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There are several research infrastructures or other data services running in Europe that cover a multitude of marine-related sciences, providing specific datasets coming from observations collected with different methods. These infrastructures constitute a diverse world, each looking at a piece of the big picture, sometimes hindering collaboration and data sharing. Blue-Cloud aims to overcome fragmentation and build a bridge between thematic science clusters - such as marine, climate, food and agriculture sciences - and EOSC, creating a data federation and providing a common access to a so-called thematic EOSC for marine data. By connecting leading marine data management infrastructures with horizontal e-infrastructures, the project aims to maximise the exploitation of data resources available from different sources. The Blue-Cloud framework consists of two major technical components: (1) a Blue-Cloud Data Discovery and Access service, already presented in a previous EOSC in practice story, to serve federated discovery and access to blue data infrastructures, and (2) a Blue-Cloud Virtual Research Environment (VRE) to provide computing platforms and analytical services facilitating the collaboration between researchers, which is detailed hereafter. The Blue-Cloud VRE is powered by the D4Science Infrastructure. [M. Assante et al. (2019) Enacting open science by D4Science. Future Gener. Comput. Syst. 101: 555-563 10.1016/j.future.2019.05.063 ] The full list of EOSC in practice stories is available here

Momarsat 2022 cruise report: summary of dives and operations, and position of moorings and observation infrastructures and sampling locations

The dataset contains meteorological observations during a measurement campaign with the drone LUCA (Lightweight high Ceiling Aerial System). The measurements were collected between the 25th and the 29th October 2021 at rather erratic launch times, as operations from the military training area Todendorf (Panker) in Northern Germany within the restricted airspace belonging to the training area depend on air traffic control clearance. As parameters, pressure, temperature, humidity and wind direction/speed were observed along with time and position of the drone. Besides the raw measurements, temperature and humidity readings have been corrected with an estimated inverse sensor transfer function. The data allows intercomparing the drone measurements with collocated radiosonde launches which enables a discussion on the possible use of the drone LUCA and similar systems for operational meteorology.

Water/ice velocity data and instrument status from a Nortek Aquadopp Profiler 2MHz acoustic doppler current profiler (ADCP) attached to a remotely operated vehicle (ROV) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. The Aquadopp System Integrator Manual by Nortek AS can be found here: https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1764/system-integrator-manual_Mar2016.pdf

The data sets under this data collection include detailed snow pit studies of snow temperature, density, specific surface area (SSA), stratigraphy (snow grain type & size and hand hardness), and salinity as well as high-resolution snow penetrometer measurement profiles. The data were collected during the ALERT2018 campaign (Multidisciplinary Arctic Program (MAP) - Last Ice) off Alert, Nunavut, Canada in the Lincoln Sea in May 2018. For more detailed information, please refer to the individual data sets.

This bibliography unites different data types collected by a remotely operated vehicle (ROV) underneath drifting sea ice during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern (AWI, 2017) between November 2019 and September 2020 (Nicolaus et al., 2022). The observation class M500 ROV was manufactured by Ocean Modules AB (Åtvidaberg, Sweden) and is owned by the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (Bremerhaven, Germany). It was equipped with an extended multidisciplinary sensor payload. To investigate the under-ice light field and bio-optical properties, the ROV was equipped with hyperspectral radiometers, transmissometers and a triplet fluorometer. Oceanographic properties were recorded with a standard CTD package including sensors for dissolved oxygen, nitrate and pH. Single beam and multibeam sonar allowed for a three-dimensional mapping of the ice underside, while an acoustic current profiler measured relative water currents. In addition to different video and still cameras for visual documentation of the under-ice environment, the ROV was equipped with a hyperspectral imager. For sampling of the under-ice ecosystem, a suction sampling system and an under-ice plankton as well as a gypsum net were attached to the ROV. Data were collected for all seasons and for various sea-ice and surface conditions. All data are provided at their original temporal resolution and have a common GPS synchronized timestamp. All times are given in UTC. Horizontal position of the ROV was determined using a long baseline acoustic positioning system and is provided in a floe-fixed, relative coordinate system (X, Y) with the origin (X=0 m, Y=0 m) at the ROV access hole in the MOSAiC central observatory (CO). Operations were conducted in a 300 m radius around the hole. A one function manipulator in combination with the ROV's six degrees of freedom enabled deployment and recovery of equipment (e.g. sediment traps) underneath the ice cover. Details about the respective deployment conditions can be found in the respective cruise reports of MOSAiC. A technical description of the ROV can be found in Katlein et al. (2017). MATLAB codes used for processing the data are published on ZENODO (Anhaus et al., 2023). The data will be described in a respective ROV data paper. When reusing the data, please refer to this data paper (Anhaus et al., in prep.) and the actual datasets listed below (Datasets listed in this bibliography). Please carefully read the comment section below and contact the author(s) before using the data.

These data consist of both underway and station echosounder observations collected during the 2020 SUMMER (Sustainable Management of Mesopelagic Resources) Mediterranean cruise (30 September 2020 to 18 October 2020) on the RV Sarmiento de Gamboa. Narrowband (18, 38, 70, 120, 200 kHz) underway acoustic data were collected continuously using hull-mounted Simrad EK80 echosounders. The recording depths for the 5 frequencies were 1000, 1000, 750, 500, and 200 m respectively. Calibrations were carried out on the 1st of October 2020 using a 33 mm tungsten sphere,and the calibration results were applied to the instruments. During the survey, a Simrad wideband autonomous receiver (WBAT) was deployed down to a depth of 500 m whilst on station. In total, 31 drops were carried out at 5 stations. Four transducers (central frequencies were 45, 120, 200, 333 kHz) were operated using the WBAT in frequency modulated (FM) mode (bandwidth ranging from 45 to 445 kHz). The WBAT calibration data were collected using a 33 mm tungsten sphere. During the deployment of the WBAT, the hull-mounted EK80 was switched to FM mode to record broadband measurements. Raw power (W), number of transducer segments and transceiver impedance (Ohm) were stored in raw proprietary Simrad format (.raw, .idx).

Raw data acquired by GPS1 position sensors on board research aircraft Polar 6 during the campaign P6_237_BACSAM_2022 were processed to receive a validated master track which can be used as reference of further expedition data. Novatel FlexPak6 GPS receiver was used as navigation sensors during the campaign. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution and a generalized track with a reduced set of the most significant positions of the master track. A detailed report on processing is also available for each flight.

Patterned ground of the polygonal tundra yields sensitive indicators of environmental and climate change. Polygon ponds, mires and cryosoils are typical components of Arctic Siberian wetlands underlain by permafrost. Field studies of recent environmental dynamics were carried out within the frame of the joint German-Russian DFG-RFBR project Polygons in tundra wetlands: state and dynamics under climate variability in Polar Regions (POLYGON) field studies were carried out in the Kolyma Delta in 2012 around the small fishing settlement Pokhodsk in summer 2012 and 2013. Using a multidisciplinary approach, several stages of polygonal systems were studied as modern tundra habitats . The floral and faunal associations of the polygonal tundra landscape were described. Ecological, hydrological, meteorological, limnological and cryological features were analyzed in order to evaluate modern environmental conditions and their essential controlling parameters. A monitoring program was carried out to measure changes of air, water and ground temperatures as well as water conductivity, water level and soil moisture and to collect water, diatom, zooplankton, and zoobenthos, samples. These data sets contain environmental field data, logger data, various ecological data, and analyses of sediments and water.

We provide two instrumental records of air pressure and temperature for the Alpine cities of Rovereto and Bolzano/Bozen, covering the periods 1800-1839 and 1842-1849, respectively. They were measured by two physics teachers and digitized at the University of Bern from a handwritten weather diary and a local newspaper. In addition to the raw (sub-daily) data, we provide daily and monthly means together with a quantitative estimation of their uncertainty. The data were converted to modern units, quality controlled, and homogenized.