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  • 2015-2019  (16)
  • 2017  (16)
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  • 2015-2019  (16)
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  • 1
    Online Resource
    Online Resource
    Zirkulation und Dynamik in der Agulhasregion anhand eines numerischen Modells (2017)
    Kiel : Inst. für Meereskunde
    Details Availability
    Keywords: Report ; Dissertation ; Hochschulschrift
    Type of Medium: Online Resource
    Pages: Online-Ressource (121 Seiten, 23 MB) , Illustrationen, Diagramme, Karten
    Series Statement: Berichte aus dem Institut für Meereskunde an der Christian-Albrechts-Universität Kiel 301
    URL: https://oceanrep.geomar.de/792/
    URL: http://dx.doi.org/10.3289/ifm_ber_301
    DOI: 10.3289/ifm_ber_301
    Language: German
    Note: Zusammenfassung in deutscher und englischer Sprache
    Location Call Number Limitation Availability
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    GEOMAR CATALOGUE
    Link to Library Catalog
    get availability status
  • 2
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    Simulation of leatherback turtle hatchling dispersion patterns in the Gulf of Guinea (2017)
    PANGAEA
    In:  Supplement to: Scott, Rebecca; Biastoch, Arne; Agamboue, Pierre D; Bayer, Till; Boussamba, Francois L; Formia, Angela; Godley, Brendan J; Mabert, Brice D K; Manfoumbi, Jean C; Schwarzkopf, Franziska; Sounguet, Guy-Philippe; Wagner, Patrick; Witt, Matthew J (2017): Spatio-temporal variation in ocean current-driven hatchling dispersion: Implications for the world's largest leatherback sea turtle nesting region. Diversity and Distributions, https://doi.org/10.1111/ddi.12554
    Details
    Publication Date: 2023-10-28
    Description: This data set describes the location of virtual floats representing turtle hatchlings throughout 60 modeled years. Floats were constrained to remain within depths of 0-6 m due to the positive buoyancy of hatchlings. Floats were first assigned to one of 20,000 random release locations within a large release area 125-400 km offshore from nesting beaches throughout the Republic/Democratic Republic of the Congo, Gabon and Equatorial Guinea spanning latitudes of c. 6°S to 3.5°N. For each month over the 4-month long hatching season (January-April), each of the 20,000 floats was assigned a random release day and drift simulations ran every year during the period 1960-2007 resulting in drift trajectories of approx. 4 million virtual floats. See Scott et al., 2017, Spatio-temporal variation in ocean current-driven hatchling dispersion: Implications for the world's largest leatherback sea turtle nesting region. Diversity Distrib, http://dx.doi.org/10.1111%2Fddi.12554 for details as to the model parameters. Each data set consists of data on the float ID (number 1,2,3 etc..) and its trajectory attributes (latitude/longitude) at each time step. Data are also provided on the temperature, salinity and density of the float at its respective position/time step. Data sets are sorted by float release date, and contain one data file for each year. Each data file has 11 columns, which contain the following data: float id, longitude, latitude, depth, time step, temperature, salinity, density, no time steps since start, distance to start point, bearing from start point
    Keywords: Climate - Biogeochemistry Interactions in the Tropical Ocean; File content; File format; File name; File size; Model; Sea-turtle_model; SFB754; Uniform resource locator/link to model result file
    Type: Dataset
    Format: text/tab-separated-values, 60 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    Physical oceanography during Maria S. Merian cruise MSM38 (2017)
    PANGAEA
    Details
    Publication Date: 2024-02-27
    Keywords: 0; 1; 10; 100; 101; 102; 103; 104; 105; 106; 107; 108; 109; 11; 110; 111; 112; 113; 114; 115; 116; 117; 118; 119; 12; 120; 121; 122; 123; 124; 125; 126; 127; 128; 13; 14; 15; 16; 17; 18; 19; 2; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 3; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 4; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 5; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 6; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 7; 70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 8; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 9; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; Calculated; CTD, Sea-Bird SBE 911plus; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Latitude of event; Longitude of event; Maria S. Merian; MSM38; MSM38_343; MSM38_344; MSM38_345; MSM38_347; MSM38_348; MSM38_349; MSM38_350; MSM38_354; MSM38_355; MSM38_358; MSM38_359; MSM38_360; MSM38_361; MSM38_363; MSM38_364; MSM38_365; MSM38_366; MSM38_367; MSM38_368; MSM38_369; MSM38_370; MSM38_372; MSM38_373; MSM38_374; MSM38_375; MSM38_376; MSM38_377; MSM38_378; MSM38_379; MSM38_380; MSM38_381; MSM38_382; MSM38_383; MSM38_384; MSM38_385; MSM38_386; MSM38_387; MSM38_388; MSM38_389; MSM38_390; MSM38_391; MSM38_392; MSM38_393; MSM38_394; MSM38_395; MSM38_396; MSM38_397; MSM38_398; MSM38_399; MSM38_400; MSM38_401; MSM38_402; MSM38_403; MSM38_404; MSM38_405; MSM38_406; MSM38_407; MSM38_408; MSM38_409; MSM38_410; MSM38_411; MSM38_412; MSM38_413; MSM38_414; MSM38_415; MSM38_417; MSM38_418; MSM38_419; MSM38_420; MSM38_421; MSM38_422; MSM38_423; MSM38_424; MSM38_425; MSM38_426; MSM38_427; MSM38_428; MSM38_429; MSM38_430; MSM38_431; MSM38_432; MSM38_433; MSM38_434; MSM38_435; MSM38_436; MSM38_437; MSM38_438; MSM38_439; MSM38_440; MSM38_441; MSM38_442; MSM38_443; MSM38_444; MSM38_445; MSM38_446; MSM38_447; MSM38_448; MSM38_449; MSM38_450; MSM38_451; MSM38_452; MSM38_453; MSM38_454; MSM38_455; MSM38_456; MSM38_457; MSM38_458; MSM38_459; MSM38_460; MSM38_461; MSM38_462; MSM38_463; MSM38_464; MSM38_465; MSM38_466; MSM38_467; MSM38_468; MSM38_469; MSM38_470; MSM38_471; MSM38_472; MSM38_473; MSM38_474; MSM38_475; MSM38_476; MSM38_477; MSM38_478; MSM38_479; MSM38_480; Oxygen; Oxygen sensor, SBE 43; Pressure, water; Salinity; Temperature, water; Temperature, water, potential
    Type: Dataset
    Format: text/tab-separated-values, 2181198 data points
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    DATA PANGAEA
  • 4
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    Composition and variability of the Denmark Strait Overflow Water in a high-resolution numerical model hindcast simulation (2017)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Oceans, 122 (4). 2830-2846 .
    Details
    Publication Date: 2020-02-06
    Description: The upstream sources and pathways of the Denmark Strait Overflow Water and their variability have been investigated using a high-resolution model hindcast. This global simulation covers the period from 1948 to 2009 and uses a fine model mesh (1/20°) to resolve mesoscale features and the complex current structure north of Iceland explicitly. The three sources of the Denmark Strait Overflow, the shelfbreak East Greenland Current (EGC), the separated EGC, and the North Icelandic Jet, have been analyzed using Eulerian and Lagrangian diagnostics. The shelfbreak EGC contributes the largest fraction in terms of volume and freshwater transport to the Denmark Strait Overflow and is the main driver of the overflow variability. The North Icelandic Jet contributes the densest water to the Denmark Strait Overflow and shows only small temporal transport variations. During summer, the net volume and freshwater transports to the south are reduced. On interannual time scales, these transports are highly correlated with the large-scale wind stress curl around Iceland and, to some extent, influenced by the North Atlantic Oscillation, with enhanced southward transports during positive phases. The Lagrangian trajectories support the existence of a hypothesized overturning loop along the shelfbreak north of Iceland, where water carried by the North Icelandic Irminger Current is transformed and feeds the North Icelandic Jet. Monitoring these two currents and the region north of the Iceland shelfbreak could provide the potential to track long-term changes in the Denmark Strait Overflow and thus also the AMOC.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
    DOI: 10.1002/2016JC012158
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Biological and physical influences on marine snowfall at the equator (2017)
    Nature Research
    In:  Nature Geoscience, 10 (11). pp. 852-858.
    Details
    Publication Date: 2020-06-18
    Description: High primary productivity in the equatorial Atlantic and Pacific oceans is one of the key features of tropical ocean biogeochemistry and fuels a substantial flux of particulate matter towards the abyssal ocean. How biological processes and equatorial current dynamics shape the particle size distribution and flux, however, is poorly understood. Here we use high-resolution size-resolved particle imaging and Acoustic Doppler Current Profiler data to assess these influences in equatorial oceans. We find an increase in particle abundance and flux at depths of 300 to 600 m at the Atlantic and Pacific equator, a depth range to which zooplankton and nekton migrate vertically in a daily cycle. We attribute this particle maximum to faecal pellet production by these organisms. At depths of 1,000 to 4,000 m, we find that the particulate organic carbon flux is up to three times greater in the equatorial belt (1° S–1° N) than in off-equatorial regions. At 3,000 m, the flux is dominated by small particles less than 0.53 mm in diameter. The dominance of small particles seems to be caused by enhanced active and passive particle export in this region, as well as by the focusing of particles by deep eastward jets found at 2° N and 2° S. We thus suggest that zooplankton movements and ocean currents modulate the transfer of particulate carbon from the surface to the deep ocean.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Format: video
    Format: video
    Format: video
    Format: video
    Format: video
    DOI: 10.1038/ngeo3042
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    Lateral eddy diffusivity estimates from simulated and observed drifter trajectories - a case study for the Agulhas Current system (2017)
    In:  [Poster] In: EGU General Assembly 2017, 23.-28.04.2017, Vienna, Austria .
    Details
    Publication Date: 2019-09-23
    Type: Conference or Workshop Item , NonPeerReviewed
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    OceanRep: Poster
  • 7
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    Multidecadal Indian Ocean variability linked to the Pacific and implications for pre-conditioning Indian Ocean Dipole events (2017)
    AMS (American Meteorological Society)
    In:  Journal of Climate, 30 (5). pp. 1739-1751.
    Details
    Publication Date: 2020-02-06
    Description: The Indian Ocean has sustained robust surface warming in recent decades, but the role of multi-decadal variability remains unclear. Using ocean model hindcasts, characteristics of low-frequency Indian Ocean temperature variations are explored. Simulated upper-ocean temperature changes across the Indian Ocean in the hindcast are consistent with those recorded in observational products and ocean reanalyses. Indian Ocean temperatures exhibit strong warming trends since the 1950s limited to the surface and south of 30°S, while extensive subsurface cooling occurs over much of the tropical Indian Ocean. Previous work focused on diagnosing causes of these long-term trends in the Indian Ocean over the second half of the 20th Century. Instead, the temporal evolution of Indian Ocean subsurface heat content is shown here to reveal distinct multi-decadal variations associated with the Pacific Decadal Oscillation and the long-term trends are thus interpreted to result from aliasing of the low-frequency variability. Transmission of the multi-decadal signal occurs via an oceanic pathway through the Indonesian Throughflow and is manifest across the Indian Ocean centered along 12°S as westward propagating Rossby waves modulating thermocline and subsurface heat content variations. Resulting low-frequency changes in the eastern Indian Ocean thermocline depth are associated with decadal variations in the frequency of Indian Ocean Dipole (IOD) events, with positive IOD events unusually common in the 1960s and 1990s with a relatively shallow thermocline. In contrast, the deeper thermocline depth in the 1970s and 1980s is associated with frequent negative IOD and rare positive IOD events. Changes in Pacific wind forcing in recent decades and associated rapid increases in Indian Ocean subsurface heat content can thus affect the basin’s leading mode of variability, with implications for regional climate and vulnerable societies in surrounding countries.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    DOI: 10.1175/JCLI-D-16-0200.1
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
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    Indian Ocean sources of Agulhas leakage (2017)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Oceans, 122 (4). pp. 3481-3499.
    Details
    Publication Date: 2020-02-06
    Description: We examine the mean pathways, transit timescales, and transformation of waters flowing from the Pacific and the marginal seas through the Indian Ocean (IO) on their way toward the South Atlantic within a high-resolution ocean/sea-ice model. The model fields are analyzed from a Lagrangian perspective where water volumes are tracked as they enter the IO. The IO contributes 12.6 Sv to Agulhas leakage, which within the model is 14.1 ± 2.2 Sv, the rest originates from the South Atlantic. The Indonesian Through-flow constitutes about half of the IO contribution, is surface bound, cools and salinificates as it leaves the basin within 10–30 years. Waters entering the IO south of Australia are at intermediate depths and maintain their temperature-salinity properties as they exit the basin within 15–35 years. Of these waters, the contribution from Tasman leakage is 1.4 Sv. The rest stem from recirculation from the frontal regions of the Southern Ocean. The marginal seas export 1.0 Sv into the Atlantic within 15–40 years, and the waters cool and freshen on-route. However, the model's simulation of waters from the Gulfs of Aden and Oman are too light and hence overly influenced by upper ocean circulations. In the Cape Basin, Agulhas leakage is well mixed. On-route, temperature-salinity transformations occur predominantly in the Arabian Sea and within the greater Agulhas Current region. Overall, the IO exports at least 7.9 Sv from the Pacific to the Atlantic, thereby quantifying the strength of the upper cell of the global conveyor belt.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/2016JC012676
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Spatio-temporal variation in ocean current-driven hatchling dispersion: Implications for the world's largest leatherback sea turtle nesting region (2017)
    Wiley
    In:  Diversity and Distributions, 23 (6). pp. 604-614.
    Details
    Publication Date: 2020-02-06
    Description: Aim: The lives of juvenile leatherback turtles are amongst the most enigmatic of all marine mega-vertebrates. For these cryptic organisms, ocean models provide important insights into their dispersion from natal sites. Here, corroborated by fisheries bycatch data, we simulate spatio-temporal variation in hatchling dispersion patterns over five decades from the World's largest leatherback turtle nesting region. Location: Equatorial Central West Africa (3.5°N to −6°S) spanning the Gulf of Guinea in the North, Gabon and the Republic/Democratic Republic of the Congo in the South. Results: Due to dynamic oceanic conditions at these equatorial latitudes, dispersion scenarios differed significantly: (1) along the north to south gradient of the study region, (2) seasonally and (3) between years. From rookeries to the north of the equator, simulated hatchling retention rates within the Gulf of Guinea were very high (〉99%) after 6 months of drift, whilst south of the equator, retention rates were as low as c. 6% with the majority of simulated hatchlings dispersing west into the South Atlantic Ocean with the South Equatorial Current. Seasonal dispersion variability was driven by wind changes arising from the yearly north/southward migration of the intertropical convergence zone resulting in the increasing westerly dispersion of hatchlings throughout the hatching season. Annual variability in wind stress drove a long-term trend for decreased retention within the Gulf of Guinea and increased westerly dispersion into habitats in the South Atlantic Ocean. Main conclusions: Shifts in dispersion habitats arising from spatio-temporal oceanic variability expose hatchlings to different environments and threats that will influence important life history attributes such as juvenile growth/survival rates; anticipated to impact the population dynamics and size/age structure of populations into adulthood. The impacts of local and dynamic oceanic conditions thus require careful considerations, such as subregional management, when managing marine populations of conservation concern.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    DOI: 10.1111/ddi.12554
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
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    Flow paths and variability of the North Atlantic Current: A comparison of observations and a high-resolution model (2017)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Oceans, 122 (4). 2686-2708 .
    Details
    Publication Date: 2020-02-06
    Description: The North Atlantic Current (NAC) is subject to variability on multiannual to decadal time scales, influencing the transport of volume, heat, and freshwater from the subtropical to the eastern subpolar North Atlantic (NA). Current observational time series are either too short or too episodic to study the processes involved. Here we compare the observed continuous NAC transport time series at the western flank of the Mid-Atlantic Ridge (MAR) and repeat hydrographic measurements at the OVIDE line in the eastern Atlantic with the NAC transport and circulation in the high-resolution (1/20°) ocean model configuration VIKING20 (1960–2008). The modeled baroclinic NAC transport relative to 3400 m (24.5 ± 7.1 Sv) at the MAR is only slightly lower than the observed baroclinic mean of 27.4 ± 4.7 Sv from 1993 to 2008, and extends further north by about 0.5°. In the eastern Atlantic, the western NAC (WNAC) carries the bulk of the transport in the model, while transport estimates based on hydrographic measurements from five repeated sections point to a preference for the eastern NAC (ENAC). The model is able to simulate the main features of the subpolar NA, providing confidence to use the model output to analyze the influence of the North Atlantic Oscillation (NAO). Model based velocity composites reveal an enhanced NAC transport across the MAR of up to 6.7 Sv during positive NAO phases. Most of that signal (5.4 Sv) is added to the ENAC transport, while the transport of the WNAC was independent of the NAO.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/2016JC012444
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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