Conductivity-temperature-depth Research Articles

Oxygen optodes on oceanographic moorings: recommendations for deployment and in situ calibration

Increasing interest in the deployment of optical oxygen sensors, or optodes, on oceanographic moorings reflects the value of dissolved oxygen (DO) measurements in studies of physical and biogeochemical processes. Optodes are well-suited for moored applications but require careful, multi-step calibrations in the field to ensure data accuracy. Without a standardized set of protocols, this can be an obstacle for science teams lacking expertise in optode data processing and calibration. Here, we provide a set of recommendations for the deployment and in situ calibration of data from moored optodes, developed from our experience working with a set of 60 optodes deployed as part of the Gases in the Overturning and Horizontal circulation of the Subpolar North Atlantic Program (GOHSNAP). In particular, we detail the correction of drift in moored optodes, which occurs in two forms: (i) an irreversible, time-dependent drift that occurs during both optode storage and deployment and (ii) a reversible and pressure-and-time-dependent drift that is detectable in some optodes deployed at depths greater than 1,000 m. The latter is virtually unidentified in the literature yet appears to cause a low-bias in measured DO on the order of 1 to 3 µmol kg−1 per 1,000 m of depth, appearing as an exponential decay over the first days to months of deployment. Comparisons of our calibrated DO time series against serendipitous mid-deployment conductivity-temperature-depth (CTD)-DO profiles, as well as biogeochemical (BGC)-ARGO float profiles, suggest the protocols described here yield an accuracy in optode-DO of ∼1%, or approximately 2.5 to 3 µmol kg−1. We intend this paper to serve as both documentation of the current best practices in the deployment of moored optodes as well as a guide for science teams seeking to collect high-quality moored oxygen data, regardless of expertise.

Mid-Summer observations of water column physical properties and circulation in the San Jorge Gulf (Patagonian Shelf)

In this study, we present detailed insights into the mid-summer density field and flow patterns within the San Jorge Gulf (Patagonian Shelf of Argentina). Utilizing unique data acquired from a towed undulating vehicle equipped with a Conductivity-Temperature-Depth (CTD) sensor and a hull-mounted acoustic Doppler current profiler (ADCP), we investigate the spatial distribution and temporal evolution of the density structure and associated currents. Our observations reveal the presence of a distinctive bottom dome-like structure comprised of dense, cold, and saline waters in the central basin of the gulf during mid-summer. Analysis of the flow dynamics indicates the presence of a near-geostrophic flow regime sustaining this dense water feature. Furthermore, our study highlights the significant role of ageostrophic velocities, primarily influenced by the modulation of pycnocline thickness by M2+M4 internal tides. These findings contribute to a deeper understanding of the oceanographic processes governing the mid-summer dynamics in the San Jorge Gulf, shedding light on the interaction between density structures and associated currents. Such insights are essential for advancing our knowledge of coastal ocean circulation and its implications for various ecological and environmental phenomena.

Refined Estimates of Global Ocean Deep and Abyssal Decadal Warming Trends

AbstractDeep and abyssal layer decadal temperature trends from the mid‐1980s to the mid‐2010s are mapped globally using Deep Argo and historical ship‐based Conductivity‐Temperature‐Depth (CTD) instrument data. Abyssal warming trends are widespread, with the strongest warming observed around Antarctic Bottom Water (AABW) formation regions. The warming strength follows deep western boundary currents transporting abyssal waters north and decreases with distance from Antarctica. Abyssal cooling trends are found in the North Atlantic and eastern South Atlantic, regions primarily ventilated by North Atlantic Deep Water (NADW). Deep warming trends are prominent in the Southern Ocean south of about 50°S, the Greenland‐Iceland‐Norwegian (GIN) Seas and the western subpolar North Atlantic, with cooling in the eastern subpolar North Atlantic and the subtropical and tropical western North Atlantic. Globally integrated decadal heat content trends of 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer are more certain than previous estimates.

Optical Detection of Underwater Propeller Wake Based on a Position-Sensitive Detector

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation, and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change in the refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. Furthermore, experiments were conducted to detect the flow field of a propeller wake. The experimental results indicate that the wake dissipation times of the propeller in a strong density-stratified water environment are approximately 800 s and 750 s. Following the stabilisation of the wake field density, the laser spot position is observed to be stable at 0.341 mm and 0.441 mm, respectively, with a corresponding refractive index change of 2.99 × 10−6 RIU (refractive index unit) and 3.87 × 10−6 RIU, respectively. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental wake measurements based on the device with the wake measurements based on a CTD (conductivity–temperature–depth) device reveals a consistent trend. The realisation of this detection technique is of great significance for the advancement of research in the field of optical detection of underwater vehicle wake streams.

Circulation and production of Cape Darnley Bottom Water on the continental slope off the Cape Darnley polynya, East Antarctica

The circulation and water properties of Cape Darnley Bottom Water (CDBW), which is a component of Antarctic Bottom Water (AABW) produced in the Cape Darnley polynya, were investigated using results of mooring measurements and hydrographic data collected by a ship-based conductivity-temperature-depth (CTD) profiler and instrumented elephant seals. CDBW was transported northwestward on the western flank of a gully located in Wild Canyon. As CDBW descended down the slope, its thickness increased from ∼100 m to ∼600 m. The basic properties of CDBW were determined near the Antarctic Slope Front (ASF), where modified shelf water (mSW) intrudes below the dense part of Circumpolar Deep Water (CDW) and mixes with the overlying CDW to produce CDBW. mSW is shown to be the mixture of 40–45 % CDW, 30–40 % winter water (WW), and 20–25 % shelf water (SW) produced in the Cape Darnley polynya. Compared with CDBW produced in 2008, CDBW produced in 2018 and 2019 was colder and less saline. The enhanced influence of dense WW, which is locally produced on the shelf, is suggested to drive the year-to-year variability of CDBW’s salinity, at least in these three years. Water properties indicate that CDBW basically corresponds to a water mass in a transition layer between mSW and CDW. The annual mean transport of mSW contained in CDBW was estimated to be 0.26–1.2×106 m3 s−1

A 70-year perspective on water-mass transformation in the Greenland Sea: From thermobaric to thermal convection

The hydrography of the central Greenland Sea was reconstructed from observations including bottle measurements, Conductivity/ Temperature/ Depth (CTD) measurements, and Argo floats for the period 1950 to 2020. Greenland Sea Deep Water was renewed during bottom-reaching convection prior to the mid-1980s, facilitated by the thermobaric effect. During a period of shallow convection in the late 1980s and early 1990s, a stratification maximum formed and isolated the deep from the intermediate Greenland Sea. As a consequence, convection was limited to depths shallower than 2000m during the past decades and a new class of intermediate water formed instead of deep water. The initial cause for the formation of the stratification maximum was a near-surface freshwater anomaly. A subsequent, rapid temperature and salinity increase in the upper 2000m resulted in an overall density reduction of the intermediate water which strengthened the stratification maximum. Along with the transition from formation of deep water to formation of intermediate water, the Greenland Sea became temperature-stratified at intermediate depths. This regime-shift in stratification can be traced to increased temperature and salinity in the inflowing Atlantic-origin Water. Below the stratification maximum, the Greenland Sea Deep Water became warmer and more saline, predominantly caused by lateral mixing with deep water masses from adjacent basins. The hydrographic changes in the Greenland Sea were investigated in the context of a reduction of the sea-ice extent and associated changes in winter heat loss. While interannual variability of convection depth may depend on atmospheric forcing, we found that the decadal variability of water-mass transformation in the Greenland Sea was largely determined by the hydrographic structure of the water column.

The first deployments of pop‐up satellite archival tags on black sea bass (Centropristis striata)

AbstractBlack sea bass (Centropristis striata; BSB) are a commercially managed species with an increasing population in the Northwest Atlantic Ocean. Understanding their movement ecology can be difficult due to their wide distribution and ability to inhabit both inshore and offshore reef habitats. BSB have been studied using a range of tagging techniques, and here we present the results of the first deployments of pop‐up satellite archival tags (PSAT) on this species. During 2019 and 2021, we conducted four fishing trips within the southern Mid‐Atlantic Bight region of the NW Atlantic and tagged a total of 30 fish with T‐bar tags and external data loggers, of which 4 received a PSAT and the rest received a Star‐Oddi conductivity–temperature–depth (CTD) archival tag. All PSATs transmitted some data, with short attachment durations (8–32 days) relative to the programmed release of 250 days, and we did not recover a Star‐Oddi tag. External tag attachment techniques need to be examined and improved before continued deployment of larger data loggers on BSB.

Measurement Biases in Ocean Temperature Profiles from Marine Mammal Dataloggers

Abstract The study focuses on biases in ocean temperature profiles obtained by means of Satellite Relay Data Loggers (SRDL recorders) and time–depth recorder (TDR) attached to marine mammals. Quasi-collocated profiles from Argo floats and from ship-based conductivity–temperature–depth (CTD) profilers are used as reference. SRDL temperature biases depend on the sensor type and vary with depth. For the most numerous group of Valeport 3 (VP3) and conductivity–temperature–fluorescence (CTF) sensors, the bias is negative except for the layer 100–200 m. The vertical bias structure suggests a link to the upper-ocean thermal structure within the upper 200-m layer. Accounting for a time lag which might remain in the postprocessed data reduces the bias variability throughout the water column. Below 200-m depth, the bias remains negative with the overall mean of −0.027° ± 0.07°C. The suggested depth and thermal corrections for biases in SRDL data are within the uncertainty limits declared by the manufacturer. TDR recorders exhibit a different bias pattern, showing the predominantly positive bias of 0.08°–0.14°C below 100 m primarily due to the systematic error in pressure. Significance Statement The purpose of this work is to improve the consistency of the data from the specific instrumentation type used to measure ocean water temperature, namely, the data from miniature temperature sensors attached to marine mammals. As mammals dive during their route to and from their feeding areas, these sensors measure water temperature and dataloggers send the measured temperature data to oceanographic data centers via satellites as soon as the mammals return to the sea surface. We have shown that these data exhibit small systematic instrumental errors and suggested the respective corrections. Taking these corrections into account is important for the assessment of the ocean climate change.

Vertical Characteristic of Water Mass in The Flores Sea: The Effect of The ITF on The Transitional Season

Abstract Indonesian Through Flow (ITF) forms unique water mass characteristics in Indonesian Marine Waters. This water mass enters through the Makassar Strait into the Banda Sea by crossing the Flores Sea. This study aims to analyse the characteristics of water masses in the Flores Sea during the transition season. In situ data was obtained using conductivity temperature depth (CTD) at four stations in the Flores Sea from April to May 2023. Next, the data was processed and analysed for layer thickness through vertical stratification and water mass characteristics using T-S diagrams. The analysis results show that the thickness of the homogeneous layer in the Flores Sea in the first transition season is between a depth of 0-40 m, the thermocline layer is at a depth of 40-300 m, and the depth layer is from a depth of 400-900 m. Apart from that, the characteristics of the water mass identified through the T-S diagram are: North Pacific Subtropical Water (NPSW) is found at a depth of 100-150 m with a temperature between 20-26° C and a salinity between 34.9-35.4 psu. Another water mass is South Pacific Intermediate Water (SPIW) at a depth of 500-800 m with a temperature of 6-8° C and a salinity of 34.55-34.65 psu. In contrast, the Antarctic Intermediate Water (AAIW) was found at a depth of >750 m with a temperature of 5-6° C and a salinity of 34.5-34.6 psu.

Ichthyoplankton Biodiversity in the Indonesian Fisheries Management Area-573 in 2015

Abstract Studying ichthyoplankton is crucial for understanding the impact of fish larvae mortality on the recruitment of adult fish and fishing resources. Fish larvae samples were collected in the southern waters of Java using the Baruna Jaya IV research vessel in September - October 2015. Fish larvae were collected using bongo-net and oceanographic data were collected using Conductivity Temperature Depth (CTD) are Temperature and salinity and chlorophyll-a using Aqua MODIS satellite L3 at 36 stations. The results showed the range of fish larvae abundance was 0 - 2,074 ind/1000 m3 with an average of 174 ind/1000 m3. The fish eggs were found with an abundance of 0 - 1,601 eggs/1000 m3. and an average of 213 eggs/1000 m3. The composition of fish larvae recorded 22 families, there were 5 dominant families namely Scombridae (28.60%), Bregmacerotidae (22.96%), Carangidae (7.93%), Blennidae (7.52%), and Gobiidae (7.52%). The diversity of fish larvae was most prevalent at station 28 (SST 26.7 0C; SSS 34.4 PSU; and CHL-a 0.43 mg/m3) and station 36 (SST 27.4 0C; SSS 34.4 PSU) each found 9 families. The abundance of fish larvae was mostly found at stasion 11 had SST 23.50 0C; SSS 34.56 PSU; and CHL-a 0.33 mg/m3 with the dominance of the family Bregmacerotidae. Scombridae was mostly found at stasion 22 with sea surface temperature (SST) 26.52 0C; sea surface salinity (SSS) 34.28 PSU; and sea surface chlorophyll-a (CHL-a) 0.41 mg/m3 which is in the southern waters of Lombok.

Machine Learning-Based Anomaly Detection on Seawater Temperature Data with Oversampling

Machine Learning-Based Anomaly Detection on Seawater Temperature Data with Oversampling

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 1000 m and 5000 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 °C to 10 °C 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