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Melt ponds have a strong impact on the Arctic surface energy balance and the ice-associated ecosystem because they transmit more solar radiation compared to bare ice. In the existing literature, melt ponds are considered as bright windows to the ocean, even during freeze-up in autumn. In the central Arctic during the summer-autumn transition in 2018, we encountered a situation where more snow accumulated on refrozen melt ponds compared to the adjacent bare ice, leading to a reduction in light transmittance of the ponds even below that of bare ice. Results from a radiative transfer model support this finding. This situation has not been described in the literature before, but has potentially strong implications for example on autumn ecosystem activity, oceanic heat budget, and thermodynamic ice growth.

Radiation transmitted through sea ice and snow has an important impact on the energy partitioning at the atmosphere-ice-ocean interface. Snow depth and ice thickness are crucial in determining its temporal and spatial variations. Under-ice surveys using autonomous robotic vehicles to measure transmitted radiation often lack coincident snow depth and ice thickness measurements so that direct relationships cannot be investigated. Snow and ice imprint distinct features on the spectral shape of transmitted radiation. Here, we use those features to retrieve snow depth. Transmitted radiance was measured underneath landfast level first-year ice using a remotely operated vehicle in the Lincoln Sea in spring 2018. Colocated measurements of snow depth and ice thickness were acquired. Constant ice thickness, clear water conditions, and low in-ice biomass allowed us to separate the spectral features of snow. We successfully retrieved snow depth using two inverse methods based on under-ice optical spectra with 1) normalized difference indices and 2) an idealized two-layer radiative transfer model including spectral snow and sea ice extinction coefficients. The retrieved extinction coefficients were in agreement with previous studies. We then applied the methods to continuous time series of transmittance and snow depth from the landfast first-year ice and from drifting, melt-pond covered multiyear ice in the Central Arctic in autumn 2018. Both methods allow snow depth retrieval accuracies of approximately 5 cm. Our results show that atmospheric variations and absolute light levels have an influence on the snow depth retrieval.

Sea ice continues to decline across many regions of the Arctic, with remaining ice becoming increasingly younger and more dynamic. These changes alter the habitats of microbial life that live within the sea ice, which support healthy functioning of the marine ecosystem and provision of resources for human-consumption, in addition to influencing biogeochemical cycles (e.g. air–sea CO2 exchange). With the susceptibility of sea ice ecosystems to climate change, there is a pressing need to fill knowledge gaps surrounding sea ice habitats and their microbial communities. Of fundamental importance to this goal is the development of new methodologies that permit effective study of them. Based on outcomes from the DiatomARCTIC project, this paper integrates existing knowledge with case studies to provide insight on how to best document sea ice microbial communities, which contributes to the sustainable use and protection of Arctic marine and coastal ecosystems in a time of environmental change.

An integrated sensor platform including an inertial navigation system (INS) and a commercial airborne laser scanner (ALS) among other sensor was mounted in the cargo compartment in one of the Polarstern helicopters during MOSAiC. ALS data was acquired from more than 60 flights between October 2019 and September 2020 with a range of survey types intended to map changes of the sea ice surface during the full annual cycle at high spatial resolution and coverage. Here we provide an overview of the collected data and the challenge of achieving centimeter elevation accuracy with a helicopter platform at high polar latitudes. The high spatial resolution and repeated coverage of the larger area around Polarstern allow to study various surface features (e.g. pressure ridges, floes, melt ponds, snow drifts, etc.), their seasonal evolution, and their impact on atmosphere and ocean. We outline methods to identify individual floes and surface types using both measured freeboard and surface reflectance. The identified surface features can be followed in time using automated feature tracking for consecutive flights to study the dynamic and thermodynamic processes that shape the sea-ice surface. Finally, we introduce a framework to train novel data methods with the transect snow and ice measurements to predict the snow and sea-ice thickness based on the surface structure in the ALS freeboard data.

During the “Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)” in 2019/2020 a Distributed Network (DN) of autonomous stations (buoys) was installed on the sea ice and drifted across the Arctic Ocean. The DN consisted of a hierarchy of sites, called medium (M) and large (L) sites. The 3 L sites (L1 to L3) were the most complex sites in terms of instrumentation. They consisted of ocean profilers, atmospheric stations and sea ice observations. The 9 M sites (M1 to M8 and LM) consisted of sea ice and snow mass balance measurements. Additional autonomous instruments were operated in the Central Observatory (CO), which consisted of the research ice breaker Polarstern and the adjacent ice camp. Over the course of the MOSAiC expedition, 3 different COs were established because of re-locations of Polarstern. Here we define one position of each main site as a reference position over time. The report describes the data sources of each site and their processing to retrieve the 16 final drift trajectories.

Moored upward-looking Acoustic Doppler Current Profilers (ADCPs) can be used to observe sea ice draft. While previous studies relied on the availability of auxiliary pressure sensors to measure the instrument depth of the ADCP, we present an adaptive approach that infers instrument depth from ADCP bottom track (BT) mode measurements of error velocity and range. The ADCP-derived ice draft time series are validated with data from adjacent Upward-Looking Sonar (ULS) moorings. We demonstrate that this method can be used to obtain daily mean sea ice draft time series that, on average, are within 20% of ULS-derived draft time series. ULS and ADCP ice draft time series were observed by four moorings in the Laptev Sea and show correlations between 0.7 and 0.9. This new approach is not a substitute for high-frequency, high-precision ULS measurements of ice draft but it provides a low-cost opportunity to derive daily mean ice draft time series accessing existing ADCP data that have not been not used for that purpose to date. This method has the potential to close data gaps and extend existing ice draft time series in all ice-covered regions and supports the validation of sea ice thickness products from satellite missions such as CryoSat-2, SMOS or ENVISAT.

Alfred Wegener Institute’s (AWI) IceBird program is a series of airborne campaigns carried out in winter and summer using a fixed-wing Basler BT-67 research aircraft to measure Arctic sea ice and to monitor its change. In 2017, the primary scientific instrument configuration including an airborne laser scanner (ALS) for surface topography and freeboard measurements and a tethered electromagnetic induction sounding instrument (EM-Bird) for total (snow+ice) thickness measurements was complemented with an ultrawideband frequency-modulated continuous-wave microwave radar to measure snow thickness. With the unique instrumentation onboard the IceBird campaigns, we are able to observe the respective thicknesses of the snow and sea-ice layers in high resolution along survey tracks on regional scale. Here, we describe the IceBird program concept and focus on the winter campaigns that take advantage of the full instrument configuration. We present recent data of high-resolution, collocated, airborne sea-ice and snow thickness and freeboard measurements based on over 3000 km of profiles collected in the western Arctic Ocean in April 2017 and 2019. The individual parameters are important for describing and monitoring the state of the Arctic sea ice and validating retrievals from satellite data, but combined they offer further possibilities to characterize sea ice. By assuming isostatic equilibrium, we are able to derive up-to-date estimates for sea-ice bulk density for first-year and multi-year ice, including deformed ice. As an outlook, we derive a parametrization of sea-ice bulk density based on sea-ice freeboard for further applications, such as evaluating the freeboard-to-thickness conversion for satellite altimetry.

Snow on Antarctic sea ice has tremendous impacts on Albedo, light transmission and sea ice mass balance. Snow Buoys (Nicolaus et al., 2021) measure snow accumu- lation over time with four ultra sonic sensors. Here we present 14 Snow Buoys which were deployed in the Wed- dell Sea since 2013. These snow surface height measu- rements are coupled with the 1D SNOWPACK Sea ice versi- on model (Wever et al. 2020) in order to retreave snow pack processes, which are not detactable from the surface. Snow ice formation is a major process on Antarctic sea ice is, when the snow pack is flooded by sea water and refreezes. This changes the snow and sea ice mass balance. Here we present the effect on snow cover depth depending on season.

Melt ponds have a strong impact on the Arctic surface energy balance and the ice-associated ecosystem because they transmit more solar radiation compared to bare ice. In the existing literature, melt ponds are considered as bright windows to the ocean, even during freeze-up in autumn. In the central Arctic during the summer-autumn transition in 2018, we encountered a situation where more snow accumulated on refrozen melt ponds compared to the adjacent bare ice, leading to a reduction in light transmittance of the ponds even below that of bare ice. Results from a radiative transfer model support this finding. This situation has not been described in the literature before, but has potentially strong implications for example on autumn ecosystem activity, oceanic heat budget, and thermodynamic ice growth.

We combine satellite data products to provide a first and general overview of the physical sea ice conditions along the drift of the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and a comparison with previous years (2005–2006 to 2018–2019). We find that the MOSAiC drift was around 20 % faster than the climatological mean drift, as a consequence of large-scale low-pressure anomalies prevailing around the Barents–Kara–Laptev sea region between January and March. In winter (October–April), satellite observations show that the sea ice in the vicinity of the Central Observatory (CO; 50 km radius) was rather thin compared to the previous years along the same trajectory. Unlike ice thickness, satellite-derived sea ice concentration, lead frequency and snow thickness during winter months were close to the long-term mean with little variability. With the onset of spring and decreasing distance to the Fram Strait, variability in ice concentration and lead activity increased. In addition, the frequency and strength of deformation events (divergence, convergence and shear) were higher during summer than during winter. Overall, we find that sea ice conditions observed within 5 km distance of the CO are representative for the wider (50 and 100 km) surroundings. An exception is the ice thickness; here we find that sea ice within 50 km radius of the CO was thinner than sea ice within a 100 km radius by a small but consistent factor (4 %) for successive monthly averages. Moreover, satellite acquisitions indicate that the formation of large melt ponds began earlier on the MOSAiC floe than on neighbouring floes.

An unusual, large, latent-heat polynya opened and then closed by freezing and convergence north of Greenland's coast in late winter 2018. The closing presented a natural but well-constrained full-scale ice deformation experiment. We observed the closing of and deformation within the polynya with satellite synthetic-aperture radar (SAR) imagery and measured the accumulated effects of dynamic and thermodynamic ice growth with an airborne electromagnetic (AEM) ice thickness survey 1 month after the closing began. During that time, strong ice convergence decreased the area of the refrozen polynya by a factor of 2.5. The AEM survey showed mean and modal thicknesses of the 1-month-old ice of 1.96 ± 1.5 m and 1.1 m, respectively. We show that this is in close agreement with modeled thermodynamic growth and with the dynamic thickening expected from the polynya area decrease during that time. We found significant differences in the shapes of ice thickness distributions (ITDs) in different regions of the refrozen polynya. These closely corresponded to different deformation histories of the surveyed ice that we reconstructed from Lagrangian ice drift trajectories in reverse chronological order. We constructed the ice drift trajectories from regularly gridded, high-resolution drift fields calculated from SAR imagery and extracted deformation derived from the drift fields along the trajectories. Results show a linear proportionality between convergence and thickness change that agrees well with the ice thickness redistribution theory. We found a proportionality between the e folding of the ITDs' tails and the total deformation experienced by the ice. Lastly, we developed a simple, volume-conserving model to derive dynamic ice thickness change from the combination of Lagrangian trajectories and high-resolution SAR drift and deformation fields. The model has a spatial resolution of 1.4 km and reconstructs thickness profiles in reasonable agreement with the AEM observations. The mo

Changes in Arctic sea ice thickness are the result of complex interactions of the dynamic and variable ice cover with atmosphere and ocean. Most of the sea ice exiting the Arctic Ocean does so through Fram Strait, which is why long-term measurements of ice thickness at the end of the Transpolar Drift provide insight into the integrated signals of thermodynamic and dynamic influences along the pathways of Arctic sea ice. We present an updated summer (July–August) time series of extensive ice thickness surveys carried out at the end of the Transpolar Drift between 2001 and 2020. Overall, we see a more than 20 % thinning of modal ice thickness since 2001. A comparison of this time series with first preliminary results from the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) shows that the modal summer thickness of the MOSAiC floe and its wider vicinity are consistent with measurements from previous years at the end of the Transpolar Drift. By combining this unique time series with the Lagrangian sea ice tracking tool, ICETrack, and a simple thermodynamic sea ice growth model, we link the observed interannual ice thickness variability north of Fram Strait to increased drift speeds along the Transpolar Drift and the consequential variations in sea ice age. We also show that the increased influence of upward-directed ocean heat flux in the eastern marginal ice zones, termed Atlantification, is not only responsible for sea ice thinning in and around the Laptev Sea but also that the induced thickness anomalies persist beyond the Russian shelves and are potentially still measurable at the end of the Transpolar Drift after more than a year. With a tendency towards an even faster Transpolar Drift, winter sea ice growth will have less time to compensate for the impact processes, such as Atlantification, have on sea ice thickness in the eastern marginal ice zone, which will increasingly be felt in other parts of the sea-ice-covered A

We present new high-resolution snow depth data on Arctic sea ice derived from airborne microwave radar measurements from the IceBird campaigns of the Alfred Wegener Institute (AWI) together with a new retrieval method using signal peakiness based on an intercomparison exercise of colocated data at different altitudes. We aim to demonstrate the capabilities and potential improvements of radar data, which were acquired at a lower altitude (200 ft) and slower speed (110 kn) and had a smaller radar footprint size (2-m diameter) than previous airborne snow radar data. So far, AWI Snow Radar data have been derived using a 2-18-GHz ultrawideband frequency-modulated continuous-wave (FMCW) radar in 2017-2019. Our results show that our method in combination with thorough calibration through coherent noise removal and system response deconvolution significantly improves the quality of the radar-derived snow depth data. The validation against a 2-D grid of in situ snow depth measurements on level landfast first-year ice indicates a mean bias of only 0.86 cm between radar and ground truth. Comparison between the radar-derived snow depth estimates from different altitudes shows good consistency. We conclude that the AWI Snow Radar aboard the IceBird campaigns is able to measure the snow depth on Arctic sea ice accurately at higher spatial resolution than but consistent with the existing airborne snow radar data of NASA Operation IceBridge. Together with the simultaneous measurements of the total ice thickness and surface freeboard, the IceBird campaign data will be able to describe the whole sea-ice column on regional scales.

Basal melting of ice shelves can result in the outflow of supercooled ice shelf water, which can lead to the formation of a sub-ice platelet layer (SIPL) below adjacent sea ice. McMurdo Sound, located in the southern Ross Sea, Antarctica, is well known for the occurrence of a SIPL linked to ice shelf water outflow from under the McMurdo Ice Shelf. Airborne, single-frequency, frequency-domain electromagnetic induction (AEM) surveys were performed in November of 2009, 2011, 2013, 2016, and 2017 to map the thickness and spatial distribution of the landfast sea ice and underlying porous SIPL. We developed a simple method to retrieve the thickness of the consolidated ice and SIPL from the EM in-phase and quadrature components, supported by EM forward modelling and calibrated and validated by drill-hole measurements. Linear regression of EM in-phase measurements of apparent SIPL thickness and drill-hole measurements of “true” SIPL thickness yields a scaling factor of 0.3 to 0.4 and rms error of 0.47 m. EM forward modelling suggests that this corresponds to SIPL conductivities between 900 and 1800 mS m−1, with associated SIPL solid fractions between 0.09 and 0.47. The AEM surveys showed the spatial distribution and thickness of the SIPL well, with SIPL thicknesses of up to 8 m near the ice shelf front. They indicate interannual SIPL thickness variability of up to 2 m. In addition, they reveal high-resolution spatial information about the small-scale SIPL thickness variability and indicate the presence of persistent peaks in SIPL thickness that may be linked to the geometry of the outflow from under the ice shelf.

This document summarizes the steps that were undertaken to process the helicopter-borne electromagnetic ice thickness measurements collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment between September 30, 2019, and September 28, 2020.

For years, the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), together with the international MOSAiC partners, had been planning and developing the scientific, logistical and financial concept for the implementation of the MOSAiC expedition. The planning and organization of this endeavor was an enormous e˙ort, involving more than 80 institutions from 20 countries. The number of groups and individuals that significantly contributed to the success of the drift observatory goes far beyond the scope of usual polar expeditions.

The importance of Antarctic sea ice and Southern Ocean warming has come into the focus of polar research during the last couple of decades. Especially around West Antarctica, where warm water masses approach the continent and where sea ice has declined, the distribution and evolution of sea ice play a critical role in the stability of nearby ice shelves. Organic geochemical analyses of marine seafloor surface sediments from the Antarctic continental margin allow an evaluation of the applicability of biomarker-based sea-ice and ocean temperature reconstructions in these climate-sensitive areas. We analysed highly branched isoprenoids (HBIs), such as the sea-ice proxy IPSO25 and phytoplankton-derived HBI-trienes, as well as phytosterols and isoprenoidal glycerol dialkyl glycerol tetraethers (GDGTs), which are established tools for the assessment of primary productivity and ocean temperatures respectively. The combination of IPSO25 with a phytoplankton marker (i.e. the PIPSO25 index) permits semi-quantitative sea-ice reconstructions and avoids misleading over- or underestimations of sea-ice cover. Comparisons of the PIPSO25-based sea-ice distribution patterns and TEXL86- and RI-OH′-derived ocean temperatures with (1) sea-ice concentrations obtained from satellite observations and (2) instrument measurements of sea surface and subsurface temperatures corroborate the general capability of these proxies to determine oceanic key variables properly. This is further supported by model data. We also highlight specific aspects and limitations that need to be taken into account for the interpretation of such biomarker data and discuss the potential of IPSO25 as an indicator for the former occurrence of platelet ice and/or the export of ice-shelf water.

Recent low summer sea ice extent in the Weddell Sea raises questions about the contributions of dynamic and thermodynamic atmospheric and oceanic energy fluxes. The roles of snow, superimposed ice, and snow ice are particularly intriguing, as they are sensitive indicators of changes in atmospheric forcing and as they could trigger snow–albedo feedbacks that could accelerate ice melt. Here we present snow depth data and ice core observations of superimposed ice and snow ice collected in the northwestern Weddell Sea in late austral summer 2019, supplemented by airborne ice thickness measurements. Texture, salinity, and oxygen isotope analyses showed mean thicknesses of superimposed and snow ice of 0.11±0.11 and 0.22±0.22 m, respectively, or 3 % to 54 % of total ice thickness. Mean snow depths ranged between 0.46±0.29 m in the south to 0.05±0.06 m in the north, with mean and modal total ice thicknesses of 4.12±1.87 to 1.62±1.05 m and 3.9 to 0.9 m, respectively. These snow and ice properties are similar to results from previous studies, suggesting that the ice's summer surface energy balance and related seasonal transition of snow properties have changed little in past decades. This is supported by our additional analyses of the summer energy balance using atmospheric reanalysis data and by melt onset observations from satellite scatterometry showing few recent changes.

The tides in the Kitikmeot Sea, in the southern Canadian Arctic Archipelago, are found to be heavily influenced by seasonal sea-ice formation and blocking in a strait. Data from a moored current profiler in Dease Strait exhibit strong tidal damping during wintertime seasonal sea-ice cover, with 50%– 60% reduction in tidal elevation and 65% reduction in tidal velocities. We used a 3D unstratified barotropic numerical tidal model of the region to show that the observed wintertime tidal damping likely requires both high sea-ice friction and a partial sea-ice blockage in Victoria Strait (VS), the eastern gateway of the Kitikmeot Sea, where tidal-induced ridging causes thick, rough ice to accumulate over its shallow sill. Our analysis of the model shows different dynamics for the M2 and K1 tides. Both tidal constituents are dominated by the Atlantic tides entering through VS. Overall, ∼90% of the M2 tidal energy entering VS does not reach Dease Strait because, in addition to dissipation in VS (∼25%), it is significantly diverted into adjoining bays and around an amphidrome in eastern Queen Maud Gulf (∼65%). In contrast, the smaller K1 tide is less diverted into the subsidiary channels, after ∼20% dissipation in VS and only ∼25% in adjoining bays, it propagates far into the region and is amplified due to resonance in Dease Strait and Coronation Gulf, resulting in larger tidal height than the M2 tide in Coronation Gulf.