Conductivity-temperature-depth Research Articles

Analysis of internal wave in the Buru Island coastal waters, Banda Sea, Indonesia

The Indonesian throughflow (ITF) in the eastern part of Indonesia passes through the Maluku, Taliabu, Sula, and Buru Islands to the Banda Sea. The average depth of the Buru and Sula Islands is between 1,000 m and 5,000 m, with a narrow gap (sill) located to the north and south at a depth of 165 m on the sea map. This topography makes for interesting research on the western waters of Buru Island. Therefore, this study aimed to obtain salinity, temperature, and density values as water column stratification associated with the internal wave (IW), thermocline area, and current patterns at specific depths in the waters of Buru Island, Banda Sea. Data were collected from initial observations of Sentinel 1 satellite imagery of Buru Island to obtain an image of the waves in the water area. Furthermore, a single beam echosounder (SBES), conductivity temperature depth (CTD), and Copernicus Marine were analysed at the same position and time. The research found a non-linear IW Mode 2 at depths of 440 ∼ 540 m with an estimated amplitude length is 40 km and an amplitude height of 100 m. Based on SBES echogram imaging, CTD data analysis, and modelling, there was an increase in IW density, a 35.25 PSU increase in salinity value at depths of 50∼200 m, a temperature decrease of 27.5 ºC to 10 ºC at depths of 50∼300 m, and a density stratification of 23.5 kg/m³ to 27 kg/m³ at depths of 50∼300 m.

A deep learning approach to estimate ocean salinity with data sampled with expendable bathythermographs

Expendable bathythermographs (XBTs) have made possible the build-up of an impressive dataset of temperature in the upper one thousand meters of the ocean. In the absence of direct measurements of salinity, the salinity profile associated with the temperature may be estimated by regression from temperature data or by objective analysis and data assimilation techniques. With the advent of the Argo program, the number of in situ salinity sampling has increased considerably. However, it is still far from ideal and XBTs continue to provide invaluable contribution to oceanography. Here, considering the large amount of data available, and motivated by the increasing use of machine learning to solve complex problems, a deep learning model based on a feed-forward neural network was used to estimate salinity directly from the temperature measurements. The model was independently trained and evaluated with two different datasets: (1) the sampled temperature and the associated salinity in XBT datasets, estimated with traditional methodologies, and (2) data sampled by conductivity-temperature-depth (CTD) profilers. The fitted deep learning model was then used to estimate the salinity from independent XBT datasets. The results show that the model’s accuracy increases substantially when longitude, latitude, depth, and month of the samplings are considered. Compared with four traditional methods, the deep learning performed much better, particularly near the ocean’s surface. In general, the results are highly accurate. However, when the CTD-trained model is used to predict salinity with XBT temperature input, the estimates are less accurate when compared with the salinity in the original XBT data. This seems to be caused by poorer estimates of salinity obtained by other methods in the original XBT datasets.

French coastal network for carbonate system monitoring: the CocoriCO2 dataset

Abstract. Since the beginning of the industrial revolution, atmospheric carbon dioxide (CO2) concentrations have risen steadily and have induced a decrease of the averaged surface ocean pH by 0.1 units, corresponding to an increase in ocean acidity of about 30 %. In addition to ocean warming, ocean acidification poses a tremendous challenge to some marine organisms, especially calcifiers. The need for long-term oceanic observations of pH and temperature is a key element to assess the vulnerability of marine communities and ecosystems to these pressures. Nearshore productive environments, where a large majority of shellfish farming activities are conducted, are known to present pH levels as well as amplitudes of daily and seasonal variations that are much larger than those observed in the open ocean. Yet, to date, there are very few coastal observation sites where these parameters are measured simultaneously and at high frequency. To bridge this gap, an observation network was initiated in 2021 in the framework of the CocoriCO2 project. Six sites were selected along the French Atlantic and Mediterranean coastlines based on their importance in terms of shellfish production and the presence of high- and low-frequency monitoring activities. At each site, autonomous pH sensors were deployed, both inside and outside shellfish production areas, next to high-frequency CTD (conductivity–temperature–depth) probes operated through two operating monitoring networks. pH sensors were set to an acquisition rate of 15 min, and discrete seawater samples were collected biweekly in order to control the quality of pH data (laboratory spectrophotometric measurements) as well as to measure total alkalinity and dissolved inorganic carbon concentrations for full characterization of the carbonate system. While this network has been up and running for more than 2 years, the acquired dataset has already revealed important differences in terms of pH variations between monitored sites related to the influence of diverse processes (freshwater inputs, tides, temperature, biological processes). Data are available at https://doi.org/10.17882/96982 (Petton et al., 2023a).

Expendable Conductivity–Temperature–Depth-Assisted Fast Underwater Sound Speed Estimation by Convolutional Neural Network with Reduced Fully Connected Layers

Obtaining accurate sound speed profiles (SSPs) in near-real-time is of great significance for ocean exploration, underwater communication and improving the performance of sonar systems. In response to the problem that traditional sound speed estimation methods cannot obtain real-time sound speed distribution or rely too much on sonar observation data, we propose an SSP estimation method based on a convolutional neural network with reduced fully connected layers (RFC-CNN) in this paper. This method utilizes neural networks to extract the complex nonlinear features of various types of data. With the help of the historical SSPs and shallow seawater sound speed and temperature data obtained by expendable conductivity–temperature–depth probes (XCTDs), a more accurate estimation of the regional sound speed distribution can be realized quickly. This approach can save the observation cost and significantly improve the real-time performance of SSP estimation.

A decade-long cruise time series (2008–2018) of physical and biogeochemical conditions in the southern Salish Sea, North America

Abstract. Coastal and estuarine waters of the northern California Current system and southern Salish Sea host an observational network capable of characterizing biogeochemical dynamics related to ocean acidification, hypoxia, and marine heatwaves. Here, we compiled data sets from a set of cruises conducted in estuarine waters of Puget Sound (southern Salish Sea) and its boundary waters (Strait of Juan de Fuca and Washington coast). This data product provides data from a decade of cruises with consistent formatting, extended data quality control, and multiple units for parameters such as oxygen with different end use needs and conventions. All cruises obtained high-quality temperature, salinity, inorganic carbon, nutrient, and oxygen observations to provide insight into the dynamic distribution of physical and biogeochemical conditions in this large urban estuary complex on the west coast of North America. At all sampling stations, conductivity–temperature–depth (CTD) casts included sensors for measuring temperature, conductivity, pressure, and oxygen concentrations. Laboratory analyses of discrete water samples collected at all stations throughout the water column in Niskin bottles provided measurements of dissolved inorganic carbon (DIC), dissolved oxygen, nutrient (nitrate, nitrite, ammonium, phosphate, and silicate), and total alkalinity (TA) content. This data product includes observations from 35 research cruises, including 715 oceanographic profiles, with >7490 sensor measurements of temperature, salinity, and oxygen; ≥6070 measurements of discrete oxygen and nutrient samples; and ≥4462 measurements of inorganic carbon variables (i.e., DIC and TA). The observations comprising this cruise compilation collectively characterize the spatial and temporal variability in a region with large dynamic ranges of the physical (temperature = 6.0–21.8 ∘C, salinity = 15.6–34.0) and biogeochemical (oxygen = 12–481 µmol kg−1, dissolved inorganic carbon = 1074–2362 µmol kg−1, total alkalinity = 1274–2296 µmol kg−1) parameters central to understanding ocean acidification and hypoxia in this productive estuary system with numerous interacting human impacts on its ecosystems. All observations conform to the climate-quality observing guidelines of the Global Ocean Acidification Observing Network, the US National Oceanic and Atmospheric Administration's Ocean Acidification Program, and ocean carbon community best practices. This ongoing cruise time series supports the estuarine and coastal monitoring and research objectives of the Washington Ocean Acidification Center and US National Oceanic and Atmospheric Administration (NOAA) Ocean and Atmospheric Research programs, and it provides diverse end users with the information needed to frame biological impacts research, validate numerical models, inform state and tribal water quality and fisheries management, and support decision-makers. All 2008–2018 cruise time-series measurements used in this publication are available at https://doi.org/10.25921/zgk5-ep63 (Alin et al., 2022).

A 12-year-long (2010–2021) hydrological and biogeochemical dataset in the Sicily Channel (Mediterranean Sea)

Abstract. The dataset presented here consists of 273 conductivity–temperature–depth (CTD) stations, as well as 2034 sampled data points in the water column, where dissolved inorganic nutrients have been measured, that were collected during 12 summer oceanographic cruises (BANSIC series) in the Sicily Channel (central Mediterranean Sea) between 2010 and 2021. The quality of the CTD dataset is ensured by regular sensor calibrations and an accurate control process adopted during the acquisition, processing, and post-processing phases. The quality of the biogeochemical dataset is ensured by the adoption of best-practice analytical and sampling methods. This data collection fills a gap of information in the Sicily Channel, i.e., a key area where complex water mass exchange processes involve the transfer of physical and biogeochemical properties between the eastern and western Mediterranean. The available dataset will be useful to evaluate the long-term variability on a wide spatial scale, supporting studies on the evolution of the Mediterranean circulation and its peculiar biogeochemistry, as well as on the physical and biogeochemical modeling of this area. The data are available in Zenodo (https://doi.org/10.5281/zenodo.8125006, Placenti et al., 2023).

Turbulence Across the Antarctic Circumpolar Current in the Indian Southern Ocean: Micro‐Temperature Measurements and Finescale Parameterizations

AbstractTurbulence structures across the Antarctic circumpolar current (ACC) in the Indian Ocean at around 50°E were revealed using microstructure measurements. Depth‐averaged turbulent energy dissipation rates (ε) in 320 m segments estimated using a conductivity‐temperature‐depth (CTD)‐attached micro‐temperature fast‐response thermistor (FP07) were well reproduced using existing finescale parameterizations excluding near‐surface and near‐bottom 160 m. The spatial variations of ε are explained by density stratification N2, bottom topographic roughness, and depth‐averaged current speed U. Diapycnal diffusivity Kρ(=0.2εN−2) is found proportional to the squared internal wave energy () and increases toward the bottom, especially over rough bottom topography. The decay scale height is >1000m and the turbulence remains large even in the upper pycnocline. Existing shear‐based finescale parameterizations were generally consistent with the FP07 measurements but tended to overestimate in the areas with large shear‐strain ratio Rω and low ε in the Continental Zone (CZ) south of the ACC fronts (58–65°S). This overestimation is improved by using the strain‐based finescale parameterization with a constant Rω = 3.

A decade of marine inorganic carbon chemistry observations in the northern Gulf of Alaska – insights into an environment in transition

Abstract. As elsewhere in the global ocean, the Gulf of Alaska is experiencing the rapid onset of ocean acidification (OA) driven by oceanic absorption of anthropogenic emissions of carbon dioxide from the atmosphere. In support of OA research and monitoring, we present here a data product of marine inorganic carbon chemistry parameters measured from seawater samples taken during biannual cruises between 2008 and 2017 in the northern Gulf of Alaska. Samples were collected each May and September over the 10 year period using a conductivity, temperature, depth (CTD) profiler coupled with a Niskin bottle rosette at stations including a long-term hydrographic survey transect known as the Gulf of Alaska (GAK) Line. This dataset includes discrete seawater measurements such as dissolved inorganic carbon and total alkalinity, which allows the calculation of other marine carbon parameters, including carbonate mineral saturation states, carbon dioxide (CO2), and pH. Cumulative daily Bakun upwelling indices illustrate the pattern of downwelling in the northern Gulf of Alaska, with a period of relaxation spanning between the May and September cruises. The observed time and space variability impart challenges for disentangling the OA signal despite this dataset spanning a decade. However, this data product greatly enhances our understanding of seasonal and interannual variability in the marine inorganic carbon system parameters. The product can also aid in the ground truthing of biogeochemical models, refining estimates of sea–air CO2 exchange, and determining appropriate CO2 parameter ranges for experiments targeting potentially vulnerable species. Data are available at https://doi.org/10.25921/x9sg-9b08 (Monacci et al., 2023).

A customized drone for ocean and atmospheric measurements and its performances

Drones- Unmanned Aerial vehicles (UAVs)- have become more significant across the world for a wide range of commercial and terrestrial defense applications in recent years. The National Institute of Ocean Technology (NIOT)- Ministry of Earth Sciences (MOES)- is exploring UAVs with a specific focus on maritime applications. NIOT has customized a heavy lift category drone, operable in marine environments and capable of withstanding coastal wind conditions of up to 40 kmph. It can lift and carry an instrumentation payload of 10 kg, conduct ocean data collection, and even take seawater samplings. The 10 kg payload of the UAV might hold a Conductivity Temperature Depth (CTD) sensor, a programmable sea water sampler, and a multi-parameter sensor (MPS) for ocean data collections, and a Light Detection and Ranging (LiDAR) device integrated with a high frame rate camera system for coastal mapping and digital elevation model (DEM) developmental applications. The customized hexacopter UAV is capable of withstanding winds of up to 10 m/s and features a waterproof IPX7 thruster with a maximum thrust of 153 N per axis. The UAV system is also interfaced with a Global Positioning System (GPS), a barometric pressure sensor, a compass, a highly accurate gyroscope, a 15 MP surveillance camera, and an accelerometer sensor connected to a reliable cube orange flight controller module with a redundant 32-bit controller through a serial peripheral interface (SPI). The drone structure and frame is composed of carbon fiber composites to provide an excellent weight-to-strength ratio. This paper presents the outcomes of an initial field test, carried out to ensure the drone’s suitability for various marine applications with intended payloads ranging from 5 - 10 kg weight, including coastal demonstrations and ocean data collections performed at Nellore (Andra Pradesh) and Chennai (Tamil Nadu) coastal waters. Highlights A drone is customised to with stand elevated wind conditions of coastal regions Design is fully flexible meeting the ease of transport from one location to other Highly stable mechanical design to sustain winds of up to 45 KMPH Redundant flight control mechanism is evolved to assure fail safe operations of drone Drone built in with redundant GPS module to avoid scenario like NO Geo-reference at any time Design is type certified and UIN registered with DGCA - India

Oceanographic dataset collected during the 2021 scientific expedition of the Canadian Coast Guard Ship Amundsen

Abstract. Since 2003, the state-of-the-art Canadian Coast Guard Ship (CCGS) research icebreaker Amundsen has furrowed the Canadian Arctic waters to support novel research endeavors and collect oceanographic data. This paper presents the data acquisition, the processing methods and an overview of the data collected during the 2021 expedition as the ship traveled over 30 000 km during 122 d across the Canadian Arctic Ocean, collecting sea surface, atmospheric and seabed underway measurements. A total of 266 casts of a conductivity, temperature and depth profiler mounted on a Conductivity Temperature Depth rosette (CTD Rosette) were also conducted to monitor the main physical, chemical and biological parameters of the water column. More specifically, the data presented here were collected with the CTD Rosette across historical sampling transects in Davis Strait, the North Water Polynya (NOW) and Cape Bathurst. A 182 km dedicated survey using the Moving Vessel Profiler® (MVP), equipped with CTD, transmissometer, dissolved oxygen, fluorescence and sound velocity sensors, was conducted across Hudson Strait. We also present an overview of the data collected by the underway systems (seabed, thermosalinograph and atmospheric). Such data are essential in understanding the impacts of climate warming on the unique environments of the Canadian Arctic Ocean. Amundsen Science supports and promotes easy access and sharing of such valuable data to the scientific community.

Stratification of Indonesian Throughflow Water and Its Circulation along 125E in the Banggai - Maluku Sea

secondary pathway of Indonesian Throughflow (ITF) that enters from its inflow portal of the northern Maluku Sea is assumed to recirculate in the Banggai - Maluku Sea, where its upper-layer circulation returns into the Pacific and deeper flows continue southward into Seram/Banda Sea via Lifamatola Strait. However, direct observation in this key region is still limited. Here, using direct CTD (Conductivity Temperature Depth) casts and shipboard ADCP (Acoustic Doppler Curent Profiler) measurement datasets from BUDEE (Banggai Upwelling Dynamics and Ecosystem Experiment) cruise in September 2023, we study stratification and structure of ITF water and its circulation in a meridional section along 125E. The results show the water mass stratification of the mixed layer having a depth of 0-75m with a temperature range of 26-29°C, while the thermocline layer has a depth of 28-407m with a temperature range of 23-26°C, and the deep layer has a depth of 407-1000m with a temperature value of 4-12°C. The current pattern of the Banggai Sea Maluku Sea at a depth of 52-400m is more dominantly influenced by non-tidal currents, the influence of tidal currents only covers a depth of 52m less than non-tidal currents.

Transformation of South Pacific Water Masses in the Halmahera Sea

The Halmahera Sea is part of the eastern entry route of the Indonesian throughflow (ITF) passages. The characteristics and transformation of the South Pacific water masses are presented based on the HYCOM model (Hybrid Coordinate Ocean Model) and direct observations of CTD (Conductivity, Temperature, Depth) acquired during the East Indonesian Expedition in October 2017 using RV Baruna Jaya VIII. This study is aimed at characterizing the typical water masses observed in the Halmahera Sea and tracking the transformation of the South Pacific water masses in the region. The results show that there was an indication of strong vertical mixing of maximum salinity of the South Pacific thermocline water masses, i.e., South Pacific Subtropical Water (SPSW), from ~35.2 PSU at isopycnal 24 – 25 kg m-3 becomes ~34.8 PSU in the Southern Halmahera Strait (around 200 km from the entry passage, the Northern Halmahera Strait), and rapidly decreases from the Southern Halmahera Strait and Obi Strait to become 34.6 PSU in the Maluku Sea. These preliminary findings suggest a strong mixing in the southern Halmahera Strait and Obi Strait.

Hydrographical implications of ship-induced turbulence in stratified waters, studied through field observations and CFD modelling

Ship-related energy pollution has received increasing attention but almost exclusively regarding radiated underwater noise, while the effect of ship-induced turbulence is lacking in the literature. Here we present novel results regarding turbulent wake development, the interaction between ship-induced turbulence and stratification, and discuss the impact of turbulent ship wakes in the surface ocean, in areas with intense ship traffic. The turbulent wake development was studied in situ, using Acoustic Doppler Current Profilers (ADCP) and conductivity, temperature, depth (CTD) observations of stratification, and through computational fluid dynamics (CFD) modelling. Our results show that the turbulent wake interacts with natural hydrography by entraining water from below the pycnocline, and that stratification influences the turbulent wake development by dampening the vertical extent, resulting in the wake water spreading out along the pycnocline rather than at the surface. The depth and intensity of the turbulent wake represent an unnatural occurrence of turbulence in the surface ocean. The ship-induced turbulence can impact local hydrography, nutrient dynamics and increase plankton mortality due to physical disturbance, especially in areas with intense traffic. Therefore, sampling and modelling of e.g., contaminants in shipping lanes need to consider hydrographic conditions, as stratification may alter the depth and spread of the wake, which in turn governs dilution. Finally, the frequent ship traffic in estuarine and coastal areas, calls for consideration of ship-induced turbulence when studying hydrographic processes.

ASSESSMENT OF THREE-DIMENSIONAL BAROCLINIC CIRCULATION MODEL FOR THE MUSI COASTAL AREA

The hydrodynamics of the Musi estuary ecosystem is influenced by the flow of water discharge from the river, tidal circulation within the estuary, and complex bathymetry. Numerical modeling is one of the best ways to explain the characteristics and processes occurring in the estuary. However, the obtained model requires validation to ensure its accuracy despite the complexity added by variability in tidal and bathymetric conditions, making the validation process more challenging. This difficulty can be overcome by using high-resolution data, which provides a refined understanding of the river-to-sea estuary flow and its variability. The validation process involves the use of conductivity-temperature-depth (CTD) instruments and mooring tidal stations. The validated model is considered capable of accurately simulating tidal propagation as it represents the temperature-salinity-density properties within the estuarine environment. The development of this model demonstrates the effective implementation of these parameters within the Musi estuary ecosystem domain. The 3D model simulation is used to consider the vertical discretization in the river-estuary-sea channel, which enhances the representation of temperature-salinity-density in the water column. The obtained results suggest that the 3D-MIKE modeling is well-suited for operational purposes, including the prediction of hydrodynamics and the management of estuarine areas, specifically in the Musi estuary ecosystem.

Multi-Sensor Observations Reveal Large-Amplitude Nonlinear Internal Waves in the Kara Gates, Arctic Ocean

We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers, and repeated conductivity–temperature–depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas during spring tide in August 2021. Analysis of the field data during an 18-h period from four stations provides evidence that a complex sill in the Kara Gates is the site of regular production of intense large-amplitude nonlinear internal waves. Satellite data show a presence of a relatively warm northeastward surface current from the Barents Sea toward the Kara Sea attaining 0.8–0.9 m/s. Triangle-shaped measurements using three thermal profilers revealed pronounced vertical thermocline oscillations up to 40 m associated with propagation of short-period nonlinear internal waves of depression generated by stratified flow passing a system of shallow sills in the strait. The most intense waves were recorded during the ebb tide slackening and reversal when the background flow was predominantly supercritical. Observed internal waves had wavelengths of ~100 m and traveled northeastward with phase speeds of 0.8–0.9 m/s. The total internal wave energy per unit crest length for the largest waves was estimated to be equal to 1.0–1.8 MJ/m.

Upwellings and downwellings on the edge of the Gaspé Current: Observations and processes

The Gaspé Current carries the relatively fresh surface waters of the St. Lawrence estuary along the Gaspé peninsula to the Gulf of St. Lawrence. It presents complex dynamics including the development of meanders. A density front separates the fresher surface waters of the estuary from the saltier surface waters of the gulf. Over the past 40 years, upwellings and downwellings observed on the edge of this front have been the subject of several investigations. Tang (1982) proposed an analytical model featuring a permanent circulation consisting of an upwelling offshore of the front and a downwelling below the front. Using a unique set of in situ observations made with CTD (Conductivity Temperature Depth) profilers and ADCP (Acoustic Doppler Current Profiler) data collected between September 1991 and June 1993, upwellings and downwellings were inferred using a water masses analysis. Even if their presence is predominant (∼ 80% of the total number of sampled transects), they are not a permanent feature over the entire length of the Gaspé Current front, and their positions relative to the front vary. This data set also made it possible to determine via the ω equation that these vertical currents mostly result from frontogenesis and frontolysis (strengthening and weakening of the front). A new method to combine the ω equation with the nonlinear Ekman pumping shows that wind-driven vertical motions were generally weaker and much shallower than those due to frongenesis/frontolysis. This analysis shows that upwellings and downwellings are dependent on favorable conditions leading to the establishment of Gaspé Current instabilities and to frontogenesis or frontolysis.

Two-Step Correction Based on In-Situ Sound Speed Measurements for USBL Precise Real-Time Positioning

The ultra-short baseline (USBL) positioning system has been widely used for autonomous and remotely operated vehicle (ARV) positioning in marine resource surveying and ocean engineering fields due to its flexible installation and portable operation. Errors related to the sound speed are a critical factor limiting the positioning performance. The conventional strategy adopts a fixed sound velocity profile (SVP) to correct the spatial variation, especially in the vertical direction. However, SVP is actually time-varying, and ignoring this kind of variation will lead to a worse estimation of ARVs’coordinates. In this contribution, we propose a two-step sound speed correction method, where, firstly, the deviation due to the acoustic ray bending effect is corrected by the depth-based ray-tracing policy with the fixed SVP. Then, the temporal variation of SVP is considered, and the fixed SVP is adaptively adjusted according to the in situ sound velocity (SV) measurements provided by the conductivity–temperature–depth (CTD) sensor equipped at the ARV. The proposed method is verified by semi-physical simulation and sea-trail dataset in the South China Sea. When compared to the fixed-SVP method, average positioning accuracy with the resilient SVP be improved by 8%, 21%, and 26% in the east, north, and up directions, respectively. The results demonstrate that the proposed method can efficiently improve the adaptability of sound speed observations and deliver better performance in USBL real-time positioning.

Integrated and compact fiber-optic conductivity-temperature-depth (CTD) sensor for marine detection

Integrated and compact fiber-optic conductivity-temperature-depth (CTD) sensor for marine detection

A meta-deep-learning framework for spatio-temporal underwater SSP inversion

Sound speed distribution, represented by a sound speed profile (SSP), is of great significance because the nonuniform distribution of sound speed will cause signal propagation path bending with Snell effect, which brings difficulties in precise underwater localization such as emergency rescue. Compared with conventional SSP measurement methods via the conductivity-temperature-depth (CTD) or sound-velocity profiler (SVP), SSP inversion methods leveraging measured sound field information have better real-time performance, such as matched field process (MFP), compressed sensing (CS) and artificial neural networks (ANN). Due to the difficulty in measuring empirical SSP data, these methods face with over-fitting problem in few-shot learning that decreases the inversion accuracy. To rapidly obtain accurate SSP, we propose a task-driven meta-deep-learning (TDML) framework for spatio-temporal SSP inversion. The common features of SSPs are learned through multiple base learners to accelerate the convergence of the model on new tasks, and the model’s sensitivity to the change of sound field data is enhanced via meta training, so as to weaken the over-fitting effect and improve the inversion accuracy. Experiment results show that fast and accurate SSP inversion can be achieved by the proposed TDML method.

A novel fast response and high precision water temperature sensor based on Fiber Bragg Grating

A novel fast response and high precision water temperature sensor scheme based on gallium alloy sensitivity enhanced Fiber Bragg Grating(FBG) is proposed and experimentally demonstrated. In order to achieve faster temperature response speed of the sensor, a fiber Bragg grating is encapsulated in a single-end sealed metal tube which is filled with liquid gallium alloy. The very high thermal conductivity of the liquid gallium alloy that is filled in the metal tube gives rise to an experimental sensitivity of 30 pm/℃. Thanks to accurate and optimal design of metal tube structure parameters, the sensor exhibits an excellent response speed of 43 ms/℃ in water. Very good linearity between center wavelength of FBG and temperature is also achieved in the experiment. The research result of this paper is especially useful for applications where rapid temperature response and high precision are required at the same time, such as ocean CTD(Conductivity Temperature Depth) measuring equipment, ocean hydrology and underwater submersible.