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Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.

 

Leads play an important role in the exchange of heat, gases, vapour, and particles between seawater and the atmosphere in ice-covered polar oceans. In summer, these processes can be modified significantly by the formation of a meltwater layer at the surface, yet we know little about the dynamics of meltwater layer formation and persistence. During the drift campaign of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), we examined how variation in lead width, re-freezing, and mixing events affected the vertical structure of lead waters during late summer in the central Arctic. At the beginning of the 4-week survey period, a meltwater layer occupied the surface 0.8 m of the lead, and temperature and salinity showed strong vertical gradients. Stable oxygen isotopes indicate that the meltwater consisted mainly of sea ice meltwater rather than snow meltwater. During the first half of the survey period (before freezing), the meltwater layer thickness decreased rapidly as lead width increased and stretched the layer horizontally. During the latter half of the survey period (after freezing of the lead surface), stratification weakened and the meltwater layer became thinner before disappearing completely due to surface ice formation and mixing processes. Removal of meltwater during surface ice formation explained about 43% of the reduction in thickness of the meltwater layer. The remaining approximate 57% could be explained by mixing within the water column initiated by disturbance of the lower boundary of the meltwater layer through wind-induced ice floe drift. These results indicate that rapid, dynamic changes to lead water structure can have potentially significant effects on the exchange of physical and biogeochemical components throughout the atmosphere–lead–underlying seawater system.

 

The increased fraction of first year ice (FYI) at the expense of old ice (second-year ice (SYI) and multi-year ice (MYI)) likely affects the permeability of the Arctic ice cover. This in turn influences the pathways of gases circulating therein and the exchange at interfaces with the atmosphere and ocean. We present sea ice temperature and salinity time series from different ice types relevant to temporal development of sea ice permeability and brine drainage efficiency from freeze-up in October to the onset of spring warming in May. Our study is based on a dataset collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition in 2019 and 2020. These physical properties were used to derive sea ice permeability and Rayleigh numbers. The main sites included FYI and SYI. The latter was composed of an upper layer of residual ice that had desalinated but survived the previous summer melt and became SYI. Below this ice a layer of new first-year ice formed. As the layer of new first-year ice has no direct contact with the atmosphere, we call it insulated first-year ice (IFYI). The residual/SYI-layer also contained refrozen melt ponds in some areas. During the freezing season, the residual/SYI-layer was consistently impermeable, acting as barrier for gas exchange between the atmosphere and ocean. While both FYI and SYI temperatures responded similarly to atmospheric warming events, SYI was more resilient to brine volume fraction changes because of its low salinity ($<$2). Furthermore, later bottom ice growth during spring warming was observed for SYI in comparison to FYI. The projected increase in the fraction of more permeable FYI in autumn and spring in the coming decades may favor gas exchange at the atmosphere-ice interface when sea ice acts as a source relative to the atmosphere. While the areal extent of old ice is decreasing, so is its thickness at the onset of freeze-up. Our study sets the foundation for studies on gas dynamics within the ice column and the gas exchange at both ice interfaces, i.e. with the atmosphere and the ocean.

 

Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm. 

First-year sea-ice thickness, draft, salinity, temperature, and density were measured during near-weekly surveys at the main first-year ice coring site (MCS-FYI) during the MOSAiC expedition (legs 1 to 4). The ice cores were extracted either with a 9-cm (Mark II) or 7.25-cm (Mark III) internal diameter ice corers (Kovacs Enterprise, US). This data set includes data from 23 coring site visits and were performed from 28 October 2019 to 29 July 2020 at coring locations within 130 m to each other in the MOSAiC Central Observatory. During each coring event, ice temperature was measured in situ from a separate temperature core, using Testo 720 thermometers in drill holes with a length of half-core-diameter at 5-cm vertical resolution. Ice bulk practical salinity was measured from melted core sections at 5-cm resolution using a YSI 30 conductivity meter. Ice density was measured using the hydrostatic weighing method (Pustogvar and Kulyakhtin, 2016) from a density core in the freezer laboratory onboard Polarstern at the temperature of –15°C. Relative volumes of brine and gas were estimated from ice salinity, temperature and density using Cox and Weeks (1983) for cold ice and Leppäranta and Manninen (1988) for ice warmer than –2°C.The data contains the event label (1), time (2), and global coordinates (3,4) of each coring measurement and sample IDs (13, 15). Each salinity core has its manually measured ice thickness (5), ice draft (6), core length (7), and mean snow height (22). Each core section has the total length of its top (8) and bottom (9) measured in situ, as well estimated depth of section top (10), bottom (11), and middle (12). The depth estimates assume that the total length of all core sections is equal to the measured ice thickness. Each core section has the value of its practical salinity (14), isotopic values (16, 17, 18) (Meyer et al., 2000), as well as sea ice temperature (19) and ice density (20) interpolated to the depth of salinity measurements. The global coordinates of coring sites were measured directly. When it was not possible, coordinates of the nearby temperature buoy 2019T66 were used. Ice mass balance buoy 2019T66 installation is described in doi:10.1594/PANGAEA.938134. Brine volume (21) fraction estimates are presented only for fraction values from 0 to 30%. Each core section also has comments (23) describing if the sample is from a false bottom, from rafted ice or has any other special characteristics.Macronutrients from the salinity core, and more isotope data will be published in a subsequent version of this data set. 

We present sea ice temperature and salinity data from first-year ice (FYI) and second-year ice (SYI) relevant to the temporal development of sea ice permeability and brine drainage efficiency from the early growth phase in October 2019 to the onset of spring warming in May 2020. Our dataset was collected in the central Arctic Ocean during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition in 2019 to 2020. MOSAiC was an international transpolar drift expedition in which the German icebreaker RV Polarstern anchored into an ice floe to gain new insights into Arctic climate over a full annual cycle. In October 2019, RV Polarstern moored to an ice floe in the Siberian sector of the Arctic at 85 degrees north and 137 degrees east to begin the drift towards the North Pole and the Fram Strait via the Transpolar Drift Stream. The data presented here were collected during the first three legs of the expedition, so all the coring activities took place on the same floe. The end dates of legs 1, 2, and 3 were 13 December, 24 February, and 4 June, respectively. The dataset contributed to a baseline study entitled, Deciphering the properties of different Arctic ice types during the growth phase of the MOSAiC floes: Implications for future studies. The study highlights downward directed gas pathways in FYI and SYI by inferring sea ice permeability and potential brine release from several time series of temperature and salinity measurements. The physical properties presented in this paper lay the foundation for subsequent analyses on actual gas contents measured in the ice cores, as well as air-ice and ice-ocean gas fluxes. Sea ice cores were collected with a Kovacs Mark II 9 cm diameter corer. To measure ice temperatures, about 4.5 cm deep holes were drilled into the core (intervals varied by site and leg) . The temperatures were measured by a digital thermometer within minutes after the cores were retrieved. The ice cores were placed into pre-labelled plastic sleeves sealed at the bottom end. The ice cores were transported to RV Polarstern and stored in a -20 degrees Celsius freezer. Each of the cores was sub-sampled, melted at room temperature, and processed for salinity within one or two days. The practical salinity was estimated by measuring the electrical conductivity and temperature of the melted samples using a WTW Cond 3151 salinometer equipped with a Tetra-Con 325 four-electrode conductivity cell. The practical salinity represents the the salinity estimated from the electrical conductivity of the solution. The dataset also contains derived variables, including sea ice density, brine volume fraction, and the Rayleigh number. 

Abstract. In September 2019, the researchicebreaker Polarstern started the largest multidisciplinary Arctic expedition to date,the MOSAiC (Multidisciplinary drifting Observatory for the Study of ArcticClimate) drift experiment. Being moored to an ice floe for a whole year,thus including the winter season, the declared goal of the expedition is tobetter understand and quantify relevant processes within theatmosphere–ice–ocean system that impact the sea ice mass and energy budget,ultimately leading to much improved climate models. Satellite observations,atmospheric reanalysis data, and readings from a nearby meteorologicalstation indicate that the interplay of high ice export in late winter andexceptionally high air temperatures resulted in the longest ice-free summerperiod since reliable instrumental records began. We show, using aLagrangian tracking tool and a thermodynamic sea ice model, that the MOSAiCfloe carrying the Central Observatory (CO) formed in a polynya event northof the New Siberian Islands at the beginning of December 2018. The resultsfurther indicate that sea ice in the vicinity of the CO (<40 kmdistance) was younger and 36 % thinner than the surrounding ice withpotential consequences for ice dynamics and momentum and heat transferbetween ocean and atmosphere. Sea ice surveys carried out on variousreference floes in autumn 2019 verify this gradient in ice thickness, andsediments discovered in ice cores (so-called dirty sea ice) around the COconfirm contact with shallow waters in an early phase of growth, consistentwith the tracking analysis. Since less and less ice from the Siberianshelves survives its first summer (Krumpen et al., 2019), the MOSAiCexperiment provides the unique opportunity to study the role of sea ice as atransport medium for gases, macronutrients, iron, organic matter,sediments and pollutants from shelf areas to the central Arctic Ocean andbeyond. Compared to data for the past 26 years, the sea ice encountered atthe end of September 2019 can already be classified as exceptionally thin,and further predicted changes towards a seasonally ice-free ocean willlikely cut off the long-range transport of ice-rafted materials by theTranspolar Drift in the future. A reduced long-range transport of sea icewould have strong implications for the redistribution of biogeochemicalmatter in the central Arctic Ocean, with consequences for the balance ofclimate-relevant trace gases, primary production and biodiversity in theArctic Ocean. 

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.