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  • PANGAEA
  • 2010-2014  (2,711)
Collection
Keywords
Publisher
Years
Year
  • 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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    Aircraft and satellite derived arctic BrO profiles of the tropospheric column (2012)
    PANGAEA
    In:  Supplement to: Choi, Su-Jin; Wang, Yujie; Salawitch, Ross J; Canty, T; Joiner, J; Zeng, T; Kurosu, T P; Chance, K; Richter, Astrid; Huey, L G; Liao, Jingjuan; Neuman, J A; Nowak, J B; Dibb, J E; Weinheimer, A J; Diskin, G S; Ryerson, T B; da Silva, A; Curry, J; Kinnison, D; Tilmes, S; Levelt, P F (2012): Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC. Atmospheric Chemistry and Physics, 12(3), 1255-1285, https://doi.org/10.5194/acp-12-1255-2012
    Details
    Publication Date: 2023-12-13
    Description: We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations of BrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL). Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo 〉0.7), for solar zenith angle 〈80° and clear sky conditions. The rapid activation of BrO due to surface processes (the bromine explosion) is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.
    Keywords: Barrow_Utqiagvik; Barrow, Alaska, USA; International Polar Year (2007-2008); IPY; MULT; Multiple investigations; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; SPP1158
    Type: Dataset
    Format: application/zip, 4 datasets
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 3
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    Surface Ocean CO2 Atlas (SOCAT) V1.4 (2013)
    PANGAEA
    In:  Supplement to: Pfeil, Benjamin; Olsen, Are; Bakker, Dorothee C E; Hankin, Steven; Koyuk, Heather; Kozyr, Alexander; Malczyk, Jeremy; Manke, Ansley; Metzl, Nicolas; Sabine, Christopher L; Akl, John; Alin, Simone R; Bellerby, Richard G J; Borges, Alberto Vieira; Boutin, Jacqueline; Brown, Peter J; Cai, Wei-Jun; Chavez, Francisco P; Chen, Arthur; Cosca, Catherine E; Fassbender, Andrea J; Feely, Richard A; González-Dávila, Melchor; Goyet, Catherine; Hardman-Mountford, Nicolas J; Heinze, Christoph; Hood, E Maria; Hoppema, Mario; Hunt, Christopher W; Hydes, David; Ishii, Masao; Johannessen, Truls; Jones, Steve D; Key, Robert M; Körtzinger, Arne; Landschützer, Peter; Lauvset, Siv K; Lefèvre, Nathalie; Lenton, Andrew; Lourantou, Anna; Merlivat, Liliane; Midorikawa, Takashi; Mintrop, Ludger J; Miyazaki, Chihiro; Murata, Akihiko; Nakadate, Akira; Nakano, Yoshiyuki; Nakaoka, Shin-Ichiro; Nojiri, Yukihiro; Omar, Abdirahman M; Padín, Xose Antonio; Park, Geun-Ha; Paterson, Kristina; Pérez, Fiz F; Pierrot, Denis; Poisson, Alain; Ríos, Aida F; Santana-Casiano, Juana Magdalena; Salisbury, Joe; Sarma, Vedula V S S; Schlitzer, Reiner; Schneider, Bernd; Schuster, Ute; Sieger, Rainer; Skjelvan, Ingunn; Steinhoff, Tobias; Suzuki, Toru; Takahashi, Taro; Tedesco, Kathy; Telszewski, Maciej; Thomas, Helmuth; Tilbrook, Bronte; Tjiputra, Jerry; Vandemark, Doug; Veness, Tony; Wanninkhof, Rik; Watson, Andrew J; Weiss, Ray F; Wong, Chi Shing; Yoshikawa-Inoue, Hisayuki (2013): A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT). Earth System Science Data, 5(1), 125-143, https://doi.org/10.5194/essd-5-125-2013
    Details
    Publication Date: 2024-02-02
    Description: A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968-2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.
    Keywords: 0306SFC_PRT; 061ASFC_PRT; 06AQ19860627-track; 06AQ19860928-track; 06AQ19911114-track; 06AQ19911210-track; 06AQ19921005-track; 06AQ19930128-track; 06AQ19930228-track; 06AQ19931019-track; 06AQ19940524-track; 06AQ19951206-track; 06AQ19960320-track; 06AQ19980411-track; 06AQ19990327-track; 06AQ20001004-track; 06AQ20001026-track; 06BE19961010-track; 06CK20060523-track; 06CK20060715-track; 06CK20060821-track; 06GA19960613-track; 06GA276_3; 06LB19831130-track; 06LB19840107-track; 06LB19840629-track; 06LB19850110-track; 06LB19850313-track; 06LB19850812-track; 06LB19860116-track; 06LB19860323-track; 06LB19860801-track; 06LB19861011-track; 06LB19861214-track; 06LB19870221-track; 06LB19870501-track; 06LB19870721-track; 06LB19870920-track; 06LB19871126-track; 06LB19871231-track; 06LB19880204-track; 06MT18_1; 06MT19910903-track; 06MT19920510-track; 06MT19921229-track; 06MT19941012-track; 06MT19941119-track; 06MT19950714-track; 06MT19960607-track; 06MT19960622-track; 06MT19970106-track; 06MT19970516-track; 06MT19970707-track; 06MT19970814-track; 06MT19981228-track; 06MT20021015-track; 06MT20060714; 06MT20060714-track; 06MT22_5; 06MT30_2; 06MT30_3; 06MT37_2; 06MT39_4; 06MT39_5; 06P119910616-track; 06P119950901-track; 06PO20050321; 06PO20050322-track; 07AL19951011-track; 07AL19960218-track; 07AL19970503-track; 07AL19990718-track; 07AL19991101-track; 07AL19991129-track; 07AL20000113-track; 07AL20000210-track; 07AL20000305-track; 07AL20010513-track; 07AL20010607-track; 07AL20010709-track; 07AL20010802-track; 09AR0103; 09AR19910926-track; 09AR19921019-track; 09AR19930105-track; 09AR19930311-track; 09AR19930807-track; 09AR19931119-track; 09AR19940101-track; 09AR19940831-track; 09AR19941213-track; 09AR19950717-track; 09AR19950916-track; 09AR19960119-track; 09AR19960822-track; 09AR19970910-track; 09AR19971114-track; 09AR19980228-track; 09AR19980404-track; 09AR19980715-track; 09AR19990716-track; 09AR20011031-track; 09AR9401; 09AR9404; 09AR9407; 09AR9501; 09AR9502; 09AR9601; 09AR9604; 09AR9701; 09AR9703; 09AR9707; 09AR9801; 09AR9806; 09AR9901; 09FA20000927-track; 09SS19951116-track; 09SS19990205-track; 11BE19940413-track; 11BE19950303-track; 11BE19950912-track; 11BE19970513-track; 11BE19970527-track; 11BE19970609-track; 11BE19970618-track; 11BE19970621; 11BE19970621-track; 11BE19970702-track; 11BE19980107-track; 11BE19980614-track; 11BE19980625-track; 11BE19980710-track; 11BE19990830-track; 11BE19990904-track; 11BE19990914-track; 11BE19990918-track; 11BE20010502-track; 11BE20010514-track; 11BE20010522-track; 11BE20020422-track; 11BE20020511-track; 11BE20020528-track; 11BE20021104-track; 11BE20030331-track; 11BE20030901; 11BE20030901-track; 11BE20031027; 11BE20031027-track; 11BE20031208; 11BE20031208-track; 11BE20040223; 11BE20040223-track; 11BE20040329; 11BE20040329-track; 11BE20040524; 11BE20040524-track; 11BE20040601-track; 11BE20041004; 11BE20041004-track; 11BE20060425; 11BE20060425-track; 11BE20060529-track; 11BE20070507-track; 18QA19730812-track; 18QA19731028-track; 18QA19760111-track; 18QA19760619-track; 18QA19760911-track; 18QA19761204-track; 18VC19740105-track; 18VC19740216-track; 18VC19741113-track; 18VC19750622-track; 18VC19750913-track; 1995-10-BS; 1996-02-BS; 1997-05-BS; 1999-07-BS; 1999-11-BS; 1999-12-BS; 2000-01-BS; 2000-02-BS; 2000-03-BS; 2001-05-BS; 2001-06-BS; 2001-07-BS; 2001-08-BS; 2003-06-BS; 2003-07-BS; 2003-08-BS; 2003-09-BS; 2003-10-BS; 2004-02-BS; 2004-03-BS; 2004-04-BS; 2004-05-BS; 2004-06-BS; 2004-07-BS; 2004-08-BS; 2004-09-BS; 2004-10-BS; 2005-01-BS; 2005-02-BS; 2005-03-BS; 2005-04-BS; 2005-05-BS; 2005-06-BS; 2005-07-BS; 2005-08-BS; 2005-09-BS; 2005-10-BS; 2005-11-BS; 2005-12-BS; 2006-03-BS; 2006-04-BS; 2006-05-BS; 2006-06-BS; 2006-07-BS; 2006-08-BS; 2006-09-BS; 20070110_TC2; 20070117_TC2; 20070123_TC2; 20070130_TC2; 20070207_TC2; 20070219_TC2; 20070227_TC2; 20070305_TC2; 20070320_TC2; 20070327_TC2; 20070402_TC2; 20070409_TC2; 20070416_TC2; 20070423_TC2; 20070430_TC2; 20070508_TC2; 20070515_TC2; 20070521_TC2; 20070529_TC2; 20070604_TC2; 20070613_TC2; 20070620_TC2; 20070627_TC2; 20070703_TC2; 20070709_TC2; 20070716_TC2; 20070723_TC2; 20070730_TC2; 2007-07-BS; 20070806_TC2; 20070815_TC2; 20070820_TC2; 20070827_TC2; 2007-08-BS; 20070903_TC2; 20070910_TC2; 20070917_TC2; 20071001_TC2; 20071008_TC2; 20071010_TC2; 20071015_TC2; 20071023_TC2; 20071105_TC2; 20071115_TC2; 20071120_TC2; 20071128_TC2; 20071204_TC2; 20071211_TC2; 20071218_TC2; 20071225_TC2; 24N98L1; 24N98L2; 26GC20010421-track; 26GC20010831-track; 26NA20050107; 26NA20050107-track; 26NA20050115; 26NA20050115-track; 26NA20050130; 26NA20050130-track; 26NA20050207; 26NA20050207-track; 26NA20050317; 26NA20050317-track; 26NA20050321; 26NA20050321-track; 26NA20050402; 26NA20050402-track; 26NA20050420; 26NA20050420-track; 26NA20050502; 26NA20050502-track; 26NA20050511; 26NA20050511-track; 26NA20050523; 26NA20050523-track; 26NA20050531; 26NA20050531-track; 26NA20050614; 26NA20050614-track; 26NA20050624; 26NA20050624-track; 26NA20050714; 26NA20050714-track; 26NA20050720; 26NA20050720-track; 26NA20050730; 26NA20050730-track; 26NA20050805; 26NA20050805-track; 26NA20050815; 26NA20050815-track; 26NA20050824; 26NA20050824-track; 26NA20050914; 26NA20050914-track; 26NA20050927; 26NA20050927-track; 26NA20051005; 26NA20051005-track; 26NA20051018; 26NA20051018-track; 26NA20051026; 26NA20051026-track; 26NA20051110; 26NA20051110-track; 26NA20051117; 26NA20051117-track; 26NA20051130; 26NA20051130-track; 26NA20060518; 26NA20060518-track; 26NA20060527; 26NA20060527-track; 26NA20060607; 26NA20060607-track; 26NA20060617; 26NA20060617-track; 26NA20060628; 26NA20060628-track; 26NA20060708; 26NA20060708-track; 26NA20060719; 26NA20060719-track; 26NA20060728; 26NA20060728-track; 26NA20060809; 26NA20060809-track; 26NA20060818; 26NA20060818-track; 26NA20060830; 26NA20060830-track; 26NA20060908; 26NA20060908-track; 26NA20060920; 26NA20060920-track; 26NA20061011; 26NA20061011-track; 26NA20061021; 26NA20061021-track; 26NA20061128; 26NA20061128-track; 26NA20061202; 26NA20061202-track; 26NA20061214; 26NA20061214-track; 26NA20061225; 26NA20061225-track; 26NA20070103; 26NA20070103-track; 26NA20070112; 26NA20070112-track; 26NA20070125; 26NA20070125-track; 26NA20070205; 26NA20070205-track; 26NA20070216; 26NA20070216-track; 26NA20070323; 26NA20070323-track; 26NA20070329; 26NA20070329-track; 26NA20070410; 26NA20070410-track; 26NA20070418; 26NA20070418-track; 26NA20070427; 26NA20070427-track; 26NA20070509; 26NA20070509-track; 26NA20070518; 26NA20070518-track; 26NA20070530; 26NA20070530-track; 26NA20070610; 26NA20070610-track; 26NA20070622; 26NA20070622-track; 26NA20070701; 26NA20070701-track; 26NA20070712; 26NA20070712-track; 26NA20070721; 26NA20070721-track; 26NA20070802; 26NA20070802-track; 26NA20070811; 26NA20070811-track; 26NA20070901; 26NA20070901-track; 26NA20070912; 26NA20070912-track; 26NA20070923; 26NA20070923-track; 26NA20071003; 26NA20071003-track; 26NA20071014; 26NA20071014-track; 26NA20071024; 26NA20071024-track; 26NA20071103; 26NA20071103-track; 26NA20071114; 26NA20071114-track; 26NA20071124; 26NA20071124-track; 29HE050; 29HE19980729-track; 29HE20001028; 29HE20001028-track; 29HE20010306; 29HE20010306-track; 29HE20011027; 29HE20011027-track; 29HE20020305; 29HE20020305-track; 29HE20021028; 29HE20021028-track; 29HE20030409; 29HE20030409-track; 29HE20041021; 29HE20041021-track; 316N0154; 316N19810401-track; 316N19810416-track; 316N19810516-track; 316N19810619-track; 316N19810721-track; 316N19810821-track; 316N19810923-track; 316N19821202-track; 316N19821230-track; 316N19830130-track; 316N19831007-track; 316N19840111-track; 316N19871030-track; 316N19871123-track; 316N19871218-track; 316N19880128-track; 316N19940404-track; 316N19941201-track; 316N19950124-track; 316N19950310-track; 316N19950423-track; 316N19950611-track; 316N19950715-track; 316N19950829-track; 316N19951111-track; 316N19951205-track; 316N19961102-track; 316N19971005-track; 318M19780921-track; 318M19780928-track; 318M19790210-track; 318M19790308-track;
    Type: Dataset
    Format: application/zip, 1851 datasets
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  • 4
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    Abundance and calculated biomass of large-scale distribution from Atlantic nitrogen fixation controlled by iron availability (2013)
    PANGAEA
    Details
    Publication Date: 2023-07-08
    Keywords: AMT17/03; AMT17/04; AMT17/05; AMT17/06; AMT17/08; AMT17/10; Atlantic; Calculated after Luo et al. (2012); DEPTH, water; Diazotrophs, total biomass as carbon; Event label; Iron; Latitude of event; Light microscope; Longitude of event; MAREDAT_Diazotrophs_Collection; Nitrate; Phosphate; Salinity; Temperature, water; Trichodesmium, biomass as carbon; Trichodesmium, carbon per trichome; Trichodesmium abundance, free trichomes; Trichodesmium abundance, total
    Type: Dataset
    Format: text/tab-separated-values, 55 data points
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  • 5
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    Nitrogen fixation rate of large-scale distribution from Atlantic nitrogen fixation controlled by iron availability (2013)
    PANGAEA
    Details
    Publication Date: 2023-07-08
    Keywords: AMT17/01; AMT17/02; AMT17/03; AMT17/04; AMT17/05; AMT17/06; AMT17/07; AMT17/08; AMT17/09; AMT17/10; Atlantic; Calculated after Luo et al. (2012); Date/Time of event; DEPTH, water; Event label; Iron; Latitude of event; Longitude of event; MAREDAT_Diazotrophs_Collection; Nitrate; Nitrogen Fixation (C2H2 Reduction); Nitrogen fixation rate, total; Nitrogen fixation rate, whole seawater; Phosphate; Salinity; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 275 data points
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  • 6
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    Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2012)
    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Details
    Publication Date: 2023-03-27
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths.
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 1.7 MBytes
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  • 7
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    The MAREDAT global database of high performance liquid chromatography marine pigment measurements - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    Details
    Publication Date: 2023-03-27
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 8.5 MBytes
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  • 8
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    (Table 2) Surface water properties of sampling sites in the Amundsen Sea (2012)
    PANGAEA
    Details
    Publication Date: 2023-12-12
    Keywords: Amundsen Sea; Area/locality; Density, sigma, in situ; Density, standard deviation; Depth, bottom/max; Depth, relative; Depth, top/min; DEPTH, water; Depth of the euphotic zone; DynaLiFe; Light attenuation coefficient; Mixed layer depth; Nathaniel B. Palmer; NBP0901; NBP0901_var; Radiation, photosynthetically active, standard deviation; Radiation, photosynthetically active per day; Salinity, standard deviation; Sample amount; Sea surface salinity, summer; Sea surface temperature, standard deviation; Sea surface temperature, summer; Standard deviation; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 100 data points
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  • 9
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    (Table 4) Phytoplankton community composition of surface waters in the Amundsen Sea (2012)
    PANGAEA
    Details
    Publication Date: 2023-12-12
    Keywords: Amundsen Sea; Area/locality; Cryptophyta; Depth, bottom/max; Depth, top/min; DEPTH, water; Diatoms; DynaLiFe; Green algae; Maximum photochemical quantum yield of photosystem II; Maximum photochemical quantum yield of photosystem II, standard deviation; Nathaniel B. Palmer; NBP0901; NBP0901_var; Phaeocystis antarctica; Phaeocystis spp.; Sample amount; Standard deviation; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 80 data points
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  • 10
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    (Table 5) Phytoplankton photosynthesis characteristics in surface waters of the Amundsen Sea (2012)
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    Publication Date: 2023-12-12
    Keywords: Amundsen Sea; Area/locality; Assimilation rate of carbon per chlorophyll a; Depth, bottom/max; Depth, top/min; DEPTH, water; DynaLiFe; Nathaniel B. Palmer; NBP0901; NBP0901_var; Quantum yield; Quantum yield, standard deviation; Sample amount; Saturation light intensity; Slope; Standard deviation; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 42 data points
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