Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM62/2 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 23.03.2017 and 27.03.2017 in the Baltic Sea. The cruise aimed to investigate the impact of the Littorina transgression on the inflow of saline waters into the western Baltic and assessed the potential for future diminution of ventilation in the central and northern deeper basins due to isostatic uplift [CSR]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM62/2 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. The echosounder has a curved transducer in which 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/. 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 MSM62/2 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 MSM62/2 has a resolution of 15 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.
Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM52 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 01.03.2016 and 28.03.2016 in the Baltic Sea. The cruise aimed gapless imagining of the major pre-alpine tectonic lineaments due to the fact that the Glückstadt Graben and the Avalonia-Baltica suture zone run across the southern Baltic [DOI: 10.2312/cr_msm52]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM52 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. It has a curved transducer of which 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/. Generally, the system was acquiring data throughout the entire cruise. Responsible person during this cruise / PI: Laura Frahm. 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 MSM52 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 MSM52 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.
This product shows globally the daily snow cover extent (SCE). The snow cover extent is the result of the Global SnowPack processor's interpolation steps and all data gaps have been filled. Snow cover extent is updated daily and processed in near real time (3 days lag). In addition to the near real-time product (NRT_SCE), the entire annual data set is processed again after the end of a calendar year in order to close data gaps etc. and the result is made available as a quality-tested SCE product. There is also a quality layer for each day (SCE_Accuracy), which reflects the quality of the snow determination based on the time interval to the next "cloud-free" day, the time of year and the topographical/geographical location. The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment. For more information please also refer to: Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480 Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551 Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432 Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752 Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130
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).
Aerosols are an indicator for episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning. Daily observations are binned onto a regular latitude-longitude grid. The Aerosol layer height is provided in kilometres. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
The importance of nutrient supply from the sub-soil for crop growth is not well understood and may vary depending on bio-pores, nutrient turnover rates and the crop specific root systems. Simulation modelling provides a means to consider the complexity of the processes involved to describe the nutrient dynamics of the plant-soil system in an integrated way. However, approaches that describe the dynamics of phosphorus and potassium in combination with soil water, soil carbon and nitrogen and specifically consider the sub-soil and the bio-pores herein are scarce. Accordingly, the main objective of SP 10 is to develop a field-scale cropping system model which describes nutrient (emphasis in the 1st phase of the project is on phosphorus) mobilization and nutrient fluxes from the sub-soil to the crops considering soil nutrient pools, the bio-pore system and the crop nutrient demand. A two step approach is followed in which results from controlled experiments on soil cores will be used to develop detailed process models of root development and nutrient acquisition. These are the basis for deriving simplified algorithms to be used in a cropping system model for the field scale. The latter model will be applied to assess, after thorough validation with data from long-term experiments, the contribution of nutrients from the sub-soil and bio-pores to the growth of different crops. The sub-project combines modelling activities with experimental measurements and has a strong integrating role within the collaborative project.
The Time Series Station Spiekeroog (TSS) was setup in 2002, in the tidal inlet between the East Frisian Islands of Langeoog and Spiekeroog in the Southern German Bight, at position 53°45′01.0″ N, 007°40′16.3″ E. The aim was to ensure the continuous measurement of physical, biological, chemical and meteorological parameters, even under extreme weather conditions such as storms, ice, and storm surges. The TSS was financed as part of the Deutsche Forschungsgemeinschaft (DFG) research unit BioGeoChemistry of Tidal Flats and the Ministry for Science and Culture of the Land of Lower Saxony (MWK). Here, sea level, water temperature and conductivity were measured in the year 2024. All raw data were revised and corrected for steps as range, outliers and stationarity checks. Water temperature and conductivity were measured in five different depths (4 m, 5.5 m, 7.5 m, 9.5 m, 11.5 m below MSL). Due to marine biofouling at the sensors and accompanying drift of instruments, the measured water temperature and conductivity data were corrected via linear regression by using reference data. As the water column in this region is well mixed and the water depth of the measurements varies with the tide, data from all five depths were averaged and referenced to a water depth of 4 m. Absolute salinity was derived from conductivity, temperature and pressure data according to TEOS 10. Data were smoothed and a quality flag was assigned for water temperature and salinity. The quality flags refer to the standard for data quality control of SeaDataNet https://www.seadatanet.org/ (0 = raw data, 1 = good data, 2 = probably good data, 3 = questionable data). A detailed description of the Time Series Station Spiekeroog, its structure and instrumentation can be found in Zielinski et al. (2022) and in Reuter et al. (2009).
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational HCHO total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
A total of 140 samples were collected from the il-Blata section outcropping on the Mediterranean Island of Malta (base of section at 35.9004˚N, 14.3309˚E, top of section at 35.9000˚N, 14.3314˚E). 16 of these samples were selected to determine the 87Sr/86Sr in the bulk sediment and used to generate numerical ages using the LOWESS FIT for Sr-Stratigraphy (McArthur et al., 2012). All 87Sr/86Sr measurements conducted at the University of Geneva using a Thermo Neptune PLUS Multi-Collector inductively coupled plasma mass spectrometer. Data and numerical age model presented in table S1. The εNd data from (Bialik et al., 2019) were recalibrated to fit the new age model and presented in table S2. The percentage carbonate matter was measured using a FOGl digital calcimeter at the University of Malta (table S3). Dry powders were used to generate a stable isotope (δ18O & δ13C) record (table S4), all measurements were conducted on a Gasbench II coupled to a Thermo Delta V Advantage isotope ratio mass spectrometer at the School of Earth and Environmental Sciences, Cardiff University. Dry bulk sediment powders were also used to obtain major element composition and calculate element ratios Sr/Ca, Ti/Al, K/Al, Zr/Al, Si/Ti. All element measurements were conducted at The School of Earth and Environmental Sciences, Cardiff University using a hand-held Olympus Delta Innov-X XRF gun. Element data presented in table S5. Mean values of the ratios Sr/Ca, Ti/Al, K/Al, Zr/Al and Si/Ti were obtained for three different parts in the section in order to determine regime changes (table S6).
Grundrisstreue Abbildung des hamburgischen Staatsgebietes. Kartengrundlage ist das Amtliche Liegenschaftskataster Informationssystem (ALKIS - inhaltlich reduziert), welches um topographische Inhalte und Informationen ergänzt wird. Die Digitale Karte 1: 5000 Hamburg (DK5) ist die digitale Neuausgabe der ehemaligen Deutschen Grundkarte (DGK) 1:5000. Sie dient der Wirtschaft, Verwaltung und Planung.
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