Wind profiles from a Galion G4000 Doppler lidar for the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project, derived from conical scans at 30 degree and 50 degree beam elevation angles. The University of Leeds participation in the project- MOSAiC Boundary Layer -was funded by the Natural Environment Research Council (NERC, grant: NE/S002472/1) and involved instrumentation from the Atmospheric Measurement and Observations Facility of the UK's National Centre for Atmospheric Science (NCAS AMOF). This was a year-long project on the German icebreaker Polarstern to study Arctic climate focused on measurements of atmospheric boundary layer dynamics and turbulent structure. The Galion wind profiler provides high resolution (~15m vertical and 5 minute temporal) measurements of wind profiles. Data are only available where sufficient particles are available to backscatter the laser light - in the clean arctic environment, this requires cloud or precipitation.

Particle number flux of airborne snow particles was measured near-continuously at 1-min resolution above the sea ice surface from October 2019 to July 2020 during the year-round MOSAiC expedition. Sensors where mounted at 0.08 m and 10 m on the mast in MetCity on the MOSAiC ice floe drifting during the measurement period within an area of 79.2 N to 88.6 N and 2.7 W to 133.6 E. The SPC measurements were part of the BAS measurement suite during MOSAiC to quantify sea salt aerosol production from blowing snow above sea ice and potential impacts on clouds and climate. Instrument and data quality checks during the year-round campaign were carried out by BAS scientists and the MOSAiC ATMOS team. Funding was provided by UKRI Natural Environment Research Council (NERC) project "Sea Salt Aerosol above Arctic Sea Ice - sources, processes and climate impacts" (SSAASI-CLIM) grant NE/S00257X/1. The project was part of the international Multi-disciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) with the tag MOSAiC20192020.

20 Ice Trackers were deployed at the MOSAiC drifting site. The deployment of the trackers was made from the helicopter onboard RV Polarstern during Leg 5 of the expedition. The data contain the GPS positioning of the trackers (and the motion of the ice on which the trackers were deployed). The data record starts from early September 2020 and lasted until July 2021 for the longest-surviving trackers. The trackers started their drift near the North Pole and move to the south through the Fram Strait. The deployment of the trackers was done in collaboration with the MOSAiC ice team. This work was funded by NERC MOSAiC program NE/S002545/1.

During the MOSAiC expedition in the Central Arctic Ocean (CAO, 2019-2020), POM was sampled weekly to fortnightly from surface waters and the Chlorophyll a maximum layer (Chl a max) via CTD casts and from bottom sea ice of the floe via ice coring (first- and second-year ice, two layers nearest to the water-ice interface). The POM was filtered onboard (GF/F filters) and deep frozen for the subsequent analysis of a suite of lipid biomarkers, including fatty acids (FA), FA-compound-specific stable isotopes (FA-CSIA), sterols, and highly-branched isoprenoids (HBI). These biomarkers can provide valuable information about the nutritional value, the taxonomic composition (e.g. diatoms vs flagellates), and the origin of the POM that represents the basis of the Central Arctic food web. This dataset comprises the results from the FA analysis only, those from other biomarkers will be submitted in due cause. The separation of the various lipid biomarkers was carried out at the University of Plymouth. After addition of internal standards for each of the 3 components, the filters were saponified with KOH. Thereafter, non-saponifiable lipids (HBI and sterols) were extracted with hexane and purified by open column chromatography (SiO2). Fatty acids were obtained by adding concentrated HCl to the saponified solution and re-extracted with hexane. Further steps of the FA analysis were carried out at the Alfred-Wegener-Institute (AWI) in Bremerhaven. Here samples were converted into fatty acid methyl esters (FAME) and analysed using an Agilent 6890N gas chromatograph. The Clarity chromatography software system (DataApex, Czech Republic) was used for chromatogram data evaluation. FAME were quantified via the internal standard, Tricosanoic acid methyl ester (23:0) (Supelco, Germany) to provide the total amount of FA (TFA) per filter. These TFA quantities per filter can be normalised to the volume of filtered seawater or melted ice core water. Additionally, we provide the mass percentage composition of the TFA, considering 48 individual FA. The FA are presented in shorthand notation, i.e., A:B(n-x), where: A indicates the number of carbon atoms in the straight fatty acid chain, B represents the number of double bonds present, n represents the terminal methyl group and x denotes the position of the first double bond from the terminal end. The biochemical nomenclature of the fatty acids is provided. The dataset is linked to a manuscript that compares pattern seen in sea ice- and water column POM in the CAO with previously published data from Arctic shelf regions. This manuscript focusses mainly on two key long-chain omega-3 FA (eicosapentaenoic acid and docosahexaenoic acid) that are considered essential for the nutrition of higher trophic levels, including humans, and their production to decline with global temperature rise. Contributions by KS were funded by the UK''s Natural Environment Research Council MOSAiC Thematic project SYM-PEL: "Quantifying the contribution of sympagic versus pelagic diatoms to Arctic food webs and biogeochemical fluxes: application of source-specific highly branched isoprenoid biomarkers" (NE/S002502/1).

This dataset contains the floe size distribution (FSD) data derived from high-resolution satellite imagery data acquired at two fixed locations in the Arctic Ocean. Satellite imagery data include MEDEA images and WorldView images. These satellite images have a spatial resolution of 1 m or higher, thus providing the FSD information, especially for small floes. The derived data contain floe size (calliper diameter), shape factor, minor/major axis, perimeter and area of the floes. This dataset has been used to evaluate the sea ice models with the FSD parameterisations. The retrieval of the FSD data was done by the University of Huddersfield team. This work was funded by NERC standard grant NE/R000654/1 and NERC MOSAiC program NE/S002545/1.

During the MOSAiC expedition in the Central Arctic Ocean (CAO, 2019-2020), POM was sampled weekly to fortnightly from surface waters and the Chlorophyll a maximum layer (Chl a max) via CTD casts and from bottom sea ice of the floe via ice coring (first- and second-year ice, two layers nearest to the water-ice interface). The POM was filtered onboard (GF/F filters) and deep frozen for the subsequent analysis of a suite of lipid biomarkers, including IP25 and other highly-branched isoprenoids (HBI), fatty acids (FA) and sterols. These biomarkers can provide valuable information about the nutritional value, the taxonomic composition (e.g. diatoms vs flagellates), and the origin of the POM that represents the basis of the Central Arctic food web. This dataset comprises the results from the HBI analysis only, while the FA dataset is already published and the sterol data will be submitted shortly. The separation of the various lipid biomarkers was carried out at the University of Plymouth. After addition of internal standards for each of the 3 components, the filters were saponified with KOH. Thereafter, non-saponifiable lipids (HBI and sterols) were extracted with hexane and purified by open column chromatography (SiO2). Fatty acids were obtained by adding concentrated HCl to the saponified solution and re-extracted with hexane. The analysis of IP25 was carried out using an Agilent 7890A gas chromatograph (GC), coupled to an Agilent 5975 mass selective detector (mass spectrometry, MS), fitted with an Agilent HP-5ms column with auto-splitless injection and helium carrier gas. Identification of IP25 and other HBIs was achieved by comparison of their individual GC retention indices and mass spectra with those obtained from purified standards. IP25 was quantified by, first, integrating individual ion responses in selected-ion monitoring mode (m/z 350.3), second, normalising these to the corresponding peak area of the internal standard and, third, applying an instrumental response factor obtained from a purified standard. These IP25 quantities per filter can be normalised to the volume of filtered seawater or melted ice core water. Contributions by KS were funded by the UK''s Natural Environment Research Council MOSAiC Thematic project SYM-PEL: ''''Quantifying the contribution of sympagic versus pelagic diatoms to Arctic food webs and biogeochemical fluxes: application of source-specific highly branched isoprenoid biomarkers''''/ (NE/S002502/1)

This dataset contains the floe size distribution (FSD) data derived from multi-satellite imagery data acquired across the Arctic Ocean. Satellite imagery data includes high-resolution visible images from the USGS Global Fiducials Library (MEDEA), TerraSAR-X/TanDEM-X and Worldview-3 (WV3). The derived data contain floe size (calliper diameter), shape factor, minor/major axis, perimeter and area of the floes. This data set has been used to investigate the characteristics of the FSD during major seasonal evaluation stages of Arctic sea ice floes. The retrieval of the FSD data was done by the University of Huddersfield team. This work was funded by NERC MOSAiC program NE/S002545/1.

This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see ''Related Data Set Metadata'' link below) has been corrected for a bug that was found in the original KuKa radar processing chain.

This dataset contains the raw data from GNSS/INS (Global Navigation Satellite System/Inertial Navigation System) buoys deployed during the 2019-2020 MOSAiC expedition. These buoys recorded the data from GNSS and Sensors. The raw GNSS data contain time, latitude, longitude, velocity, and fix type. The raw Sensors data contain time, acceleration, gyroscope, magnetometer, and temperature. These data were sampled at 10 Hz. The original data was in ANPP format (see advancednavigation.com), which have been converted to structured ASCII formats (such as RINEX, CSV) using Spatial Manager software. The buoys were assembled by the University of Huddersfield team and the deployment was done by the MOSAiC ice team throughout the expedition. This work was funded by NERC MOSAiC program NE/S002545/1.

This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (Leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection.