Buoy Drift Research Articles

A numerical analysis of wave type and steepness effects on cylindrical buoy dynamic characteristics

In the intricate realm of ocean-atmosphere dynamics, the sustained and stable operation of buoy observation systems under rough seas is crucial for ensuring marine resource security. This study employs a coupled Level-Set and Volume of Fluid (CLSVOF) method alongside the immersed boundary method. It investigates the physical processes of wind-wave interaction, the dynamic characteristics of cylindrical buoys, as well as the underlying mechanisms. The research highlights the significant impact of wave types (wind waves, swells) and wave steepness on the buoy's drift and oscillatory behavior. An increase in wave steepness and a shift from wind waves to swell markedly intensify both the buoy's drift and its oscillatory motions. Additionally, a thorough analysis of the loads on the buoy under varying maritime conditions is performed. By examining the vertical momentum equation on the windward and leeward sides, the secondary load cycle phenomenon is found to originate from collapse of the water column formed by the convergence of water flow behind the buoy. Wind waves are found to be less conducive to secondary load cycles compared to swell waves. Furthermore, the study investigates the relationship between the drag coefficient and the wave crest height on the windward side of the buoy, revealing a robust negative correlation between the two. This research not only illuminates the complex dynamics of wind-wave couplings but also offers theoretical insights for the optimization of buoy design.

The fabrication and testing drifting buoys of marine data collection

This paper presents the primary contents of successfully researching, designing and manufacturing drifting buoys to collect marine data to measure temperature, salinity, and ocean currents in surface layers. The paper presents the basic information about the structure, specifications, the buoys working as the laboratory results, and field tests of drift buoys at sea. The drifting buoy test results at the sea of Van Don - Quang Ninh area met the criteria of water-tightness, buoyancy, and balance; the ability to collect temperature and salinity data of the sensors; the ability to transmit and receive information from drifting buoy at sea to the central computer via a web server; operability of the parachute and the travel of the buoy. The buoy database management software is on the website at http://vnsea.vn. It manages the collected data in real-time, showing the parameters and their variables in space and time, the buoy's tracking on the Google map.

Sea ice drift tracks from autonomous buoys in the MOSAiC Distributed Network

A network of autonomous, ice-tethered buoys was deployed around the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in late September 2019 for a year-long drift in the Arctic Transpolar Drift Stream. The buoys were deployed as part of the MOSAiC distributed network (DN) which included 12 multi-instrumented ice stations and an additional 116 GPS buoys distributed primarily within a 40 km radius of the MOSAiC Central Observatory. Buoy coverage within the DN was maintained with additional deployments throughout the year-long drift allowing for collection of data over a full sea ice growth and melt cycle. All GPS position data from buoys deployed within the DN have been assembled and processed into the collection of 216 quality-controlled buoy drift tracks presented in this dataset covering the period 26 September 2019 – 23 May 2021. The drift tracks in this collection are ideal for studies of dynamic sea ice motion around the MOSAiC experiment at cascading spatial scales ranging from 100s of meters to 100s of km.

LORA: a local ensemble transform Kalman filter-based ocean research analysis

We have produced an eddy-resolving local ensemble transform Kalman filter (LETKF)-based ocean research analysis (LORA) for the western North Pacific (WNP) and Maritime Continent (MC) regions (LORA-WNP and LORA-MC, respectively). This paper describes the system configuration and validation comparisons with Japan Coastal Ocean Predictability Experiment 2M (JCOPE2M) reanalysis and Archiving, Validation, and Interpretation of Satellite Oceanographic Data (AVISO) observational datasets. The results show that the surface horizontal velocity in the LORA-WNP is closer to independent drifter buoy observations in the mid-latitude region, especially along the Kuroshio Extension (KE), and is less close in the subtropical region than the JCOPE2M, although the AVISO is the closest over the whole domain. The sea surface temperatures (SSTs) in the LORA-WNP correspond better to assimilated satellite observations than the JCOPE2M over most of the domain except for coastal regions. The results using an independent buoy south of the KE indicate that better fit of temperature in the LORA-WNP may be limited to the upper 300 m depth, probably because of the prescribed vertical localization cutoff length of 370 m. In the MC region, the surface velocity in the LORA-MC is closer to the independent drifter buoys in the equatorial coastal region and is less close in the offshore region than the AVISO. The SSTs in the LORA-MC correspond better to the assimilated satellite observations in the offshore region than the nearshore region. Therefore, the LORA-WNP and LORA-MC have sufficient accuracy for geoscience research applications as well as for fisheries, marine transport, and environment consultants.

Hydrodynamic and hydrological processes within a variety of coral reef lagoons: field observations during six cyclonic seasons in New Caledonia

Abstract. From 2014 to 2021 during the cyclone seasons, extensive monitoring of the hydrodynamics within a variety of lagoons of New Caledonia was conducted as a part of the PRESENCE project (PRESsures on coral Ecosystems of New CalEdonia). The PRESENCE project is aimed at building an efficient representation of the land–lagoon–ocean continuum at Grande Terre, New Caledonia's main island. Overall, coastal physical observations encompassed five different lagoons (four of which were never before monitored) and at least eight major atmospheric events ranging from tropical depressions to category 4 cyclones. The main objectives of this study were to characterize the processes controlling the hydrodynamics and hydrology of these lagoons (e.g., ocean–lagoon exchanges, circulation, level dynamics, temperature, and salinity variability), and to capture the magnitude of change during extreme events. An additional objective was to compile an adequate data set for future use in high-resolution hydrodynamic models. Autonomous oceanographic instruments were moored at strategic locations to collect time series of temperature, salinity, pressure, and Eulerian currents. Additionally, Lagrangian surface currents were observed through deploying drifter buoys, and cross-shore hydrological profile radials were carried out using CTDs (conductivity, temperature, depth). In total, five survey campaigns were conducted, beginning with the SPHYNX campaign which lasted 15 months (December 2014 to February 2016) in the Hienghène–Touho lagoon and ended with the 9 months NEMO campaign (September 2020 to April 2021) in Moindou lagoon. Between these were the 5 months NOUMEA campaign (December 2016 to April 2017) in Noumea lagoon, the 6 months ELADE campaign (February to August 2018) in the Poe lagoon, and the 5 months CADHYAK campaign (December 2019 to May 2020) in Koumac lagoon. In addition to characterizing these lagoons, the data set identifies important features and processes, such as the presence of internal waves on forereefs, wave-driven fluxes over reef barriers, and exchanges through passes. Signatures from strong events were also identified, including surges, thermal drops inside lagoons, and massive flash flood plume dispersion. Raw data sets were processed, controlled for quality, validated, and analyzed. Processed files are made publicly available in dedicated repositories on the SEANOE marine data platform in NetCDF format. Links (DOI) of individual data sets are provided herein.

Predicting larval alewife transport in Lake Michigan using hydrodynamic and Lagrangian particle dispersion models

AbstractSeveral species of fish in large lakes and marine environments have a pelagic larval stage, and are subject to variable transport that can ultimately regulate survival and recruitment success. Alewife, Alosa pseudoharengus, are subject to transport by complex coastal currents during their pelagic larval stage (~ 30 d). We assessed backward‐trajectory simulations, consisting of a Lagrangian particle dispersion model linked to the Finite Volume Community Ocean Model, to estimate likely hatch locations of aged larval alewife collected from locations on both the eastern and western sides of Lake Michigan during July 2015. We used four deployments of three satellite‐tracked drifter buoys in coastal waters to assess model skill in estimating the origin of a drifter from its final location. We found that the trajectories of drifters varied greatly, depending on wind events and associated coastal transport processes, including upwelling/downwelling and coastal jet currents. In 2 of 12 cases, the backward trajectory simulations failed to predict the drifter origin, associated with transport of 170 km in a narrow coastal jet current. In the remaining 10 cases, the known drifter origin was within 3.5 km of the spatial patch of predicted possible origins for a scenario of horizontal diffusivity (188 m2 s−1) consistent with the offshore model grid resolution. Modeled backward trajectories estimated that alewife originated from the same side of the lake where they were collected, within ~ 100 km of the collection site. Our paper demonstrates the utility of hydrodynamic models to estimate a region of origin for aged larval fish.

Short-Term Drift Prediction of Multi-Functional Buoys in Inland Rivers Based on Deep Learning.

The multi-functional buoy is an important facility for assisting the navigation of inland waterway ships. Therefore, real-time tracking of its position is an essential process to ensure the safety of ship navigation. Aiming at the problem of the low accuracy of multi-functional buoy drift prediction, an integrated deep learning model incorporating the attention mechanism and ResNet-GRU (RGA) to predict short-term drift values of buoys is proposed. The model has the strong feature expression capability of ResNet and the temporal memory capability of GRU, and the attention mechanism can capture important information adaptively, which can solve the nonlinear time series drift prediction problem well. In this paper, the data collected from multi-functional buoy #4 at Nantong anchorage No. 2 in the Yangtze River waters in China were studied as an example, and first linear interpolation was used for filling in missing values; then, input variables were selected based on Pearson correlation analysis, and finally, the model structure was designed for training and testing. The experimental results show that the mean square error, mean absolute error, root mean square error and mean percentage error of the RGA model on the test set are 5.113036, 1.609969, 2.261202 and 15.575886, respectively, which are significantly better than other models. This study provides a new idea for predicting the short-term drift of multi-functional buoys, which is helpful for their tracking and management.

A Study on the Prediction of the Surface Drifter Trajectories in the Korean Strait

In order to improve the accuracy of particle tracking prediction techniques near the Korean Strait, this study compared and analyzed a particle tracking model based on a seawater flow numerical model and a machine learning based on a particle tracking model using field observation data. The data used in the study were the surface drifter buoy movement trajectory data observed in the Korea Strait, prediction data by machine learning (linear regression, decision tree) using the tide and wind data from three observation stations (Gageo Island, Geoje Island, Gyoboncho), and prediciton data by numerical models (ROMS, MOHID). The above three data were compared through three error evaluation methods (Correlation Coefficient (CC), Root Mean Square Errors (RMSE), and Normalized Cumulative Lagrangian Separation (NCLS)). As a final result, the decision tree model had the best prediction accuracy in CC and RMSE, and the MOHID model had the best prediction results in NCLS.

A new state-dependent parameterization for the free drift of sea ice

Abstract. Free-drift estimates of sea ice motion are necessary to produce a seamless observational record combining buoy and satellite-derived sea ice motion vectors. We develop a new parameterization for the free drift of sea ice based on wind forcing, wind turning angle, sea ice state variables (thickness and concentration), and estimates of the ocean currents. Given the fact that the spatial distribution of the wind–ice–ocean transfer coefficient has a similar structure to that of the spatial distribution of sea ice thickness, we take the standard free-drift equation and introduce a wind–ice–ocean transfer coefficient that scales linearly with ice thickness. Results show a mean bias error of −0.5 cm s−1 (low-speed bias) and a root-mean-square error of 5.1 cm s−1, considering daily buoy drift data as truth. This represents a 35 % reduction of the error on drift speed compared to the free-drift estimates used in the Polar Pathfinder dataset (Tschudi et al., 2019b). The thickness-dependent transfer coefficient provides an improved seasonality and long-term trend of the sea ice drift speed, with a minimum (maximum) drift speed in May (October), compared to July (January) for the constant transfer coefficient parameterizations which simply follow the peak in mean surface wind stresses. Over the 1979–2019 period, the trend in sea ice drift in this new model is +0.45 cm s−1 per decade compared with +0.39 cm s−1 per decade from the buoy observations, whereas there is essentially no trend in a free-drift parameterization with a constant transfer coefficient (−0.09 cm s−1 per decade) or the Polar Pathfinder free-drift input data (−0.01 cm s−1 per decade). The optimal wind turning angle obtained from a least-squares fitting is 25∘, resulting in a mean error and a root-mean-square error of +3 and 42∘ on the direction of the drift, respectively. The ocean current estimates obtained from the minimization procedure resolve key large-scale features such as the Beaufort Gyre and Transpolar Drift Stream and are in good agreement with ocean state estimates from the ECCO, GLORYS, and PIOMAS ice–ocean reanalyses, as well as geostrophic currents from dynamical ocean topography, with a root-mean-square difference of 2.4, 2.9, 2.6, and 3.8 cm s−1, respectively. Finally, a repeat of the analysis on two sub-sections of the time series (pre- and post-2000) clearly shows the acceleration of the Beaufort Gyre (particularly along the Alaskan coastline) and an expansion of the gyre in the post-2000s, concurrent with a thinning of the sea ice cover and the observed acceleration of the ice drift speed and ocean currents. This new dataset is publicly available for complementing merged observation-based sea ice drift datasets that include satellite and buoy drift records.

Fine-Scale Velocity Measurement on the Wirewalker Wave-Powered Profiler

Abstract The Wirewalker (WW) ocean-wave-powered vertical profiling system allows the collection of high-resolution oceanographic data due to its rapid profiling, hydrodynamically quiet operation, and long endurance. We have assessed the potential for measuring fine-scale ocean velocities from the Wirewalker platform using commercially available acoustic velocimeters. Although the vertical profiling speed is relatively steady, platform motion affects the velocity measurements and requires correction. We present an algorithm to correct our velocity estimates using platform motion calculated from the inertial sensors—accelerometer, gyroscope, and magnetometer—on a Nortek Signature1000 acoustic Doppler current profiler (ADCP). This correction, carried out ping by ping, was effective in removing the vehicle motion from the measured velocities. The motion-corrected velocities contain contributions from surface wave orbital velocities, especially near the surface, and the background currents. To proceed, we use an averaging approach that leverages both the vertical platform profiling of the system and the ∼15–20 m vertical profiling range resolution of the down-looking ADCP to separate the surface wave orbital velocities and the background flow. The former can provide information on the wave conditions. From the latter, we are able to estimate fine-scale velocity and shear with spectral wavenumber rolloff at vertical scales around 3 m, a vertical resolution several times finer than that possible from modern shipboard or fixed ADCPs with similar profiling range, and similar to recent glider measurements. When combined with a continuous time series of buoy drift calculated from the onboard GPS, a highly resolved total velocity field is obtained, with a unique combination of space and time resolution.

Assessment of the depth of the upper boundary of the hydrogen sulphide zone of the black sea with the buoys' data of 2015-2022

Biocenoses of the Black Sea are ones of the most vulnerable natural systems of the Earth. About 87 % of the Black Sea water volume is occupied by the hydrogen sulfide zone. Ecosystems of the thin layer of the upper oxygen zone are extremely sensitive to both anthropogenic impact and the influence of natural factors, the intensification of which has been observed recently due to rapid global climate change. The aim of the work is to assess the depth appearance, spatial distribution and change of the upper boundaries of the hydrogen sulfide zone of the Black Sea with the buoys ARGO data. In the article it was used hydrophysical and hydrochemical information obtained from the oceanographic database of the ARGO project in the Black Sea for the period from March 2015 to March 2022, such as: temperature, salinity, dissolve oxygen and hydrogen sulfide. A total of 591 arrays were analysed. A critical analysis of the quality of the selected information was carried out. The profile data has been adjusted. When processing the material, the method of optimal interpolation, graphic and statistical analysis were used. The original programs of UkrSCES were used. It was concluded according to the results of the work that the upper boundary of the anaerobic zone of the Black Sea in areas of buoy drift was located at depths of 100-180 meters. The difference in the indications for determining the boundaries according to two independent criteria: the depth of the water bodies with a hydrogen sulfide concentration of 3 μmol/kg, and the depth of the iso-surface of the conditional density of 16.18, which on average fluctuated within ±7 meters. In some areas, significant fluctuations in the upper limit of the anaerobic zone, caused by the influence of local hydrodynamic vortices, or removal of intrusive water from the Bosphorus Strait, were noted. The spatiotemporal variability of the sub-oxygen zone in the areas of buoy-profilometer drift, as well as the areas where this layer has minimum and maximum power.

Drift of Surface Lagrangian Buoys in the Central Sea of Japan in October–November 2011

Drift of Surface Lagrangian Buoys in the Central Sea of Japan in October–November 2011

Metop First Generation AVHRR FRAC SST Reanalysis Version 1

The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance.

Performance Statistics of a Real-Time Pacific Ocean Weather Sensor Network

AbstractA distributed sensor network of over 100 free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next-generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open-ocean regions. Despite the demand for better weather forecasts and climate data in the oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Because of the large expanse of Earth’s oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open-ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open-ocean weather dataset and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in the oceans.

Modeled Stokes drift in the marginal ice zones of the Arctic Ocean

This study modeled Stokes drift in the marginal ice zone (MIZ) of the Arctic Ocean using WAVEWATCH III. Applying two viscoelastic and one empirical frequency-dependent wave–ice models, modeled wave parameters and spectra were compared with field observations from the Beaufort–Chukchi Sea. The three wave–ice parameterizations showed similar ability in reproducing the surface Stokes drift estimated using buoy measurements. Comparison with buoy drift showed the estimation of total surface drift was improved by considering Stokes drift during significant wave events. Based on 5-year (2015–2019) hindcasted directional spectra of the summer-autumn Arctic, we investigated monthly mean surface Stokes drift (1–10 cm/s), e-folding depth (1–14 m), and vertically integrated transport (< 0.23 m2/s) in the MIZ. The results showed that Stokes drift in the MIZ increased in strength from July to October. When bulk wave parameters were adopted to estimate Stokes drift fields, the surface Stokes drift was underestimated by about 34–50%, while the Stokes e-folding depth was overestimated by approximately 1.4–5.0 times, increasing from the interior to the edge of the ice cover. We compared the modeled surface Stokes drift with the Eulerian mean flow from reanalyzed data. It showed the mean surface Stokes drift is typically approximately 30% of the Eulerian current over large parts of the Arctic Ocean MIZ with mean ice concentration < 60%, and is the same order of magnitude as (or even larger than) some areas of the Chukchi, East Siberian, and Laptev Seas. It implies Stokes drift should be considered to improve modeling of the dynamic processes of sea ice, especially ice floe drift.

Bathymetric observations of an extreme tidal flow: Approaches to the Gulf of Corryvreckan, western Scotland, UK

The growing interest in tidal energy has led to a need to better understand the interaction between energetic tidal flows and submarine bathymetry. The Gulf of Corryvreckan (GoC) is a highly energetic tidal channel, ∼3.2 km long and ∼1.1 km wide with a maximum depth of 220 m occurring between the islands of Scarba and Jura, western Scotland, UK. A high-resolution bathymetric survey of the region, groundtruthed by sediment samples, has enabled the bathymetry to be related to Lagrangian flow data from GPS-tracked surface drifter buoys. The maximum recorded drifter velocity was 4.75m/s within the GoC during the ebb (east-flowing) tide. Exiting the GoC into open water to the west on the flood tide, the ‘Great Race’ decelerates and subsequently flows in a curve to the north. East and west of the GoC, sedimentary bedforms lie on the flanks of the main flow paths. The northern flank of the Great Race aligns with a 6 km elongate bedform (‘banner bank’) extending from the GoC. East of the GoC, complex tidal bottom flows are suspected to result in uncommon sediment morphology, including suspected sediment wave interference patterns expressed by the mobile bedforms. The novelty of these findings indicates the importance of further research into sediment pathways in energetic tidal zones. A greater understanding of how sediment transport may be modified during offshore construction is an important consideration for offshore installations and the feasibility of marine renewables.

The Western Eurasian Basin Halocline in 2017: Insights From Autonomous NO Measurements and the Mercator Physical System

AbstractWe present the first sensor‐based profiles of the quasi‐conservative NO parameter obtained with an autonomous ice‐tethered buoy in the Arctic Ocean. Data documented the halocline in the Transpolar Drift and Nansen Basin in 2017. A NO minimum was found in the Nansen Basin on a σ‐horizon of 27.8 kg·m−3 corresponding to the lower halocline, while a lower NO minimum of 380 μM straddled the 27.4 σ‐horizon and marked the cold halocline in the Transpolar Drift. Back trajectories of water parcels encountered along the buoy drift were computed using the Mercator physical system. They suggested that waters within the NO minimum at 27.4 kg·m−3 could be traced back to the East Siberian Sea continental. These trajectories conformed with the prevailing positive phase of the Arctic Oscillation. The base of the lower halocline, at the 27.85 σ‐horizon, corresponded to the density attained in the deepest winter mixed layer north of Svalbard and cyclonically slowly advected from the slope into the central Nansen Basin. The 27.85 σ‐horizon is associated with an absolute salinity of 34.9 g·kg−1, a significantly more saline level than the 34.3 psu isohaline commonly used to identify the base of the lower halocline. This denser and more saline level is in accordance with the deeper winter mixed layers observed on the slopes of Nansen Basin in the last 10 years. A combination of simulations and NO parameter estimates provided valuable insights into the structure, source, and strength of the Arctic halocline.

A study of ocean parameters in Bay of Bengal (BoB) using indigenised drifting buoys

Drifting buoys (DBs) are widely deployed to observe near-surface ocean currents and sea surface temperature. The National Institute of Ocean Technology (NIOT), Chennai, India, had indigenised the DB with the Indian satellite (INSAT) in 2012. This paper describes the results of various studies conducted by NIOT using the indigenised DBs and also describes unique features attempted in indigenised DBs to measure the near-surface ocean current with 24 position acquisitions per day to capture small-scale surface eddies and the use of real-time geostationary satellite communication every hour. Additionally, the surface currents observed with indigenous DB are compared with DBs available in the market, Marlin-Yug (coefficient of determination R2 > 0.88) and forecast using the ocean surface current analyses real-time (coefficient of determination R2 > 0.90). Our results show that the DBs in the Bay of Bengal are carried with the East India Coastal Current in the March–May periods and the in-situ observations by the DB provide accurate surface current observations than satellite-based data. Furthermore, the new observations near the world’s largest tidal mangrove and delta system, the Sundarbans and Bengal Delta, will help in further enhancing our understanding of the spatiotemporal variability in the region in terms of coastal currents and its influence on marine environments.

Local acoustic habitat relative to hearing sensitivities in beluga whales (Delphinapterus leucas)

Background noise can have a substantial effect on communication signals, however far less is known about how natural soundscapes may influence hearing sensitivity. Here we compare the audiograms of 26 wild beluga whales measured in their natural environment to a series of ecoacoustic measurements within a primary portion of their Bristol Bay summer habitat, the Nushagak Estuary in Bristol Bay, AK, USA. Environmental acoustic measurements were made during 2012 and 2016 using two different methods: a moored recorder and drifter buoys. Environmental noise curves varied substantially. Drifter recordings from the middle of Nushgak Estuary had the highest spectrum levels during ebb tides with acoustic energy from sediment transport extending well into higher frequencies (ca. 60 kHz), likely due to rapidly moving tidal flow and shifting sediment in that location. Drifter recordings near the estuary mouth and shallow tidal flats were lower amplitude. Noise levels generally varied during drifts (in one case up to ca. 6 dB) reflecting acoustic cues available to the local belugas. The moored recorder showed a substantially different spectral profile, especially at lower frequencies, perhaps due to its attachment to a pier piling and subsequent pier noise. Hearing sensitivity varied by individual and thresholds often fell above 1/3 octave-band noise levels, but not overall noise spectral density. Audiograms of the most sensitive animals closely paralleled the lowest ambient noise power spectral density curves, suggesting that an animal’s auditory dynamic range may extend to include its habitat’s quietest conditions. These data suggest a cautious approach is necessary when estimating the sound-sensitivity of odontocetes found in quiet environments as they may have sensitive auditory abilities that allow for hearing within the lowest noise-level conditions. Further, lower level ambient noise conditions could provide a conservative estimate of the maximal sensitivity of some cetacean populations within specific environments.

Accuracy Improvement of Particle-tracking Simulation Considering Wind Speed using Various Drift Objects

ABSTRACT Choi, J.-W.; Kwon, J.-I.; Heo, K.-Y.; Park, K.-S., and Choi, J.-Y., 2018. Accuracy improvement of particle-tracking simulation considering wind speed using various drift objects. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 901–905. Coconut Creek (Florida), ISSN 0749-0208. The simulation accuracy of the particle-tracking model (PTM) primarily depends on wind and current, among various parameters. This study explored the effect of wind on particle tracking using drift objects (drift buoy and mannequin). For numerical experiments, wind and current generated from the weather research and forecasting model (WRF) and Modelo Hidrodinâmico (MOHID) were used in the PTM. Furthermore, a field experiment was conducted using a surface drift buoy nearby Gageo Island, which is located on the south-western coast of the Korean Peninsula. Drifting buoy data from Ju...