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  • Springer Nature  (37,991)
  • Molecular Diversity Preservation International  (15,911)
  • American Society of Hematology
  • PANGAEA
  • 2015-2019  (67,793)
  • 2005-2009
  • 1985-1989
  • 1980-1984
  • 2015  (67,793)
Collection
Keywords
Publisher
Years
  • 2015-2019  (67,793)
  • 2005-2009
  • 1985-1989
  • 1980-1984
Year
  • 1
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Description: The upper air soundings are normally performed once a day to measure vertical profiles of air pressure, temperature, relative humidity and the wind vector. Helium filled balloons (TOTEX 600 g, 800 g) were used to carry Vaisala RS92-SGPW radiosondes. Whenever possible, the launches were performed about 10 UTC. Condensed measurements (TEMP Format FM-35) were transferred without delay into the Global Telecommunication System GTS were they contribute for the world wide weather forecasts. The profile data were taken every 5-10 seconds which result in a vertical profile resolution of about 25-50 meter. The profiles start at the helideck 10 m above sea level and terminate at the burst level of the balloons, normally at heights between 25 and 37 km.
    Keywords: AWI_Meteo; Meteorological Long-Term Observations @ AWI
    Type: Dataset
    Format: application/zip, 90 datasets
    Location Call Number Expected Availability
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  • 2
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    PANGAEA
    In:  Supplement to: Méheust, Marie; Stein, Ruediger; Fahl, Kirsten; Max, Lars; Riethdorf, Jan-Rainer (2015): High-resolution IP25-based reconstruction of sea-ice variability in the western North Pacific and Bering Sea during the past 18,000 years. Geo-Marine Letters, https://doi.org/10.1007/s00367-015-0432-4
    Publication Date: 2023-03-16
    Description: Due to its strong influence on heat and moisture exchange between the ocean and the atmosphere, sea ice is an essential component of the global climate system. In the context of its alarming decrease in terms of concentration, thickness and duration, understanding the processes controlling sea-ice variability and reconstructing paleo-sea-ice extent in polar regions have become of great interest for the scientific community. In this study, for the first time, IP25, a recently developed biomarker sea-ice proxy, was used for a high-resolution reconstruction of the sea-ice extent and its variability in the western North Pacific and western Bering Sea during the past 18,000 years. To identify mechanisms controlling the sea-ice variability, IP25 data were associated with published sea-surface temperature as well as diatom and biogenic opal data. The results indicate that a seasonal sea-ice cover existed during cold periods (Heinrich Stadial 1 and Younger Dryas), whereas during warmer intervals (Bølling-Allerød and Holocene) reduced sea ice or ice-free conditions prevailed in the study area. The variability in sea-ice extent seems to be linked to climate anomalies and sea-level changes controlling the oceanographic circulation between the subarctic Pacific and the Bering Sea, especially the Alaskan Stream injection though the Aleutian passes.
    Keywords: AWI_Paleo; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 3
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Description: FIL2013: Polar 6 conducted a systematic digital photographic aerial survey of the area of the Filchner Outflow System during two survey flights from Halley VI on 15 and 16 November 2013. The total survey distance covered 3,000 km each on 15 (eastern section) and 16 (western section) November 2013. Due to a low cloud ceiling on 15 November, the first flight operation was terminated prematurely and thus the westernmost track could not be flown. This track was flown on 16 November, and the total number of tracks numbered 11 instead of 12 as had been planned originally. FIL2014: Visual surveys of pack ice seals using helicopters were conducted from 4 January to 9 February 2014 from aboard RV Polarstern (PS82). For all seal related operations (including deployments of satellite transmitte rs and reconnaissance flights) a total of 30:13 hours during 20 flights were flown (MIN 0:11; MAX 3:13). The survey region was sampled by flying systematically spaced line transects (parallel lines approximately 10 nm apart) whenever ship position and weather conditions allowed, with out clustering transects in areas of easier access. When a full transect length could not be flown on a day, we attempted to complete (extend) the particular transect on a following day.
    Keywords: Marine Mammal Tracking; MMT
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 4
    Publication Date: 2023-03-14
    Keywords: BIOACID; Biological Impacts of Ocean Acidification; Cell density; Cell density, standard deviation; Figure; pH; Species
    Type: Dataset
    Format: text/tab-separated-values, 43 data points
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  • 5
    Publication Date: 2023-03-14
    Keywords: Aleutian Islands Alaska; Attu_Island; BIOACID; Biological Impacts of Ocean Acidification; Constant; Distance; DIVER; pH; Sample code/label; Sampling by diver; δ11B
    Type: Dataset
    Format: text/tab-separated-values, 455 data points
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  • 6
    Publication Date: 2023-03-14
    Keywords: Biomass; Biomass, standard error; Experiment day; pH; pH, standard deviation; Species; Strain; Time in hours
    Type: Dataset
    Format: text/tab-separated-values, 288 data points
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  • 7
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Aragonite saturation state, standard deviation; Bottom water temperature; Calcite saturation state; Calcite saturation state, standard deviation; Calculated using CO2SYS; Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate ion, standard deviation; Carbon dioxide; Carbon dioxide, partial pressure; Carbon dioxide, partial pressure, standard deviation; Carbon dioxide, standard deviation; CIMR_V1-3_C1-3; Columbretes Islands, Mediterranean Sea; CTD/STD SD204, SAIV A/S; DATE/TIME; Group; MULT; Multiple investigations; pH; pH, standard deviation; Potentiometric open-cell titration; Salinity; Site
    Type: Dataset
    Format: text/tab-separated-values, 120 data points
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  • 8
    Publication Date: 2023-03-13
    Keywords: AGE; Color, a*; DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand
    Type: Dataset
    Format: text/tab-separated-values, 5639 data points
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  • 9
    Publication Date: 2023-03-13
    Keywords: AGE; Color RED; DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand; interpolated
    Type: Dataset
    Format: text/tab-separated-values, 9629 data points
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  • 10
    Publication Date: 2023-03-13
    Keywords: DEPTH, sediment/rock; DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand; Inclination
    Type: Dataset
    Format: text/tab-separated-values, 1680 data points
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  • 11
    Publication Date: 2023-03-13
    Keywords: Chlorophyll total; CTD/Rosette; CTD-RO; Dana01/15; Dana01/15_104; Dana01/15_105; Dana01/15_106; Dana01/15_114; Dana01/15_119; Dana01/15_121; Dana01/15_122; Dana01/15_128; Dana01/15_129; Dana01/15_131; Dana01/15_134; Dana01/15_139; Dana01/15_140; Dana01/15_141; Dana01/15_142; Dana01/15_150; Dana01/15_151; Dana01/15_154; Dana01/15_155; Dana01/15_160; Dana01/15_162; Dana01/15_163; Dana01/15_170; Dana01/15_171; Dana01/15_172; Dana01/15_173; Dana01/15_174; Dana01/15_182; Dana01/15_183; Dana01/15_184; Dana01/15_185; Dana01/15_192; Dana01/15_193; Dana01/15_194; Dana01/15_195; Dana01/15_200; Dana01/15_203; Dana01/15_204; Dana01/15_205; Dana01/15_213; Dana01/15_214; Dana01/15_215; Dana01/15_216; Dana01/15_217; Dana01/15_218; Dana01/15_221; Dana01/15_222; Dana01/15_223; Dana01/15_224; Dana01/15_225; Dana II; Date/Time of event; DEPTH, water; Elevation of event; Event label; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Kattegat; Latitude of event; Longitude of event; Nitrate; Nitrite; Nitrogen, total; Oxygen; Phosphate; Phosphorus, total; Pressure, water; Salinity; Silicate; Skagerrak; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 2734 data points
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  • 12
    Publication Date: 2023-03-13
    Keywords: CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; Event label; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Latitude of event; Longitude of event; North Sea; Norwegian Sea; Pressure, water; Salinity; Scotia; Scotia15/1; Scotia15/1_1; Scotia15/1_10; Scotia15/1_11; Scotia15/1_12; Scotia15/1_13; Scotia15/1_14; Scotia15/1_15; Scotia15/1_16; Scotia15/1_17; Scotia15/1_18; Scotia15/1_19; Scotia15/1_2; Scotia15/1_20; Scotia15/1_21; Scotia15/1_22; Scotia15/1_23; Scotia15/1_24; Scotia15/1_25; Scotia15/1_26; Scotia15/1_27; Scotia15/1_28; Scotia15/1_29; Scotia15/1_3; Scotia15/1_30; Scotia15/1_31; Scotia15/1_32; Scotia15/1_33; Scotia15/1_34; Scotia15/1_35; Scotia15/1_36; Scotia15/1_37; Scotia15/1_38; Scotia15/1_39; Scotia15/1_4; Scotia15/1_40; Scotia15/1_41; Scotia15/1_42; Scotia15/1_43; Scotia15/1_44; Scotia15/1_45; Scotia15/1_46; Scotia15/1_47; Scotia15/1_48; Scotia15/1_49; Scotia15/1_5; Scotia15/1_6; Scotia15/1_7; Scotia15/1_8; Scotia15/1_9; South Atlantic Ocean; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 2865 data points
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  • 13
    Publication Date: 2023-03-13
    Keywords: CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; Event label; G. O. Sars (2003); GS15/122; GS15/122_1; GS15/122_10; GS15/122_100; GS15/122_101; GS15/122_102; GS15/122_103; GS15/122_104; GS15/122_105; GS15/122_106; GS15/122_107; GS15/122_108; GS15/122_109; GS15/122_11; GS15/122_110; GS15/122_111; GS15/122_112; GS15/122_113; GS15/122_114; GS15/122_115; GS15/122_116; GS15/122_117; GS15/122_118; GS15/122_119; GS15/122_12; GS15/122_120; GS15/122_121; GS15/122_122; GS15/122_123; GS15/122_124; GS15/122_125; GS15/122_126; GS15/122_127; GS15/122_128; GS15/122_129; GS15/122_13; GS15/122_130; GS15/122_131; GS15/122_132; GS15/122_133; GS15/122_134; GS15/122_135; GS15/122_136; GS15/122_137; GS15/122_138; GS15/122_139; GS15/122_14; GS15/122_140; GS15/122_141; GS15/122_142; GS15/122_143; GS15/122_144; GS15/122_145; GS15/122_15; GS15/122_16; GS15/122_17; GS15/122_18; GS15/122_19; GS15/122_2; GS15/122_20; GS15/122_21; GS15/122_22; GS15/122_23; GS15/122_24; GS15/122_25; GS15/122_26; GS15/122_27; GS15/122_28; GS15/122_29; GS15/122_3; GS15/122_30; GS15/122_31; GS15/122_32; GS15/122_33; GS15/122_34; GS15/122_35; GS15/122_36; GS15/122_37; GS15/122_38; GS15/122_39; GS15/122_4; GS15/122_40; GS15/122_41; GS15/122_42; GS15/122_43; GS15/122_44; GS15/122_45; GS15/122_46; GS15/122_47; GS15/122_48; GS15/122_49; GS15/122_5; GS15/122_50; GS15/122_51; GS15/122_52; GS15/122_53; GS15/122_54; GS15/122_55; GS15/122_56; GS15/122_57; GS15/122_58; GS15/122_59; GS15/122_6; GS15/122_60; GS15/122_61; GS15/122_62; GS15/122_63; GS15/122_64; GS15/122_65; GS15/122_66; GS15/122_67; GS15/122_68; GS15/122_69; GS15/122_7; GS15/122_70; GS15/122_71; GS15/122_72; GS15/122_73; GS15/122_74; GS15/122_75; GS15/122_76; GS15/122_77; GS15/122_78; GS15/122_79; GS15/122_8; GS15/122_80; GS15/122_81; GS15/122_82; GS15/122_83; GS15/122_84; GS15/122_85; GS15/122_86; GS15/122_87; GS15/122_88; GS15/122_89; GS15/122_9; GS15/122_90; GS15/122_91; GS15/122_92; GS15/122_93; GS15/122_94; GS15/122_95; GS15/122_96; GS15/122_97; GS15/122_98; GS15/122_99; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Latitude of event; Longitude of event; North Sea; Norwegian Sea; Pressure, water; Salinity; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 8979 data points
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  • 14
    Publication Date: 2023-03-13
    Keywords: CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; English Channel; Event label; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Latitude of event; Longitude of event; North Sea; Pressure, water; Salinity; Temperature, water; Thalassa; Thalassa15/1; Thalassa15/1_1; Thalassa15/1_10; Thalassa15/1_100; Thalassa15/1_101; Thalassa15/1_102; Thalassa15/1_103; Thalassa15/1_106; Thalassa15/1_107; Thalassa15/1_108; Thalassa15/1_109; Thalassa15/1_11; Thalassa15/1_110; Thalassa15/1_111; Thalassa15/1_112; Thalassa15/1_113; Thalassa15/1_114; Thalassa15/1_115; Thalassa15/1_116; Thalassa15/1_117; Thalassa15/1_118; Thalassa15/1_119; Thalassa15/1_12; Thalassa15/1_120; Thalassa15/1_121; Thalassa15/1_122; Thalassa15/1_123; Thalassa15/1_124; Thalassa15/1_125; Thalassa15/1_126; Thalassa15/1_127; Thalassa15/1_128; Thalassa15/1_129; Thalassa15/1_13; Thalassa15/1_130; Thalassa15/1_131; Thalassa15/1_132; Thalassa15/1_133; Thalassa15/1_134; Thalassa15/1_135; Thalassa15/1_136; Thalassa15/1_137; Thalassa15/1_138; Thalassa15/1_139; Thalassa15/1_140; Thalassa15/1_141; Thalassa15/1_142; Thalassa15/1_143; Thalassa15/1_153; Thalassa15/1_155; Thalassa15/1_156; Thalassa15/1_157; Thalassa15/1_158; Thalassa15/1_159; Thalassa15/1_160; Thalassa15/1_161; Thalassa15/1_162; Thalassa15/1_163; Thalassa15/1_164; Thalassa15/1_165; Thalassa15/1_166; Thalassa15/1_167; Thalassa15/1_169; Thalassa15/1_170; Thalassa15/1_171; Thalassa15/1_172; Thalassa15/1_173; Thalassa15/1_174; Thalassa15/1_175; Thalassa15/1_176; Thalassa15/1_177; Thalassa15/1_178; Thalassa15/1_179; Thalassa15/1_18; Thalassa15/1_180; Thalassa15/1_181; Thalassa15/1_182; Thalassa15/1_183; Thalassa15/1_184; Thalassa15/1_185; Thalassa15/1_186; Thalassa15/1_187; Thalassa15/1_188; Thalassa15/1_189; Thalassa15/1_19; Thalassa15/1_190; Thalassa15/1_191; Thalassa15/1_192; Thalassa15/1_193; Thalassa15/1_194; Thalassa15/1_2; Thalassa15/1_20; Thalassa15/1_21; Thalassa15/1_22; Thalassa15/1_23; Thalassa15/1_24; Thalassa15/1_25; Thalassa15/1_26; Thalassa15/1_27; Thalassa15/1_28; Thalassa15/1_29; Thalassa15/1_3; Thalassa15/1_30; Thalassa15/1_31; Thalassa15/1_32; Thalassa15/1_33; Thalassa15/1_34; Thalassa15/1_35; Thalassa15/1_36; Thalassa15/1_37; Thalassa15/1_38; Thalassa15/1_39; Thalassa15/1_4; Thalassa15/1_40; Thalassa15/1_41; Thalassa15/1_42; Thalassa15/1_43; Thalassa15/1_44; Thalassa15/1_45; Thalassa15/1_46; Thalassa15/1_47; Thalassa15/1_48; Thalassa15/1_49; Thalassa15/1_5; Thalassa15/1_50; Thalassa15/1_51; Thalassa15/1_52; Thalassa15/1_53; Thalassa15/1_54; Thalassa15/1_55; Thalassa15/1_56; Thalassa15/1_57; Thalassa15/1_58; Thalassa15/1_59; Thalassa15/1_6; Thalassa15/1_60; Thalassa15/1_61; Thalassa15/1_62; Thalassa15/1_63; Thalassa15/1_64; Thalassa15/1_65; Thalassa15/1_66; Thalassa15/1_67; Thalassa15/1_68; Thalassa15/1_69; Thalassa15/1_7; Thalassa15/1_70; Thalassa15/1_71; Thalassa15/1_72; Thalassa15/1_73; Thalassa15/1_74; Thalassa15/1_75; Thalassa15/1_76; Thalassa15/1_77; Thalassa15/1_78; Thalassa15/1_79; Thalassa15/1_8; Thalassa15/1_80; Thalassa15/1_81; Thalassa15/1_82; Thalassa15/1_83; Thalassa15/1_84; Thalassa15/1_85; Thalassa15/1_86; Thalassa15/1_87; Thalassa15/1_88; Thalassa15/1_89; Thalassa15/1_9; Thalassa15/1_90; Thalassa15/1_91; Thalassa15/1_92; Thalassa15/1_93; Thalassa15/1_94; Thalassa15/1_95; Thalassa15/1_96; Thalassa15/1_97; Thalassa15/1_98; Thalassa15/1_99
    Type: Dataset
    Format: text/tab-separated-values, 8988 data points
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  • 15
    Publication Date: 2023-03-13
    Keywords: CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Event label; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Latitude of event; Longitude of event; North Sea; Pressure, water; Salinity; Temperature, water; Tridens; Tridens15/1; Tridens15/1_10; Tridens15/1_11; Tridens15/1_12; Tridens15/1_13; Tridens15/1_14; Tridens15/1_15; Tridens15/1_16; Tridens15/1_17; Tridens15/1_18; Tridens15/1_19; Tridens15/1_2; Tridens15/1_20; Tridens15/1_21; Tridens15/1_22; Tridens15/1_23; Tridens15/1_24; Tridens15/1_25; Tridens15/1_26; Tridens15/1_27; Tridens15/1_28; Tridens15/1_29; Tridens15/1_3; Tridens15/1_30; Tridens15/1_31; Tridens15/1_32; Tridens15/1_33; Tridens15/1_34; Tridens15/1_35; Tridens15/1_36; Tridens15/1_37; Tridens15/1_38; Tridens15/1_39; Tridens15/1_4; Tridens15/1_40; Tridens15/1_41; Tridens15/1_42; Tridens15/1_44; Tridens15/1_45; Tridens15/1_46; Tridens15/1_5; Tridens15/1_7; Tridens15/1_8; Tridens15/1_9
    Type: Dataset
    Format: text/tab-separated-values, 2658 data points
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  • 16
    Publication Date: 2023-03-13
    Keywords: CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; Event label; International Young Fish Survey/International Bottom Trawl Survey; IYFS/IBTS; Latitude of event; Longitude of event; North Sea; Norwegian Sea; Oxygen; Pressure, water; Salinity; Temperature, water; Walther Herwig III; WH382; WH382_100; WH382_105; WH382_113; WH382_114; WH382_115; WH382_116; WH382_125; WH382_126; WH382_127; WH382_128; WH382_137; WH382_138; WH382_139; WH382_140; WH382_147; WH382_148; WH382_149; WH382_158; WH382_159; WH382_160; WH382_161; WH382_170; WH382_171; WH382_172; WH382_179; WH382_180; WH382_181; WH382_190; WH382_191; WH382_192; WH382_193; WH382_200; WH382_201; WH382_202; WH382_203; WH382_216; WH382_217; WH382_218; WH382_22; WH382_223; WH382_224; WH382_225; WH382_230; WH382_231; WH382_27; WH382_28; WH382_29; WH382_30; WH382_39; WH382_40; WH382_41; WH382_50; WH382_51; WH382_52; WH382_53; WH382_60; WH382_61; WH382_62; WH382_63; WH382_71; WH382_72; WH382_73; WH382_74; WH382_84; WH382_85; WH382_86; WH382_97; WH382_98; WH382_99
    Type: Dataset
    Format: text/tab-separated-values, 4960 data points
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  • 17
    Publication Date: 2023-03-14
    Keywords: Benthocosm_A1; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 320136 data points
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  • 18
    Publication Date: 2023-03-14
    Keywords: Benthocosm_B2; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 309000 data points
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  • 19
    Publication Date: 2023-03-14
    Keywords: Benthocosm_D2; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 315284 data points
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  • 20
    Publication Date: 2023-03-14
    Keywords: BIOACID; Biological Impacts of Ocean Acidification; Cell density; Cell density, standard deviation; Experiment day; Figure; Nitrate; Nitrate, standard deviation; pH; Replicates; Species; Standard deviation; Sulfate; Sulfate, standard deviation; Thiosulfate
    Type: Dataset
    Format: text/tab-separated-values, 425 data points
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  • 21
    Publication Date: 2023-03-14
    Keywords: Benthocosm_B1; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 319735 data points
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  • 22
    Publication Date: 2023-03-14
    Keywords: Benthocosm_C1; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 321026 data points
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  • 23
    Publication Date: 2023-03-14
    Keywords: Benthocosm_C2; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 312493 data points
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  • 24
    Publication Date: 2023-03-14
    Keywords: Benthocosm_A2; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 261286 data points
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  • 25
    Publication Date: 2023-03-14
    Keywords: Benthocosm_D1; DATE/TIME; Event label; Experiment; Experimental treatment; Kiel Fjord; MESO; Mesocosm experiment; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 317138 data points
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  • 26
    Publication Date: 2023-03-14
    Keywords: Aluminium; Arnstein_Forest; Bavaria; Cation exchange capacity; Classification; Comment; Ebrach_Forest; Event label; Field capacity; Identification; Iron; Kaisheim_Forest; Latitude of event; Light Condition; Light condition, openness; Light condition, site factor; Longitude of event; Magnesium; Manganese; Number of years; Percentage; pH; Potassium; Shannon Diversity Index; Sodium; Trees, basal area
    Type: Dataset
    Format: text/tab-separated-values, 960 data points
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  • 27
    Publication Date: 2023-03-14
    Keywords: AB; Ayer_Besar; B; C; Chlorophyll a; DATE/TIME; DEPTH, water; Event label; Gosong_Conkak; Gosong_Panggang; Java Sea; Kayu_Angin_Bira; Latitude of event; Longitude of event; MULT; Multiple investigations; Oxygen; Oxygen saturation; P; Pari_North; Pari_South; pH; PN; PS; R; Rambut; Salinity; Site; Temperature, water; Turbidity (Nephelometric turbidity unit); UJ; Untung_Jawa
    Type: Dataset
    Format: text/tab-separated-values, 1952 data points
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  • 28
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Ammonium; BIOACID; BIOACID 2 PNG2013; Biological Impacts of Ocean Acidification; Carbon, inorganic, dissolved; DEPTH, water; DIVER; Environment; LATITUDE; Layer description; Location; LONGITUDE; M.V. Chertan; Nitrate and Nitrite; Nitrite; Papua_New_Guinea_CO2_vent; pH; Phosphate; Replicate; Sample code/label; Sample ID; Sampling by diver; Silicate; Site
    Type: Dataset
    Format: text/tab-separated-values, 1615 data points
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  • 29
    Publication Date: 2023-03-14
    Description: This work aimed to explore evaluated the effects of the increased of hydrostatic pressure on a defined bacterial community on aggregates formed from an axenic culture of marine diatoms by simulating sedimentation to the deep sea by increase of hydrostatic pressure up to 30 bar (equivalent to 3000 m water depth) against control at ambient surface pressure. Our hypothesis was that microbial colonization and community composition and thus microbial OM turnover is greatly affected by changes in hydrostatic pressure during sinking to the deep ocean.
    Keywords: Alanine; Amino acid, total hydrolysable; Amino acids; Arginine; Aspartic acid; Aspartic acid/beta-Alanine ratio; beta-Alanine; BIOACID; Biological Impacts of Ocean Acidification; Carbon, inorganic, particulate; Carbon, organic, particulate; Carbon, total; Carbon/Nitrogen ratio; Dauwe index; Experimental treatment; gamma-Aminobutyric acid; Glutamic acid; Glutamic acid/gamma-Aminobutyric acid ratio; Glycine; Histidine; Isoleucine; Leucine; Lysine; Methionine; Nitrogen, total; Ornithine; Particle concentration; pH; Phenylalanine; Ratio; Serine; Sinking velocity; Size; Threonine; Time in hours; Tyrosine; Valine
    Type: Dataset
    Format: text/tab-separated-values, 552 data points
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  • 30
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    PANGAEA
    In:  Water and Sanitation Agency Lahore | Supplement to: Abbas, Zainab; Mapoma, Harold Wilson Tumwitike; Su, Chunli; Aziz, Syed Zahid; Abbas, Naaz (2018): Spatial analysis of groundwater suitability for drinking and irrigation in Lahore, Pakistan. Environmental Monitoring and Assessment, 190(7), https://doi.org/10.1007/s10661-018-6775-3
    Publication Date: 2023-03-14
    Description: The dataset provides detailed information on the study that was conducted in Lahore's 7 major towns. The sample was taken from 472 tubewells and analyzed for major cations and anions using APHA 2012 techniques as explained herein. Besides, E.coli determination was done to check for microbial contamination. The data includes results from PHREEQC modeling of As(III)/ As(V) species and saturation indices as well as Aquachem's computed hydrochemical water facies. The WHO (2011) and EPA standards included in Aquachem identified the parameters that where in violation. Bicarbonates dominated the groundwater types with 50.21% of the samples exceeding the EPA maximum permissible limit of 250 mg/L in drinking water. Similarly, 30.51% of the samples had TDS values greater than 500 mg/L while 85.38 % of the samples exceed 10 µg/L threshold limit value of arsenic. Also, instances of high magnesium hazard values were observed which requires constant assessment if the groundwater is used for irrigation. Higher than 50% MH values are detrimental to crops which may reduce the expected yields. The membrane filtration technique using m-Endo Agar indicated that 3.59% samples had TNC (too numerous to count) values for E.coli while 5.06% showed values higher than 0 cfu/ 100 ml acceptable value in drinking water. Any traces of E-coli in a groundwater sample indicate recent fecal contamination. Such outcomes signify presence of enteric pathogens. If the groundwater is not properly dosed with disinfectants it may cause harm to human health. It is concluded that more studies are needed and proper groundwater management implement to safeguard the lives of communities that depend solely on groundwater in the city.
    Keywords: Acid Base titration; Anhydrite; AquaChem; Aragonite; Area/locality; Argentometric method; Arsenic; Arsenic(III); Arsenic(V); Automated hydrazine reduction method; Bicarbonate ion; Calcite; Calcium; Calculated; Chloride; Comment; Conductivity, electrical; DATE/TIME; Dolomite; EDTA titration method; Escherichia coli in colony forming units; Flame photometry; Fluoride; Fluorite; Geographic name/locality; Gravimetric analysis; Gypsum; Halite; Hand held digital pH meter; Hardness of water; ICP-OES, Inductively coupled plasma - optical emission spectrometry; Lahore_Towns; LATITUDE; LONGITUDE; Magnesium; Magnesium hazard; Membrane filtration technique using m-Endo Agar; Microcomputer based meter (JENCO); Nitrate; Nitrite; Number; Pakistan; pH; PHREEQC modeling; Portable microprocessor turbidity meter (Hanna Instruments); Potassium; Sample code/label; Sodium; Sodium absorption ratio; SPADNS method; Spectrophotometric method (NOVA); Station label; Sulfate; Total dissolved solids; Turbidity (Nephelometric turbidity unit); Type; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 15841 data points
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  • 31
    Publication Date: 2023-03-16
    Keywords: Alpine wind monitor, R.M. Young, model 05108-45; Automatic weather station; AWS; Barometric pressure sensor, R.M. Young, model 61302V; DATE/TIME; HEIGHT above ground; Humidity, relative; Humidity, relative, standard deviation; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Pressure, atmospheric; Pressure, atmospheric, standard deviation; Temperature, air; Temperature, air, standard deviation; Warszawa_Icefield_AWS; Wind direction; Wind direction, standard deviation; Wind speed; Wind speed, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 647320 data points
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  • 32
    Publication Date: 2023-03-16
    Keywords: Alpine wind monitor, R.M. Young, model 05108-45; Automatic weather station; AWS; Barometric pressure sensor, R.M. Young, model 61302V; DATE/TIME; HEIGHT above ground; Humidity, relative; Humidity, relative, standard deviation; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Pressure, atmospheric; Pressure, atmospheric, standard deviation; Temperature, air; Temperature, air, standard deviation; Warszawa_Icefield_AWS; Wind direction; Wind direction, standard deviation; Wind speed; Wind speed, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 741672 data points
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  • 33
    Publication Date: 2023-03-16
    Keywords: Automatic weather station; AWS; DATE/TIME; HEIGHT above ground; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, air; Warszawa_Icefield_PG19
    Type: Dataset
    Format: text/tab-separated-values, 986 data points
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  • 34
    Publication Date: 2023-03-16
    Keywords: Adiabatic temperature lapse rate, low; Adiabatic temperature lapse rate, up; Alpine wind monitor, R.M. Young, model 05108-45; Automatic weather station; AWS; Calculated; DATE/TIME; HEIGHT above ground; Humidity, relative; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, air; Temperature, air, standard deviation; Warszawa_Icefield_ZAWS; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 5822 data points
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  • 35
    Publication Date: 2023-03-16
    Keywords: 10001; 1301; 1501; 1701; 1901; 2101; 21-2001,ARKTIEF II,SFB512; 2501; 2701; 2901; 301; 3401; 4001; 4201; 4301; 501; 5601; 5801; 6001; 6201; 6501; 6801; 701; 8501; 8701; 8901; 901; 9101; 9501; 9701; AWI_BioOce; Biological Oceanography @ AWI; Chlorophyll a; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Event label; LA01/9; LA01/9_100; LA01/9_13; LA01/9_15; LA01/9_17; LA01/9_19; LA01/9_21; LA01/9_25; LA01/9_27; LA01/9_29; LA01/9_3; LA01/9_34; LA01/9_40; LA01/9_42; LA01/9_43; LA01/9_5; LA01/9_56; LA01/9_58; LA01/9_60; LA01/9_62; LA01/9_65; LA01/9_68; LA01/9_7; LA01/9_85; LA01/9_87; LA01/9_89; LA01/9_9; LA01/9_91; LA01/9_95; LA01/9_97; Lance; Latitude of event; Longitude of event; North Greenland Sea
    Type: Dataset
    Format: text/tab-separated-values, 161 data points
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  • 36
    Publication Date: 2023-03-16
    Keywords: ARKTIEF; AWI_BioOce; Biological Oceanography @ AWI; Chlorophyll a; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Event label; LA00/105; LA00/111; LA00/112; LA00/113; LA00/114; LA00/115; LA00/116; LA00/117; LA00/118; LA00/119; LA00/120; LA00/121; LA00/123; LA00/124; LA00/125; LA00/126; LA00/127; LA00/128; LA00/129; LA00/130; LA00/131; LA00/132; LA00/134; LA00/136; LA00/138; LA00/153; LA00/158; LA00/9; Lance; Latitude of event; Longitude of event; North Greenland Sea
    Type: Dataset
    Format: text/tab-separated-values, 160 data points
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  • 37
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE266/1; HE266/1-track; Heincke; LATITUDE; LONGITUDE; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 574 data points
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  • 38
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE292/1; HE292/1-track; Heincke; LATITUDE; LONGITUDE; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 2302 data points
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  • 39
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE312/1; HE312/1-track; Heincke; LATITUDE; LONGITUDE; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 1870 data points
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  • 40
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE439; HE439-track; Heincke; LATITUDE; LONGITUDE; North Sea; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 5470 data points
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  • 41
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    PANGAEA
    In:  Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky University of Oldenburg, Germany
    Publication Date: 2023-03-17
    Keywords: Conductivity; CTD, Sea-Bird; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Event label; ICBM_Ot_1503; ICBM_Ot_1503_15; ICBM_Ot_1503_16; ICBM_Ot_1503_17; ICBM_Ot_1503_18; ICBM_Ot_1503_19; ICBM_Ot_1503_20; ICBM_Ot_1503_21; ICBM_Ot_1503_22; ICBM_Ot_1503_23; ICBM_Ot_1503_24; ICBM_Ot_1503_25; ICBM_Ot_1503_26; ICBM_Ot_1503_27; Latitude of event; Longitude of event; Pressure, water; Salinity; Temperature, water; Temperature, water, potential; Turbidity (Nephelometric turbidity unit)
    Type: Dataset
    Format: text/tab-separated-values, 1890 data points
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  • 42
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    PANGAEA
    In:  Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky University of Oldenburg, Germany
    Publication Date: 2023-03-17
    Keywords: Conductivity; CTD, Sea-Bird; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Event label; ICBM_Ot_1503; ICBM_Ot_1503_1; ICBM_Ot_1503_10; ICBM_Ot_1503_11; ICBM_Ot_1503_12; ICBM_Ot_1503_13; ICBM_Ot_1503_14; ICBM_Ot_1503_2; ICBM_Ot_1503_3; ICBM_Ot_1503_4; ICBM_Ot_1503_5; ICBM_Ot_1503_6; ICBM_Ot_1503_7; ICBM_Ot_1503_8; ICBM_Ot_1503_9; Latitude of event; Longitude of event; Pressure, water; Salinity; Temperature, water; Temperature, water, potential; Turbidity (Nephelometric turbidity unit)
    Type: Dataset
    Format: text/tab-separated-values, 896 data points
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  • 43
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    PANGAEA
    In:  Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky University of Oldenburg, Germany
    Publication Date: 2023-03-17
    Keywords: Conductivity; CTD, Sea-Bird; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Event label; ICBM_Ot_1503; ICBM_Ot_1503_28; ICBM_Ot_1503_29; ICBM_Ot_1503_30; ICBM_Ot_1503_31; ICBM_Ot_1503_32; ICBM_Ot_1503_33; ICBM_Ot_1503_34; ICBM_Ot_1503_35; ICBM_Ot_1503_36; ICBM_Ot_1503_37; ICBM_Ot_1503_38; ICBM_Ot_1503_39; ICBM_Ot_1503_40; ICBM_Ot_1503_41; ICBM_Ot_1503_42; ICBM_Ot_1503_43; ICBM_Ot_1503_44; ICBM_Ot_1503_45; ICBM_Ot_1503_46; ICBM_Ot_1503_47; ICBM_Ot_1503_48; Latitude of event; Longitude of event; Pressure, water; Salinity; Temperature, water; Temperature, water, potential; Turbidity (Nephelometric turbidity unit)
    Type: Dataset
    Format: text/tab-separated-values, 1470 data points
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  • 44
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: Akademik Boris Petrov; AWI_Paleo; BP00; BP00-14; Kara Sea; MULT; Multiple investigations; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
    Type: Dataset
    Format: unknown
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  • 45
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: Akademik Boris Petrov; AWI_Paleo; BP01; BP01-40/04; Giant box corer; GKG; Kara Sea; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
    Type: Dataset
    Format: unknown
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  • 46
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: Akademik Boris Petrov; AWI_Paleo; BP99; BP99-04; MULT; Multiple investigations; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
    Type: Dataset
    Format: unknown
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  • 47
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-02; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 48
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-10; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 49
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-37; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 50
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-42; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 51
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-40; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 52
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-18; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 53
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-58; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 54
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-62; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 55
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    PANGAEA
    In:  Alfred Wegener Institute - Polarstern core repository
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; KAL_R; Kara Sea/St. Anna Trough; Kasten corer RUS; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PL-1994; PL94-68; Professor Logachev
    Type: Dataset
    Format: unknown
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  • 56
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2005; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 354 data points
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  • 57
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2009; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 516 data points
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  • 58
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2010; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 541 data points
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  • 59
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2013; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 551 data points
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  • 60
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2011; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 561 data points
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  • 61
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2012; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 480 data points
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  • 62
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2014; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 543 data points
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  • 63
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Brandal; Conductivity/temperature logger µS-Log540, Driesen + Kern GmbH; DATE/TIME; DEPTH, water; Kongsfjorden, Spitsbergen, Arctic; MULT; Multiple investigations; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 52266 data points
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  • 64
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: AWI_Coast; AWI Arctic Land Expedition; Carbon, organic, dissolved; Coastal Ecology @ AWI; Colorometric autoanalysis; DATE/TIME; Depth, bathymetric; DEPTH, water; High temperature catalytic oxidation; LATITUDE; Lena2010; Lena Delta, Siberia, Russia; Location type; LONGITUDE; MULT; Multiple investigations; Nitrate and Nitrite; Nitrogen, total dissolved; Phosphate; RU-Land_2010_Lena; Salinity; Sample code/label; Sample ID; Spectrophotometry; Station label; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 606 data points
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  • 65
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    In:  Supplement to: Falk, Ulrike; Gieseke, Hilke; Kotzur, Franziska; Braun, Matthias Holger (2015): Monitoring snow and ice surfaces on King George Island, Antarctic Peninsula, with high-resolution TerraSAR-X time series. Antarctic Science, 15 pp, https://doi.org/10.1017/S0954102015000577
    Publication Date: 2023-03-16
    Description: Changes of glaciers and snow cover in polar regions affect a wide range of physical and ecosystem processes on land and in the adjacent marine environment. In this study, we investigate the potential of 11-day repeat high-resolution satellite image time series from the TerraSAR-X mission to derive glaciological and hydrological parameters on King George Island, Antarctica during the period Oct/25/2010 to Apr/19/2011. The spatial pattern and temporal evolution of snow cover extent on ice-free areas can be monitored using multi-temporal coherence images. SAR coherence is used to map glacier extent of land terminating glaciers with an average accuracy of 25 m. Multi-temporal SAR color composites identify the position of the late summer snow line at about 220 m above sea level. Glacier surface velocities are obtained from intensity feature-tracking. Surface velocities near the calving front of Fourcade Glacier were up to 1.8 ± 0.01 m/d. Using an intercept theorem based on fundamental geometric principles together with differential GPS field measurements, the ice discharge of Fourcade Glacier was estimated to 20700 ± 5500 m**3/d (corresponding to ~19 ± 5 kt/d). The rapidly changing surface conditions on King George Island and the lack of high-resolution digital elevation models for the region remain restrictions for the applicability of SAR data and the precision of derived products.
    Keywords: File content; File format; File size; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King_George_Island; King George Island, Antarctic Peninsula; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
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  • 66
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    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE280/1; HE280/1-track; Heincke; LATITUDE; LONGITUDE; North Sea; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 380 data points
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  • 67
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    In:  Supplement to: Falk, Ulrike; López, Damián; Sala, Hernán (in prep.): Tipping point of glacier mass balance changes for the inland ice cap of King George Island, West Antarctica.
    Publication Date: 2023-03-16
    Description: The east coast of the AP is highly influenced by cold and dry air masses stemming from the adjacent Weddell Sea. By the contrary, the west coast jointly with the South Shetland Islands are directly exposed to the humid and relatively warm air masses from the South Pacific Ocean carried by the strong and persistent westerly winds. Systematic glaciological field studies are very scarce on both sides of the AP, among them can be mentioned a mass-balance program performed continuously since summer 1998/99 by the Instituto Antártico Argentino (IAA) on Vega Island, James Ross Archipelago, on the northeastern flank of the AP. Another continuous plurianual glaciological research has been initiated in 2010 jointly by the University of Bonn and the IAA at the Fourcade Glacier on King George Island (KGI) within the framework of the ESF project IMCOAST (FK 03F0617B). Two transects of mass balance stakes were installed from the top of the Warszawa Ice Dome down to the border of the glaciers Fourcade and Polar Club, to serve for calibration and validation of modeling efforts. The stakes were measured at the beginning and end of each summer field campaign in November 2010, February - March 2011, January - March 2012, and especially during the austral winter 2012 up to March 2013 every 10 to 14 days depending on weather conditions. During the austral winter 2013 and until June 2014 the measurements were conducted every 20 to 30 days, weather permitting. Snow density was measured as well in every field trip from June 2012 until June 2104, establishing a rather homogeneous value along the different parts of the glacier. Snow density in late summer, rho_s is usually higher than the one in late winter, rho_w. Seasonal average values were calculated for the area covered by the mass balance stakes, being rho_s= 471 Kg/m**3 and rho_w = 363 Kg/m**3.
    Keywords: Automatic weather station; AWS; Calculated; DATE/TIME; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Length, difference; Melt rate in water equivalent per day; Warszawa_Icefield_AWS
    Type: Dataset
    Format: text/tab-separated-values, 186 data points
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  • 68
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    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Type: Dataset
    Format: application/zip, 8.6 MBytes
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  • 69
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven | Supplement to: Driemel, Amelie; Loose, Bernd; Grobe, Hannes; Sieger, Rainer; König-Langlo, Gert (2016): 30 years of upper air soundings on board of R/V POLARSTERN. Earth System Science Data, 8, 213-220, https://doi.org/10.5194/essd-8-213-2016
    Publication Date: 2023-03-16
    Description: The research vessel and supply icebreaker POLARSTERN is the flagship of the Alfred-Wegener-Institut in Bremerhaven (Germany) and one of the infrastructural pillars of German Antarctic research. Since its commissioning in 1982, POLARSTERN has conducted 30 campaigns to Antarctica (157 legs, mostly austral summer), and 29 to the Arctic (94 legs, northern summer). Usually, POLARSTERN is more than 300 days per year in operation and crosses the Atlantic Ocean in a meridional section twice a year. The first radiosonde on POLARSTERN was released on the 29th of December 1982, two days after POLARSTERN started on its maiden voyage to the Antarctic. And these daily soundings have continued up to the present. Due to the fact that POLARSTERN has reliably and regularly been providing upper air observations from data sparse regions (oceans and polar regions), the radiosonde data are of special value for researchers and weather forecast services alike. In the course of 30 years (1982-12-29 to 2012-11-25) a total of 12378 radiosonde balloons were started on POLARSTERN. All radiosonde data can now be found here. Each dataset contains the directly measured parameters air temperature, relative humidity and air pressure, and the derived altitude, wind direction and wind speed. 432 datasets additionally contain ozone measurements.
    Keywords: AWI_Meteo; Campaign; Date/time end; Date/time start; Meteorological Long-Term Observations @ AWI; Method comment; Number of observations; Persistent Identifier; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 1453 data points
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  • 70
    Publication Date: 2023-03-16
    Keywords: Alpine wind monitor, R.M. Young, model 05108-45; Automatic weather station; AWS; Barometric pressure sensor, R.M. Young, model 61302V; DATE/TIME; HEIGHT above ground; Humidity, relative; Humidity, relative, standard deviation; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Pressure, atmospheric; Pressure, atmospheric, standard deviation; Temperature, air; Temperature, air, standard deviation; Warszawa_Icefield_AWS; Wind direction; Wind direction, standard deviation; Wind speed; Wind speed, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 109360 data points
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  • 71
    Publication Date: 2023-03-16
    Keywords: Automatic weather station; AWS; DATE/TIME; DEPTH, ice/snow; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, ice/snow; Temperature, ice/snow, standard deviation; Thermistor soil temperature probe 107, Campbell Scientific; Warszawa_Icefield_AWS
    Type: Dataset
    Format: text/tab-separated-values, 51064 data points
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  • 72
    Publication Date: 2023-03-16
    Keywords: Automatic weather station; AWS; Battery terminal voltage; Calculated; DATE/TIME; DEPTH, ice/snow; Depth, relative; HEIGHT above ground; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, ice/snow; Thermistor soil temperature probe 107, Campbell Scientific; Warszawa_Icefield_ZAWS
    Type: Dataset
    Format: text/tab-separated-values, 8874 data points
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  • 73
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    In:  Supplement to: Jung, Richard (submitted): Sediment classification on Norderney. Remote Sensing of Environment
    Publication Date: 2023-03-08
    Description: The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.
    Keywords: WIMO; Wissenschaftliche Monitoringkonzepte für die Deutsche Bucht
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 74
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    PANGAEA
    In:  Supplement to: Overduin, Pier Paul; Liebner, Susanne; Knoblauch, Christian; Günther, Frank; Wetterich, Sebastian; Schirrmeister, Lutz; Hubberten, Hans-Wolfgang; Grigoriev, Mikhail N (2015): Methane oxidation following submarine permafrost degradation: Measurements from a central Laptev Sea shelf borehole. Journal of Geophysical Research: Biogeosciences, 120(5), 965-978, https://doi.org/10.1002/2014JG002862
    Publication Date: 2023-03-07
    Description: Submarine permafrost degradation has been invoked as a cause for recent observations of methane emissions from the seabed to the water column and atmosphere of the East Siberian shelf. Sediment drilled 52 m down from the sea ice in Buor Khaya Bay, central Laptev Sea revealed unfrozen sediment overlying ice-bonded permafrost. Methane concentrations in the overlying unfrozen sediment were low (mean 20 µM) but higher in the underlying ice-bonded submarine permafrost (mean 380 µM). In contrast, sulfate concentrations were substantially higher in the unfrozen sediment (mean 2.5 mM) than in the underlying submarine permafrost (mean 0.1 mM). Using deduced permafrost degradation rates, we calculate potential mean methane efflux from degrading permafrost of 120 mg/m**2 per year at this site. However, a drop of methane concentrations from 190 µM to 19 µM and a concomitant increase of methane d13C from -63 per mil to -35 per mil directly above the ice-bonded permafrost suggest that methane is effectively oxidized within the overlying unfrozen sediment before it reaches the water column. High rates of methane ebullition into the water column observed elsewhere are thus unlikely to have ice-bonded permafrost as their source.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 75
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    In:  Supplement to: Fritz, Michael; Herzschuh, Ulrike; Wetterich, Sebastian; Lantuit, Hugues; De Pascale, Gregory P; Pollard, Wayne H; Schirrmeister, Lutz (2012): Late glacial and Holocene sedimentation, vegetation, and climate history from easternmost Beringia (northern Yukon Territory, Canada). Quaternary Research, 78(3), 549-560, https://doi.org/10.1016/j.yqres.2012.07.007
    Publication Date: 2023-03-07
    Description: Beringian climate and environmental history are poorly characterized at its easternmost edge. Lake sediments from the northern Yukon Territory have recorded sedimentation, vegetation, summer temperature and precipitation changes since ~16 cal ka BP. Herb-dominated tundra persisted until ~14.7 cal ka BP with mean July air temperatures less than or equal to 5 °C colder and annual precipitation 50 to 120 mm lower than today. Temperatures rapidly increased during the Bølling/Allerød interstadial towards modern conditions, favoring establishment of Betula-Salix shrub tundra. Pollen-inferred temperature reconstructions recorded a pronounced Younger Dryas stadial in east Beringia with a temperature drop of ~1.5 °C (~2.5 to 3.0 °C below modern conditions) and low net precipitation (90 to 170 mm) but show little evidence of an early Holocene thermal maximum in the pollen record. Sustained low net precipitation and increased evaporation during early Holocene warming suggest a moisture-limited spread of vegetation and an obscured summer temperature maximum. Northern Yukon Holocene moisture availability increased in response to a retreating Laurentide Ice Sheet, postglacial sea level rise, and decreasing summer insolation that in turn led to establishment of Alnus-Betula shrub tundra from ~5 cal ka BP until present, and conversion of a continental climate into a coastal-maritime climate near the Beaufort Sea.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 76
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    In:  Supplement to: Boike, Julia; Grau, Thomas; Heim, Birgit; Günther, Frank; Langer, Moritz; Muster, Sina; Gouttevin, Isabelle; Lange, Stephan (2016): Satellite-derived changes in the permafrost landscape of central Yakutia, 2000–2011: Wetting, drying, and fires. Global and Planetary Change, 139, 116-127, https://doi.org/10.1016/j.gloplacha.2016.01.001
    Publication Date: 2023-03-07
    Description: The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products (250-1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km**2 the total area covered by lakes increased by 17.9% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year. The average rate of warming during the April-May transition period was 0.17 °C/year and 0.19 °C/year in the September-October period, but ranged up to 0.49 °C/year during September-October. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover. Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying).
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 9 datasets
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  • 77
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    In:  Supplement to: Niemeyer, Bastian; Klemm, Juliane; Pestryakova, Luidmila A; Herzschuh, Ulrike (2015): Relative pollen productivity estimates for common taxa of the northern Siberian Arctic. Review of Palaeobotany and Palynology, 221, 71-82, https://doi.org/10.1016/j.revpalbo.2015.06.008
    Publication Date: 2023-03-07
    Description: Pollen productivity estimates (PPE) are used to quantitatively reconstruct variations in vegetation within a specific distance of the sampled pollen archive. Here, for the first time, PPEs from Siberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larixis the sole forest-line forming tree taxon. Pollen spectra from two different sedimentary environments, namely terrestrial mosses (n=16) and lakes (n=15, median radius ~100 m) and their surrounding vegetation were investigated to extract PPEs. Our results indicate some differences in pollen spectra between moss and lake pollen. Larix and Cyperaceae for example obtained higher representation in the lacustrine than in terrestrial moss samples. This highlights that in calibration studies modern and fossil dataset should be of similar sedimentary origin. The results of the Extended R-Value model were applied to assess the relevant source area of pollen (RSAP) and to calculate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10 m) compared to the lacustrine samples (about 25 km). Calculation of PPEs for the six most common taxa yielded generally similar results for both datasets. Relative to Poaceae (reference taxon, PPE=1) Betula nana-type (PPEmoss: 1.8, PPElake: 1.8) and Alnusfruticosa-type (PPEmoss: 6.4, PPElake: 2.9) were overrepresented while Cyperaceae (PPEmoss: 0.5, PPElake: 0.1), Ericaceae (PPEmoss: 0.3, PPElake 〈0.01), Salix (PPEmoss: 0.03, PPElake 〈0.01) and Larix (PPEmoss 〈0.01, PPElake: 0.2) were under-represented in the pollen spectra compared to the vegetation in the RSAP. The estimation for the dominant tree in the region, Larixgmelinii, is the first published result for this species, but need to be considered very preliminary. The inferred sequence from over- to under-representation is mostly consistent with results from Europe; however, still the absolute values show some differences. Gathering vegetation data was limited by flowering season and low resolute satellite imagery and accessibility of the remote location of our study area. Therefore, our estimate may serve as first reference to strengthen future vegetation reconstructions in this climate-sensitive region.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 78
    Publication Date: 2023-03-07
    Description: This vector data layer covers 6 major lake districts (Baldwin Peninsula, Kobuk Delta, Selawik Lowland, Northern Seward Peninsula, Central Seward Peninsula, and Yukon-Kuskokwim Delta) in the northern and central sub-regions of the Western Alaska Landscape Conservation Cooperative (WALCC) region and consists of polygons of lakes with areas equal or greater than 1.0 ha. More than 58000 Lakes were mapped from Landsat TM and ETM+ imagery acquired between 1972 and 1975, 2002 and 2009, and 2013 and 2014 using Object-Based Image Analysis (OBIA) techniques with an classification accuracy of 96%. The spatial image resolution of Landsat TM and ETM+ is 30 m. Permafrost characteristics and surficial geology associated with lake polygons were determined from the Alaska permafrost map (Jorgenson et al. 2008).
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 79
    Publication Date: 2023-03-07
    Keywords: 11-CH-17A; Age; Age, 14C AMS; Age, 14C calibrated; Age, dated; Age, dated material; Age, dated standard deviation; Age, standard deviation; AWI_PerDyn; AWI Arctic Land Expedition; Calculated; Chatanga2011; DEPTH, sediment/rock; GCUWI; Gravity corer, UWITEC; Permafrost Research (Periglacial Dynamics) @ AWI; RU-Land_2011_Khatanga; Sample, optional label/labor no; Taymyr peninsula, northern Siberia
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 80
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 18.2 MBytes
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  • 81
    Publication Date: 2023-03-07
    Keywords: 11-CH-moss10I; 11-CH-moss16I; 11-CH-moss17I; 11-CH-moss17II; 11-CH-moss2I; 11-CH-moss2II; 11-CH-moss6I; 11-CH-moss6II; 11-CH-moss6III; 11-CH-moss6IV; 13-TY-moss4K1; 13-TY-moss4K2; 13-TY-moss7K1; 13-TY-moss7K2; 13-TY-moss9K1; 13-TY-moss9K2; AWI_PerDyn; AWI Arctic Land Expedition; Calculated; Chatanga2011; Counting, palynology; Event label; Khatanga region, Russia; LAKE; LAND; Latitude of event; Longitude of event; Permafrost Research (Periglacial Dynamics) @ AWI; Pollen productivity estimate; Ring sector, in; Ring sector, out; RU-Land_2011_Khatanga; Sample ID; Sampling/measurement on land; Sampling lake
    Type: Dataset
    Format: text/tab-separated-values, 2410 data points
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  • 82
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 10.2 MBytes
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  • 83
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 10.2 MBytes
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  • 84
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 480.6 kBytes
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  • 85
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 23.9 MBytes
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  • 86
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 2 MBytes
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  • 87
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 1.7 MBytes
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  • 88
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; File content; File size; Latitude, northbound; Latitude, southbound; Longitude, eastbound; Longitude, westbound; Permafrost Research (Periglacial Dynamics) @ AWI; Projection; Sakha Republic, Russia; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
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  • 89
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 336.6 kBytes
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  • 90
    Publication Date: 2023-03-07
    Description: The dataset was obtained on samples taken from 6 stations in the Dardanelles Straits, Marmara Sea and Bosporus Straits. These experiments were set up according to DoW of SESAME project. Ciliate abundance: Borax-buffered formalin (final concentration 2% formaldehyde). Samples for ciliate counting were stored at 4°C in the dark until observation. For ciliate identification and enumeration, 100 ml samples were left for 24 h in sedimentation cylinders and then observed under an inverted epifluorescence microscope. Ciliate biomass: Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae (Peuto-Moreau 1991). For biomass estimation, the conversion factor 140 fgC µm**3 was used (Putt and Stoecker (1989), doi:10.4319/lo.1989.34.6.1097)).
    Keywords: Bilim_TurkishStraits__L095L029_NIS_200804_53; Bilim_TurkishStraits_2008-04; Bilim_TurkishStraits_K03I45_NIS_200804_49; Bilim_TurkishStraits_K35J18_NIS_200804_52; Bilim_TurkishStraits_K465L00_NIS_200804_51; Bilim_TurkishStraits_K51K03_NIS_200804_50; Bilim_TurkishStraits_NIS_200804_54; Bilim 2; Bottle, Niskin; Ciliates; Ciliates, biomass as carbon; Computed/Converted; Date/Time of event; DEPTH, water; Eastern Mediterranean Sea; Event label; K03I45; K35J18; K465L00; K51K03; L095L029; L18L105; Latitude of event; Longitude of event; Measured/Determined; NIS; Optional event label; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes
    Type: Dataset
    Format: text/tab-separated-values, 52 data points
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  • 91
    Publication Date: 2023-03-07
    Description: The SES_GR2-Mesozooplankton faecal pellet production rates dataset is based on samples taken during August and September 2008 in the Northern Libyan Sea, Southern Aegean Sea and the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the 0–100 m layer or within the Black sea water body mass layer in the case of the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 00A1b; 0A10c; 0I05d; 0L02c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern Mediterranean Sea; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR2; SES_GR2-00A1b_WP2; SES_GR2-0A10c_WP2; SES_GR2-0I05d_WP2; SES_GR2-0L02c_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
    Location Call Number Expected Availability
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  • 92
    Publication Date: 2023-03-07
    Description: The SES_GR1-Mesozooplankton faecal pellet production rates dataset is based on samples taken during April 2008 in the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the Black sea water body mass layer in the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 00NA3b; 00NA4; 00NA6; 00NA7; 00NA8b; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR1; SES_GR1-00NA3b_WP2; SES_GR1-00NA4_WP2; SES_GR1-00NA6_WP2; SES_GR1-00NA7_WP2; SES_GR1-00NA8b_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
    Location Call Number Expected Availability
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  • 93
    Publication Date: 2023-03-07
    Description: The SES_UNLUATA_GR1-Mesozooplankton faecal pellet production rates dataset is based on samples taken during March and April 2008 in the Northern Libyan Sea, Southern Aegean Sea and in the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the 0-100 m layer or within the Black sea water body mass layer in the case of the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets and are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 000L2a; 0A01c; 0A10c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR1; SES_GR1-000L2a_WP2; SES_GR1-0A01c_WP4; SES_GR1-0A10c_WP3; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
    Location Call Number Expected Availability
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  • 94
    Publication Date: 2023-03-07
    Description: Mesozooplankton is collected by vertical tows within the Black sea water body mass layer in the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 0NA1b; 0NA7c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern Mediterranean Sea; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Optional event label; SES_GR2; SES_GR2-0NA1b_WP2; SES_GR2-0NA7c_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
    Location Call Number Expected Availability
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  • 95
    Publication Date: 2023-03-07
    Description: The NA64-Mesozooplankton dataset contains biogeochemistry and mesozooplankton data collected in a series of 9 cruises in the Northern Adriatic completed from January 1965 to September 1965 monthly, and December 1965. Biogeochemistry sampling was undertaken using 5L Nansen bottles fired at 0m, 5m, 10m, 20m, 30m and/or bottom depths. The dataset includes 709 samples analysed for nitrate, phosphate, temperature, salinity and density. Mesozooplankton sampling was undertaken at the same locations as for biogeochemistry, using two different net (Hensen non-closing and Appstein closing net). The dataset includes 146 samples analysed for mesozooplankton composition (at higher taxonomic level), abundance and volume settlement. Temperature was measured with a standard oceanographic thermometers. Salinity was determined by titration after Mohr-Knudsen using standardised water I.C.E.S. Copenhagen with 0,01 permil accuracy. Density was calculated using the following equation Sigma-t = T - (sigma 0 + 0,1324) 1 - At + Bt (sigma 0 - 0,1324). Phosphate samples for the determination of nutrients were collected in 500 ml and filtrated through 0,3 µm membrane filter. 3ml of cloroform was added to stabilize the samples. They were analysed after few days in the laboratory on land. Nitrate samples for the determination of nutrients were collected in 500 ml and filtrated through 0,3 µm membrane filter. 3ml of cloroform was added to stabilize the samples. They were analysed after few days in the laboratory on land.
    Keywords: 1; 10; 11; 12; 13; 14; 15; 16; 17; 18; 2; 3; 4; 5; 6; 7; 8; 9; Adriatic Sea; Bottle, Nansen; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Event label; Latitude of event; Longitude of event; NA64; NA64_19650126-02; NA64_19650126-03; NA64_19650126-04; NA64_19650126-05; NA64_19650126-08; NA64_19650126-12; NA64_19650127-10; NA64_19650127-13; NA64_19650127-14; NA64_19650127-15; NA64_19650127-17; NA64_19650128-01; NA64_19650128-18; NA64_19650225-2; NA64_19650225-3; NA64_19650225-4; NA64_19650225-5; NA64_19650225-6; NA64_19650225-7; NA64_19650225-8; NA64_19650225-9; NA64_19650226-10; NA64_19650226-11; NA64_19650226-12; NA64_19650227-17; NA64_19650227-18; NA64_19650228-1; NA64_19650324-15; NA64_19650324-16; NA64_19650324-17; NA64_19650324-18; NA64_19650327-10; NA64_19650327-11; NA64_19650327-12; NA64_19650327-13; NA64_19650327-14; NA64_19650327-8; NA64_19650327-9; NA64_19650328-2; NA64_19650328-3; NA64_19650328-4; NA64_19650328-5; NA64_19650328-6; NA64_19650328-7; NA64_19650507-2; NA64_19650507-3; NA64_19650507-4; NA64_19650507-5; NA64_19650507-6; NA64_19650507-7; NA64_19650507-8; NA64_19650507-9; NA64_19650508-10; NA64_19650508-11; NA64_19650508-12; NA64_19650508-13; NA64_19650508-14; NA64_19650508-15; NA64_19650508-16; NA64_19650509-1; NA64_19650509-17; NA64_19650509-18; NA64_19650526-10; NA64_19650526-2; NA64_19650526-3; NA64_19650526-4; NA64_19650526-5; NA64_19650526-6; NA64_19650526-7; NA64_19650526-8; NA64_19650526-9; NA64_19650527-11; NA64_19650527-12; NA64_19650527-13; NA64_19650527-14; NA64_19650527-15; NA64_19650527-16; NA64_19650528-1; NA64_19650528-17; NA64_19650528-18; NA64_19650628-2; NA64_19650628-3; NA64_19650628-4; NA64_19650628-5; NA64_19650628-6; NA64_19650628-7; NA64_19650628-8; NA64_19650628-9; NA64_19650630-10; NA64_19650630-11; NA64_19650630-12; NA64_19650630-13; NA64_19650630-14; NA64_19650630-15; NA64_19650705-16; NA64_19650705-17; NA64_19650706-1; NA64_19650706-18; NA64_19650805-2; NA64_19650805-3; NA64_19650805-4; NA64_19650805-5; NA64_19650805-6; NA64_19650805-7; NA64_19650805-8; NA64_19650805-9; NA64_19650806-10; NA64_19650806-11; NA64_19650806-12; NA64_19650806-13; NA64_19650806-14; NA64_19650806-15; NA64_19650807-16; NA64_19650808-1; NA64_19650808-17; NA64_19650808-18; NA64_19650915-2; NA64_19650915-3; NA64_19650915-4; NA64_19650915-5; NA64_19650915-6; NA64_19650915-7; NA64_19650915-8; NA64_19650915-9; NA64_19650916-10; NA64_19650916-11; NA64_19650916-12; NA64_19650916-13; NA64_19650916-14; NA64_19650916-15; NA64_19650918-16; NA64_19650918-17; NA64_19650919-1; NA64_19651214-16; NA64_19651214-17; NA64_19651214-18; NA64_19651226-10; NA64_19651226-11; NA64_19651226-12; NA64_19651226-13; NA64_19651226-14; NA64_19651226-15; NA64_19651226-9; NA64_19651227-3; NA64_19651227-4; NA64_19651227-5; NA64_19651227-6; NA64_19651227-7; NA64_19651227-8; NAS; Nitrate; Phosphate; Salinity; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 2705 data points
    Location Call Number Expected Availability
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  • 96
    Publication Date: 2023-03-07
    Description: hyDRaCAT Spectral Reflectance Library for tundra provides the surface reflectance data and the bidirectional reflectance distribution function (BRDF) of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites. The aim of this dataset is the hyperspectral and spectro-directional reflectance characterization as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. The spectroscopic and field spectro-goniometric measurements were undertaken on the YAMAL2011 expedition of representative Siberian vegetation fields and on the North American Arctic Transect NAAT2012 expedition of Alaskan vegetation fields both belonging to the Greening-of-the-Arctic (GOA) program. For the field spectroscopy each 100 m2 vegetation study grid was divided into quadrats of 1 × 1 m. The averaged reflectance of all quadrats represents the spectral reflectance at the scale of the whole grid at the 10 × 10 m scale. For the surface radiometric measurements two GER1500 portable field spectroradiometers (Spectra Vista Corporation, Poughkeepsie, NY, USA) were used. The GER1500 measures radiance across the wavelength range of 350-1,050 nm, with sampling intervals of 1.5 nm and a radiance accuracy of 1.2 × 10**-1 W/cm**2/nm/sr. In order to increase the signal-to-noise ratio, 32 individual measurements were averaged per one target scan. To minimize variations in the target reflectance due to sun zenith angle changes, all measurements at one study location have been performed under similar sun zenith angles and during clear-sky conditions. The field spectrometer measurements were carried out with a GER1500 UV-VIS spectrometer The spectrogoniometer measurements were carried out with a self-designed spectro-goniometer: the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS, patent publication number: DE 10 2011 117 713.A1). The ManTIS was equipped with the GER1500 spectrometer allowing spectro-directional measurements with up to 30° viewing zenith angle by full 360° viewing azimuth angles. Measurements in central Yamal (Siberia) at the research site 'Vaskiny Dachi' were carried out in the late summer phenological state from August 12 2011 to August 28 2011. All measurements in Alaska along the North South transect on the North Slope were taken between 29 June and 11 July 2012, ensuring that the vegetation was in the same phenological state near peak growing season.
    Keywords: AWI_PerDyn; AWI Arctic Land Expedition; Comment of event; Date/Time of event; Elevation of event; Event label; FBG1; FBG2; FBG3; FBG4; File name; File size; Franklin Bluffs, Arctic North Slope, Alaska, United States of America; Happy Valley, Arctic North Slope, Alaska, United States of America; HVG1; HVG2; Latitude of event; Location of event; Longitude of event; Permafrost Research (Periglacial Dynamics) @ AWI; Persistent Identifier; Remote Sensing of POlar Non-glaciated and Sensitive Environments; RESPONSE; Vaskiny Dachi, Yamal Peninsula, West Siberia, Russian Federation; VDG1; VDG2
    Type: Dataset
    Format: text/tab-separated-values, 35 data points
    Location Call Number Expected Availability
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  • 97
    Publication Date: 2023-03-10
    Keywords: Bubble catcher; Bubble flux; BUC; Carbon dioxide, flux; DATE/TIME; DEPTH, water; ECO2; ECO2-9; ECO2-9-162; ECO2-9-167; Event label; LATITUDE; LONGITUDE; Panarea; Sample code/label; Sub-seabed CO2 Storage: Impact on Marine Ecosystems
    Type: Dataset
    Format: text/tab-separated-values, 18 data points
    Location Call Number Expected Availability
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  • 98
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; CSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Corona); Seward_Peninsula
    Type: Dataset
    Format: application/zip, 569.9 MBytes
    Location Call Number Expected Availability
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  • 99
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    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Publication Date: 2023-03-07
    Keywords: 11-CH-12A; AWI_PerDyn; AWI Arctic Land Expedition; awilinescan2015; Chatanga2011; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; File size; GCUWI; Gravity corer, UWITEC; Line Scan Camera; Permafrost Research (Periglacial Dynamics) @ AWI; RU-Land_2011_Khatanga; Taymyr peninsula, northern Siberia; Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Expected Availability
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  • 100
    Publication Date: 2023-03-04
    Keywords: Mode of life; North America, U.S.A.; Parameter; Western_North_America; Zone
    Type: Dataset
    Format: text/tab-separated-values, 13776 data points
    Location Call Number Expected Availability
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