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  • 1
    facet.materialart.
    Unknown
    In:  (Master thesis), Christian-Albrechts-Universität Kiel, Kiel, Germany, 41 pp
    Publication Date: 2017-12-08
    Keywords: Course of study: MSc Biological Oceanography
    Type: Thesis , NonPeerReviewed
    Format: text
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  • 2
    Publication Date: 2024-02-07
    Description: A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, especially in coastal areas, and some of them are still in operation. However, while in earlier times these measurements were done by hand every day, current environmental long-term observation stations (ELTOS) are often fully automated and integrated in cabled underwater observatories (UWOs). With this new technology, year-round measurements became feasible even in remote or difficult to access areas, such as coastal areas of the Arctic Ocean in winter, where measurements were almost impossible just a decade ago. In this context, there is a question over what extent the sampling frequency and accuracy influence results in long-term monitoring approaches. In this paper, we address this with a combination of lab experiments on sensor accuracy and precision and a simulated sampling program with different sampling frequencies based on a continuous water temperature dataset from Svalbard, Arctic, from 2012 to 2017. Our laboratory experiments showed that temperature measurements with 12 different temperature sensor types at different price ranges all provided measurements accurate enough to resolve temperature changes over years on a level discussed in the literature when addressing climate change effects in coastal waters. However, the experiments also revealed that some sensors are more suitable for measuring absolute temperature changes over time, while others are more suitable for determining relative temperature changes. Our simulated sampling program in Svalbard coastal waters over 5 years revealed that the selection of a proper sampling frequency is most relevant for discriminating significant long-term temperature changes from random daily, seasonal, or interannual fluctuations. While hourly and daily sampling could deliver reliable, stable, and comparable results concerning temperature increases over time, weekly sampling was less able to reliably detect overall significant trends. With even lower sampling frequencies (monthly sampling), no significant temperature trend over time could be detected. Although the results were obtained for a specific site, they are transferable to other aquatic research questions and non-polar regions.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
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  • 3
    Publication Date: 2023-09-28
    Keywords: dissolved methane; Modular Observation Solutions for Earth Systems; MOSES; Salinity; sediment methane; turbidity
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 4
    Publication Date: 2024-02-12
    Description: During Stern_3 single water samples were taken either from a rosette (vertical) or from on the way systems. For the on the way systems a time off-set was calculated and subtracted from the original time. The aim of the sampling was mainly to counter-check with different sensors. More details can be found in the expedition report (Fahrtbericht Moses Sternfahrten). For methane concentrations, water was transferred to glass bottles (120 ml) and stored cold (4°).
    Keywords: Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; dissolved methane; Event label; KON_stern_3; L19-11_stern_3; LATITUDE; Littorina; LONGITUDE; Ludwig Prandtl; Methane; Methane, sediment; Name; OPTIMARE Precision Salinometer System; Salinity; Sample ID; sediment methane; Sediment sample; SES; stern_3-1; stern_3-10; stern_3-100; stern_3-101; stern_3-102; stern_3-103; stern_3-104; stern_3-105; stern_3-106; stern_3-107; stern_3-108; stern_3-109; stern_3-11; stern_3-110; stern_3-111; stern_3-112; stern_3-113; stern_3-114; stern_3-115; stern_3-116; stern_3-117; stern_3-118; stern_3-119; stern_3-12; stern_3-120; stern_3-121; stern_3-122; stern_3-123; stern_3-124; stern_3-125; stern_3-126; stern_3-127; stern_3-128; stern_3-129; stern_3-13; stern_3-130; stern_3-131; stern_3-132; stern_3-133; stern_3-134; stern_3-135; stern_3-136; stern_3-137; stern_3-138; stern_3-139; stern_3-14; stern_3-140; stern_3-141; stern_3-142; stern_3-143; stern_3-144; stern_3-145; stern_3-146; stern_3-147; stern_3-148; stern_3-149; stern_3-15; stern_3-150; stern_3-151; stern_3-152; stern_3-153; stern_3-154; stern_3-155; stern_3-156; stern_3-157; stern_3-158; stern_3-16; stern_3-17; stern_3-18; stern_3-19; stern_3-2; stern_3-20; stern_3-21; stern_3-22; stern_3-23; stern_3-24; stern_3-25; stern_3-26; stern_3-27; stern_3-28; stern_3-29; stern_3-3; stern_3-30; stern_3-31; stern_3-32; stern_3-33; stern_3-34; stern_3-35; stern_3-36; stern_3-37; stern_3-38; stern_3-39; stern_3-4; stern_3-40; stern_3-41; stern_3-42; stern_3-43; stern_3-44; stern_3-45; stern_3-46; stern_3-47; stern_3-48; stern_3-49; stern_3-5; stern_3-50; stern_3-51; stern_3-52; stern_3-53; stern_3-54; stern_3-55; stern_3-56; stern_3-57; stern_3-58; stern_3-59; stern_3-6; stern_3-60; stern_3-61; stern_3-62; stern_3-63; stern_3-64; stern_3-65; stern_3-66; stern_3-67; stern_3-68; stern_3-69; stern_3-7; stern_3-70; stern_3-71; stern_3-72; stern_3-73; stern_3-74; stern_3-75; stern_3-76; stern_3-77; stern_3-78; stern_3-79; stern_3-8; stern_3-80; stern_3-81; stern_3-82; stern_3-83; stern_3-84; stern_3-85; stern_3-86; stern_3-87; stern_3-88; stern_3-89; stern_3-9; stern_3-90; stern_3-91; stern_3-92; stern_3-93; stern_3-94; stern_3-95; stern_3-96; stern_3-97; stern_3-98; stern_3-99; Sternfahrt 3, KON; Sternfahrt 3, L19-11, 20190201; Sternfahrt 3, UT09; Time in seconds; turbidity; Turbidity; Turbidity meter, Hach, 2100N IS; Type; UT09_stern_3; Uthörn; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 1089 data points
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  • 5
    Publication Date: 2024-02-12
    Description: During Stern_2 cruise single water samples were taken either from a rosette (vertical) or from on the way systems. For the on the way systems a time off-set was calculated and subtracted from the original time. The aim of the sampling was mainly to counter-check with different sensors. More details can be found in the expedition report (Fahrtbericht Moses Sternfahrten). For methane concentrations, water was transferred to glass bottles (120 ml) and stored cold (4°). In the home laboratory a 20 ml head space was created and analyzed via gas chromatography. Magen et al. (2014).
    Keywords: Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; dissolved methane; Event label; KON_stern_2; LATITUDE; LONGITUDE; Ludwig Prandtl; Methane; Name; OPTIMARE Precision Salinometer System; Salinity; Sample ID; stern_2-1; stern_2-10; stern_2-100; stern_2-101; stern_2-102; stern_2-103; stern_2-104; stern_2-105; stern_2-106; stern_2-107; stern_2-108; stern_2-109; stern_2-11; stern_2-110; stern_2-111; stern_2-112; stern_2-113; stern_2-114; stern_2-115; stern_2-116; stern_2-117; stern_2-118; stern_2-12; stern_2-13; stern_2-14; stern_2-15; stern_2-16; stern_2-17; stern_2-18; stern_2-19; stern_2-2; stern_2-20; stern_2-21; stern_2-22; stern_2-23; stern_2-24; stern_2-25; stern_2-26; stern_2-27; stern_2-28; stern_2-29; stern_2-3; stern_2-30; stern_2-31; stern_2-32; stern_2-33; stern_2-34; stern_2-35; stern_2-36; stern_2-37; stern_2-38; stern_2-39; stern_2-4; stern_2-40; stern_2-41; stern_2-42; stern_2-43; stern_2-44; stern_2-45; stern_2-46; stern_2-47; stern_2-48; stern_2-49; stern_2-5; stern_2-50; stern_2-51; stern_2-52; stern_2-53; stern_2-54; stern_2-55; stern_2-56; stern_2-57; stern_2-58; stern_2-59; stern_2-6; stern_2-60; stern_2-61; stern_2-62; stern_2-63; stern_2-64; stern_2-65; stern_2-66; stern_2-67; stern_2-68; stern_2-69; stern_2-7; stern_2-70; stern_2-71; stern_2-72; stern_2-73; stern_2-74; stern_2-75; stern_2-76; stern_2-77; stern_2-78; stern_2-79; stern_2-8; stern_2-80; stern_2-81; stern_2-82; stern_2-83; stern_2-84; stern_2-85; stern_2-86; stern_2-87; stern_2-88; stern_2-89; stern_2-9; stern_2-90; stern_2-91; stern_2-92; stern_2-93; stern_2-94; stern_2-95; stern_2-96; stern_2-97; stern_2-98; stern_2-99; Sternfahrt 2, KON, 20190244; Sternfahrt 2, UT05/2019; Time in seconds; turbidity; Turbidity; Turbidity meter, Hach, 2100N IS; Type; UT05/2019_stern_2; Uthörn; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 774 data points
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  • 6
    Publication Date: 2024-02-12
    Description: During Stern_1 single water samples were taken either from a rosette (vertical) or from on the way systems. For the on the way systems a time off-set was calculated and subtracted from the original time. The aim of the sampling was mainly to counter-check with different sensors. More details can be found in the expedition report (Fahrtbericht Moses Sternfahrten). For methane concentrations, water was transferred to glass bottles (120 ml) and stored cold (4°). In the home laboratory a 20 ml head space was created and analyzed via gas chromatography. Magen et al. (2014).
    Keywords: Cruise/expedition; DATE/TIME; DEPTH, water; dissolved methane; Event label; KON_stern_1; L19-03_stern_1; LATITUDE; Littorina; LONGITUDE; Ludwig Prandtl; Methane; MYA2019/04_stern_1; Mya II; Name; OPTIMARE Precision Salinometer System; Salinity; Sample ID; stern_1-1; stern_1-10; stern_1-11; stern_1-12; stern_1-13; stern_1-14; stern_1-15; stern_1-16; stern_1-17; stern_1-18; stern_1-19; stern_1-2; stern_1-20; stern_1-21; stern_1-22; stern_1-23; stern_1-24; stern_1-25; stern_1-26; stern_1-27; stern_1-28; stern_1-29; stern_1-3; stern_1-30; stern_1-31; stern_1-32; stern_1-33; stern_1-34; stern_1-35; stern_1-36; stern_1-37; stern_1-38; stern_1-39; stern_1-4; stern_1-40; stern_1-41; stern_1-42; stern_1-43; stern_1-44; stern_1-45; stern_1-46; stern_1-47; stern_1-48; stern_1-49; stern_1-5; stern_1-50; stern_1-51; stern_1-52; stern_1-53; stern_1-54; stern_1-55; stern_1-6; stern_1-7; stern_1-8; stern_1-9; Sternfahrt 1, KON, 20190239; Sternfahrt 1, L19-03, 20190193; Sternfahrt 1, MYA2019/04; Time in seconds; turbidity; Turbidity; Turbidity meter, Hach, 2100N IS; Type; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 404 data points
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  • 7
    Publication Date: 2024-05-11
    Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll a and turbidity data from the Helgoland MarGate underwater observatory from the year 2020 in a temporal resolution of 1 hour. The cabled observatory is located in 10m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-helgoland.html). For a detailed description of the data see associated metadatafile "Metadata_description_heluwobs_data_2020.pdf"
    Keywords: ACROSS; Advanced Remote Sensing – Ground-Truth Demo and Test Facilities; Alfred-Wegener-Institute; BAH; Chlorophyll a; Chlorophyll a, confidence value; Coastal Observing System for Northern and Arctic Seas; COSYNA; DATE/TIME; Helgoland, North Sea; Helgoland-UWO; Helmholtz-Zentrum Geesthacht, Institute of Coastal Research; HZG; in situ data; MarGate; MarGate underwater experimental area; Modular Observation Solutions for Earth Systems; MOSES; OBSE; Observation; Observatory; Oxygen saturation; Oxygen saturation, confidence value; Salinity; Salinity, confidence value; Scientific diving; See further details: Metadata for the Helgoland underwater observatory; Shelf Seas Systems Ecology @ AWI (former Biologische Anstalt Helgoland); Temperature, water; Temperature, water, confidence value; Turbidity, confidence value; Turbidity (Formazin Turbidity Unit)
    Type: Dataset
    Format: text/tab-separated-values, 61644 data points
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  • 8
    Publication Date: 2024-05-11
    Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll a and turbidity data from the Helgoland MarGate underwater observatory from the year 2018 in a temporal resolution of 1 hour. The cabled observatory is located in 10m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-helgoland.html). For a detailed description of the data see associated metadatafile "metadata_heluwobs_2018_hydrography.pdf".
    Keywords: ACROSS; Advanced Remote Sensing – Ground-Truth Demo and Test Facilities; Alfred-Wegener-Institute; BAH; Chlorophyll a; Chlorophyll a, confidence value; Coastal Observing System for Northern and Arctic Seas; COSYNA; DATE/TIME; Helgoland, North Sea; Helgoland-UWO; Helmholtz-Zentrum Geesthacht, Institute of Coastal Research; HZG; in situ data; MarGate; MarGate underwater experimental area; Modular Observation Solutions for Earth Systems; MOSES; OBSE; Observation; Observatory; Oxygen saturation; Oxygen saturation, confidence value; Salinity; Salinity, confidence value; Scientific diving; See further details: Metadata for the Helgoland underwater observatory; Shelf Seas Systems Ecology @ AWI (former Biologische Anstalt Helgoland); Temperature, water; Temperature, water, confidence value; Turbidity, confidence value; Turbidity (Formazin Turbidity Unit)
    Type: Dataset
    Format: text/tab-separated-values, 73786 data points
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  • 9
    Publication Date: 2024-05-11
    Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll a and turbidity data from the Helgoland MarGate underwater observatory from the year 2019 in a temporal resolution of 1 hour. The cabled observatory is located in 10m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-helgoland.html). For a detailed description of the data see associated metadatafile "metadata_heluwobs_2019_hydrography.pdf"
    Keywords: ACROSS; Advanced Remote Sensing – Ground-Truth Demo and Test Facilities; Alfred-Wegener-Institute; BAH; Chlorophyll a; Chlorophyll a, confidence value; Coastal Observing System for Northern and Arctic Seas; COSYNA; DATE/TIME; Helgoland, North Sea; Helgoland-UWO; Helmholtz-Zentrum Geesthacht, Institute of Coastal Research; HZG; in situ data; MarGate; MarGate underwater experimental area; Modular Observation Solutions for Earth Systems; MOSES; OBSE; Observation; Observatory; Oxygen saturation; Oxygen saturation, confidence value; Salinity; Salinity, confidence value; Scientific diving; See further details: Metadata for the Helgoland underwater observatory; Shelf Seas Systems Ecology @ AWI (former Biologische Anstalt Helgoland); Temperature, water; Temperature, water, confidence value; Turbidity (Formazin Turbidity Unit)
    Type: Dataset
    Format: text/tab-separated-values, 50146 data points
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  • 10
    Publication Date: 2024-05-11
    Description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll a and turbidity data from the AWIPEV underwater observatory from the year 2020 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html). For a detailed description of the data see associated metadatafile "Metadata_description_svluwobs_data_2020.pdf"
    Keywords: ACROSS; Advanced Remote Sensing – Ground-Truth Demo and Test Facilities; AWIPEV; AWIPEV_based; AWIPEV_UW-Observatory; BAH; Chlorophyll a; Chlorophyll a, confidence value; Coastal Observing System for Northern and Arctic Seas; COSYNA; DATE/TIME; Helmholtz-Zentrum Geesthacht, Institute of Coastal Research; HZG; Kongsfjorden, Spitsbergen, Arctic; MarGate; Modular Observation Solutions for Earth Systems; MOSES; OBSE; Observation; Oxygen saturation; Oxygen Saturation; Oxygen saturation, confidence value; Salinity; Salinity, confidence value; Scientific diving; See further details: Metadata for the AWIPEV underwater observatory; Sensor technology; Shelf Seas Systems Ecology @ AWI (former Biologische Anstalt Helgoland); Svalbard; Temperature; Temperature, water; Temperature, water, confidence value; turbidity; Turbidity (Formazin Turbidity Unit); Underwater observatory
    Type: Dataset
    Format: text/tab-separated-values, 61309 data points
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