We will collect stool samples from the volunteers at the Mario Zucchelli Station at different time points. The samples will be analysed by shotgun metagenomic sequencing, considering only the microbial component.

Disdrometric data from an OTT Parsivel with 32 size classes and 32 velocity classes positioned at Mario Zucchelli Station (Antarctica), with monthly spectra and particle size distributions (PSD).

The effects of sea ice melting, and the consequent changes in the trophic conditions in Antarctic ecosystems, have been focused on phytoplankton with cross-food web links from krill to penguins, while the consequences on the planktonic microbial food web (viruses, prokaryotes and unicellular eukaryotes), driving biogeochemical cycles, have been largely ignored. This research investigates how changes related to sea ice melting influence the diversity and functioning of planktonic microbes in the Ross Sea coastal ecosystem of Terranova Bay. The objectives are: i) to investigate the temporal changes of planktonic microbial biodiversity, ii) to investigate the biodiversity/ecosystem functioning relationships iii) to assess the role of viruses on biodiversity and biogeochemical cycles, iv) to identify the drivers that shape microbial biodiversity and functions, and v) to shed light on the interactions within the planktonic food web, and their response to the ice melting. META-ICE-ROSS integrates ad hoc sampling with sophisticated methodologies of high-throughput sequencing of microbial DNA (metagenomics), never documented in previous Italian expeditions at Terranova Bay. The sampling includes the collection of seawater beneath the pack ice at increasing distance from the MZ Station and characterised by different thermohaline conditions, on a weekly basis from early November to mid January. The groundbreaking nature of META-ICE-ROSS will allow to provide unprecedented evidences on the role of microbial interactions in the functioning of the Ross Sea coastal ecosystem, to improve knowledge on biological changes due to global climate changes and, nonetheless, to provide a baseline assessment of the functioning of the microbial food webs and carbon sequestration in the pelagic environment in the Ross Sea region, within the context of the Ross Sea Region Marine Protected Area (RSRMPA) and its monitoring and research plan.

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De novo transcriptome analysis of Colobanthus quitensis Antarctic vascular plant grown under condition miming the global warm-up.

This dataset reports the water stable isotope composition (d18O, dD, D-excess) of precipitation at the Concordia Station, Antarctica. Daily precipitations are collected on benches (height: 1 m) in the clean area 800 m from the Station by the Concordia winter-over personnel. All samples are analyzed with laser spectroscopy (CRDS) or mass spectrometry (IRMS). 2008-2017 data are available here: https://doi.org/10.5281/zenodo.10197160; 2017-2021 data are available here: https://doi.org/10.1594/PANGAEA.971486

The RESTORE project is dedicated to the development of portable robotic technologies with the capability to perform multi-disciplinary multi-parametric 3-D monitoring of marine environment. Its primary focus lies in examining critical areas such as the air-sea-ice and water-sediment interfaces in Antarctica. This endeavour aims to support various research aspects, including the study of microbial ecology and DNA tracing, as well as the investigation of Antarctic geology, particularly the dynamics surrounding glaciers and ice-covered coastal regions. Furthermore, RESTORE is committed to scrutinising the impacts of climate change on the Antarctic atmosphere and the exchanges that occur between the sea and air. The comprehensive dataset collected during RESTORE will provide researchers with a holistic perspective on an extreme and remote environment such as Antarctica, facilitating the interpretation of atmospheric and oceanic dynamics at the interface zones and, the 3D mapping of the underwater environment and the physical characterisation of the sampled region.

This dataset contains a selection of bias-corrected data from the preoperational MiKlip system for decadal climate predictions (Mueller et al., 2018) used within the project PNRA18_00199-IPSODES. The adopted method for bias correction is described in the file bias_correction.pdf attached to the dataset. Also data from the assimilation run are provided. Nomenclature of variables follows that of the original MiKlip output. Mueller, W., et al. A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR). J. Adv. Model. Earth Syst. 10, 1383-1413 (2018)

This dataset reports the snow density, temperature and hardness observations from the surface to 1 m depth at the Concordia Station, Antarctica. A snow trench is dig once per month (or every three months during winter) in the clean area near the Station (< 1 km). The snow density measurements are taken inserting a core barrel (with a diameter of 4.5 cm and a length of 25 cm) horizontally into the snow every 10 cm from 0 to 1 m depth. The snow density is calculated from the weight. For each layer the temperature and the hardness (ranging from 1 to 6) are also recorded.

The lidar observatory at Dome C, Concordia station, is one of the primary stations of the NDACC network (Network for the Detection of Atmospheric Composition Change). Since 2014 the lidar observes polar stratospheric clouds at a height between 12 and 26 km typically, from early June until the end of Settember. These PSCs play an important role in the ozone chemistry and promote the depletion of the stratospheric ozone layer. The lidar can detect even very thin PSC layers and can provide important information about their chemical composition. The lidar can be used to study formation and dynamical processes and to provide long term records useful for climate studies.