Other language confidence: 0.6280295752276465
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).
The sea surface microlayer (SML) is the boundary layer on top of all oceans and is crucial for all exchange processes between the ocean and atmosphere. This less than 1 mm thick layer is heavily influenced by biological processes and events like algal blooms. To quantify the influence of an algal bloom in a controlled environment, we conducted a mesocosm study at the Sea sURface Facility (SURF) of the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany (53.5148 °N, 8.1463°E). SURF is an 8.5 m long, 2 m wide and 1 m deep water basin, which can directly be filled with seawater from the Jade Bay, North Sea. The facility is equipped with a retractable roof, pumps for water circulation and dedicated mounts for multiple sensor systems. The mesocosm experiment was conducted from 18 May to 16 June 2023 as part of the project BASS (Biogeochemical processes and Air-sea exchange in the Sea-Surface microlayer). SURF was filled with seawater a few days before the start of the experiment (water depth 0.7 m). The water was then filtered and the surface skimmed to remove initial pollution. To prevent particle and microbial sedimentation during the experiment, the pumps operated at low speed to maintain gentle mixing of the water column. The roof of SURF was closed during the night, while it was open during the day except when it rained. To induce an algal bloom, a mix of nutrients (nitrogen, phosphorus and silicate) was added on 26 May, 30 May and 01 June. Based on the chlorophyll measurements which show the development of the bloom, three phases of the experiment were determined: the pre-bloom phase (18 May to 26 May), the bloom phase (27 May to 04 June) and the post-bloom phase (05 June to 16 June). Several physical, chemical and biological parameters were measured, which will be published in other datasets. To evaluate the impact of the algal bloom within the SML, oxygen concentration, pH, and temperature were measured in situ using microsensors (UNISENSE, Denmark) mounted on a MicroProfiling System (UNISENSE, Denmark). With this setup, direct in situ measurements inside both the thermal boundary layer and diffusion boundary layer at the sea surface can be made. One oxygen microsensor, two pH microsensors and three temperature microsensors were mounted on the microprofiler with their tips pointing upward to avoid disturbance in the SML. They were positioned a few centimeters apart. The microprofiler was used to automatically move the sensors down, from the air through the SML and into the underlying water over a total distance of 10 000 µm in steps of 125 µm (250 µm at the start of the experiment). At each depth, the sensors stayed for about 10 s, giving a mean value and a standard deviation over that time. Three of these measurements were taken at every depth before the sensor moved down to the next step. After completing a profile, the microprofiler returned to its initial position with the tips in the air to start the next profile. The resulting profiles mostly took between 40 to 50 minutes. These profiles were conducted continuously during day and night, except for small breaks to clean and if needed replace or readjust the sensors and recalibrate the pH sensors. The sensors' height required manual adjustment to position the tip precisely at the water surface (0 µm). Through this manual adjustment, small inaccuracies may occur. As a result, the sensor depth readings form the microprofiler system may not reflect the true sensor position, which can also vary between the sensors. The true sensor positions can later be obtained by analysing the measured profiles.
Cosmic Ray neutron sensing (CRNS) is an emerging technology which is used to close the scaling gap between point measurements, such as TDR or soil samples, and the airborne remote sensing data. CRNS estimates the area-average soil water content by the detection of soil-reflected cosmic-ray neutrons in air. This method is characterized by an non-linearly shaped horizontal footprint of hundreds of meters and a vertical footprint of tens of centimetres (Köhli et al. 2015). During the campaign, a portable sensor (the so-called CRNS Rover) was used to study the spatial soil moisture variability in the target area in Hordorf. The rover was equipped with a CRNS-RV unit from Hydroinnova LLC (HI-RC01 detector) and a polyethylene shield below the detector to better reduce local effects of the field track. Neutron count data were processed including several physical, soil, and terrain corrections (see Schrön 2020, cfg file and the software <https://git.ufz.de/CRNS/cornish_pasdy>) to obtain the spatial soil moisture distribution at the Hordorf ground truthing site.
This database expands the Poulton et al., 2018 (doi:10.1594/PANGAEA.888182) database of pelagic calcium carbonate (CP) rate measurements from isotopic tracer uptake in incubated discrete water samples, as discussed in Daniels et al., 2018 (doi:10.5194/essd-10-1859-2018), and accompanies Marsh et al. (in prep.). The database now includes more CP (new data n = 400; complete database n = 3165), net primary production rate (PP) (new data n = 399; complete database n = 3150), total coccolithophore cell counts (new data n = 240; complete database n = 1512), and Emiliania huxleyi cell counts (new data n = 27; complete database n = 612). This expanded database maintains the record of data, including the principal investigator, expedition, OS region, doi reference (where available), collection date and year, sample ID, latitude, longitude, sampling and light depth, and method of measuring CP. We further expand the Poulton et al. (2018) data collection by including ancillary and environmental data, including: optical depth (OD, n = 3165), pHtotal (hereinafter referred to as pHT, n = 398), temperature (n = 1160), salinity (n = 1161), and the concentrations of chlorophyll a (n = 1363), NOx (NO3 or the sum of NO3 + NO2, n = 1161), silicic acid (Si(OH)4, n= 1156), phosphate (PO4, n = 1232), dissolved inorganic carbon (DIC, n = 318), total alkalinity (TA, n = 307), bicarbonate ion concentration (n = 349), and carbonate ion concentration (n = 352). All data was matched to CP, sample bottle identifiers (Niskin bottle numbers), and/or sampling depth values. This global database (81 °N - 64 °S, 132 °E - 174 °W) now covers expeditions and upper ocean measurements (0 - 193 m) from 1989 to 2024. Global in-situ geolocated data spanning time is valuable for modelling, satellite algorithms, and capturing calcium carbonate production in the global ocean. This expanded database, including the environmental, nutrient, chlorophyll a, and carbonate chemistry data, also allows for analysis of factors influencing calcium carbonate production on a global scale. This data amalgamation contributes to understanding the biogeochemistry of the oceans, global carbon cycle, and ocean acidification.
Dieser Darstellungs-Dienst (WMS) der Marinen Dateninfrastruktur Deutschland (MDI-DE) stellt Copernicus-Daten für die Ostsee zur Verfügung. Die Daten wurden für den Zeitraum 2022-2024 aggregiert (gemittelt) sowie zeitvariant ausgewertet und können u.a. für das MSRL Reporting genutzt werden. Bereitgestellte Parameter sind: Cyanobakterien, Trübung, Salinität, Temperatur und Azidität. Die Daten werden über unterschiedliche Zeiträume (täglich, monatlich, saisonal, 2-wöchentlich, MSRL-abgestimmt Jul-Aug) aggregiert, repräsentiert durch statistische Kennziffern.
Die Marine Dateninfrastruktur Deutschland (MDI-DE) stellt Copernicus-Daten für die Ostsee zur Verfügung. Die Daten wurden für den Zeitraum 2022-2024 aggregiert (gemittelt) sowie zeitvariant ausgewertet und können u.a. für das MSRL Reporting genutzt werden. Bereitgestellte Parameter sind: Cyanobakterien, Trübung, Salinität, Temperatur und Azidität. Die Daten werden über unterschiedliche Zeiträume (täglich, monatlich, saisonal, 2-wöchentlich, MSRL-abgestimmt Jul-Aug) aggregiert, repräsentiert durch statistische Kennziffern.
Mit diesem Dienst werden waldbauliche Informationen wie die Bestandeszustandstypen des Landesbetriebes Forst Brandenburg veröffentlicht.
Der Datenbestand enthält aus Hauskoordinaten abgeleitete Daten für das INSPIRE-Thema Adressen gemäß INSPIRE-Datenspezifikation.
Der Datenbestand enthält aus ALKIS abgeleitete Daten für das INSPIRE-Thema Bodenbedeckungsvektor gemäß INSPIRE-Datenspezifikation.
Der Datenbestand enthält aus ATKIS Basis-DLM abgeleitete Daten für das INSPIRE-Thema Verkehrsnetze gemäß INSPIRE-Datenspezifikation.
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