ALBERT

Description: To gain information on the physical parameters of deep water in the Northwest Atlantic, CTD measurements were taken during seven dives to the RMS Titanic wreck (front of bow approx. 41.7330181, -49.9460561; 3816 m water depth) and one dive to the Nargeolet-Fanning Ridge (approx. 41.5980514, -49.4386889; 2896 m water depth) during the OceanGate expedition aboard the AHTS Horizon Arctic, 15 June - 25 July 2022. The CTD measurements of the water column down to a maximum water depth of 3853 m were conducted using a Valeport MIDAS SVX2 6000 unit attached to the submersible Titan for the duration of each dive and provided standard data for conductivity, temperature, and pressure. Conductivity and temperature data were used to compute salinity.

Description: We present station-specific depth integrated abundance and biomass of Calanus spp. (stage-specific abundance, CI-CVI, of C. finmarchicus, C. glacialis, C. hyperboreus and combined biomass of late stages, CIV-CVI, of Calanus spp.) collected from zooplankton monitoring programs from 19 subregions spanning the Newfoundland and Labrador Shelves, Gulf of St. Lawrence (GSL), Scotian Shelf, and Gulf of Maine (GoM). These data span years 1999-2016, except the southwest GSL subregion (1982-2016) and GoM (1977-2016). We also present data on near surface and bottom temperature and salinity from subregions in Canadian waters. We then present derived annual anomalies of abundance of the three species of Calanus, their combined biomass, and near surface and bottom temperature and salinity from all subregions. This is a contribution by Canadian and USA scientists and their institutions. Sampling and data processing methods are provided in detail in Sorochan et al. (2019), and zooplankton sampling methods are summarized here. Zooplankton samples from the southwest GSL subregion were collected from the DFO mackerel egg production survey (Mackerel Survey) using a 0.61-m diameter bongo frame (0.333-µm mesh) towed obliquely to the surface from a maximum sampling depth that varied among years, but was usually 〉 50 m. All other samples from Canadian waters were collected as part of the DFO Atlantic Zone Monitoring Program (AZMP) using a 0.75-m diameter ring net (202-µm mesh) towed vertically to the surface from a depth of ~ 5 m above bottom or a maximum depth of 1000 m. Samples from the GoM were collected from the NOAA Marine Resources Monitoring, Assessment and Prediction and Ecosystem Monitoring Surveys (EcoMon), which used the same gear as the Mackerel Survey, but sampled from a depth of ~ 5 m above bottom or a maximum depth of 200 m. These data were supplemented with surveys from the western GoM, which used sampling methods identical to AZMP. When samples were not collected from near bottom to surface in the Mackerel Survey and EcoMon, the data were adjusted using a Generalized Additive Model to estimate the depth integrated abundance or biomass from near to bottom to surface. Annual anomalies correspond to those published in Sorochan et al. (2019) with exception of abundance and biomass of Calanus spp. from the GoM and southwest GSL, which have been slightly modified to reflect updates on the data inclusion and standardization. We also note that the linear model used to derive anomalies of Calanus spp. abundance and biomass in the GoM uses Month as a factor rather than Season, which was incorrectly reported in Table 3 of Sorochan et al. (2019).

Description: These bundled biogeochemical data of sediment core EN20001, from Lake Khamra (59.99095° N, 112.98345° E), in SW Yakutia consist of four datasets: (1) Radiocarbon age dating of bulk sediments from sediment core EN20001 from Lake Khamra, measured at AWI MICADAS; (2) Element composition of the sediment core EN20001 from Lake Khamra, measured at the Bundesanstalt für Geowissenschaften und Rohstoffe (BGR); (3) TOC and TN of the sediment core EN20001 from Lake Khamra, measured in the sediment laboratory at AWI, Potsdam; (4) Pollen and non-pollen palynomorphs of the sediment core EN20001 from Lake Khamra, measured at AWI, Potsdam. This study was additionally supported by a short-term grant (not numbered) from AWI Graduate School (POLMAR), and PhD Completion Scholarship (not numbered) provided by University of Potsdam.

Description: Data presented here were collected between January 2022 to December 2023 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 Processcontrol Weather (c) -4H- JENA engineering GmbH (v20.1.0.1 2020) 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: 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: Laboratory O2 clumped-isotope data (as D36 values measured at Rice University) for air occluded in ice core GISP2-D spanning gas ages of 18000-21000 ky BP for the Last Glacial Maximum (LGM). Modeled atmospheric history for the LGM via outputs of the GISS-E2.1 driven and Data Assimilation (DAv2.0) driven chemical transport model incorporated into a 2-box model of the atmosphere.

Description: This data set contains the concentrations of chlorohyll a (chla) and the phytoplankton fuctional types from the CTD stations during PS 92, which were calculated from marker pigment ratios using the CHEMTAX program (Mackey et al, 1996).Pigment ratios were constrained as suggested by Higgins et al. (2011) based on microscopic examination of representative samples during the cruise, and the input matrix published by Fragoso et al. (2016) was applied. The resulting phytoplankotn group composition is represented in chl a concentrations. From the same bottles various trace gases were measured as carbon monoxide (CO) and the Volatile Organic Compounds (VOCs) as Dimethyl sulphide (DMS), methanethiol (MeSH) and isoprene.

Description: For the station-based current velocity measurements during MSM76, a pair of 307kHz. Lowered Acoustic Doppler Current Profilers (LADCPs) was used, mounted on the CTD rosette. Each cast was processed with LDEO Software Version IX-13 from ftp://ftp.ldeo.columbia.edu/pub/LADCP.