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  • 2000-2004  (50)
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  • 1
    Publication Date: 2023-02-24
    Keywords: WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/html, 7 kBytes
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  • 2
    Publication Date: 2024-02-29
    Keywords: A150/180; A152-84; A153-154; A157-3; A164-13; A164-15; A164-16; A164-17; A164-23; A167-12; A167-13; A167-18TW; A167-1TW; A179-13; A179-15; A179-20; A179-24; A179-6; A179-7; A180-13; A180-15; A180-20; A180-39; A180-69; A180-70; A180-72; A180-76; A180-78; A181/185; A181-7; A181-9; A260210A; Atlantic; Atlantic Ocean; AWI_Paleo; Barcelona Coast; Calculated; Calculated, see reference(s); Chlorophyll total; CIRCE; CIRCE-239; CLIMAP; Climate: Long-Range Investigation, Mapping, and Prediction; Cork Harbour; Danube Delta; Danube Delta Coast; DEPTH, water; Event label; FFC; Free fall corer; Grab; GRAB; Guadiana Estuary; Gulf of Riga; Himmerfjarden; Indian Ocean; KM1-41; LATITUDE; Limfjorden; LONGITUDE; Melville; Oder Estuary; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; PC; Pertuis Charentais; Piston corer; RC08; RC08-16; RC08-18; RC08-22; RC08-23; RC08-27; RC08-28; RC09; RC09-212; RC09-222; RC09-225; RC09-61; RC10; RC10-22; RC10-49; RC11; RC11-10; RC11-11; RC1112; RC11-12; RC11-13; RC11-14; RC11-15; RC11-16; RC11-21; RC11-22; RC11-255; RC11-26; RC11-260; RC11-35; RC11-37; RC11-78; RC11-79; RC11-80; RC11-86; RC11-9; RC12; RC12-233; RC12-235; RC12-241; RC12-266; RC12-268; RC12-291; RC12-292; RC12-293; RC12-294; RC12-297; RC12-298; RC12-299; RC12-300; RC12-303; RC12-304; RC13; RC13-158; RC13-189; RC13-190; RC13-195; RC13-196; RC13-197; RC13-199; RC13-209; RC13-210; RC13-229; RC13-242; RC13-253; RC13-275; RC15; RC15-115; RC15-143; RC15-145; RC15-151; RC15-91; RC15-93; RC15-94; RE009-7; Robert Conrad; Scheldt Delta Estuary; Sea surface temperature, annual mean; Sea surface temperature, production weighted; Sea surface temperature, seasonal, delta; Sea surface temperature, spring; SFB261; South Atlantic in Late Quaternary: Reconstruction of Budget and Currents; South Atlantic Ocean; SP009-003; SP010-005; Taranto Mare Piccolo; TC; Thau Lagoon; Thermaikos Gulf; Trigger corer; V02; V02-9; V03; V03-128; V04; V04-12; V04-32; V04-8; V05; V05-1; V05-31; V05-40; V06; V06-5; V07; V07-13; V07-42; V07-53; V07-67; V07-68; V09; V09-31; V10; V10-88; V10-89; V12; V12-122; V12-18; V12-4; V12-43; V12-53; V12-56; V12-66; V12-7; V12-79; V12-80; V14; V14-4; V14-47; V14-5; V14-7; V15; V15-136; V15-137; V15-164; V15-206; V16; V16-189; V16-190; V16-20; V16-200; V16-205; V16-206; V16-209; V16-21; V16-227; V16-23; V16-31; V16-33; V16-35; V16-36; V16-37; V16-39; V16-41; V16-50; V17; V17-1; V17-144; V17-147; V17-158; V17-162; V17-163; V17-164; V17-165; V17-192; V17-196; V18; V18-110; V18-117; V18-126; V18-16; V18-168; V18-182; V18-21; V18-34; V18-373; V19; V19-240; V19-242; V19-245; V19-246; V19-248; V19-262; V19-283; V19-296; V19-298; V19-308; V20; V20-213; V20-227; V20-228; V20-230; V20-233; V20-234; V20-235; V20-242; V20-253; V20-7; V22; V22-106; V22-107; V22-122; V22-168; V22-169; V22-172; V22-175; V22-177; V22-179; V22-180; V22-182; V22-188; V22-202; V22-204; V22-211; V22-219; V22-232; V22-24; V22-26; V22-36; V22-38; V22-71; V22-92; V22-93; V22-94; V23; V23-101; V23-105; V23-107; V23-13; V23-22; V23-29; V23-38; V23-60; V23-81; V23-82; V23-83; V23-84; V23-96; V24; V24-220; V24-221; V24-223; V24-229; V24-235; V24-237; V24-241; V24-8; V25; V25-24; V25-46; V26; V26-100; V26-165; V26-31; V26-50; V26-51; V26-52; V26-53; V26-55; V26-63; V26-68; V27; V27-10; V27-104; V27-114; V27-122; V27-126; V27-136; V27-137; V27-143; V27-144; V27-15; V27-16; V27-162; V27-164; V27-167; V27-172; V27-175; V27-178; V27-181; V27-184; V27-188; V27-190; V27-191; V27-192; V27-20; V27-206; V27-21; V27-215; V27-227; V27-228; V27-23; V27-233; V27-234; V27-239; V27-24; V27-248; V27-25; V27-250; V27-254; V27-266; V27-28; V27-30; V27-32; V27-33; V27-38; V27-7; V28; V28-124; V28-25; V28-28; V28-29; V28-30; V28-34; V28-36; V28-41; V28-55; V28-65; V28-66; V28-7; V28-82; V28-83; V28-89; V28-90; V28-98; V29; V29-134; V29-135; V29-144; V29-167; V29-170; V29-176; V29-177; V29-178; V29-179; V29-180; V29-183; V29-184; V29-189; V29-190; V29-193; V29-194; V29-198; V29-200; V29-202; V29-203; V29-204; V29-205; V29-209; V29-210; V29-211; V29-214; V29-215; V29-220; V29-222; V29-223; V29-93; V30; V30-49; V30-52; V30-54; V30-56; V30-58; V30-59; V30-61; V30-62; V30-64; V30-65; V30-67; V30-68; Vema
    Type: Dataset
    Format: text/tab-separated-values, 1780 data points
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  • 3
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    In:  EPIC3Eos Trans. AGU, 81(5), 45 p.
    Publication Date: 2019-07-16
    Description: As part of the World Climate Research Programme, the World OceanCirculation Experiment (WOCE) has produced during the last decade aglobal set of hydrographic, nutrient and tracer data that is ofunprecedented quality and quantity. Large parts of this dataset arenow publicly available and are being used for general oceanographicresearch and climate studies. However, wide-spread use of thecombined WOCE dataset is hampered by the fact that the data residein many separate data files and by the complexity of the fileformat.In an effort to facilitate the use of the global WOCE dataset, allcurrently released data of the WOCE Hydrographic Programme (WHP)have been compiled into an integrated dataset. Together with theOcean Data View visualization software for Windows, thisdataset constitutes an ``Electronic Atlas of WOCE Data''(eWOCE) that allows the graphical display and interactive analysisof the data in many different ways. Because of extensiveinteractive controls like, for instance, user-defined plotconfiguration, zooming, auto-scaling, color adjustment andstation/sample selection, this electronic atlas complements and goesbeyond the printed atlases that are being prepared now.More than 200 property distributions along WHP sections are providedwith eWOCE. Starting from these template plots, users can easilyproduce (1) arbitrary property/property plots, (2) distributions ongeneral iso-surfaces, (3) property difference distributions betweenrepeats, (4) time-series plots, (5) geostrophic velocity sectionsand many other plot types. With eWOCE, the data can either bepresented as color-shaded and/or contoured fields or as coloredsymbols or numbers at the measurement locations. In addition to themeasured, basic variables, a large number of derived quantities canbe calculated and analyzed just as the basic variables. The WOCEdata collection can be extended easily: data from the WorldOcean Atlas 1994, the World Ocean Database 1998 and otherpopular data formats can be imported without modification. Asadd-ons, eWOCE comes with a gazetteer of WOCE sections andwith the GEBCO (General Bathymetric Chart of the Oceans) gazetteerof undersea features which allow easy identification of sections andtopographic features. In addition to research applications,eWOCE can be useful for teaching and training.For more information on eWOCE visit the Web page http://www.awi-bremerhaven.de/GEO/eWOCE.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 4
    Publication Date: 2019-07-16
    Description: The usage of dissolved nutrients and carbon for photosynthesis in the euphotic zone and the subsequent downward transport of particulate and dissolved organic material strongly affect the carbon concentrations in surface water and thus the air-sea exchange of CO2. Efforts to quantify the downward carbon flux for the whole ocean or on basin-scales are hampered by the sparseness of direct productivity or flux measurements. Here, a global ocean circulation, biogeochemical model is used to determine rates of export production and vertical carbon fluxes in the Southern Ocean. The model exploits the existing large sets of hydrographic, oxygen, nutrient and carbon data, that contain information on the underlying biogeochemical processes. The model is fitted to the data by systematically varying circulation, air-sea fluxes, production and remineralization rates simultaneously. Use of the adjoint method yields model property simulations that are in very good agreement with measurements.In the model, the total integrated export flux of particulate organic matter (POC) necessary for the realistic reproduction of nutrient data is significantly larger than export estimates derived from primary productivity maps. Of the about 10,000~\TgC\ (10~\GtC )required globally, the Southern Ocean south of 30\degree S contributes about 3000~\TgC\ (33\%), most of which is occurring in a zonal belt along the Antarctic Circumpolar Current and in the Peru, Chile and Namibia coastal upwelling regions. The export flux of POC for the area south of 50\degree S amounts to 1100$\pm$200~\TgC\ and the particle flux in 1000~m for the same area is 120$\pm$20~\TgC . Unlike for the global ocean, the contribution of the downward flux of dissolved organic carbon (DOC) is significant in the Southern Ocean. Comparison with satellite based productivity estimates (CZCS and SeaWiFS) show a relatively good agreement over most of the ocean except for the Southern Ocean, where the model fluxes are systematically higher than the satellite based values by factors between two and five. This discrepancy is significant, and an attempt to reconcile the low satellite-derived productivity values with ocean-interior nutrient budgets failed. Too low productivity estimates from satellite chlorophyll observations in the Southern Ocean could arise because of the inability of the satellite sensors to detect frequently occurring sub-surface chlorophyll patches, and to a poor calibration of the conversion algorithms in the Southern Ocean because of the very limited amount of direct measurements.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 5
    Publication Date: 2019-07-16
    Description: Biological production lowers the CO_2 concentrations in the surfacelayer of the ocean, and sinking detritus ``pumps'' nutrients andCO_2 into the deep ocean. Quantifying the efficiency of thebiological pump is a prerequisite for global CO_2 budgets. Sedimenttraps are commonly used to directly measure the vertical particleflux, however, for logistical and financial reasons traps cannotprovide area-wide data sets. Moreover, it has been shownthat sediment traps can under- or overestimate particle fluxes considerably.In this paper we present a new technique to estimate the downward fluxof particulate matter with an adjoint model. Hydrographic and nutrientdata are used to calculate the mean ocean circulation together withparameters for particle fluxes using the AWI Adjoint Model for OceanicCarbon Cycling (AAMOCC). The model is fitted to the propertyconcentrations by systematically varying circulation, air-sea fluxes,export production and remineralization rates of particulate biogenicmatter simultaneously.The deviations of model fluxes based on nutrient budgets from directmeasurements with sediment traps yield an independent estimate ofapparent trapping efficiencies. While consistent with hydrographicand nutrient data, model particle fluxes rarely agree with sedimenttrap data: (1) At shallow water depth (〈 1000m), sediment trapfluxes are at the average 50% lower than model fluxes, which confirmsflux calibrations using radionuclides; (2) in the very deep traps,model fluxes tend to be lower compared to data which might beexplained by lateral inputs into the traps. According to these modelresults, particle fluxes from the euphotic zone into mid water depthare considerably higher and the shallow loop of nutrient is morevigorous than would be derived fromsediment trap data.Our results imply that fluxes as collected with sediment traps areinconsistent with model derived long-term mean particle fluxes basedon nutrient budgets in the water column. In agreement with recentradionuclide studies we conclude that reliable export flux estimatescan only be obtained from sediment trap data if appropriatecorrections are applied.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 6
    Publication Date: 2019-07-16
    Description: The production and downward transport of particulate organic matter (POM) creates vertical nutrient and carbon gradients controlling the CO2 exchange between ocean and atmosphere. C:N:P element ratios of POM determine relative magnitudes of downward phosphorus, nitrogen and carbon fluxes. Despite observational evidence for variable element ratios, it is common practice to use the constant Redfield ratios for biogeochemical modeling, which might lead to an underestimation of downward carbon fluxes. To determine elemental ratios of POM and their impact on the marine carbon cycle, we assembled C/N data for particulate material from different sources into a single data collection for joint evaluation. The dataset contains 10200 C/N values, encompassing all major oceans and trophic levels. This dataset shows that C/N ratios are highly variable with values below the traditional Redfield ratio (C/N=6.6) to values greatly exceeding it. On a global mean, C/N ratios of marine sinking particles from the surface water amount to 7.1, and there is a systematic increase of C/N ratios with depth of 0.2 units per 1000 m. The discrepancy with results from dissolved nutrient fields (constant ratios close to Redfield's value) can be explained by implicit depth averaging caused by depth variations of the surfaces under consideration. Due to preferential remineralization of N, the C/N ratio of the dissolving component (seen on dissolved nutrient fields) is smaller than the C/N ratio of the remaining particles. For flux estimations, variable C/N ratios should be implemented in biogeochemical models to correctly represent relative strengths of carbon and nitrogen fluxes.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
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    In:  EPIC3Eiskalte Entdeckungen, Delius & Klasing Verlag
    Publication Date: 2014-04-15
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , peerRev
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  • 8
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    In:  EPIC3Greenhouse Gas Control Technologies, edited by D. Williams, B. Durie, P. McMullan, C. Paulson, and A. Smith, CSIRO, pp. 469-474
    Publication Date: 2019-07-16
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , peerRev
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  • 9
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    In:  EPIC3in: 'Siberian River Runoff in the Kara Sea: Characterisation, Quantification, Variability and Environmental Significance', Stein, Fahl, Fütterer, Galimov (Eds.), Elsevier, Proceedings in Marine Science, pp. 47-69
    Publication Date: 2019-07-16
    Description: The Kara Sea, due to its geographic location downstream of the main eastward Atlantic Water inflow through the Barents Sea, is strongly influenced by the history of the Atlantic Water masses which enter at its western entrances: the Kara Strait and the passage between Franz Josef Land and Novaya Semlya. Little is known about the interannual variability of temperature, salinity and volume fluxes through these entrances.The present investigation analyzes model results from 1979 to 1999 and compares them to hydrographic observations in the Barents and Kara seas with respect to the interannual variability of Atlantic Water flow through the western entrances of the Kara Sea. Model results and observations suggest the propagation of sequences of warm and cold anomalies through the area of investigation. Most prominent are anomalously cold years 1986, 1993 and 1998 for the Kara Strait throughflow which are associated with weak eastward or even westward flow over periods up to several months. For the passage between Franz Josef Land and Novaya Semlya, the entire period of the 1990s is characterized by warm deep water temperatures. In the early and late 1990s also the eastward volume fluxes are at their maximum. We discuss an Empirical Orthogonal Function analysis of the velocity in the Barents and Kara Seas. The warm and cold phases are associated with the first two modes of the velocity pattern in the domain. The links of these velocity patterns with the large scale sea level pressure are discussed.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 10
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    In:  EPIC3in: Wefer, G., Mulitza, S., Rathmeyer, V., (eds.), The South Atlantic in the Late Quaternary - Reconstruction of Material Budget and Current Systems, pp. 1-19, Springer-Verlag, Berlin
    Publication Date: 2019-07-16
    Description: The biological production of particulate material near the ocean surface and the subsequent remineralization during sinking and after deposition on the seafloor strongly affect the distributions of oxygen, dissolved nutrients and carbon in the ocean. Dissolved nutrient distributions therefore reveal the underlying biogeochemical processes, and these data can be used to determine production-, remineralization and accumulation rates using inverse techniques. Here, an ocean circulation, biogeochemical model that exploits the existing large sets of hydrographic, oxygen, nutrient and carbon data is presented and results for the export production of particulate organic matter, vertical fluxes in the water column and sedimentation rates are presented. In the model, the integrated export flux of particulate organic carbon (POC) for the South Atlantic amounts to about 1300 Tg C yr-1 (equivalent to 1.3 Gt C yr-1), most of which occurring in the Benguela/Namibia upwelling region and in a zonal band following the course of the Antarctic Circumpolar Current (ACC). Remineralization of POC in the upper water column is intense, and only about 7% of the export reaches a depth of 2000 m. Comparison of model particle fluxes with sediment trap data suggests that shallow traps tend to underestimate the downward flux, whereas the deep traps seem to be affected by lateral input of material and apparently overestimate the vertical flux. These findings are consistent with recent radionuclide studies. The rapid degradation of POC with depth leads to geographical patterns of POC fluxes to the seafloor and POC accumulation in the sediment that are very different from the pattern of surface productivity, because of modulation with varying bottom depth. Whereas there is significant surface production in deep-water, open-ocean regions, the benthic fluxes occur predominantly in coastal and shelf areas.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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