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  • 1
    Publication Date: 2022-05-26
    Description: © The Author(s), [year]. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Carvalho, F., Gorbunov, M. Y., Oliver, M. J., Haskins, C., Aragon, D., Kohut, J. T., & Schofield, O. FIReglider: mapping in situ chlorophyll variable fluorescence with autonomous underwater gliders. Limnology and Oceanography: Methods, (2020), doi:10.1002/lom3.10380.
    Description: Nutrient and light availability regulate phytoplankton physiology and photosynthesis in the ocean. These physiological processes are difficult to sample in time and space over physiologically and ecologically relevant scales using traditional shipboard techniques. Gliders are changing the nature of data collection, by allowing a sustained presence at sea over regional scales, collecting data at resolution not possible using traditional techniques. The integration of a fluorescence induction and relaxation (FIRe) sensor in a Slocum glider allows autonomous high‐resolution and vertically‐resolved measurements of photosynthetic physiological variables together with oceanographic data. In situ measurements of variable fluorescence under ambient light allows a better understanding of the physical controls of primary production (PP). We demonstrate this capability in a laboratory setting and with several glider deployments in the Southern Ocean. Development of these approaches will allow for the in situ evaluation of phytoplankton light stress and photoacclimation mechanisms, as well as the role of vertical mixing in phytoplankton dynamics and the underlying physiology, especially in remote locations and for prolonged duration.
    Description: This work was supported by National Science Foundation (NSF Palmer LTER program, grant 0823101), National Oceanographic Partnership Program (NOPP, grant NA05OAR4601089), and NASA Ocean Biology and Biogeochemistry Program (grants NNX16AT54G and 80NSSC18K1416). Filipa Carvalho was funded by a Portuguese doctoral fellowship from Fundação para a Ciência e Tecnologia (FCT, grant DFRH ‐ SFRH/BD/72705/2010), a Teledyne Marine Graduate Fellowship and a European Research Council Consolidator grant (GOCART, agreement number 724416).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-11-03
    Description: The EXPORTS North Atlantic field campaign (EXPORTS-NA) of May 2021 used a diverse array of ship-based and autonomous platforms to measure and quantify processes leading to carbon export in the open ocean. The success of this field program relied heavily on the ability to make measurements following a Lagrangian trajectory within a coherent, retentive eddy (Sections 1, 2). Identifying an eddy that would remain coherent and retentive over the course of a monthlong deployment was a significant challenge that the EXPORTS team faced. This report details the processes and procedures used by the primarily shore-based eddy tracking team to locate, track, and sample with autonomous assets such an eddy before and during EXPORTS-NA.
    Description: This field deployment was funded by the NASA Ocean Biology and Biogeochemistry program and the National Science Foundation Biological and Chemical Oceanography programs. Initial gliders deployments were performed by the RRS Discovery and the authors thank the Porcupine Abyssal Plain – Sustained Observatory of the Natural Environment Research Council (NERC, UK), which is principally funded through the Climate Linked Atlantic Sector Science (CLASS) project supported by NERC National Capability funding (NE/R015953/1) and by IFADO (Innovation in the Framework of the Atlantic Deep Ocean) EAPA_165/2016. Technical assistance with glider deployment was provided by Marine Autonomous Robotic Systems (NOC). The authors thank Inia Soto Ramos for assistance in publishing this manuscript through the NASA Technical Memorandum series. This is PMEL contribution number 5372.
    Keywords: NASA/TM–20220009705
    Repository Name: Woods Hole Open Access Server
    Type: Working Paper
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  • 3
    Publication Date: 2024-04-26
    Description: The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Format: text
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  • 4
    Publication Date: 2024-04-27
    Description: Physical, chemical and biogeochemical measurements derived from CTD-rosette deployments during three visits to site P3 (November to December, 2017) in the South Atlantic. Measurements were made during COMICS cruise DY086 on the RRS Discovery using a trace metal free Titanium Rosette (events 4, 7, 15, 19, 24, 26, 29) and a Stainless Steel Rosette (all other events). Physical parameters include temperature, salinity, density, photosynthetically active radiation and turbulence; chemical parameters include dissolved oxygen, dissolved oxygen saturation, nitrate, phosphate and silicate; biogeochemical parameters include turbidity, beam transmittance, beam attenuation, fluorescence, particulate organic carbon (POC), dissolved organic carbon (DOC), chlorophyll-a, net primary productivity (NPP), ambient leucine assimilation and bacterial cell count. To determine turbulence, a downward facing lowered acoustic doppler current profiler (LADCP, Teledyne Workhorse Monitor 300 kHz ADCP) was attached to the CTD frame. Shear and strain, which are obtained from velocity and density measurements, were used to estimate the dissipation rate of turbulent kinetic energy and the diapycnal eddy diffusivity from a fine-scale parameterisation. Estimates are calculated by parameterising internal wave-wave interactions and assuming that wave breaking modulates turbulent mixing. A detailed description of the method for calculating diffusivity from LADCP and CTD can be found in Kunze et al. (2006). Two datasets with different vertical resolutions were produced: one in which the shear is integrated from 150 to 300 m and the strain over 20-150 m, and one in which the shear is integrated from 70 to 200 m and the strain over 30-200 m. Nutrients (nitrate, phosphate, silicate) were determined via colourimetric analysis (see cruise report, Giering and Sanders, 2019), POC was determined as described in Giering et al. (2023), DOC and DOC flux were determined as described in Lovecchio et al. (2023), NPP was determined as described in Poulton et al. (2019), and ambient leucine assimilation and bacterial cell count were determined as described in Rayne et al. (2024). Bacterial abundance and leucine assimilation were made from bottle samples of six CTD casts of the stainless-steel rosette. Water was collected at six depths (6 m, deep-chlorophyll maximum, mixed layer depth + 10, 100, 250 and 500 m). Acid-cleaned HDPE carboys and tubing were used for sampling. Samples were then stored in the dark and at in-situ temperature prior to on-board laboratory sample preparation or analysis. Flow cytometry was used to measure bacterial abundance. Room temperature paraformaldehyde was used to fix 1.6 ml samples for 30 minutes. Then, using liquid nitrogen, the samples were flash frozen and stored at -80°C. Samples were then defrosted before being stained using SYBR Green I and run through the flow cytometer (BD FACSort™). The method of Hill et al. (2013) was applied to determine prokaryotic leucine assimilation using L-[4,5-³H] leucine which has a specific activity of 89.3 Ci/mmol­. In the mixed and upper layers of the water column, the protocol in Zubkov et al. (2007) was followed. Below the mixed layer, adaptions to the method included reducing the concentration of ³H-Leucine to 0.005, 0.01, 0.025, 0.04 and 0.05 nM; increasing experimental volumes to 30 ml; enhancing incubation times to 30, 60, 90 and 120 min. These adaptions were made to improve accuracy where lower rates of leucine assimilation were expected. Data were provided by the British Oceanographic Data Centre and funded by the National Environment Research Council.
    Keywords: 74EQ20171115; Angular scattering coefficient, 700 nm; Attenuation, optical beam transmission; Bacteria; Barometer, Paroscientific, Digiquartz TC; biological carbon pump; Calculated; Calculated according to UNESCO (1983); Calculation according to Kunze et al. (2006); Carbon, organic, dissolved; Carbon, organic, dissolved, flux; Carbon, organic, particulate; Chlorophyll a; Colorimetric analysis; COMICS; Conductivity sensor, SEA-BIRD SBE 4C; Controls over Ocean Mesopelagic Interior Carbon Storage; CTD/Rosette; CTD-RO; DATE/TIME; Density, sigma-theta (0); DEPTH, water; Discovery (2013); Dissipation rate; Dissolved Oxygen Sensor, Sea-Bird, SBE 43 and SBE 43F; DY086; DY086_CTD002; DY086_CTD003; DY086_CTD004; DY086_CTD005; DY086_CTD006; DY086_CTD007; DY086_CTD008; DY086_CTD009; DY086_CTD010; DY086_CTD015; DY086_CTD016; DY086_CTD017; DY086_CTD018; DY086_CTD019; DY086_CTD020; DY086_CTD021; DY086_CTD022; DY086_CTD023; DY086_CTD024; DY086_CTD026; DY086_CTD027; DY086_CTD028; DY086_CTD029; DY086_CTD030; DY086_CTD031; DY086_CTD032; DY086_CTD033; Eddy diffusivity; Event label; Flow cytometer, Becton Dickinson, FACSort; Fluorometer, Chelsea Instruments, Aquatracka MKIII; fluxes; High Temperature Catalytic Oxidation (Shimadzu TOC-VCPN); LATITUDE; Leucine uptake rate; Liquid scintillation counter, Packard, TRI-CARB 3100TR; LONGITUDE; marine biogeochemistry; Net primary production of carbon; Nitrate; Organic Elemental Analyzer, Thermo Fisher Scientific, Flash 2000; Oxygen; Oxygen saturation; PAR sensor, Biospherical, LI-COR, SN 70510; PAR sensor, Biospherical, LI-COR, SN 70520; Phosphate; Radiation, photosynthetically active; Radioassays, liquid scintillation counting; Salinity; Scattering meter, WET Labs, ECO-BB OBS; Silicate; Site; SUMMER; Sustainable Management of Mesopelagic Resources; Temperature, water; Temperature sensor, SEA-BIRD SBE 3Plus; Transmissometer, WET Labs, C-Star
    Type: Dataset
    Format: text/tab-separated-values, 171794 data points
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  • 5
    Publication Date: 2024-04-27
    Description: Discrete measurements of particulate organic carbon (POC) concentration and flux were made on the RRS Discovery during COMICS cruise DY086 at site P3 in the South Atlantic from November to December, 2017 (Giering et al. 2023). Data is from a variety of equipment including marine snow catchers, neutrally-buoyant sediment traps (PELAGRA) and a stand-alone pump system. Marine snow catchers settled on-deck for 2 hours. Slow sinking particles were collected from the base and fast sinking particles were collected from the tray. These data were used along with bottle POC data to calibrate glider backscatter data from the GOCART project.
    Keywords: 74EQ20171115; biological carbon pump; Carbon, organic, particulate; Carbon, organic, particulate, flux; COMICS; Controls over Ocean Mesopelagic Interior Carbon Storage; Date/Time of event; DEPTH, water; Discovery (2013); DY086; DY086_MSC006; DY086_MSC007; DY086_MSC010; DY086_MSC015; DY086_MSC016; DY086_MSC019; DY086_MSC020; DY086_MSC022; DY086_MSC027; DY086_MSC028; DY086_MSC029; DY086_MSC034; DY086_MSC035; DY086_MSC036; DY086_MSC037; DY086_MSC038; DY086_MSC039; DY086_MSC040; DY086_MSC061; DY086_MSC062; DY086_MSC063; DY086_MSC067; DY086_MSC068; DY086_MSC069; DY086_MSC071; DY086_MSC072; DY086_MSC076; DY086_MSC077; DY086_MSC078; DY086_MSC079; DY086_MSC081; DY086_MSC082; DY086_MSC083; DY086_MSC084; DY086_MSC093; DY086_MSC094; DY086_MSC099; DY086_MSC100; DY086_MSC101; DY086_MSC103; DY086_MSC104; DY086_MSC105; DY086_MSC106; DY086_MSC111; DY086_MSC112; DY086_MSC113; DY086_MSC114; DY086_MSC125; DY086_MSC126; DY086_MSC127; DY086_MSC128; DY086_Pelagra006; DY086_Pelagra007; DY086_Pelagra008; DY086_Pelagra009; DY086_Pelagra010; DY086_Pelagra011; DY086_Pelagra012; DY086_Pelagra013; DY086_Pelagra014; DY086_Pelagra015; DY086_Pelagra016; DY086_Pelagra017; DY086_Pelagra018; DY086_Pelagra019; DY086_Pelagra020; DY086_Pelagra021; DY086_Pelagra022; DY086_Pelagra023; DY086_Pelagra024; DY086_Pelagra025; DY086_Pelagra026; DY086_Pelagra027; DY086_Pelagra028; DY086_Pelagra029; DY086_Pelagra030; DY086_Pelagra031; DY086_Pelagra032; DY086_Pelagra033; DY086_Pelagra034; DY086_Pelagra035; DY086_Pelagra036; DY086_Pelagra037; DY086_Pelagra038; DY086_SAPS001; DY086_SAPS002; DY086_SAPS003; DY086_SAPS004; DY086_SAPS005; Event label; fluxes; Latitude of event; Longitude of event; marine biogeochemistry; Marine snow catcher; MSC; PELAGRA; SAPS; Site; Stand-alone pumps; SUMMER; Sustainable Management of Mesopelagic Resources; Trap, sediment, drifting
    Type: Dataset
    Format: text/tab-separated-values, 366 data points
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  • 6
    Publication Date: 2024-05-07
    Description: Binned median of Slocum G2 glider data from 0 to 1000 m depth. The data were collected in the northern Benguela region between 14 February 2018 and 19 June 2018 at a site approximately 100 km from the coast. The glider sampled continuously following a triangular path of ~12 km per side roughly centred on 10.8°E, 18.1°S. The glider sampled only on the upward dive with a vertical resolution of ~20 cm, emerging 5 to 6 times per day. Temperature, Conductivity and Depth were measured with a standard Slocum Glider Payload CTD (pumped) from Seabird (SN 9109). Dissolved oxygen was measured with an Aanderaa optode, model 4831 (SN286). Depth-averaged currents (DAC) for each 1000 m downward and upward dive were estimated from the difference between the glider's actual and predicted surfacing locations. Glider surface currents were also estimated at each surfacing via linear regression of GPS location with respect to time. Salinity and oxygen data were calibrated against shipboard CTD bottle samples. The data have been binned (median) into 6 hourly, 2 m depth bins for all variables while the currents timeseries were binned daily (median). 1D variables consist of: time (seconds since 00:00:00 on 1 January 0000), depth (meters), longitude (degrees East), latitude (degrees South), zonal and meridional glider surface currents (U_surf and V_surf, m/s), and zonal and meridional glider depth averaged currents (U_dac and V_dac, m/s). 2D variables consist of: conservative temperature (°C), absolute salinity (g/kg), potential density (kg/m³), and dissolved oxygen concentration (µmol/kg).
    Keywords: Benguela_transect; Benguela Upwelling System; COMICS; Controls over Ocean Mesopelagic Interior Carbon Storage; Gauging ocean Organic Carbon fluxes using Autonomous Robotic Technologies; Glider; GOCART; hypoxia; ocean; Oxygen; Salinity; Slocum G2 glider; SNF_184251; Temperature; The influence of mesoscale variability on organic carbon export fluxes: bridging models and observations
    Type: Dataset
    Format: application/zip, 6.3 MBytes
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