Description: Zooplankton samples were collected between 03/26/2018 and 04/27/2018 around the northern tip of the Antarctic Peninsula (63° 0' 1.843'' S, 60° 0' 16.901''W) onboard the RV Polarstern during the PS112 campaign in order to identify spatial distribution in response to environmental variables (CTD raw data files from POLARSTERN cruise PS112, https://doi.org/10.1594/PANGAEA.895969) and the abundance of krill (Euphausia superba) and salps (Salpa thompsoni). Samples were taken using a Bongo net with a mesh size of 150 µm. The net was equipped with a flowmeter (HydroBios) to measure the filtered volume. On board, the net sample was sieved over a 2000 µm mesh in order to separate organisms 〉2000 µm. The smaller fraction (150 – 2000 µm) was homogenized in 200 mL 0.2 µm filtered seawater and equally split into 4 x 50 mL by using a Hensen-Stempel pipette. The mesozooplankton size range of 150 – 2000 µm was defined according to Atkinson et al. (2012). Two parts were then filtered on 47 mm GF/C Whatman filters (precombusted, acidified and weighed) for analysis of dry weight (DW), bulk carbon (C), nitrogen (N) and phosphorus (P) content, while the third part was preserved in 4 % formalin for abundance, biovolume and size structure analysis. The C/N filters were sealed in tin capsules and analyzed using a CHN analyzer (Thermo, Flash EA 1112). Prior to the analysis, filters for particulate phosphorus were combusted at 450 °C for 5 hours. Particulate organic phosphorus (POP) was measured photometrically as orthophosphate (PO4) by molybdate reaction after sulfuric acid and heat digestion at 90 °C, modified after (Grasshoff et al., 2009). Another filter containing the 4th part served as a back-up. Mesozooplankton bulk stoichiometry data are shown in dataset one. The zooplankton subsamples for taxonomic analysis were scanned using the ZooScan digital imaging system (Model Biotom, Hydroptic Inc., France), a water-proof scanner with a resolution of 2400 dpi (Gorsky et al., 2010; doi:10.1093/plankt/fbp124). Prior to scanning, the formalin preserved samples were rinsed and five samples were further subdivided with a Motoda splitter to reduce the number of organisms per scan and avoid overlapping in the scanning frame. The splits were then placed on the scanner and overlapping organisms were separated manually. Subsequently, the obtained scanning image was processed with ZooProcess, a macro of the image processing software ImageJ (Rasband, 2012) to allow automated processing and measurement of images. These single object images and their metadata were uploaded to the web-based application EcoTaxa (https://ecotaxa.obs-vlfr.fr/prj/2529). Manual validation of the results was required to ensure correct classification. The images were identified to the lowest taxonomic level possible. Prior to quantitative analysis of the obtained data, the image categories containing no zooplankton organisms such as “detritus”, “fiber”, “bubbles” etc. were removed. Abundance of zooplankton taxa was calculated based on the number of images per taxonomic category. Zooplankton organisms were identified to the lowest possible taxonomical level. Whenever identification to species level was not possible, the sample was identified to the next identifiable taxonomical category and assigned a putative species name. The abundance and biovolume data are shown in dataset two and three. The metadata of each image also contain the estimates for body size (body length: major axis of the best fitting ellipse; body width: minor axis) that were used to calculate the biovolume of each object. For the biovolume per size class, the biovolume (mm³/m³) was sorted in octave-scale size class intervals given as individual biovolume (mm3). The lowest limit of the first size class corresponded to the smallest detected ellipsoidal biovolume of 0.00025 mm³. Each size class was then doubled with respect to the previous one. Consequently, the resulting intervals were narrow for small body sizes and became progressively wider with increasing body size. The largest size class was determined by the largest individuals in each sample. As a result, the lower boundary of each size class equaled the interval width. The biovolume (mm³/m³) was then summed for each size class interval. The size distribution (mm³) with total biovolume (mm³/m³) per size bin is given in dataset four.

Description: Observations of vertical fluxes of CO2, latent heat, and sensible heat were made at the Spiekeroog Coastal Observatory in the German Wadden Sea between 1.1.2021 and 28.12.2022. Measurements were made with an eddy covariance (EC) system consisting of a sonic anemometer (Gill Windmaster) and infrared gas analyzer (Li-7200), and processed in EddyPro according to standard methods. This dataset was gathered for the purpose of investigating the drivers of air-sea fluxes, but includes observations of fluxes influenced by the nearby Spiekeroog island, which may also be of interest. Identification of land vs sea fluxes can be made with a flux footprint analysis and by screening according to wind direction.

Description: Data presented here were collected during the cruise SO290 (PaläoTaNZ) with RV Sonne from Nouméa, New Caledonia to Nouméa, New Caledonia (April, 11th, 2022 to May 12th, 2022). In total, 21 vertical deep CTD-hauls were conducted. The CTD system used was a Sea-Bird Electronics Inc. SBE 911plus probe (SN 09-1266). The CTD was attached to a SBE 32 Carousel Water Sampler (SN 32-1119) containing 24 20-liter Ocean Test Equipment Inc. bottles. The system was equipped with double temperature (SBE 3) and conductivity sensors (SBE 4), a pressure sensor (Digiquartz) an oxygen Optode (Aanderaa Optode 4831F), an altimeter (Benthos), and a chlorophyll fluorometer combined with a turbidity sensor (WET Labs ECO_AFL FL). The sensors were pre-calibrated by the manufacturers. Data were recorded with the Seasave V 7.26.7.107 software and processed using the SeaBird SBE Data Processing. Data were despiked, filtered, bin averaged (size 0.5 m) and also visually checked. The ship position was derived from the shipboard GPS-system linked to the CTD data. The time zone is given in UTC. Salinity was quality checked by reference samples [n=16], measured with an Optimare Precision Salinometer (OPS) after the cruise (S1: R² 1, S2: R² 1). Samples for oxygen [n=103] were measured in the lab by Winkler titration to correct values of the Oxygen Optode (R² 0.97). Raw data on request.

Description: Data obtained by a thermosalinograph (SBE21, SeaBird GmbH) and an external temperature sensor (SBE38, Sea-Bird GmbH) were processed to receive a validated data set of temperature and salinity on board RV Heincke during cruise HE563. Unvalidated data of conductivity sensor, internal and external temperature are extracted from the DAVIS SHIP data base (https://dship.awi.de) in a 1-second interval. The salinity was calculated using conductivity and internal temperature by applying the Practical Salinity Scale 1978 (PSS-78). After applying different filters, processed data are provided as 5min means of salinity and water temperature aligned with position data taken from master track of the respective cruise. For further details see the processing reports of each cruise.

Description: Conductivity-temperature-depth profiles were measured using a Seabird SBE 911plus CTD during RV HEINCKE cruise HE586 between 2021-10-04 and 2021-10-16. Additional sensors included a WET Labs C-Star transmissometer and a WET Labs ECO-AFL fluorometer. Data were connected to the station book of the specific cruise as available in the DSHIP database. Processing of the data including removal of obvious outliers followed the procedures described in CTD Processing Logbook of RV Heincke (hdl:10013/epic.47427). A detailed report on the CTD data of HE586 is available at https://hdl.handle.net/10013/epic.0ce60f0f-9925-4bcd-89b0-df87a7ffa481.

Description: Raw data acquired by an SBE21 thermosalinograph and an auxiliary SBE38 temperature sensor (Sea-Bird Scientific, USA) installed in an underway seawater flow-through system on board RV Heincke were processed to yield a calibrated and validated data set of seawater temperature and salinity along the cruise track. The seawater inlet is located at a depth of 2 m. The raw hexadecimal data were downloaded from the DAVIS SHIP data base (https://dship.awi.de) at a resolution of 1 s, and converted to temperature and conductivity using the pre-deployment factory calibration coefficients. The converted data were averaged to 1 min values, outliers were removed, and sensor drift was corrected using coefficients obtained from a post-season calibration performed at Sea-Bird at the end of the measurement season. Salinity was calculated from internal temperature, conductivity and pressure according to the PSS-78 Practical Salinity Scale. Processed data are provided as 1 min means of seawater temperature, conductivity and salinity, aligned with position data taken from the master track. Quality flags are appended according to the SeaDataNet Data Quality Control Procedures (version from May 2010). More details are described in the attached processing report.

Description: Upper-ocean velocities along the cruise track of Sonne cruise SO290 were continuously collected by a vessel-mounted Teledyne RD Instruments 75 kHz Ocean Surveyor ADCP. The transducer was located at 6.0 m below the water line. The instrument was operated in narrowband mode with 8 m bins and a blanking distance of 8.0 m, while 100 bins were recorded using a pulse of 1.44 s. The ship's velocity was calculated from position fixes obtained by the Global Positioning System (GPS). Heading, pitch and roll data from the ship's gyro platforms and the navigation data were used by the data acquisition software VmDas internally to convert ADCP velocities into earth coordinates. Accuracy of the ADCP velocities mainly depends on the quality of the position fixes and the ship's heading data. Further errors stem from a misalignment of the transducer with the ship's centerline. Data post-processing included water track calibration of the misalignment angle (-0.12° +/- 0.5821°) and scale factor (1.0004 +/- 0.0099) of the Ocean Surveyor signal. The average interval was set to 120 s. Velocity quality flagging is based on following threshold criteria: abs(UC) or abs(VC) 〉 1.5 m/s, rms(UC_z) or rms(VC_z) 〉 0.3.