ALBERT

Description: Nitrous oxide (N2O) is an important atmospheric trace gas involved in tropospheric warming and stratospheric ozone depletion. The ocean is a net source of this gas, contributing around 25% of global N2O sources, although this emission is highly variable. It is the case of eastern South Pacific, a region with marked zonal gradients, ranging from highly productive and suboxic conditions in coastal upwelling systems to oligotrophic and oxygenated conditions in the subtropical gyre. Indeed, South Pacific Ocean has the largest permanent anticyclonic oceanic gyre which has been described as the most oligotrophic zone in the world ocean. Nitrous oxide concentration in the water column was measured on a transect crossing the Subtropical South Pacific Gyre during the BIOSOPE cruise (austral spring, 2004). This dataset includes nitrous oxide and nutrient concentrations at different depths from French program BIOSOPE, funded by the Centre National de la Recherche Scientifique (CNRS), the Institut des Sciences de l'Univers (INSU), the Centre National d'Etudes Spatiales (CNES), the European Space Agency (ESA), The National Aeronautics and Space Administration (NASA) and the Natural Sciences and Engineering Research Council of Canada (NSERC). Nitrous oxide measurements belong to Concepción University.

Description: KML files showing the distribution of lagoons wider than 500 m along the Arctic coast from the Taimyr Peninsula in Russia to the Tuktoyaktuk Peninsula in Canada. There are two files: one specific to thermokarst lagoons and the other showing all lagoons. Interconnected lagoons are marked as one system. The criteria for the identification of thermokarst lagoons is described in Angelopoulos et al. (2021).

Description: Between October 12 and November 5, 2015, the Cimar 21 “Ocean Islands” cruise was developed, organized and managed by the Navy's Hydrographic and Oceanographic Service (SHOA). This cruise covered the zonal transect in the subtropical region of the Eastern South Pacific Basin from Caldera (27.00°S; 70.88°W) to near Rapa Nui Island (27.04°S; 109.31°W). This region is characterized by presenting very contrasting trophic systems; from the coastal zone with eutrophic (rich in nutrients), colder and suboxic ([O2] 〈22 µM); to ultra-oligotrophic (with undetectable nutrient levels Raimbault et al., 2008), warmer and oxygenated waters that belong to South Pacific Subtropical Gyre, which has the clearest waters of the global ocean (Morel et al., 2010). In addition to trophic gradient, the Eastern South Pacific region presents an oxygen minimum zone (OMZ (Fuenzalida et al, 2009) with marked oxygen gradients where various biogeochemical processes can recycle greenhouse gases such as nitrous oxide (N2O) (Trocoso et al., 2018) and even methane (CH4) (Farías et al., 2021). From a total of 19 stations sampled, we present a set of data collected between 0 and 500 m depth using a CTD rosette for physicochemical variables such as temperature, salinity and oxygen (obtained from the CTD) and nutrients (nitrite, nitrate, phosphate, silicate) and greenhouse gases N2O and CH4 (obtained from Niskin bottles mounted in an oceanographic rosette). The gas samples were analyzed by gas chromatography through a gas chromatograph (Schimadzu 17A) using an electron capture detector at 350ºC and connected to an autoanalyzer, while the CH4 samples were analyzed manually in a chromatograph gas with flame ionization detector (Agilent Model 6850 GC-Fid) with a Restek RT QS-Bond column (30 meters 053 mm ID, 20 μm Film) with a temperature of 40ºC and a column flow of 4mL min-1. Meanwhile, nutrient samples with micromolar concentration (≥ 1 µM) were analyzed using standard colorimetric techniques (Grasshoff et al., 1983) in a Seal AA3 segmented flow auto-analyzer, whereas when the nutrient concentration was submicromolar (〈 1 µM) for samples of nitrite, nitrate, and phosphate in the gyre, the Seal AA3 segmented flow autoanalyzer was used coupled to two 50 cm Liquid waveridge capillary cells (LWCC, Type II), which allowed to increase the sensitivity of the detection spectrophotometric (Troncoso et al., 2018).

Description: This study was designed to assess the concentration of heavy metals in water, two fish species (Clarias gariepinus and Oreochromis niloticus), and three different vegetables (Spinach, Rosella, and Jute mallow) which were grown around the riverbank of River Benue. A laboratory-based study was adopted. Fish, water samples, and vegetables were collected monthly at different locations named points A, B, and C from River Benue for five consecutive months between October 2019 and February 2020 and analyzed for physicochemical parameters. The parameters included pH, dissolved oxygen (DO), temperature, conductivity, lead, cadmium, manganese, zinc, Iron, and copper.

Description: The Surface Ocean CO2 Atlas (SOCAT) version 2021 (v2021) dataset (Bakker et al., 2016, Bakker et al., 2021) is a quality-controlled dataset containing 30.6 million surface ocean gaseous CO2 measurements collated from thousands of individual submissions. These gaseous CO2 measurements are typically collected at many different depths (of the order of several metres below the surface) using many different systems, and the sampling depth varies dependent upon the sampling platform and/or setup. Different platforms (e.g. ships of opportunity, research vessels) and systems will collect water samples at different depths, and the sampling depth can even vary dependent upon sea state. Therefore, the collated SOCAT dataset contains high quality data, but these data are all valid for different and inconsistent depths. This means that the SOCAT provided individual gaseous CO2 measurements and gridded data are sub-optimal for calculating global or regional atmosphere-ocean gas exchange (and the resultant net CO2 sinks) and sub-optimal for verifying gas fluxes from (or assimilation into) numerical models. Accurate calculations of CO2 flux between the atmosphere and oceans require CO2 concentrations at the top and bottom of the mass boundary layer, the ~100 μm deep layer that forms the interface between the ocean and the atmosphere (Woolf et al., 2016). Ignoring vertical temperature gradients across this very small layer can result in significant biases in the concentration differences and the resulting gas fluxes (e.g. ~5 to 29% underestimate in global net CO2 sink values, Woolf et al., 2016). It is currently impossible to measure the CO2 concentrations either side of this very thin layer, but it is possible to calculate the concentrations either side of this layer using the SOCAT data, satellite observations and knowledge of the carbonate system. Therefore to enable the SOCAT data to be optimal for an accurate atmosphere-ocean gas flux calculation, a reanalysis methodology was developed to enable the calculation of the fugacity of CO2 (fCO2) for the bottom of the mass boundary layer (termed sub-skin value). The theoretical basis and justification for this is described in detail within Woolf et al., (2016) and the re-analysis methodology is described in detail in (Goddijn-Murphy et al., 2015). The re-analysis calculation exploits paired in situ temperature and fCO2 measurements in the SOCAT dataset, and uses an Earth observation dataset to provide a depth-consistent (sub-skin) temperature field to which all fugacity data are reanalysed. The outputs provide paired fCO2 (and partial pressure of CO2) and temperature data that correspond to a consistent sub-skin layer temperature. These can then be used to accurately calculate concentration differences and atmosphere-ocean CO2 gas fluxes. This data submission contains a reanalysis of the fugacity of CO2 (fCO2) from the SOCAT version 2021 dataset to a consistent sub-skin temperature field. The reanalysis was performed using a tool that is distributed within the FluxEngine V4.0.1 open source software toolkit (https://github.com/oceanflux-ghg/FluxEngine) (Shutler et al., 2016; Holding et al., 2019). All data processing and driver scripts are available from the FluxEngine Ancillary Tools (FEAT) repository https://github.com/oceanflux-ghg/FluxEngineAncillaryTools. The National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation Sea Surface Temperature (OISST) dataset (Reynolds et al., 2007) were used to provide the climate quality and depth consistent temperature data. The original ¼ degree OISST weekly data (v2.1) were first resampled to provide monthly mean values on a 1º by 1º degree grid (using the Python tools provided in the FEAT repository). These monthly 1º by 1º data were then used as the temperature input for the reanalysis. The resulting reanalysed data are provided as a tab-separated value file (individual data points) and as netCDF-5 file (gridded monthly means). These are the same file formats as provided by SOCAT and analogous to the SOCAT single data point and gridded data. Each row in the tab-separated value file corresponds to a row in the original SOCAT version 2021 dataset. The original SOCAT version 2021 data are included in full, with four additional columns containing the reanalysed data: * T_reynolds - The temperature (in degrees C) taken from the consistent OISST temperature field for the corresponding time and location. * fCO2_reanalysed - The fugacity of CO2 (in μatm) reanalysed to the consistent surface temperature indicated by T_reynolds. * pCO2_SST - The partial pressure of CO2 (in μatm) corresponding to the in situ (measured) temperature. * pCO2_reanalysed - The partial pressure of CO2 (in μatm) reanalysed to the consistent surface temperature indicated by T_reynolds. The netCDF gridded version of the reanalysed dataset contains monthly mean data, binned into a 1º by 1º grid and uses the same units, missing value indicators and time and space resolution as the original SOCAT gridded product to maximise compatibility. The gridding is performed using the SOCAT gridding methodology (Sabine et al. 2013). The implementation of the gridding has been verified by performing the gridding on the original (non-reanalysed) SOCAT data and all results were identical to 8 decimal places. The result of gridding the original SOCAT data are included within these netCDF data, along with additional variables containing the equivalent results for the reanalysed SOCAT data. Statistical sample mean, minimum, maximum, standard deviation and count data for each grid cell are included, with unweighted and cruise-weighted versions (following the convention used by SOCAT). Full meta data are included within the file.

Description: Data presented here were collected between September 2020 to December 2020 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Meteorological data were collected near the experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Meteo-Online (V4.5.0.20253) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Data presented here were collected between January 2020 to December 2020 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Data presented here were collected between January 2020 to December 2020 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

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: Data presented here were collected between January 2020 to November 2020 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Sediment samples for the determination of pore-water salinity in soil were taken bi-/monthly in surface sediments (0-3 cm depth). Samples were measured in the laboratory within two months after sampling according to DIN ISO 11265:1997-06. Post-processing of measured data was done using MATLAB (R2018a). Quality control was performed by quality check algorithms: QC = 4 (bad data) - do not use this data-point. QC = 3 (questionable data) - likely bad data-point. QC = 2 (probably good data) - likely good data-point. QC = 1 (good data) - certainly good data-point. QC = 0 (unknown data) - no data point available. Further data sets will be uploaded regularly.

Description: The present dataset reports the properties of cirrus clouds over the research site of Ny-Alesund, Svalbard, as retrieved from lidar measurements from 2011 to 2020. Several essential geometrical (cloud thickness (GT), cloud base and top heights) and optical properties (Cloud Optical Depth (COD), lidar ratio (LR), linear particle depolarization ratio (LPDR) and color ratio (CR)) were derived. Additionally, meteorological parameters (temperature, wind speed and wind direction) were extracted from AWIPEV radiosonde ascents. The meteorological parameters were subsetted within the altitude of cirrus clouds and only measurements up to 2 hours apart from the cirrus observations were used. In this way, the meteorological parameters can be considered representative of the prevailing meteorological conditions in the presence of cirrus clouds. The original radiosonde datasets are already available at doi:10.1594/PANGAEA.914973.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Meteorological data were collected near the DynaCom experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline of Spiekeroog. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Meteo-Online (V4.5.0.20253) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Data presented here were collected between Januar 2019 to November 2020 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Sediment samples for the determination of pH, water content and loss on ignition were taken bi-/monthly in surface sediments (0-3 cm depth). Samples were measured in the laboratory within two months after sampling. Further data sets will be uploaded regularly.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer’s data processing, quality controlled for appropriate physical ranges.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths 〈 0.05m represented low tide data.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: At AWIPEV research base in Ny-Ålesund, Svalbard, regular radiosonde launches are operated once per day. The launch frequency may increase to 6-hourly soundings during specific campaign periods. The Vaisala RS41-SGP radiosondes provide data of pressure, temperature, relative humidity, wind speed and wind direction from ground to about 30 km height. The given data set contains vertical profiles with 1-second time resolution data as obtained by the manufacturer's data processing, quality controlled for appropriate physical ranges.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Description: Temperature in the sediment surface layer (in approximately 0.05m depth) was measured with DEFI-T miniature temperature recorders (JFE Advantech Co., Ltd., Tokyo; DEFI-T). The manufacturer pre-calibrated temperature recorders and were installed on the experimental islands and in salt-marsh enclosed plots at different elevation levels. Recorded data were internally logged until the readout with the DEFI Series software (V1.02). The position was derived from a portable DGPS-system. Date and Time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.