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Dissolved organic carbon concentrations from the dissolved organic matter (DOM) and extracted particulate OM (POM) obtained from purple glacier ice- and red snow-algae dominated surface habitats collected close to the QAS-M Promice weather station on the southern tip of the Greenland Ice Sheet

This dataset provides the dissolved organic carbon (DOC) concentrations of the organic matter (OM) obtained from glacier purple ice- and red snow-algae dominated samples collected upwind of the DEEP PURPLE ice camp (deeppurple-ercsyg.eu) on the surface of the Greenland Ice Sheet. The samples are represented by the initial OM from glacier ice- (T0_Ice) and snow-algae (T0_Snow) dominated habitats and the up to 24 days (T3-T24) in situ incubated samples under dark (D) and light (L) conditions. OM samples, include dissolved organic matter (DOM) and particulate organic matter (POM), the latter extracted with hot water (HW) and sodium hydroxide (Na) to represent water-soluble and particle-associated OM, respectively (see methods). Dissolved organic carbon concentrations were determined as non-purgeable organic carbon obtained from replicate measurements of DOM and POM extracts analyzed in a Shimadzu high-sensitivity TOC-V analyzer. The concentrations in this dataset are part of the supplementary material in Rossel et al. (2025).

Total sediment thickness of the world's oceans and marginal seas, version 3 (GlobSed)

NCEI's global ocean sediment thickness grid of Divins (2003) updated by Whittaker et al. (2013) has been updated again for the NE Atlantic, Arctic, Southern Ocean, and Mediterranean regions. The new global 5‐arc‐minute total sediment thickness grid, GlobSed, incorporates new data and several regional oceanic sediment thickness maps, which have been compiled and published for the, (1) NE Atlantic (Funck et al., 2017; Hopper et al., 2014), (2) Mediterranean (Molinari & Morelli, 2011), (3) Arctic (Petrov et al., 2016), (4) Weddell Sea (Huang et al., 2014), and (5) the Ross Sea, Amundsen Sea, and Bellingshausen Sea sectors off West Antarctica (Lindeque et al., 2016; Wobbe et al., 2014). This version also includes updates in the White Sea region based on the VSEGEI map of Orlov and Fedorov (2001). GlobSed covers a larger area than NCEI's previous global grids (Divins, 2003; Whittaker et al. 2013), and the new updates results in a 29.7% increase in estimated total oceanic sediment volume. This dataset has been archived in the framework of the PANGAEA US data rescue initiative 2025.

Master tracks in different resolutions from POLAR 5 flight P5-256_COMPEX-EC_2025_2503260101 (test flight)

Master tracks in different resolutions during POLAR 5 campaign P5-256_COMPEX-EC_2025

Raw data acquired by GPS1 position sensors on board research aircraft Polar 5 during the campaign P5-256_COMPEX-EC_2025 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 AWI Datamanagement System (https://dms.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.

Master track from POLAR 5 flight P5-256_COMPEX-EC_2025_2503260101 (test flight) in 1 sec resolution (zipped, 296 KB)

Arctic PASSION - High Resolution Synthetic Aperture Radar based Risk Index Outcome (AP-RIO)

The Risk Index Outcome (RIO) is a critical component of the Polar Operational Limit Assessment Risk Indexing System (POLARIS) developed by the International Maritime Organization (IMO, 2016). RIO evaluates the operational risks for ships navigating in ice-infested waters by evaluating ice conditions and offers a quantifiable measure of risk that aids in decision-making for safe navigation in polar regions based on ship ice class, sea ice type/stage of development (SOD) and sea ice concentration (SIC). The DMI-led Automated Sea Ice Products (DMI-ASIP; Wulf et al., 2024, dataset) provides daily maps of SOD and SIC based on Sentinel-1 SAR imagery, AMSR-2 Passive Microwave and Ice Charts from the Greenland and Canadian Ice Services, combined with novel AI retrieval and processing techniques. In the framework of EU funded Arctic PASSION project, we produced 10 years of satellite observation based weekly RIO maps referred as the Arctic PASSION-RIO (AP-RIO) by leveraging DMI-ASIP datasets. The AP-RIO dataset will provide weekly risk assessment maps for the given ship classes and will support the establishment of a 10 year climatology thereby enabling the assessment of RIO variability in the years covered by the input DMI-ASIP products. The AP-RIO dataset will enhance the safety and efficiency of maritime operations in the polar seas, providing a robust reference for evaluating normal and extreme ice conditions. AP-RIO is produced in the framework of the Arctic PASSION project (European Union's Horizon 2020 research and innovation program under grant agreement No. 101003472) and supported by the DMI-ASIP development team. Algorithm and Processing Scheme: SIC and SOD from ASIP are processed (by taking the mean and mode respectively) into a weekly field based on the daily files for that week. This is done for the time period of 3 Oct. 2014 - 3 Oct. 2024. The weekly SOD is used to find the Risk Value (RV) by looking at the lookup table (Dybkjær et al. 2025a). Risk Index Outcome (RIO) values are computed for each pixel in the field based on the RIO formula (RIO = SIC x RV) using the SIC from ASIP and the found RV. The meaning of the computed RIO values can be interpreted using the table in (Dybkjær et al. 2025b). The RIO field is finally saved to weekly NetCDF files.

Collection of data sets for the Clouds over cOMPlEX environment - EarthCARE (COMPEX-EC) campaign, carried out in Kiruna in spring 2025

This data collection unites the individual data sets of the COMPEX-EC (Clouds over cOMPlEX environment - EarthCARE) campaign, carried out in Kiruna 2.-16.4.2025. COMPEX-EC has been designed as an EarthCARE validation campaign. For that purpose, Polar 5 (C-GAWI) has been equipped with instrumentation similar to the one operated on EarthCARE (W-band radar, lidar, radiometers, spectral imagers). Seven research flights (summing up to more than 30 flight hours) were conducted each of them underflying the EarthCARE satellite to validate its performance.

(Table 2) Species density and composition of an inshore and offshore station in Kongsfjord, Svalbard

Megafauna plays an important role in benthic ecosystems and contributes significantly to benthic biomass in the Arctic. The distribution is mostly studied using towed cameras. Here, we compare the megafauna from two sites located at different distances from the Kongsfjord: one station at the entrance to the fjord, another on the outer shelf. Although they are only located 25 km apart and at comparable depth, there were significant differences in their species composition. While the inshore station was characterized by shrimps (2.57 +/- 2.18 ind./m**2) and brittlestars (3.21 +/- 3.21 ind./m**2), the offshore site harboured even higher brittlestar densities (15.23 +/- 9.32 ind./m**2) and high numbers of the sea urchin Strongylocentrotus pallidus (1.23 +/- 1.09 ind./m**2). Phytodetrital concentrations of the upper sediment centimetres were significantly higher inshore compared with offshore. At a smaller scale, there were also differences in the composition of different transect sections. Several taxa were characterized by a patchy distribution along transects. We conclude that these differences were caused primarily by habitat characteristics. The seafloor inshore was characterized by glacial soft sediments, whereas the station offshore harboured large quantities of stones. Although the use of a new web-2.0-based tool, BIIGLE (http://www.BIIGLE.de), allowed us to analyse more images (~90) than could have been achieved by hand, taxon area curves indicated that the number of images analysed was not sufficient to capture the species inventory fully. New automated image analysis tools would enable a rapid analysis of larger quantities of camera footage.

Surface seawater carbonate chemistry, nutrients and phytoplankton community composition on a transect between North Sea and Arctic Ocean, 2008

This data was collected during the 'ICE CHASER' cruise from the southern North Sea to the Arctic (Svalbard) in July-Aug 2008. This data consists of coccolithophore abundance, calcification and primary production rates, carbonate chemistry parameters and ancillary data of macronutrients, chlorophyll-a, average mixed layer irradiance, daily irradiance above the sea surface, euphotic and mixed layer depth, temperature and salinity.

Classification and Mapping of the North

Our research efforts intend to contribute to the development of a syntaxonomical vegetation classification system for the entire Arctic territory. Such a system enables a proper identification of the vegetation types and consequently an evaluation of their biological and ecological importance on local, regional and circumpolar scales. We use a modified, modern version of the Braun-Blanquet approach. Special attention is paid to detailed analyses of the composition of the bryophyte and lichen flora within the sample plots as well as to a detailed analysis of habitat and distribution of the vegetation. We focus on Greenland which holds geographically an intermediate position between Eurosiberia and the North-America continent. The syntaxonomical survey includes characterization of the plant communities and their habitat and distribution. Vegetation mapping displays local and regional distribution. Comparative studies are carried out in - Alaska and Canada (Southwest Alaska, Nunuvat) and we closely cooperate with Russian, European and American geobotanists and landscape ecologists. Ongoing research: Survey of the vegetation of Northwest Greenland (between 70-73 degree N)- vegetation of eastern North Greenland (southem Mylius Erichsen Land and southern Kronsprins Christian Land)-classification of dwarf shrub and terricolous lichen vegetation-vegetation mapping (CAVM-project) and characterization and delimination of altitudinal belts in the inland of West Greenland (project AZV Greenland).

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