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  • PANGAEA  (21,334)
  • Copernicus
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  • 1
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    Unknown
    Charcoal records of two sediment cores off SW Africa (2012)
    PANGAEA
    In:  Supplement to: Daniau, Anne-Laure; Bartlein, Patrick J; Harrison, S P; Prentice, Iain Colin; Brewer, Simon; Friedlingstein, Pierre; Harrison-Prentice, T I; Inoue, J; Izumi, K; Marlon, Jennifer R; Mooney, Scott D; Power, Mitchell J; Stevenson, J; Tinner, Willy; Andric, M; Atanassova, J; Behling, Hermann; Black, M; Blarquez, O; Brown, K J; Carcaillet, C; Colhoun, Eric A; Colombaroli, Daniele; Davis, Basil A S; D'Costa, D; Dodson, John; Dupont, Lydie M; Eshetu, Z; Gavin, D G; Genries, A; Haberle, Simon G; Hallett, D J; Hope, Geoffrey; Horn, S P; Kassa, T G; Katamura, F; Kennedy, L M; Kershaw, A Peter; Krivonogov, S; Long, C; Magri, Donatella; Marinova, E; McKenzie, G Merna; Moreno, P I; Moss, Patrick T; Neumann, F H; Norstrom, E; Paitre, C; Rius, D; Roberts, Neil; Robinson, G S; Sasaki, N; Scott, Louis; Takahara, H; Terwilliger, V; Thevenon, Florian; Turner, R; Valsecchi, V G; Vannière, Boris; Walsh, M; Williams, N; Zhang, Yancheng (2012): Predictability of biomass burning in response to climate changes. Global Biogeochemical Cycles, 26(4), https://doi.org/10.1029/2011GB004249
    Details
    Publication Date: 2024-01-13
    Description: We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 2
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    The Global Plankton Database: an inventory and data from the Former Soviet Union expeditions
    PANGAEA
    Details
    Publication Date: 2023-05-12
    Description: At present time, there is a lack of knowledge on the interannual climate-related variability of zooplankton communities of the tropical Atlantic, central Mediterranean Sea, Caspian Sea, and Aral Sea, due to the absence of appropriate databases. In the mid latitudes, the North Atlantic Oscillation (NAO) is the dominant mode of atmospheric fluctuations over eastern North America, the northern Atlantic Ocean and Europe. Therefore, one of the issues that need to be addressed through data synthesis is the evaluation of interannual patterns in species abundance and species diversity over these regions in regard to the NAO. The database has been used to investigate the ecological role of the NAO in interannual variations of mesozooplankton abundance and biomass along the zonal array of the NAO influence. Basic approach to the proposed research involved: (1) development of co-operation between experts and data holders in Ukraine, Russia, Kazakhstan, Azerbaijan, UK, and USA to rescue and compile the oceanographic data sets and release them on CD-ROM, (2) organization and compilation of a database based on FSU cruises to the above regions, (3) analysis of the basin-scale interannual variability of the zooplankton species abundance, biomass, and species diversity.
    Keywords: AAK106; AAK62; AAK65; AAK7/1; AAK7/2; AAK7/3; AAK7/4; AAK7/5; AAK71; AAK88; AAK90; AAK95; Adriatic Sea; Aegean Sea; Akademik A Kovalyevskiy; Akademik Vernadsky; AKov_106-track; AKov_62-track; AKov_65-track; AKov_7/1-track; AKov_7/2-track; AKov_7/3-track; AKov_7/4-track; AKov_7/5-track; AKov_71-track; AKov_88-track; AKov_90-track; AKov_95-track; Arabian Sea; Aral_Sea; Atlantic Ocean; AV10; AV10_938-1; AV10_938-2; AV10_939-1; AV10_939-2; AV10_940-1; AV10_940-2; AV10_941-1; AV10_941-2; AV10_942-1; AV10_942-2; AV10_943-1; AV10_943-2; AV10_944-1; AV10_944-2; AV10_945-1; AV10_945-2; AV10_946-1; AV10_947-1; AV10_948-1; AV10_948-2; AV10_949-1; AV10_949-2; AV10_950-1; AV10_950-2; AV10_950-3; AV10_950-4; AV10_951-1; AV10_951-2; AV10_952-1; AV10_952-2; AV10_953-1; AV10_953-2; AV10_954-1; AV10_954-2; AV10_955-1; AV10_955-2; AV10_956-1; AV10_956-2; AV10_957-1; AV10_958-1; AV10_959-1; AV10_960-1; AV10_961-1; AV10_961-10; AV10_961-100; AV10_961-101; AV10_961-102; AV10_961-103; AV10_961-104; AV10_961-105; AV10_961-106; AV10_961-107; AV10_961-108; AV10_961-109; AV10_961-11; AV10_961-110; AV10_961-111; AV10_961-112; AV10_961-113; AV10_961-114; AV10_961-115; AV10_961-116; AV10_961-117; AV10_961-118; AV10_961-119; AV10_961-12; AV10_961-120; AV10_961-121; AV10_961-122; AV10_961-123; AV10_961-124; AV10_961-125; AV10_961-126; AV10_961-127; AV10_961-128; AV10_961-129; AV10_961-13; AV10_961-130; AV10_961-131; AV10_961-132; AV10_961-133; AV10_961-134; AV10_961-135; AV10_961-136; AV10_961-137; AV10_961-138; AV10_961-139; AV10_961-14; AV10_961-140; AV10_961-141; AV10_961-142; AV10_961-143; AV10_961-144; AV10_961-145; AV10_961-146; AV10_961-147; AV10_961-148; AV10_961-149; AV10_961-15; AV10_961-150; AV10_961-151; AV10_961-152; AV10_961-153; AV10_961-154; AV10_961-155; AV10_961-156; AV10_961-157; AV10_961-158; AV10_961-159; AV10_961-16; AV10_961-160; AV10_961-161; AV10_961-162; AV10_961-163; AV10_961-164; AV10_961-165; AV10_961-166; AV10_961-167; AV10_961-168; AV10_961-169; AV10_961-17; AV10_961-170; AV10_961-171; AV10_961-172; AV10_961-173; AV10_961-174; AV10_961-175; AV10_961-176; AV10_961-177; AV10_961-178; AV10_961-179; AV10_961-18; AV10_961-180; AV10_961-181; AV10_961-182; AV10_961-183; AV10_961-184; AV10_961-185; AV10_961-186; AV10_961-187; AV10_961-188; AV10_961-189; AV10_961-19; AV10_961-190; AV10_961-191; AV10_961-192; AV10_961-193; AV10_961-194; AV10_961-195; AV10_961-196; AV10_961-197; AV10_961-198; AV10_961-199; AV10_961-2; AV10_961-20; AV10_961-200; AV10_961-201; AV10_961-202; AV10_961-203; AV10_961-204; AV10_961-205; AV10_961-206; AV10_961-207; AV10_961-208; AV10_961-209; AV10_961-21; AV10_961-210; AV10_961-211; AV10_961-212; AV10_961-213; AV10_961-214; AV10_961-215; AV10_961-216; AV10_961-217; AV10_961-218; AV10_961-219; AV10_961-22; AV10_961-220; AV10_961-221; AV10_961-222; AV10_961-223; AV10_961-224; AV10_961-225; AV10_961-226; AV10_961-227; AV10_961-228; AV10_961-229; AV10_961-23; AV10_961-230; AV10_961-231; AV10_961-232; AV10_961-233; AV10_961-234; AV10_961-235; AV10_961-236; AV10_961-237; AV10_961-238; AV10_961-239; AV10_961-24; AV10_961-240; AV10_961-241; AV10_961-242; AV10_961-243; AV10_961-244; AV10_961-245; AV10_961-246; AV10_961-247; AV10_961-248; AV10_961-249; AV10_961-25; AV10_961-250; AV10_961-251; AV10_961-252; AV10_961-253; AV10_961-254; AV10_961-255; AV10_961-256; AV10_961-257; AV10_961-258; AV10_961-259; AV10_961-26; AV10_961-260; AV10_961-261; AV10_961-262; AV10_961-263; AV10_961-264; AV10_961-265; AV10_961-266; AV10_961-267; AV10_961-268; AV10_961-269; AV10_961-27; AV10_961-270; AV10_961-271; AV10_961-272; AV10_961-273; AV10_961-274; AV10_961-275; AV10_961-276; AV10_961-277; AV10_961-2771; AV10_961-278; AV10_961-279; AV10_961-28; AV10_961-280; AV10_961-281; AV10_961-282; AV10_961-283; AV10_961-284; AV10_961-285; AV10_961-286; AV10_961-287; AV10_961-288; AV10_961-289; AV10_961-29; AV10_961-290; AV10_961-291; AV10_961-292; AV10_961-293; AV10_961-294; AV10_961-295; AV10_961-296; AV10_961-297; AV10_961-298; AV10_961-299; AV10_961-3; AV10_961-30; AV10_961-300; AV10_961-301; AV10_961-302; AV10_961-303; AV10_961-304; AV10_961-305; AV10_961-306; AV10_961-307; AV10_961-308; AV10_961-309; AV10_961-31; AV10_961-310; AV10_961-311; AV10_961-312; AV10_961-313; AV10_961-314; AV10_961-315; AV10_961-316; AV10_961-317; AV10_961-318; AV10_961-319; AV10_961-32; AV10_961-320; AV10_961-321; AV10_961-322; AV10_961-323; AV10_961-324; AV10_961-325; AV10_961-326; AV10_961-327; AV10_961-328; AV10_961-329; AV10_961-33; AV10_961-330; AV10_961-331; AV10_961-332; AV10_961-333; AV10_961-334; AV10_961-34; AV10_961-35; AV10_961-36; AV10_961-37; AV10_961-38; AV10_961-39; AV10_961-4; AV10_961-40; AV10_961-41; AV10_961-42; AV10_961-43; AV10_961-44; AV10_961-45; AV10_961-46; AV10_961-47; AV10_961-48; AV10_961-49; AV10_961-5; AV10_961-50; AV10_961-51; AV10_961-52; AV10_961-53; AV10_961-54; AV10_961-55; AV10_961-56; AV10_961-57; AV10_961-58; AV10_961-59; AV10_961-6; AV10_961-60; AV10_961-61; AV10_961-62; AV10_961-63; AV10_961-64; AV10_961-65; AV10_961-66; AV10_961-67; AV10_961-68; AV10_961-69; AV10_961-7; AV10_961-70; AV10_961-71; AV10_961-72; AV10_961-73; AV10_961-74; AV10_961-75; AV10_961-76; AV10_961-77; AV10_961-78; AV10_961-79; AV10_961-8; AV10_961-80; AV10_961-81; AV10_961-82; AV10_961-83; AV10_961-84; AV10_961-85; AV10_961-86; AV10_961-862; AV10_961-87; AV10_961-88; AV10_961-89; AV10_961-9; AV10_961-90; AV10_961-91; AV10_961-92; AV10_961-93; AV10_961-94; AV10_961-95; AV10_961-96; AV10_961-97; AV10_961-98; AV10_961-99; AV10_962-1; AV10_963-1; AV10_964-1; AV10_965-1; AV10_966-1; AV10_967-1; AV10_968-2; AV10_969-2; AV10_970-1; AV10_970-2; AV10_971-2; AV10_974-1; AV11; AV11_1000-2; AV11_1001-2; AV11_1002-2; AV11_1003-1; AV11_1005-1; AV11_1006-1; AV11_1006-10; AV11_1006-11; AV11_1006-12; AV11_1006-13; AV11_1006-15; AV11_1006-16; AV11_1006-17; AV11_1006-18; AV11_1006-19; AV11_1006-2; AV11_1006-20; AV11_1006-21; AV11_1006-22; AV11_1006-23; AV11_1006-24; AV11_1006-25; AV11_1006-26; AV11_1006-27; AV11_1006-28; AV11_1006-29; AV11_1006-3; AV11_1006-30; AV11_1006-31; AV11_1006-32; AV11_1006-33; AV11_1006-34; AV11_1006-35; AV11_1006-36; AV11_1006-37; AV11_1006-38; AV11_1006-39; AV11_1006-4; AV11_1006-40; AV11_1006-41; AV11_1006-42; AV11_1006-43; AV11_1006-44; AV11_1006-45; AV11_1006-46; AV11_1006-47; AV11_1006-48; AV11_1006-49; AV11_1006-5; AV11_1006-50; AV11_1006-51; AV11_1006-52; AV11_1006-6; AV11_1006-7; AV11_1006-8; AV11_1006-9; AV11_1007-10; AV11_1007-11; AV11_1007-12; AV11_1007-13; AV11_1007-14; AV11_1007-15; AV11_1007-16; AV11_1007-17; AV11_1007-18; AV11_1007-19; AV11_1007-2; AV11_1007-20; AV11_1007-21; AV11_1007-22; AV11_1007-23; AV11_1007-24; AV11_1007-25; AV11_1007-26; AV11_1007-27; AV11_1007-28; AV11_1007-29; AV11_1007-3; AV11_1007-30; AV11_1007-31; AV11_1007-32; AV11_1007-33; AV11_1007-34; AV11_1007-35; AV11_1007-36; AV11_1007-37; AV11_1007-38; AV11_1007-39; AV11_1007-4; AV11_1007-40; AV11_1007-41; AV11_1007-42; AV11_1007-43; AV11_1007-44; AV11_1007-45; AV11_1007-46; AV11_1007-47; AV11_1007-48; AV11_1007-49; AV11_1007-5; AV11_1007-50; AV11_1007-51; AV11_1007-52; AV11_1007-53; AV11_1007-54; AV11_1007-55; AV11_1007-56; AV11_1007-57; AV11_1007-58; AV11_1007-59; AV11_1007-6; AV11_1007-60; AV11_1007-61; AV11_1007-62; AV11_1007-63; AV11_1007-7; AV11_1007-8; AV11_1007-9; AV11_1008-1; AV11_1010-1; AV11_1010-2; AV11_1011-1; AV11_1011-2; AV11_1012-1; AV11_1013-1; AV11_1013-2; AV11_1014-1; AV11_1014-2; AV11_1015-1; AV11_1015-2; AV11_1016-1; AV11_1016-2; AV11_1017-1; AV11_1017-2; AV11_1018-1; AV11_1018-2; AV11_1019-1; AV11_1019-2; AV11_1021-2; AV11_1022-2; AV11_1023-2; AV11_1024-2; AV11_1025-2; AV11_1026-2; AV11_1027-2; AV11_1028-2; AV11_1029-2; AV11_1030-2; AV11_1032-2; AV11_1033-2; AV11_1034-2; AV11_1035-2; AV11_1036-2; AV11_1037-2; AV11_1038-2; AV11_1039-2; AV11_1040-2; AV11_1041-2; AV11_1042-2; AV11_1043-2; AV11_1044-2; AV11_1045-2; AV11_1046-2; AV11_1051-1; AV11_1051-10; AV11_1051-11; AV11_1051-12; AV11_1051-13; AV11_1051-14; AV11_1051-15; AV11_1051-16; AV11_1051-17; AV11_1051-18;
    Type: Dataset
    Format: application/zip, 752 datasets
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    DATA PANGAEA
  • 3
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    An update to the Surface Ocean CO2 Atlas (SOCAT version 2) (2014)
    Copernicus
    In:  EPIC3Earth System Science Data, Copernicus, 6(1), pp. 69-90, ISSN: 1866-3516
    Details
    Publication Date: 2015-03-19
    Description: The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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    PAPER (OA)
  • 4
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    Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE) (2008)
    Copernicus
    Details
    Publication Date: 2008-02-08
    Description: This paper presents extensive validation analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. The ACE satellite instruments operate in the mid-infrared and ultraviolet-visible-near-infrared spectral regions using the solar occultation technique. In order to continue the long-standing record of solar occultation measurements from space, a detailed quality assessment is required to evaluate the ACE data and validate their use for scientific purposes. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the mean differences range generally between 0 and +10% with a slight but systematic positive bias (typically +5%). At higher altitudes (45–60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments by up to ~40% (typically +20%). For the ACE-MAESTRO version 1.2 ozone data product, agreement within ±10% (generally better than ±5%) is found between 18 and 40 km for the sunrise and sunset measurements. At higher altitudes (45–55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (by as much as −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS and indicate a large positive bias (+10 to +30%) in this altitude range. In contrast, there is no significant difference in bias found for the ACE-FTS sunrise and sunset measurements. These systematic effects in the ozone profiles retrieved from the measurements of ACE-FTS and ACE-MAESTRO are being investigated. This work shows that the ACE instruments provide reliable, high quality measurements from the tropopause to the upper stratosphere and can be used with confidence in this vertical domain.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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    PAPER CURRENT
  • 5
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    Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE) (2009)
    Copernicus
    Details
    Publication Date: 2009-01-16
    Description: This paper presents extensive {bias determination} analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45–60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (~35–55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45–55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
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    Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) experiment: design, execution and science overview (2013)
    Copernicus
    Details
    Publication Date: 2013-07-01
    Description: We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of air masses that contain the emission products from seasonal boreal wildfires and how these air masses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada, based out of Halifax, Nova Scotia. Atmospheric ground-based and sonde measurements over Canada and the Azores associated with the planned July 2010 deployment of the ARA, which was postponed by 12 months due to UK-based flights related to the dispersal of material emitted by the Eyjafjallajökull volcano, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 involved the same atmospheric measurements, but included the ARA, special satellite observations and a more comprehensive ground-based measurement suite. The high-frequency aircraft data provided a comprehensive chemical snapshot of pyrogenic plumes from wildfires, corresponding to photochemical (and physical) ages ranging from 〈 1 day to ~
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
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    Bedmap2: improved ice bed, surface and thickness datasets for Antarctica (2013)
    Copernicus
    Details
    Publication Date: 2013-02-28
    Description: We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved data-coverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10%. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets.
    Print ISSN: 1994-0416
    Electronic ISSN: 1994-0424
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
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    Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) experiment: design, execution and science overview (2013)
    Copernicus
    Details
    Publication Date: 2013-02-14
    Description: We describe the design and execution of the BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which has the overarching objective of understanding the chemical aging of airmasses that contain the emission products from seasonal boreal wildfires and how these airmasses subsequently impact downwind atmospheric composition. The central focus of the experiment was a two-week deployment of the UK BAe-146-301 Atmospheric Research Aircraft (ARA) over eastern Canada. The planned July 2010 deployment of the ARA was postponed by 12 months because of activities related to the dispersal of material emitted by the Eyjafjallajökull volcano. However, most other planned model and measurement activities, including ground-based measurements at the Dalhousie University Ground Station (DGS), enhanced ozonesonde launches, and measurements at the Pico Atmospheric Observatory in the Azores, went ahead and constituted phase A of the experiment. Phase B of BORTAS in July 2011 included the same measurements, but included the ARA, special satellite observations and a more comprehensive measurement suite at the DGS. The high-frequency aircraft data provided a comprehensive snapshot of the pyrogenic plumes from wildfires. The coordinated ground-based and sonde data provided detailed but spatially-limited information that put the aircraft data into context of the longer burning season. We coordinated aircraft vertical profiles and overpasses of the NASA Tropospheric Emission Spectrometer and the Canadian Atmospheric Chemistry Experiment. These space-borne data, while less precise than other data, helped to relate the two-week measurement campaign to larger geographical and longer temporal scales. We interpret these data using a range of chemistry models: from a near-explicit gas-phase chemical mechanism, which tests out understanding of the underlying chemical mechanism, to regional and global 3-D models of atmospheric transport and lumped chemistry, which helps to assess the performance of the simplified chemical mechanism and effectively act as intermediaries between different measurement types. We also present an overview of some of the new science that has originated from this project from the mission planning and execution to the analysis of the ground-based, aircraft, and space-borne data.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
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    Alkenone production along the California Margin
    PANGAEA
    In:  Supplement to: Herbert, Timothy D; Schuffert, Jeffrey D; Thomas, D; Lange, Carina Beatriz; Weinheimer, Amy L; Peleo-Alampay, Alyssa; Herguera, Juan-Carlos (1998): Depth and seasonality of alkenone production along the California Margin inferred from a core top transect. Paleoceanography, 13(3), 263-271, https://doi.org/10.1029/98PA00069
    Details
    Publication Date: 2023-05-12
    Description: Alkenone unsaturation indices (Uk'37) of marine sediment could prove particularly useful on organic-rich continental margins where carbonate dissolution hampers the use of other paleoclimatic proxies [McCaffrey et al., 1990, doi:10.1016/0016-7037(90)90399-6; Kennedy and Brassell, 1992, doi:10.1016/0146-6380(92)90040-5]. Forty core top samples of Recent sediment from a latitudinal transect (23°-40°N) along the California margin yield Uk'37 values that correlate linearly with modern mean annual sea surface temperatures (SSTs) in the range of 12°-23°C. Reproducibility of the unsaturation value in closely spaced cores is near analytical error. Uk'37 data define a relationship to temperature nearly identical to the Prahl et al. [1988, doi:10.1016/0016-7037(88)90132-9] laboratory cultures of Emiliania huxleyi. The close agreement is particularly significant in light of the nannofossil composition of the sediments, where the abundance of the coccolith taxon Gephyrocapsa oceanica (known to synthesize alkenones) equals or exceeds that of E. huxleyi. Comparison with seasonal temperature variations at different depths indicates that little if any alkenone production occurs at depths 〉30 m along the continental margin (water depths 〈2 km). Sediments in more pelagic locations exhibit small but consistent biases toward winter and/or subsurface production similar to previously reported sediment trap and core top data from the Oregon margin [Prahl et al., 1993, doi:10.1016/0967-0637(93)90045-5; Doose et al., 1997, doi:10.1029/97PA00821].
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 10
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    Measurements of Urban, Marine and Biogenic Air (MUMBA): characterisation of trace gases and aerosol at the urban, marine and biogenic interface in summer in Wollongong, Australia (2017)
    PANGAEA
    In:  Supplement to: Paton-Walsh, Clare; Guérette, Elise-Andrée; Kubistin, Dagmar; Humphries, Ruhi S; Wilson, Stephen R; Dominick, Doreena; Galbally, Ian; Buchholz, Rebecca R; Bhujel, Mahendra; Chambers, Scott D; Cheng, Min; Cope, Martin; Davy, Perry; Emmerson, Kathryn M; Griffith, David W T; Griffiths, Alan D; Keywood, Melita D; Lawson, Sarah; Molloy, Suzie; Rea, Geraldine; Selleck, Paul; Shi, Xue; Simmons, Jack B; Velazco, Voltaire (2017): The MUMBA Campaign: Measurements of Urban, Marine and Biogenic Air. Earth System Science Data, 9(1), 349-362, https://doi.org/10.5194/essd-9-349-2017
    Details
    Publication Date: 2023-01-13
    Description: The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia), from 21st December 2012 to 15th February 2013. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean/forest/urban interface that could be used to test the skill of atmospheric models. Gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. Aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts; mass concentration of PM2.5, number concentration size distribution, aerosol chemical analyses and elemental analysis. Meteorological measurements and LIDAR measurements were also performed. The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of background concentrations of these trace gases within this poorly sampled region of the globe. Here we present the observations recorded at the MUMBA site during the campaign, as well as radon and air quality data from nearby sites. These records can be used for testing chemical transport models.
    Type: Dataset
    Format: application/zip, 17 datasets
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