales. The instrument developed here can be used to cost-effectively screen areas of interest for marine mammals for several months at a time. The near-real-time detection and reporting capabilities of the glider can help to protect marine mammals during potentially harmful anthropogenic activities such as seismic exploration for sub-sea fossil fuels or naval sonar exercises. Furthermore, the glider is capable of under-ice operation, allowing investigation of otherwise inaccessible polar environments that are critical habitats for many endangered marine mammal species

    Glider track (v-shaped line) and hypothetical dive profile of tagged Cuvier's beaked whale (u-shaped line); see text for details.

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    <p><b>Blue line indicates the time/depth when the acoustic system of the glider operated.</b> Red line represents time/depth when Cuvier's beaked whales were acoustically detected by the glider. Green line marks periods when the whale was presumably vocally active. Black star indicates surfacing position of the whale. Remarks: [1] This graph does not consider horizontal distances and the orientation of the whale towards the glider. [2] For illustration purposes, the whale's dive profile was limited to deep dives only.</p

    Map of the study area off the Kona coast, Hawai'i, USA.

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    <p>Inset at upper right shows the Seaglider at the beginning of a dive. Bathymetric map source: Hawai'i Mapping Research Group, School of Ocean and Earth Sciences and Technology, University of Hawai'i, USA.</p

    Locations of acoustic encounters as derived from the manual data analysis.

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    <p>Panels indicate locations of [a] beaked whale, [b] delphinid, and [c] sperm whale acoustic encounters. Size of each dot represents the percentage (logarithmic scale) of acoustic data recorded per glider dive containing respective target signal. Map source: Google Earth. Contours: Hawai'i Mapping Research Group, School of Ocean and Earth Sciences and Technology, University of Hawai'i, USA.</p
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