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  • Copernicus Publications (EGU)  (12)
  • AGU (American Geophysical Union)  (9)
  • PANGAEA  (4)
  • 2020-2024  (25)
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Keywords
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Year
  • 1
    Publication Date: 2023-03-25
    Description: Connectivity is a fundamental process driving the persistence of marine populations and their adaptation potential in response to environmental change. In this study, we analysed the population genetics of two morphologically highly similar deep-sea sponge clades (Phakellia hirondellei and the 'Topsentia-and-Petromica (TaP)' clade) at three locations in the Cantabrian Sea. Sponge taxonomy was assessed by spicule analyses, as well as by 18S sequencing and COI sequencing. The corresponding host microbiome was analysed by 16S rRNA gene sequencing. In addition we set up an oceanographic modelling framework, for which we used seawater flow cytometry data (derived from bottom depths of CTD casts) as ground-truthing data.
    Keywords: Accession number, genetics; amplicon sequencing; Angeles Alvarino; Area/locality; Bacteria; Bay of Biscay; CTD/Rosette; CTD1; CTD10; CTD11; CTD12; CTD13; CTD14; CTD15; CTD2; CTD3; CTD4; CTD5; CTD6; CTD7; CTD8; CTD9; CTD-RO; Date/Time of event; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; DEPTH, water; DR10; DR15; DR4; DR7; DR9; Dredge, rock; DRG_R; Event label; flow cytometry; Flow cytometry; Geology, comment; Latitude of event; Longitude of event; Measurement conducted; Method/Device of event; Phytoplankton; population genetics; Porifera; Sample code/label; Sample ID; single-nucleotide polymorphisms (SNPs); SponGES; SponGES_0617; SPONGES_0617_04-DR4; SPONGES_0617_07-CTD1; SPONGES_0617_12-CTD2; SPONGES_0617_13-CTD3; SPONGES_0617_15-DR7; SPONGES_0617_18-CTD4; SPONGES_0617_19-CTD5; SPONGES_0617_23-DR9; SPONGES_0617_24-CTD6; SPONGES_0617_27-CTD7; SPONGES_0617_28-DR10; SPONGES_0617_29-CTD8; SPONGES_0617_40-CTD9; SPONGES_0617_42-CTD10; SPONGES_0617_46-CTD11; SPONGES_0617_49-CTD12; SPONGES_0617_55-CTD13; SPONGES_0617_58-CTD14; SPONGES_0617_60-DR15; SPONGES_0617_61-CTD15
    Type: Dataset
    Format: text/tab-separated-values, 550 data points
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2024-04-20
    Description: This data set presents the results of an automated cluster analysis using Gaussian mixture models of the entire Atlantic seafloor environment. The analysis was based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities (see Source data set). We obtained nine seabed areas (SBAs) that portray the Atlantic seafloor that are shown as polygons in the data set. The attribute table holds short descriptions of each SBA as well as about the colours used in the accompanying paper publication. Data sets like this can be used for further analysis like e.g. for landscape ecology metrics to identify regions of interest. The compressed file further contains a style file that can be used to directly load the correct style in the QGIS software package.
    Keywords: Atlantic; Atlantic_Ocean_Seabed_Areas; Atlantic Ocean; Binary Object; Binary Object (File Size); Classification; cluster analysis; Cluster analysis; ecology metrics; File content; Horizontal datum; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; landscape; landscape metrics; Latitude, northbound; Latitude, southbound; Longitude, eastbound; Longitude, westbound; multivariate; seafloor; Vertical datum
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2024-04-20
    Description: A projection of larval dispersal patterns of Atlantic cold seep mussels Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae and B. boomerang was carried out for the next 50 years under the constraint of global warming predicted by the IPCC for the most pessismistic scenario. Simulations were run at +00 years, +25 years and +50 years from initial years of 2014 to 2019 (+00Y) at 21 locations on the US, European and African coasts using the VIKING20X model, in which the Atlantic water temperatures predicted by the FOCI model were forced to the future dates. The dataset consists of a number of 5775 simulations carried out over 5 years X 5 spawning dates per prediction period (+00Y, +25Y, +50Y) with, for predictions at +25Y and +50Y, a repetition of simulations per quantile (0.025, 0.16, 0.5, 0.67 and 0.975) to take into account for the most extreme variations in water mass temperatures predicted by the FOCI model for a given date.
    Keywords: Analysis; Atlantic; Atlantic_Larval_Dispersal_Modelling_Experiment; Barbados_Prism_Kick_em_Jenny_crater_(KJC); Barbados_Prism_Trinidad_prism_(TRI); Barbados Prism; Bathymodiolus; Binary Object; Binary Object (File Size); Binary Object (Media Type); Climate change predictions; DATE/TIME; ELEVATION; Event label; EXP; Experiment; Experiment duration; File content; Gigantidas; Gulf_of_Guinea_Guiness_(GUIN); Gulf_of_Guinea_Nigeria_margin_(NM); Gulf_of_Guinea_West_Africa_margin_(WAM); Gulf_of_Mexico_Alaminos_Canyon_(AC); Gulf_of_Mexico_Brine_Pool_(BP); Gulf_of_Mexico_Louisiana_Slope_(LS); Gulf of Guinea; Gulf of Mexico; iAtlantic; Index; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; larval dispersal modelling; LATITUDE; Location; LONGITUDE; Mid-Atlantic_Ridge_Logatchev_seeps_(LOG); Mid-Atlantic Ridge; Model; N_Mid-Atlantic_Ridge_Atlantis_Fracture_Zone_(LOST); NE_Atlantic_margin_Gulf_of_Cadiz_(GC); NE_Atlantic_margin_SWIM_fault_(SWIM); NE Atlantic margin; North_Brazil_margin_Amazon_fan_(AM); North Brazil margin; North Mid-Atlantic Ridge; Ocean and sea region; Particles; Quantile; Regime; seep mussels; South_Brazil_margin_Sao_Paulo_1_(SP); South_Brazil_margin_Sao_Paulo_2_(SPD); South Brazil margin; Speed, swimming; Temperature, water; US_Atlantic_Margin_Baltimore_Canyon_(BC); US_Atlantic_Margin_Bodie_Island_(BI); US_Atlantic_Margin_New_England_(NE); US_Atlantic_Margin_Norfolk_Canyon_(NC); US Atlantic Margin; VIKING20X; West_Africa_Margin_Arguin_bank_(ARG); West_Africa_Margin_Cadamostro_Seamount_(CS); West Africa Margin
    Type: Dataset
    Format: text/tab-separated-values, 74550 data points
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2024-04-20
    Description: These data aim at evaluating the hypothesis of long-distance dispersal across the North Atlantic and the Equatorial Atlantic belt for the cold seep mussels Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae and B. boomerang. We combined mitochondrial Cox1 barcoding of some mussel specimens from both sides of the Atlantic (American vs European/African margins) with larval dispersal trajectories simulated from the VIKING20X model of the Atlantic circulation at a spatial scale not yet investigated. Larval dispersal modelling data correspond to transports of larvae over one year in surface waters from 21 geographic localities over 5 consecutive years (2015, 2016, 2017, 2018 and 2019) and 5 spawning dates (November, December, January, February and March) per year. Genetic data correspond to the geo-referenced sequences obtained for the 4 mussel species from some of the localities where larvae have been released during the modelling approach.
    Keywords: Analysis; Atlantic; Atlantic_Larval_Dispersal_Modelling_Experiment; Barbados_Prism_Kick_em_Jenny_crater_(KJC); Barbados_Prism_Trinidad_prism_(TRI); Barbados Prism; Bathymodiolus; Binary Object; Binary Object (File Size); Binary Object (Media Type); Cold seeps; DATE/TIME; ELEVATION; Equatorial Atlantic belt; Event label; EXP; Experiment; Experiment duration; File content; Gigantidas; Gulf_of_Guinea_Guiness_(GUIN); Gulf_of_Guinea_Nigeria_margin_(NM); Gulf_of_Guinea_West_Africa_margin_(WAM); Gulf_of_Mexico_Alaminos_Canyon_(AC); Gulf_of_Mexico_Brine_Pool_(BP); Gulf_of_Mexico_Louisiana_Slope_(LS); Gulf of Guinea; Gulf of Mexico; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; larval dispersal; LATITUDE; Location; LONGITUDE; Mid-Atlantic_Ridge_Logatchev_seeps_(LOG); Mid-Atlantic Ridge; Model; Mussel; N_Mid-Atlantic_Ridge_Atlantis_Fracture_Zone_(LOST); NE_Atlantic_margin_Gulf_of_Cadiz_(GC); NE_Atlantic_margin_SWIM_fault_(SWIM); NE Atlantic margin; North_Brazil_margin_Amazon_fan_(AM); North Atlantic; North Brazil margin; North Mid-Atlantic Ridge; Ocean and sea region; Particles; South_Brazil_margin_Sao_Paulo_1_(SP); South_Brazil_margin_Sao_Paulo_2_(SPD); South Brazil margin; Speed, swimming; Temperature, water; US_Atlantic_Margin_Baltimore_Canyon_(BC); US_Atlantic_Margin_Bodie_Island_(BI); US_Atlantic_Margin_New_England_(NE); US_Atlantic_Margin_Norfolk_Canyon_(NC); US Atlantic Margin; West_Africa_Margin_Arguin_bank_(ARG); West_Africa_Margin_Cadamostro_Seamount_(CS); West Africa Margin
    Type: Dataset
    Format: text/tab-separated-values, 5252 data points
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2023-02-08
    Description: A new Earth system model, the Flexible Ocean and Climate Infrastructure (FOCI), is introduced. A first version of FOCI consists of a global high-top atmosphere (ECHAM6.3) and an ocean model (NEMO3.6) as well as sea ice (LIM2) and land surface model components (JSBACH), which are coupled through the OASIS3-MCT software package. FOCI includes a number of optional modules which can be activated depending on the scientific question of interest. In the atmosphere, interactive stratospheric chemistry can be used (ECHAM6-HAMMOZ) to study, for example, the effects of the ozone hole on the climate system. In the ocean, a biogeochemistry model (MOPS) is available to study the global carbon cycle. A unique feature of FOCI is the ability to explicitly resolve mesoscale ocean eddies in specific regions. This is realized in the ocean through nesting; first examples for the Agulhas Current and the Gulf Stream systems are described here. FOCI therefore bridges the gap between coarse-resolution climate models and global high-resolution weather prediction and ocean-only models. It allows to study the evolution of the climate system on regional and seasonal to (multi-) decadal scales. The development of FOCI resulted from a combination of the long-standing expertise in ocean and climate modeling in several research units and divisions at GEOMAR. FOCI will thus be used to complement and interpret long-term observations in the Atlantic, enhance the process understanding of the role of mesoscale oceanic eddies for large-scale oceanic and atmospheric circulation patterns, study feedback mechanisms with stratospheric processes, estimate future ocean acidification, improve the simulation of the Atlantic Meridional Overturning Circulation changes and their influence on climate, ocean chemistry and biology. In this paper we present both the scientific vision for the development of FOCI as well as some technical details. This includes a first validation of the different model components using several configurations of FOCI. Results show that the model in its basic configuration runs stably under pre-industrial control as well as under historical forcing, and produces a mean climate and variability which compares well with observations, reanalysis products and other climate models. The nested configurations reduce some long-standing biases in climate models and are an important step forward to include the atmospheric response in multi-decadal eddy-rich configurations.
    Type: Article , PeerReviewed
    Format: text
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  • 6
    Publication Date: 2023-02-08
    Description: Rapid increases in upper 700‐m Indian Ocean heat content (IOHC) since the 2000s have focused attention on its role during the recent global surface warming hiatus. Here, we use ocean model simulations to assess distinct multidecadal IOHC variations since the 1960s and explore the relative contributions from wind stress and buoyancy forcing regionally and with depth. Multidecadal wind forcing counteracted IOHC increases due to buoyancy forcing from the 1960s to the 1990s. Wind and buoyancy forcing contribute positively since the mid‐2000s, accounting for the drastic IOHC change. Distinct timing and structure of upper ocean temperature changes in the eastern and western Indian Ocean are linked to the pathway how multidecadal wind forcing associated with the Interdecadal Pacific Oscillation is transmitted and affects IOHC through local and remote winds. Progressive shoaling of the equatorial thermocline—of importance for low‐frequency variations in Indian Ocean Dipole occurrence—appears to be dominated by multidecadal variations in wind forcing.
    Type: Article , PeerReviewed
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  • 7
    Publication Date: 2023-02-08
    Description: The Atlantic meridional overturning circulation (AMOC) represents the zonally integrated stream function of meridional volume transport in the Atlantic Basin. The AMOC plays an important role in transporting heat meridionally in the climate system. Observations suggest a heat transport by the AMOC of 1.3 PW at 26°N—a latitude which is close to where the Atlantic northward heat transport is thought to reach its maximum. This shapes the climate of the North Atlantic region as we know it today. In recent years there has been significant progress both in our ability to observe the AMOC in nature and to simulate it in numerical models. Most previous modeling investigations of the AMOC and its impact on climate have relied on models with horizontal resolution that does not resolve ocean mesoscale eddies and the dynamics of the Gulf Stream/North Atlantic Current system. As a result of recent increases in computing power, models are now being run that are able to represent mesoscale ocean dynamics and the circulation features that rely on them. The aim of this review is to describe new insights into the AMOC provided by high-resolution models. Furthermore, we will describe how high-resolution model simulations can help resolve outstanding challenges in our understanding of the AMOC.
    Type: Article , PeerReviewed
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  • 8
    Publication Date: 2024-02-07
    Description: Warming of the North Atlantic region in climate history often was associated with massive melting of the Greenland Ice Sheet. To identify the meltwater’s impacts and isolate these from internal variability and other global warming factors, we run single-forcing simulations including small ensembles using three complex climate models differing only in their ocean components. In 200-year long pre-industrial climate simulations, we identify robust consequences of abruptly increasing Greenland runoff by 0.05 Sv: sea-level rise of 44±10 cm, subpolar North Atlantic surface cooling of 0.7˚C and a moderate AMOC decline of 1.1–2.0 Sv. The latter two emerge in under three decades—and reverse on the same timescale after the perturbation ends in year 100. The ocean translates the step-change perturbation into a multi-decadal to centennial signature in the deep overturning circulation. In all simulations, internal variability creates notable uncertainty in estimating trends, time of emergence and duration of the response.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 9
    Publication Date: 2024-02-07
    Description: The North Atlantic Deep Water (NADW) is a crucial component of the Atlantic meridional overturning circulation and is therefore an important factor of the climate system. In order to estimate the mean relative contributions, sources, and pathways of the NADW at the southern exit of the Labrador Sea, a Lagrangian particle experiment is performed. The particles were seeded according to the strength of the velocity field along the 53∘ N section and traced 40 years backward in time in the three-dimensional velocity and hydrography field. The resulting transport pathways, their sources and corresponding transit timescales were inferred. Our experiment shows that, of the 30.1 Sv of NADW passing 53∘ N on average, the majority of this water is associated with a diapycnal mass flux without contact to the atmosphere, accounting for 14.3 Sv (48 %), where 6.2 Sv originate from the Labrador Sea, compared to 4.7 Sv from the Irminger Sea. The second-largest contribution originates from the mixed layer with 7.2 Sv (24 %), where the Labrador Sea contribution (5.9 Sv) dominates over the Irminger Sea contribution (1.0 Sv). Another 5.7 Sv (19 %) of NADW crosses the Greenland–Scotland Ridge within the NADW density class, where about two-thirds pass the Denmark Strait, while one-third crosses the Iceland–Scotland Ridge. The NADW exported at 53∘ N is hence dominated by entrainment through the diapycnal mass flux and mixed-layer origin in the Labrador Sea.
    Type: Article , PeerReviewed
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  • 10
    Publication Date: 2024-02-07
    Description: With the increase in computational power, ocean models with kilometer-scale resolution have emerged over the last decade. These models have been used for quantifying the energetic exchanges between spatial scales, informing the design of eddy parametrizations, and preparing observing networks. The increase in resolution, however, has drastically increased the size of model outputs, making it difficult to transfer and analyze the data. It remains, nonetheless, of primary importance to assess more systematically the realism of these models. Here, we showcase a cloud-based analysis framework proposed by the Pangeo project that aims to tackle such distribution and analysis challenges. We analyze the output of eight submesoscale-permitting simulations, all on the cloud, for a crossover region of the upcoming Surface Water and Ocean Topography (SWOT) altimeter mission near the Gulf Stream separation. The cloud-based analysis framework (i) minimizes the cost of duplicating and storing ghost copies of data and (ii) allows for seamless sharing of analysis results amongst collaborators. We describe the framework and provide example analyses (e.g., sea-surface height variability, submesoscale vertical buoyancy fluxes, and comparison to predictions from the mixed-layer instability parametrization). Basin- to global-scale, submesoscale-permitting models are still at their early stage of development; their cost and carbon footprints are also rather large. It would, therefore, benefit the community to document the different model configurations for future best practices. We also argue that an emphasis on data analysis strategies would be crucial for improving the models themselves.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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