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Forschergruppe (FOR) 1740: Ein neuer Ansatz für verbesserte Abschätzungen des atlantischen Frischwasserhaushalts und von Frischwassertransporten als Teil des globalen Wasserkreislaufs, Variation of the fresh water in the western Nordic Seas

The goal of this project is to capture and analyse fluctuations of the fresh water in the western Nordic Seas and to understand the related processes. The East Greenland Current in the Nordic Seas constitutes an important conduit for fresh water exiting the Arctic Ocean towards the North Atlantic. The Arctic Ocean receives huge amounts of fresh water by continental runoff and by import from the Pacific Ocean. Within the Arctic Ocean fresh water is concentrated at the surface through sea ice formation. The East Greenland Current carries this fresh water in variable fractions as sea ice and in liquid form; part of it enters the central Nordic Seas, via branching of the current and through eddies. It controls the intensity of deep water formation and dilutes the water masses which result from convection. The last decades showed significant changes of the fresh water yield and distribution in the Nordic Seas and such anomalies were found to circulate through the North Atlantic. In this project the fresh water inventory, its spatial distribution and its pathways between the East Greenland Current and the interior Greenland and Icelandic seas shall be captured by autonomous glider missions. The new measurements and existing data will, in combination with the modeling work of the research group, serve as basis for understanding the causes of the fresh water variability and their consequences for the North Atlantic circulation and deep water formation.

Supporting metadata for multiple oceanographic cruises with RV SONNE (SO254, SO245, SO248) and RV POLARSTERN (PS79), Bermuda Atlantic Time-series Study and Hawaii Ocean Time-series

The data presented here include the metadata (cruise, station number, geographic coordinates, water depth, temperature, salinity and solid-phase extracted dissolved organic carbon concentrations (SPE-DOC)) for multiple oceanographic cruises in the Atlantic, Pacific and Southern oceans (HOTS, BATS, SO254, SO245, SO248, ANT 28-II, ANT 28-IV, and 28-V) between 2009 and 2017. These metadata were used in conjunction with the accompanying dataset to assess the role of deep ocean mixing in the molecular composition of dissolved organic matter was compiled from the CTD bottle data of multiple cruises, some of which are available on PANGAEA at the following links: SO248: https://doi.org/10.1594/PANGAEA.864673, SO245: https://doi.org/10.1594/PANGAEA.890394, SO254: https://doi.org/10.1594/PANGAEA.890453.

Multibeam bathymetry processed data (Atlas Hydrosweep DS 3 echo sounder entire dataset) of RV POLARSTERN during cruise PS127, Atlantic Ocean

Multibeam data were collected during RV Polarstern cruise PS127 (2021-12-04 to 2022-01-02). Multibeam sonar system was Atlas Hydrographic Hydrosweep DS 3 multibeam echo sounder. Data are processed with Caris HIPS, including sound velocity correction with SV data from SVPs, CTDs, UCTDs and World Ocean Atlas 13 (https://doi.org/10.7289/v5f769gt), tidal correction with TPXO9_atlas_v5 (https://www.tpxo.net), and manual cleaning. The soundings are combined in daily files, the format is XYZ ASCII (<Lon> <Lat> <Depth in meters, positive up, relative to mean sea level>). Additional blockmedian grids have been computed with depth dependent cell size to visualize the data. These grids are not meant for scientific analysis or navigation, but for overview purposes only.

Multibeam bathymetry processed data (Atlas Hydrosweep DS 3 echo sounder entire dataset) of RV POLARSTERN during cruise PS145/1, Atlantic Ocean

Multibeam data were collected during RV Polarstern cruise PS145/1 (2024-11-25 to 2024-12-07). Multibeam sonar system was Atlas Hydrographic Hydrosweep DS 3 multibeam echo sounder. Data are processed with Caris HIPS, including sound velocity correction with SV data from SVPs, CTDs and World Ocean Atlas 18 (https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18), tidal correction with TPXO9_atlas_v5 (https://www.tpxo.net), and manual cleaning. The soundings are combined in daily files, the format is XYZ ASCII (<Lon> <Lat> <Depth in meters, positive up, relative to mean sea level>). Additional grids have been computed with depth dependent cell size to visualize the data. These grids are not meant for scientific analysis or navigation, but for overview purposes only.

Visualisierung mikrobieller Gemeinschaften auf marinem Mikroplastik: Identifikation, Interaktionen und Auswirkungen

Marines Mikroplastik (MMP) ist eine zunehmende anthropogene Verschmutzung in den Meeren. Der Einfluss auf marine Tiere, durch Verfangen und verschlucken von Plastikmüll, ist bekannt. Aber der Einfluss von MMP auf Mikroorganismen, wie Bakterien, Archaeen und Protisten, die die Basis der Nahrungsnetze bilden, ist kaum verstanden. Auf Grund der besonderen Eigenschaften von MMP, kann es als neues Habitat und als Transportmittel für bestimmte u.a. auch gesundheitsgefährdende Mikroorganismen dienen, die über lange Distanzen bis in entlegene Regionen transportiert werden können. Darüber hinaus kann MMP das Zusammenleben von Mikroorganismen in enger Nachbarschaft ermöglichen und die Stoffwechselwege vieler verschiedener Verbindungen beeinflussen. Um den Einfluss von MMP und ihrer assoziierten Mikroorgansimen auf marine Ökosysteme zu verstehen, müssen wir die Zusammensetzung und Interaktionen von mikrobiellen Gemeinschaften auf MMP identifizieren und ihre globale Ausbreitung untersuchen. Ich möchte die Diversität und die räumliche Verteilung von mikrobiellen Gemeinschaften auf MMP charakterisieren. Proben von MMP wurde bereits von meinem Gastinstitut in verschiedenen Meeresregionen (Atlantik, Pazifik, Indischer Ozean) gesammelt. Mein Ziel ist es: 1) zu identifizieren, welche Mikroorganismen auf MMP vorkommen; 2) die lokale Verteilung und Struktur der mikrobiellen Gemeinschaft auf MMP und in Experimenten auf Bioplastikpartikeln zu untersuchen; 3) zu verstehen, welche Mikroorganismen am stärksten mit der Polymer Oberfläche assoziiert sind; 4) herauszufinden, ob es charakteristische Mikrobiome auf MMP in verschiedenen Meeresregionen gibt und 5) zu untersuchen, welche Mikroorganismen MMP abbauen können. Die Chancen für die erfolgreiche Durchführung des vorgeschlagenen Projekts ist hoch, da präperierte Proben bereits in meinem Gastlabor vorhanden sind, an denen die innovative Mikroskopiertechnik namens CLASIFISH (Combinatorial Labelling and Spectral Imaging Fluorescence In Situ Hybridization) angewandt werden kann. Diese Methode ermöglicht es viele verschiedene Mikroorganismen und ihre räumliche Verteilung auf einem Plastikpartikel schnell und präzise zu identifizieren. Ich möchte diese Methode an Proben aus dem Atlantik und Pazifik anwenden, sowie Mikroben identifizieren, die im offenen Ozean Plastik abbauen. Zusätzlich möchte ich Inkubationsexperimente mit Bakterienkulturen, die bereits auf Plastik identifiziert wurden und in meinem Gastinstitut zur Verfügung stehen, auf Bioplastikpartikeln durchführen. Mit diesen Experimenten möchte ich herausfinden, wie sich mikrobielle Gemeinschaften auf Bioplastik über die Zeit entwickeln und ob bzw. wie diese Mikroben Plastik abbauen. Für diese Inkubationsexperimente möchte ich FISH, CLASIFISH, scanning electron microscopy sowie metagenomische und metatranscriptomische Ansätze verwenden.

Modeled environmental data-layers and changes predicted under RCP2.6, 4.5 and 8.5 for the deep Atlantic Ocean

The data layers provided show current values for seawater temperature, pH, calcite and aragonite saturation (%), oxygen concentration, and particulate organic carbon (POC) flux to the seafloor at different depths (500, 1000, 2000, 3000, and 4000m) at the present day (1951-2000) and changes in these variables expected between 2041-2060 and 2081-2100 under different RCP scenarios. The data layers were generated following the methods described in Levin et al. (2020). In short, in 2019, we obtained the present day and future ocean projections for the different years which were compiled from all available data generated by Earth Systems Models as part of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Three Earth System Models, including GFDL‐ESM‐2G, IPSL‐CM5A‐MR, and MPI‐ESM‐MR were collected and multi-model averages of temperature, pH, O2 , export production at 100-m depth (epc100), carbonate ion concentration (co3), and carbonate ion concentration for seawater in equilibrium with aragonite (co3satarg) and calcite (co3satcalc) were calculated. The epc100 was converted to export POC flux at the seafloor using the Martin curve (Martin et al., 1987) following the equation: POC flux = export production*(depth/export depth)0.858. The export depth was set to 100 m, and the water depth using the ETOPO1 Global Relief Model (Amante and Eakins, 2008). Seafloor aragonite and calcite saturation were computed by dividing co3 by co3satarg and co3satcalc. All variableswere reported as the inter-annual mean projections between 1951-2000, 2041-2060, and 2081-2100. The data for calcite and aragonite saturation can be found in Morato et al. (2020).

Total sediment thickness of the world's oceans and marginal seas, version 3 (GlobSed)

NCEI's global ocean sediment thickness grid of Divins (2003) updated by Whittaker et al. (2013) has been updated again for the NE Atlantic, Arctic, Southern Ocean, and Mediterranean regions. The new global 5‐arc‐minute total sediment thickness grid, GlobSed, incorporates new data and several regional oceanic sediment thickness maps, which have been compiled and published for the, (1) NE Atlantic (Funck et al., 2017; Hopper et al., 2014), (2) Mediterranean (Molinari & Morelli, 2011), (3) Arctic (Petrov et al., 2016), (4) Weddell Sea (Huang et al., 2014), and (5) the Ross Sea, Amundsen Sea, and Bellingshausen Sea sectors off West Antarctica (Lindeque et al., 2016; Wobbe et al., 2014). This version also includes updates in the White Sea region based on the VSEGEI map of Orlov and Fedorov (2001). GlobSed covers a larger area than NCEI's previous global grids (Divins, 2003; Whittaker et al. 2013), and the new updates results in a 29.7% increase in estimated total oceanic sediment volume. This dataset has been archived in the framework of the PANGAEA US data rescue initiative 2025.

Multibeam bathymetry processed data (EM 1002 echosounder entire dataset) of RV MARIA S. MERIAN during cruise MSM32

Bathymetry data was acquired during R/V MARIA S. MERIAN cruise MSM32 in the northeastern Atlantic between 25.09.2013 and 30.10.2013. The cruise aimed to gain a better understanding of the Agadir Canyon. To investigate why some submarine landslides remain as coherent blocks of sediment throughout their passage downslope, while others mix and disintegrate almost immediately after initial failure MSM32 combined seismic, hydroacoustic and sidescan surveys [DOI: 10.2312/cr_msm32]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM32 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. 111 beams are formed for each ping while the seafloor is detected using amplitude and phase information for each beam sounding. For further information on the system, consult https://www.km.kongsberg.com/. During the cruise, the swath width was adjusted manually to get the best compromise between coverage and data quality with changing water depth and sea state [DOI: 10.2312/cr_msm32]. Responsible person during this cruise / PI: P. Feldens. Postprocessing and products were conducted by the Seafloor-Imaging & Mapping group of MARUM/FB5, responsible person Paul Wintersteller (seafloor-imaging@marum.de). The open source software MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, https://www.mbari.org/products/research-software/mb-system, 2017) was utilized for this purpose. A sound velocity correction profile was applied to the MSM32 data; there were no further corrections for roll, pitch and heave applied during postprocessing. A tide correction was applied, based on the Oregon State University (OSU) tidal prediction software (OTPS) that is retrievable through MB-System. CTD measurements during the cruise were sufficient to represent the changes in the sound velocity throughout the study area. Using Mbeditviz, artefacts were cleaned manually. NetCDF (GMT) grids of the edited data as well as statistics were created with mbgrid. The published bathymetric EM1002 grid of the cruise MSM32 has a resolution of 35 m. No total propagated uncertainty (TPU) has been calculated to gather vertical or horizontal accuracy. A higher resolution is, at least partly, achievable. The grid extended with _num represents a raster dataset with the statistical number of beams/depths taken into account to create the depth of the cell. The extended _sd -grid contains the standard deviation for each cell. The DTMs projections are given in Geographic coordinate system Lat/Lon; Geodetic Datum: WGS84.

Multibeam bathymetry processed data (Atlas Hydrosweep DS 3 echo sounder entire dataset) of RV POLARSTERN during cruise PS151, Atlantic Ocean

Multibeam data were collected during RV Polarstern cruise PS151 (2025-11-13 to 2025-12-12). Multibeam sonar system was Atlas Hydrographic Hydrosweep DS 3 multibeam echo sounder. Data are processed with Caris HIPS, including sound velocity correction with SV data from CTDs and World Ocean Atlas 23 (https://www.ncei.noaa.gov/archive/accession/NCEI-WOA23), tidal correction with TPXO9_atlas_v5 (https://www.tpxo.net), and manual cleaning. The soundings are combined in daily files, the format is XYZ ASCII (<Lon> <Lat> <Depth in meters, positive up, relative to mean sea level>). Additional grids have been computed with depth dependent cell size to visualize the data. These grids are not meant for scientific analysis or navigation, but for overview purposes only.

Mean Deep Ocean volume-weighted stacks

Mean Deep Ocean stacked records weighted by ocean basin volume are also provided for: benthic δ18O, MDOT and δ18Oseawater and compiled from records described for the non-weighted stacks. The weighted stacks were created using basin weights defined using fixed deep ocean volume fractions following the volumetric approach of Lisiecki and Stern (2016) (see their Table S2), and renormalised to unity at each time step to reflect the ocean volume represented by the available records.

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