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  • PANGAEA
  • 2010-2014  (1,324)
  • 1955-1959  (3)
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Year
  • 1
    Publication Date: 2023-07-10
    Keywords: Analysis; Sample amount
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
    Location Call Number Expected Availability
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  • 2
    Publication Date: 2023-07-10
    Keywords: Analysis; B-2-10-SF; BRP01; BRP02; BRP03; BRP04; BRP05; BRP06; BRP07; BRP08; BRP09; BRP10; BRP11; BRP12; BRP13; BRP14; BRP15; BRP16; BRP17; BRP18; BRP19; BRP20; Campaign of event; CBP02; CBP05; CBP06; CBP07; CBP08; CBP09; CBP10; CBP11; CBP12; CBP14; CBP15; CBP17; CBP18; CBP19; CBP20; CBP21; CBP22; CBP23; CBP25; CBP26; CBP27; CBP28; CBP29; CBP30; CBP31; CBP32; CBP33; CBP34; CBP35; CBP36; CBP37; CBP38; CBP39; CBP40; CBP41; CBP42; CBP43; CBP45; CBP46; CBP47; CBP48; Comment; CR_01; CR_02A; CR_02B; CR_02C; CR_02D; CR_03; CR_04; CR_06B; CR_07B; CR_08; CR_09; CR_10; CR_11A1; CR_11A2; CR_11B; CR_15A; CR_15B; Date/Time of event; Event label; GGP01; GGP03; GGP07; GGP08; GGP09; GGP10; GGP11; GGP12; GGP13; GGP14; GGP15; GGP16; Grab; GRAB; HAND; Hand trowel; Latitude of event; Layer thickness; Longitude of event; OSP01; OSP02; OSP03; OSP05; OSP06; OSP07; OSP08; OSP09; OSP10; OSP11; OSP12; OSP13; OSP14; OSP15; OSP16; OSP17; OSP18; OSP22; OSP23; OSP24; OSP25; OSP26; OSP28; OSP29; OSP30; OSP31; OSP32; OSP33; OSP34; OSP35; OSP36; OSP37; OSP38; OSP39; Parke Snavely; S-7-10-SF; S-8-10-SF; SAC01; SAC02; SACFP; SACHD; Sample comment; Sample type; Sampling by hand; San Francisco Bay, California; SBP01; SBP02; SBP03; SBP04; SBP05; SBP06; SBP07; SBP08; SBP09; SBP10; SBP11; SBP12; SBP13; SBP14; SBP15; SBP16; SBP17; SBP18; SBP19; SBP20; SBP21; SBP22; SBP23; SBP24; SBP25; SBP27; SBP28; SFPBCH01; SFPBCH02; SFPBCH03; SFPBCH04; SFPBCH05; SFPBCH06; SFPBCH07; SFPBCH08; SFPBCH09; SFPBCH10; SFPBCH11; SFPBCH12; SFPBCH13; SFPBCH14; SFPBCH15; SFPBCH16; SFPBCH17; SFPBCH18; SFPBCH19; SFPBCH20; SFPBCH21; SFPBCH22; SFPBCH23; SFPBCH24; SFPBCH25; SFPBCH26; SFPBCH27; SFPBCH28; SFPBCH29; SFPBCH30; SFPBCH31; SFPBCH32; SFPBCH33; SFPBCH34; SFPBCH35; SFPBCH36; SFPBCH37; SFPBCH38; SFPBCH39; SFPBCH40; SFPBCH41; SFPBCH42; SFPCLF01; SFPCLF02A; SFPCLF02B; SFPCLF02C; SFPCLF03; SFPCLF04; SFPCLF05A; SFPCLF05B; SFPCLF05C; SFPCLF06; SFPCLF07; SFPCLF08; SFPCLF09; SFPCLF10; SFPCLF11A; SFPCLF11B_C; SFPCLF11D_E; SFPCLF13; SFPCLF14; SFPCLF15; SJC01; SJC02; SJRST; SPP01; SPP02; SPP03; SPP04; SPP05; SPP06; SPP07; SPP08; SPP09; SPP10; SPP11; SPP12; SPP13; SPP14; SPP15; SPP16; SSP01; SSP02; SSP03; SSP04; SSP05; SSP06; SSP07; SSP08; SSP09; SSP10; SSP11; SSP12; SSP13; SSP14; SSP15; SSP16; SSP17; SSP18; SSP19; TROW
    Type: Dataset
    Format: text/tab-separated-values, 2131 data points
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  • 3
    Publication Date: 2023-06-27
    Keywords: Alameda; BRP01; BRP02; BRP03; BRP04; BRP05; BRP06; BRP07; BRP08; BRP09; BRP10; BRP11; BRP12; BRP13; BRP14; BRP15; BRP16; BRP17; BRP18; BRP19; BRP20; C-1-3, Sunnyvale; C-3-0, San Jose; Campaign of event; CBP02; CBP05; CBP06; CBP07; CBP08; CBP09; CBP10; CBP11; CBP12; CBP14; CBP15; CBP17; CBP18; CBP19; CBP20; CBP23; CBP30; CBP31; CBP37; CBP38; CBP39; Coyote Creek; Date/Time of event; Date/Time of event 2; David Johnston; Davis Point; Dumbarton Bridge; Elevation of event; Event label; GGP01; GGP09; GGP10; GGP11; GGP12; GGP15; Grab; GRAB; Grizzly Bay; Guadalupe River; Honker Bay; Horseshoe Bay; J-1-98_01; J-1-98_02; J-1-98_03; J-1-98_04; J-1-98_05; J-1-98_06; J-1-98_07; J-1-98_08; J-1-98_10a; J-1-98_11; J-1-98_12; J-1-98_13; J-1-98_14; J-1-98_15; J-1-98_16; J-1-98_17a; J-1-98_18; J-1-98_19; J-1-98_20; J-1-98_21; J-1-98_22; J-1-98_23; J-1-98_24; J-1-98_25; J-1-98_26; J-1-98_27; J-1-98_28; J-1-98_29; J-1-98_30; J-1-98_31; J-1-98_32; J-1-98_33; J-1-98_34; J-1-98_35; J-1-98_36; J-1-98_37; J-1-98_38; J-1-98_39; J-1-98_40; J-1-98_41; J-1-98_42; J-1-98_43; J-1-98_44; J-1-98_45; J-1-98_46; J-1-98_47; J-1-98_48; J-1-98_49; J-1-98_50; J-1-98_51; J-1-98_52; J-1-98_53; J-1-98_54; J-1-98_55; J-1-98_56; J-1-98-SF; Latitude of event; Longitude of event; Napa River; Number; Optional event label; OSP01; OSP03; OSP05; OSP06; OSP10; OSP12; OSP13; OSP14; OSP15; OSP16; OSP17; OSP18; OSP22; OSP23; OSP24; OSP25; OSP26; OSP28; OSP29; OSP31; OSP32; OSP35; OSP36; OSP38; OSP39; Oyster Point; Pacheco Creek; Parke Snavely; Petaluma River; Pinole Point; Point Isabel; Red Rock; Redwood Creek; Richardson Bay; S-7-10-SF; S-8-10-SF; Sacramento River; Sample comment; San Bruno Shoal; San Francisco Bay, California; San Francisco Estuary Institute Regional Monitoring Program 1995-1998; San Joaquin River; San Pablo Bay; SBP01; SBP02; SBP03; SBP04; SBP05; SBP06; SBP07; SBP08; SBP09; SBP10; SBP11; SBP12; SBP13; SBP14; SBP15; SBP16; SBP17; SBP18; SBP19; SBP20; SBP21; SBP22; SBP23; SBP24; SBP25; SBP27; SBP28; SFEI; SFEI_BA05; SFEI_BA06; SFEI_BA10; SFEI_BA21; SFEI_BA30; SFEI_BA41; SFEI_BB15; SFEI_BB30; SFEI_BB70; SFEI_BC11; SFEI_BC21; SFEI_BC32; SFEI_BC41; SFEI_BC60; SFEI_BD15; SFEI_BD22; SFEI_BD31; SFEI_BD41; SFEI_BD50; SFEI_BF10; SFEI_BF21; SFEI_BF40; SFEI_BG20; SFEI_BG30; SFEI_BW10; SFEI_BW15; South Bay; SPP01; SPP02; SPP03; SPP04; SPP05; SPP06; SPP07; SPP08; SPP09; SPP10; SPP11; SPP12; SPP13; SPP14; SPP15; SPP16; SSP01; SSP02; SSP03; SSP04; SSP05; SSP06; SSP07; SSP08; SSP09; SSP16; SSP17; SSP18; SSP19; Standish Dam; Yerba Buena Island
    Type: Dataset
    Format: text/tab-separated-values, 241 data points
    Location Call Number Expected Availability
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  • 4
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    Unknown
    PANGAEA
    In:  Supplement to: Gruber, Thomas; Bamber, Jonathan L; Bierkens, Marc F P; Dobslaw, Henryk; Murböck, M; Thomas, M; van Beek, L P H; van Dam, T; Vermeersen, L L A; Visser, P N A M (2011): Simulation of the time-variable gravity field by means of coupled geophysical models. Earth System Science Data, 3(1), 19-35, https://doi.org/10.5194/essd-3-19-2011
    Publication Date: 2023-09-02
    Description: Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth's surface or by geophysical processes in the Earth's interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US/German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking successor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on ''Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites''. The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the different domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earthquake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth's global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested.
    Keywords: DATE/TIME; File name; Method comment; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 180 data points
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  • 5
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    Unknown
    PANGAEA
    In:  Supplement to: Wong, Florence L; Woodrow, Donald L; McGann, Mary L (2013): Heavy mineral analysis for assessing the provenance of sandy sediment in the San Francisco Bay Coastal System. Marine Geology, 345, 170-180, https://doi.org/10.1016/j.margeo.2013.05.012
    Publication Date: 2023-07-07
    Description: Heavy or high-specific gravity minerals make up a small but diagnostic component of sediment that is well suited for determining the provenance and distribution of sediment transported through estuarine and coastal systems worldwide. By this means, we see that surficial sand-sized sediment in the San Francisco Bay Coastal System comes primarily from the Sierra Nevada and associated terranes by way of the Sacramento and San Joaquin Rivers and is transported with little dilution through the San Francisco Bay and out the Golden Gate. Heavy minerals document a slight change from the strictly Sierran-Sacramento mineralogy at the confluence of the two rivers to a composition that includes minor amounts of chert and other Franciscan Complex components west of Carquinez Strait. Between Carquinez Strait and the San Francisco Bar, Sierran sediment is intermingled with Franciscan-modified Sierran sediment. The latter continues out the Gate and turns southward towards beaches of the San Francisco Peninsula. The Sierran sediment also fans out from the San Francisco Bar to merge with a Sierran province on the shelf in the Gulf of the Farallones. Beach-sand sized sediment from the Russian River is transported southward to Point Reyes where it spreads out to define a Franciscan sediment province on the shelf, but does not continue southward to contribute to the sediment in the Golden Gate area.
    Keywords: Actinolite; Amphibole; Apatite; Augite; B-2-10-SF; BRP06; BRP08; BRP10; BRP14; Carbonates; CBP11; CBP15; CBP19; CBP33; CBP42; CBP46; Chert; Chromspinel; Clinopyroxene; Clinozoisite; CR_01; CR_03; CR_04; CR_08; DEPTH, sediment/rock; Enstatite; Epidote; Event label; Garnet; GGP01; GGP09; GGP12; GGP15; Glaucophane; Grab; GRAB; Grains, counted/analyzed; HAND; Hand trowel; Hornblende, basaltic; Hornblende, brown; Hornblende, green; Hypersthene; Latitude of event; Lawsonite; Longitude of event; Non-opaque minerals; OSP01; OSP05; OSP13; OSP22; OSP25; OSP28; OSP31; OSP35; Parke Snavely; Rock fragments; Rutile; S-7-10-SF; S-8-10-SF; SAC01; Sample type; Sampling by hand; San Francisco Bay, California; SBP02; SBP13; SFPBCH14; SFPBCH17; SFPBCH19; SFPBCH20; SFPBCH21; SFPBCH22; SFPBCH32; SFPBCH33; SFPCLF09; SJC02; Sphene; SPP07; SPP12; SSP01; Tourmaline; Tremolite; TROW; Zircon; Zoisite
    Type: Dataset
    Format: text/tab-separated-values, 1218 data points
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  • 6
    Publication Date: 2023-07-01
    Description: Zircons from the oldest magmatic and metasedimentary rocks in the Podolia domain of the Ukrainian shield were studied and dated by the U-Pb method on a NORDSIM secondary-ion mass spectrometer. Age of zircon cores in enderbite gneisses sampled in the Kazachii Yar and Odessa quarries on the opposite banks of the Yuzhnyi Bug River reaches 3790 Ma. Cores of terrigenous zircons in quartzites from the Odessa quarry as well as in garnet gneisses from the Zaval'e graphite quarry have age within 3650-3750 Ma. Zircon rims record two metamorphic events around 2750-2850 Ma and 1900-2000 Ma. Extremely low U content in zircons of the second age group indicates conditions of the granulite facies metamorphism in Paleoproterozoic within the Podolia domain. Measured data on orthorocks (enderbite-gneiss) and metasedimentary rocks unambiguously suggest existence of the ancient Paleoarchean crust in the Podolia (Dniester-Bug) domain of the Ukrainian shield. They contribute in our knowledge of scales of formation and geochemical features of the primordial crust.
    Keywords: Archive of Ocean Data; ARCOD
    Type: Dataset
    Format: application/zip, 7 datasets
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  • 7
    Publication Date: 2023-11-18
    Keywords: DATE/TIME; Duration, number of days; Identification; Melville_Bay; Monodon monoceros, standard deviation; Monodon monoceros, time at surface, fraction; Monodon monoceros, total length; MULT; Multiple investigations; West Greenland
    Type: Dataset
    Format: text/tab-separated-values, 119 data points
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  • 8
    Publication Date: 2023-11-18
    Keywords: Area/locality; E_Greenland_whale; East Greenland; Event label; Inglefield_Bredn; Length; Melville_Bay; Monodon monoceros; MULT; Multiple investigations; Number; Province; W_Greenland_area2; West Greenland; Whale watching; WHW
    Type: Dataset
    Format: text/tab-separated-values, 75 data points
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  • 9
    Publication Date: 2023-11-18
    Keywords: Area; Area/locality; Blosseville_Coast; Coefficient; East Greenland; Encounter rate; Event label; Inglefield_Bredn; Kangerlussuaq/Sondrestrom, western Greenland; KangerlussuaqFjordEast; Kangertigtivatsiaq; Kulusuk_Fjord; Latitude of event; Length of transect; Longitude of event; Melville_Bay; Monodon monoceros; Monodon monoceros, density; Monodon monoceros, density of groups; Monodon monoceros, group size; Monodon monoceros, number of groups; MULT; Multiple investigations; Number; Number of observations; Province; Scoresby_Sound; Sermiligaaq; Sermilik; Tasiliaq; W_Greenland_area2; West Greenland; Whale watching; WHW
    Type: Dataset
    Format: text/tab-separated-values, 634 data points
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  • 10
    Publication Date: 2023-11-18
    Keywords: E_Greenland_whale; East Greenland; Event label; Inglefield_Bredn; Melville_Bay; Monodon monoceros, group size; MULT; Multiple investigations; Number of observations; Province; W_Greenland_area2; West Greenland; Whale watching; WHW
    Type: Dataset
    Format: text/tab-separated-values, 82 data points
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