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Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the 1-year drift campaign Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in describing the surface meltwater volume; it is necessary to estimate budgets and used in model parameterization to simulate pond coverage evolution. However, observational data on pond depth are spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air–pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements and the importance of such high-resolution data for new satellite retrievals, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea ice surface emerging from the increasingly available visual image data recorded from uncrewed aerial vehicles (UAVs) or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models. [ABSTRACT FROM AUTHOR]

If and how the sea ice cycle drives the methane cycle in the high Arctic is an open question and crucial to improving source/sink balances. This study presents new insights into the effects of strong and fast freezing on the physical-chemical properties of ice and offers implications for methane fluxes into and out of newly formed lead ice. During the 2019-2020 transpolar drift of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC), we took weekly samples of growing lead ice and underlying seawater at the same site between January and March 2020. We analyzed concentrations and stable carbon isotopic signatures (513C-CH4) of methane and calculated methane solubility capacities (MSC) and saturation levels in both environments. During the first month, intense cooling resulted in the growth of two-thirds of the final ice thickness. In the second month, ice growth speed decreased by 50%. Both growth phases, disentangled, exposed different freeze impacts on methane pathways. The fast freeze caused strong brine entrapment, keeping the newly formed lead ice permeable for 2 weeks. These physical conditions activated a methane pump. An increased MSC induced methane uptake at the air-ice interface, and the still-open brine channels provided top-down transport to the ocean interface with brine drainage. When the subsurface layer became impermeable, the top-down pumping stopped, but the ongoing uptake induced a methane excess on top. During the second growth phase, methane exchange exclusively continued at the ice-ocean interface. The shift in the relative abundance of the 12C and 13C isotopes between lead ice and seawater toward a 13C-enrichment in seawater reveals brine drainage as the main pathway releasing methane from aging lead ice. We conclude that in winter, refrozen leads temporarily function as active sinks for atmospheric methane and postulate that the relevance of this process may even increase when the Arctic fully transitions into a seasonally ice-covered ocean when leads may be more abundant. To highlight the relevance of methane in-gassing at the air-ice interface as a potential but still unconsidered pathway, we include estimates of the occurrence and frequency of young lead ice from satellite observations of leads during MOSAiC. [ABSTRACT FROM AUTHOR]

Automated sea ice charting from synthetic aperture radar (SAR) has been researched for more than a decade, and we are still not close to unlocking the full potential of automated solutions in terms of resolution and accuracy. The central complications arise from ground truth data not being readily available in the polar regions. In this paper, we build a data set from 20 near-coincident x-band SAR acquisitions and as many airborne laser scanner (ALS) measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), between October and May. This data set is then used to assess the accuracy and robustness of five machine-learning-based approaches by deriving classes from the freeboard, surface roughness (standard deviation at 0.5 m correlation length) and reflectance. It is shown that there is only a weak correlation between the radar backscatter and the sea ice topography. Accuracies between 44 % and 66 % and robustness between 71 % and 83 % give a realistic insight into the performance of modern convolutional neural network architectures across a range of ice conditions over 8 months. It also marks the first time algorithms have been trained entirely with labels from coincident measurements, allowing for a probabilistic class retrieval. The results show that segmentation models able to learn from the class distribution perform significantly better than pixel-wise classification approaches by nearly 20 % accuracy on average. [ABSTRACT FROM AUTHOR]

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. We estimated lead fractions from high-resolution divergence obtained from satellite synthetic aperture radar (SAR) data and evaluated them against existing lead products. We derived two new lead fraction products from divergence with a spatial resolution of 700 m calculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time instances. With those accumulated divergence-derived lead fractions, we comprehensively described the presence of up to 10 d old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of up to a few hundred meters. We presented a Lagrangian time series of the divergence-based lead fractions along the drift of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic Ocean during winter 2019–2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50–150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with six others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 order of magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application. [ABSTRACT FROM AUTHOR]

Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the one-year drift campaign MOSAiC in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in the description of the surface meltwater volume, necessary to estimate budgets, and used in model parametrization to simulate pond coverage evolution. However, observational data on pond depth is spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains entirely unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air—pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea-ice surface emerging from the increasingly available visual image data recorded from UAVs or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models. [ABSTRACT FROM AUTHOR]

Airborne laser scanners (ALS) are used to map the sea-ice surface at sub-meter resolution. We conducted 64 flights over the Arctic sea ice between September 2019 and September 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to measure sea-ice surface elevation. The flights ranged from repeated, local-scale 5 × 5 km2 floe grid surveys to regional-scale transects more than 100 km long. We provide data at different processing levels: geolocated elevation point clouds and gridded segments of elevation and freeboard with a spatial resolution of 0.5 m. The latter product is corrected for atmospheric backscatter, sea-ice drift, and offset in elevation due to degraded INS/GNSS solutions > 85° N. For floe grid surveys, all data are combined to merged two-dimensional elevation maps. Other provided parameters include laser reflectance and echo width. The presented data offer a unique possibility to study the temporal evolution, spatial distribution, and variability of the snow and sea-ice surface and their properties in addition to validating satellite products. [ABSTRACT FROM AUTHOR]

During the winter of 2019/2020, as the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project started its work, the Arctic Oscillation (AO) experienced some of its largest shifts, ranging from a highly negative index in November 2019 to an extremely positive index during January–February–March (JFM) 2020. The permanent positive AO phase for the 3 months of JFM 2020 was accompanied by a prevailing positive phase of the Arctic Dipole (AD) pattern. Here we analyze the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite-derived data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 was large SIT anomalies of up to 1.3 m that emerged in the Barents Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents and Kara seas (BKS), they are a result of enhanced ice growth connected with low-temperature anomalies and the consequence of intensified atmospherically driven sea ice transport and deformations (i.e., ice divergence and shear) in this area. The Davies Strait, the east coast of Greenland and the BS regions are characterized by convergence and divergence changes connected with thinner sea ice at the ice borders along with an enhanced impact of atmospheric wind forcing. Low-pressure anomalies that developed over the eastern Arctic during JFM 2020 increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds of up to 6 km d -1. As a consequence, sea ice transport and deformations driven by atmospheric surface wind forcing accounted for the bulk of the SIT anomalies, especially in January 2020 and February 2020. RASM intra-annual ensemble forecast simulations with 30 ensemble members forced with different atmospheric boundary conditions from 1 November 2019 through 30 April 2020 show a pronounced internal variability in the sea ice volume, driven by thermodynamic ice-growth and ice-melt processes and the impact of dynamic surface winds on sea ice formation and deformation. A comparison of the respective SIT distributions and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 corroborates the conclusion that winter sea ice conditions in the Arctic Ocean can be significantly altered by AO variability. [ABSTRACT FROM AUTHOR]

Knowledge of sea-ice thickness and volume depends on freeboard observations from satellite altimeters and in turn on information of snow mass and sea-ice density required for the freeboard-to-thickness conversion. These parameters, especially sea-ice density, are usually based on climatologies constructed from in situ observations made in the 1980s and earlier while contemporary and representative measurements are lacking. Our aim with this paper is to derive updated sea-ice bulk density estimates suitable for the present Arctic sea-ice cover and a range of ice types to reduce uncertainties in sea-ice thickness remote sensing. Our sea-ice density measurements are based on over 3000 km of high-resolution collocated airborne sea-ice and snow thickness and freeboard measurements in the western Arctic Ocean in 2017 and 2019. Sea-ice bulk density is derived assuming isostatic equilibrium for different ice types. Our results show higher average bulk densities for both first-year ice (FYI) and especially multi-year ice (MYI) compared to previous studies. In addition, we find a small difference between deformed and possibly unconsolidated FYI and younger MYI. We find a negative-exponential relationship between sea-ice bulk density and sea-ice freeboard and apply this parameterisation to one winter of monthly gridded CryoSat-2 sea-ice freeboard data. We discuss the suitability and the impact of the derived FYI and MYI bulk densities for sea-ice thickness retrievals and the uncertainty related to the indirect method of measuring sea-ice bulk density. The results suggest that retrieval algorithms be adapted to changes in sea-ice density and highlight the need of future studies to evaluate the impact of density parameterisation on the full sea-ice thickness data record. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 IPSO 25 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 IPSO 25 with a phytoplankton marker (i.e. the PIPSO 25 index) permits semi-quantitative sea-ice reconstructions and avoids misleading over- or underestimations of sea-ice cover. Comparisons of the PIPSO 25 -based sea-ice distribution patterns and TEX 86L - 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 IPSO 25 as an indicator for the former occurrence of platelet ice and/or the export of ice-shelf water. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 Arctic. [ABSTRACT FROM AUTHOR]

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 modeled ITD resembles the main characteristics of the observed ITD, including mode, e folding, and full width at half maximum. Thus, we demonstrate that high-resolution SAR deformation observations are capable of producing realistic ice thickness distributions. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: In the Canadian Arctic Archipelago tides influence the nutrient distribution, heat flux, and sea‐ice dynamics amid other processes. While most tidal models of the Arctic do not include the seasonal growth and melt of sea ice, we show that tides in the Kitikmeot Sea are greatly impacted by this. Tidal elevation and velocities from a moored current profiler in Dease Strait are damped 50%–65% during wintertime seasonal sea‐ice cover. In Victoria Strait (VS), the eastern gateway of the Kitikmeot Sea, thick, rough ice accumulates over the shallow sill. We use numerical models to show that our observed tidal damping in Dease Strait requires both large sea‐ice friction and a partial sea‐ice blockage in VS. Key Points: Tidal height and currents are damped >50% in winter, likely due to high sea‐ice friction and tidal‐induced sea‐ice blockages upstreamUpon entering the Kitikmeot Sea, the dominant Atlantic‐origin tides dissipate, resulting in relatively low tidal energyThe K1 tidal height is larger than the M2 tidal height in the western Kitikmeot Sea due to tidal resonance [ABSTRACT FROM AUTHOR]

Using airborne measurements, we provide a first direct glimpse of the sea ice thickness distribution in the western Ross Sea, Antarctica, where the distinguishing sea ice process is the regular occurrence of the Ross Sea, McMurdo Sound, and Terra Nova Bay polynyas. Two flights in November 2017 over a length of 800 km reveal a heavily deformed ice regime with a mean thickness of 2.0 ± 1.6 m. Supported by satellite image analysis, we identify regional variability in ice thickness based on formation history. Sea ice thickness gradients are highest within 100 and 200 km of the Terra Nova Bay and McMurdo Sound polynyas, respectively, where the mean thickness of the thickest 10% of ice is 7.6 m. Overall, about 80% of the ice is heavily deformed, concentrated in ridges with thicknesses of 3.0–11.8 m. This is evidence that sea ice is much thicker than in the central Ross Sea. Plain Language Summary: Antarctic sea ice is a stabilizing factor for global climate but has an unknown mass trend as thickness is particularly hard to measure. The western Ross Sea is an important region of sea ice formation; here, persistent off‐shore winds form so called coastal polynyas enabling continued freezing by pushing new ice out into the pack ice zone. Using a specialized instrument on a fixed wing aircraft, we measured in this region a mean sea ice thickness of 2 m over a distance of 800 km, which is much thicker than measured in the central Ross Sea. Making use of high‐resolution satellite images and aerial photos, we found that narrow deformational ridges grow up to 16 m in thickness and more rapidly than level ice. Such deformed ice holds up to 80% of the ice mass, which is quite easily overlooked by satellite sensors. Our observations hold a link between wind driven ice dynamics and the ice mass exported from the western Ross Sea, which with this new thickness data could be higher than previously thought. Providing this information, we establish a basis for change detection and the evaluation of computer simulations of Antarctic sea ice in a changing climate. Key Points: Airborne measurements of sea ice thickness in the Western Ross Sea reveal strongly deformed ice with a mean of 2.0 and a maximum of 15.6 mTime series of satellite images show evolution and deformation history of polynya‐derived pack ice along a total survey length of 800 kmSea ice thickness gradients are highest within 100–200 km of polynyas, where the mean thickness of the thickest 10% of ice is 7.6 m [ABSTRACT FROM AUTHOR]

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 mSm-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. [ABSTRACT FROM AUTHOR]

Local-scale variations in snow density and layering on Arctic sea ice were characterized using a combination of traditional snow pit and SnowMicroPen (SMP) measurements. In total, 14 sites were evaluated within the Canadian Arctic Archipelago and Arctic Ocean on both first-year (FYI) and multi-year (MYI) sea ice. Sites contained multiple snow pits with coincident SMP profiles as well as unidirectional SMP transects. An existing SMP density model was recalibrated using manual density cutter measurements (n=186) to identify best-fit parameters for the observed conditions. Cross-validation of the revised SMP model showed errors comparable to the expected baseline for manual density measurements (RMSE = 34 kg m -3 or 10.9 %) and strong retrieval skill (R2= 0.78). The density model was then applied to SMP transect measurements to characterize variations at spatial scales of up to 100 m. A supervised classification trained on snow pit stratigraphy allowed separation of the SMP density estimates by layer type. The resulting dataset contains 58 882 layer-classified estimates of snow density on sea ice representing 147 m of vertical variation and equivalent to more than 600 individual snow pits. An average bulk density of 310 kg m -3 was estimated with clear separation between FYI and MYI environments. Lower densities on MYI (277 kg m -3) corresponded with increased depth hoar composition (49.2 %), in strong contrast to composition of the thin FYI snowpack (19.8 %). Spatial auto-correlation analysis showed layered composition on FYI snowpack to persist over long distances while composition on MYI rapidly decorrelated at distances less than 16 m. Application of the SMP profiles to determine propagation bias in radar altimetry showed the potential errors of 0.5 cm when climatology is used over known snow density. [ABSTRACT FROM AUTHOR]

In September 2019, the research icebreaker Polarstern started the largest multidisciplinary Arctic expedition to date, the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) drift experiment. Being moored to an ice floe for a whole year, thus including the winter season, the declared goal of the expedition is to better understand and quantify relevant processes within the atmosphere–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 meteorological station indicate that the interplay of high ice export in late winter and exceptionally high air temperatures resulted in the longest ice-free summer period since reliable instrumental records began. We show, using a Lagrangian tracking tool and a thermodynamic sea ice model, that the MOSAiC floe carrying the Central Observatory (CO) formed in a polynya event north of the New Siberian Islands at the beginning of December 2018. The results further indicate that sea ice in the vicinity of the CO (<40 km distance) was younger and 36 % thinner than the surrounding ice with potential consequences for ice dynamics and momentum and heat transfer between ocean and atmosphere. Sea ice surveys carried out on various reference floes in autumn 2019 verify this gradient in ice thickness, and sediments discovered in ice cores (so-called dirty sea ice) around the CO confirm contact with shallow waters in an early phase of growth, consistent with the tracking analysis. Since less and less ice from the Siberian shelves survives its first summer (Krumpen et al., 2019), the MOSAiC experiment provides the unique opportunity to study the role of sea ice as a transport medium for gases, macronutrients, iron, organic matter, sediments and pollutants from shelf areas to the central Arctic Ocean and beyond. Compared to data for the past 26 years, the sea ice encountered at the end of September 2019 can already be classified as exceptionally thin, and further predicted changes towards a seasonally ice-free ocean will likely cut off the long-range transport of ice-rafted materials by the Transpolar Drift in the future. A reduced long-range transport of sea ice would have strong implications for the redistribution of biogeochemical matter in the central Arctic Ocean, with consequences for the balance of climate-relevant trace gases, primary production and biodiversity in the Arctic Ocean. [ABSTRACT FROM AUTHOR]

The gridded sea ice thickness (SIT) climate data record (CDR) produced by the European Space Agency (ESA) Sea Ice Climate Change Initiative Phase 2 (CCI-2) is the longest available, Arctic-wide SIT record covering the period from 2002 to 2017. SIT data are based on radar altimetry measurements of sea ice freeboard from the Environmental Satellite (ENVISAT) and CryoSat-2 (CS2). The CCI-2 SIT has previously been validated with in situ observations from drilling, airborne remote sensing, electromagnetic (EM) measurements and upward-looking sonars (ULSs) from multiple ice-covered regions of the Arctic. Here we present the Laptev Sea CCI-2 SIT record from 2002 to 2017 and use newly acquired ULS and upward-looking acoustic Doppler current profiler (ADCP) sea ice draft (VAL) data for validation of the gridded CCI-2 and additional satellite SIT products. The ULS and ADCP time series provide the first long-term satellite SIT validation data set from this important source region of sea ice in the Transpolar Drift. The comparison of VAL sea ice draft data with gridded monthly mean and orbit trajectory CCI-2 data, as well as merged CryoSat-2–SMOS (CS2SMOS) sea ice draft, shows that the agreement between the satellite and VAL draft data strongly depends on the thickness of the sampled ice. Rather than providing mean sea ice draft, the considered satellite products provide modal sea ice draft in the Laptev Sea. Ice drafts thinner than 0.7 m are overestimated, while drafts thicker than approximately 1.3 m are increasingly underestimated by all satellite products investigated for this study. The tendency of the satellite SIT products to better agree with modal sea ice draft and underestimate thicker ice needs to be considered for all past and future investigations into SIT changes in this important region. The performance of the CCI-2 SIT CDR is considered stable over time; however, observed trends in gridded CCI-2 SIT are strongly influenced by the uncertainties of ENVISAT and CS2 and the comparably short investigation period. [ABSTRACT FROM AUTHOR]

In the last decades, changing climate conditions have had a severe impact on sea ice at the western Antarctic Peninsula (WAP), an area rapidly transforming under global warming. To study the development of spring sea ice and environmental conditions in the pre-satellite era we investigated three short marine sediment cores for their biomarker inventory with a particular focus on the sea ice proxy IPSO 25 and micropaleontological proxies. The core sites are located in the Bransfield Strait in shelf to deep basin areas characterized by a complex oceanographic frontal system, coastal influence and sensitivity to large-scale atmospheric circulation patterns. We analyzed geochemical bulk parameters, biomarkers (highly branched isoprenoids, glycerol dialkyl glycerol tetraethers, sterols), and diatom abundances and diversity over the past 240 years and compared them to observational data, sedimentary and ice core climate archives, and results from numerical models. Based on biomarker results we identified four different environmental units characterized by (A) low sea ice cover and high ocean temperatures, (B) moderate sea ice cover with decreasing ocean temperatures, (C) high but variable sea ice cover during intervals of lower ocean temperatures, and (D) extended sea ice cover coincident with a rapid ocean warming. While IPSO 25 concentrations correspond quite well to satellite sea ice observations for the past 40 years, we note discrepancies between the biomarker-based sea ice estimates, the long-term model output for the past 240 years, ice core records, and reconstructed atmospheric circulation patterns such as the El Niño–Southern Oscillation (ENSO) and Southern Annular Mode (SAM). We propose that the sea ice biomarker proxies IPSO 25 and PIPSO 25 are not linearly related to sea ice cover, and, additionally, each core site reflects specific local environmental conditions. High IPSO 25 and PIPSO 25 values may not be directly interpreted as referring to high spring sea ice cover because variable sea ice conditions and enhanced nutrient supply may affect the production of both the sea-ice-associated and phytoplankton-derived (open marine, pelagic) biomarker lipids. For future interpretations we recommend carefully considering individual biomarker records to distinguish between cold sea-ice-favoring and warm sea-ice-diminishing environmental conditions. [ABSTRACT FROM AUTHOR]

During the 2018 Multidisciplinary Arctic Program‐Last Ice in the Lincoln Sea, we sampled 45 multiyear ice (MYI) and 34 first‐year ice (FYI) cores, combined with snow depth, ice thickness, and transmittance surveys from adjacent level FYI and undeformed MYI. FYI sites show a decoupling between bottom‐ice chlorophyll a (chl a) and snow depth; however, MYI showed a significant correlation between ice‐algal chl a biomass and snow depth. Topographic control of the snow cover resulted in greater spatiotemporal variability of the snow over the level FYI, and consequently transmittance, compared to MYI with an undulating surface. The coupled patterns of snow depth, transmittance, and chl a indicate that MYI provides an environment with more stable light conditions for ice algal growth. The importance of sea ice surface topography for ice algal habitat underpins the potential ecological changes associated with projected increased ice dynamics and deformation. Plain Language Summary: This study presents first results from the 2018 Multidisciplinary Arctic Program‐Last Ice, the most intensive ecologically focused research project ever conducted within the so‐called "Last Ice Area." This region is of key importance because it is the only place in the Arctic expected to retain summer sea ice by the year 2050. Continued changes to the sea ice environment will have ecological consequences because sea ice is an important habitat for many animals from microscopic ice algae, the base of the food chain, to seals and polar bears. Since the older ice is being replaced by younger ice, we compared older ice to younger ice in order to provide a glimpse into the future. We found that the older ice has a more stable light environment for ice algae due to snow depth patterns associated with surface topography. This can mean that as the older ice is replaced by newer ice, the availability of ice algae as a food source may become more unpredictable. The importance of surface topography for ice algae indicates that the projected acceleration in sea ice drift and increased ridging due to thinner ice will likely have an impact on key sea ice habitat properties. Key Points: Spatiotemporal changes in snow cover and transmittance were observed for FYI but remained stable for MYI due to differences in topographyThe spatial distribution of bottom‐ice chl a biomass was coupled to snow depth and transmittance in MYI but decoupled in FYIA projected shift to a more dynamic and deformed sea ice cover is likely to be a key driver of ice‐algal habitat variability in the future [ABSTRACT FROM AUTHOR]

We combine Eulerian ice draft observations from moored ice‐profiling sonars with buoy‐ and satellite‐derived ice drift data to obtain Lagrangian observations of changes in the thickness distribution of sea ice circulating the Beaufort Sea. We examine repeat measurements of ice draft by identifying events where buoys or pseudobuoys made repeat overpasses within 30 km of ice‐profiling sonar‐equipped Beaufort Gyre Exploration Project moorings. Comparison of ice draft distributions from each overpass indicates that summertime melt rates are related to drift track, with more melt occurring in the southern Beaufort Sea than to the north. Additionally, we find that ice surviving summer in the Beaufort Sea since 2007 is similar in thickness to surrounding first‐year sea ice by the end of the following winter. These findings are supported by continuous ice thickness data from ice mass balance buoys. By examining "plumes" of pseudobuoys originating at each mooring location, we identify anomalous northward transport of ice in the southern Beaufort Sea in 2007 that likely contributed to the record‐breaking reduction in sea ice extent that year. We also find that repeat overpasses have been much rarer since 2007, due to reduced summertime sea ice extent in the Beaufort Gyre and possible changes in ice drift patterns. These changes contribute to diminished replenishment of multiyear sea ice volume in the Arctic. Plain Language Summary: Using ice motion data from buoys and satellites, we track sea ice as it circulates in the Beaufort Gyre and measure changes in its thickness as it passes over moored upward looking sonars. Our results show that ice drifting through the southern Beaufort Sea in summer experiences significant thinning and that multiyear ice surviving the summer does not grow much thicker than first‐year ice even after multiple winters. We also find that the northward retreat of the summertime ice edge in Beaufort Sea is leading to a reduced likelihood of ice recirculating and growing older and thicker in the Beaufort Gyre. Together, these changes make any recovery of the Arctic ice pack increasingly unlikely. Key Points: Sea ice in the Beaufort Gyre is tracked as it drifts over upward looking sonars to derive Lagrangian changes in its thickness distributionSea ice traversing the Beaufort Sea south of ~75°N experiences significantly greater melt since 2007 than ice to the northBy the end of winter, perennial ice surviving summer in the Beaufort Gyre is similar in thickness to first‐year ice grown in just one season [ABSTRACT FROM AUTHOR]

Organic geochemical and micropaleontological analyses of surface sediments collected in the southern Drake Passage and the Bransfield Strait, Western Antarctic Peninsula, enable a proxy-based reconstruction of recent sea ice conditions in this climate-sensitive area. We study the distribution of the sea ice biomarker IPSO 25 , and biomarkers of open marine environments such as more unsaturated highly branched isoprenoid alkenes and phytosterols. Comparison of the sedimentary distribution of these biomarker lipids with sea ice data obtained from satellite observations and diatom-based sea ice estimates provide for an evaluation of the suitability of these biomarkers to reflect recent sea surface conditions. The distribution of IPSO 25 supports earlier suggestions that the source diatom seems to be common in near-coastal environments characterized by annually recurring sea ice cover, while the distribution of the other biomarkers is highly variable. Offsets between sea ice estimates deduced from the abundance of biomarkers and satellite-based sea ice data are attributed to the different time intervals recorded within the sediments and the instrumental records from the study area, which experienced rapid environmental changes during the past 100 years. To distinguish areas characterized by permanently ice-free conditions, seasonal sea ice cover and extended sea ice cover, we apply the concept of the PIP 25 index from the Arctic Ocean to our data and introduce the term PIPSO 25 as a potential sea ice proxy. While the trends in PIPSO 25 are generally consistent with satellite sea ice data and winter sea ice concentrations in the study area estimated by diatom transfer functions, more studies on the environmental significance of IPSO 25 as a Southern Ocean sea ice proxy are needed before this biomarker can be applied for semi-quantitative sea ice reconstructions. [ABSTRACT FROM AUTHOR]

The timing and intensity of snowmelt processes on sea ice are key drivers determining the seasonal sea-ice energy and mass budgets. In the Arctic, satellite passive microwave and radar observations have revealed a trend towards an earlier snowmelt onset during the last decades, which is an important aspect of Arctic amplification and sea-ice decline. Around Antarctica, snowmelt on perennial ice is weak and very different than in the Arctic, with most snow surviving the summer. Here we compile time series of snowmelt onset dates on seasonal and perennial Antarctic sea ice from 1992 to 2014/15 using active microwave observations from the European Space Agency's (ESA) European Remote Sensing (ERS) 1 and 2 missions (ERS-1 and ERS-2), Quick Scatterometer (QSCAT), and Advanced Scatterometer (ASCAT) radar scatterometers. We define two snowmelt transition stages: a weak backscatter rise, indicating the initial warming and destructive metamorphism of the snowpack (pre-melt), followed by a rapid backscatter rise, indicating the onset of thaw–freeze cycles (snowmelt). Results show large interannual variability, with an average pre-melt onset date of 29 November and melt onset of 10 December, respectively, on perennial ice, without any significant trends over the study period, consistent with the small trends of Antarctic sea-ice extent. There was a latitudinal gradient from early snowmelt onsets in mid-November in the northern Weddell Sea to late (end of December) or even absent snowmelt conditions in the southern Weddell Sea. We show that QSCAT Ku-band-derived (13.4 GHz signal frequency) pre-melt and snowmelt onset dates are earlier by 20 and 18 d, respectively, than ERS and ASCAT C-band-derived (5.6 GHz) dates. This offset has been considered when constructing the time series. Snowmelt onset dates from passive microwave observations (37 GHz) are later by 14 and 6 d than those from the scatterometers, respectively. Based on these characteristic differences between melt onset dates observed by different microwave wavelengths, we developed a conceptual model which illustrates how the seasonal evolution of snow temperature profiles may affect different microwave bands with different penetration depths. These suggest that future multi-frequency active and passive microwave satellite missions could be used to resolve melt processes throughout the vertical snow column of thick snow on perennial Antarctic sea ice. [ABSTRACT FROM AUTHOR]

Observations of sea-ice concentration are available from satellites year-round and almost weather-independently using passive microwave radiometers at resolutions down to 5 km. Thermal infrared radiometers provide data with a resolution of 1 km but only under cloud-free conditions. We use the best of the two satellite measurements and merge thermal infrared and passive microwave sea-ice concentrations. This yields a merged sea-ice concentration product combining the gap-free spatial coverage of the passive microwave sea-ice concentration and the 1 km resolution of the thermal infrared sea-ice concentration. The benefit of the merged product is demonstrated by observations of a polynya which opened north of Greenland in February 2018. We find that the merged sea-ice concentration product resolves leads at sea-ice concentrations between 60 % and 90 %. They are not resolved by the coarser passive microwave sea-ice concentration product. The benefit of the merged product is most pronounced during the formation of the polynya. Next, the environmental conditions during the polynya event are analysed. The polynya was caused by unusual southerly winds during which the sea ice drifted northward instead of southward as usual. The daily displacement was 50 % stronger than normal. The polynya was associated with a warm-air intrusion caused by a high-pressure system over the Eurasian Arctic. Surface air temperatures were slightly below 0 ∘ C and thus more than 20 ∘ C higher than normal. Two estimates of thermodynamic sea-ice growth yield sea-ice thicknesses of 60 and 65 cm at the end of March in the area opened by the polynya. This differed from airborne sea-ice thickness measurements, indicating that sea-ice growth processes in the polynya are complicated by rafting and ridging. A sea-ice volume of 33 km3 was produced thermodynamically. [ABSTRACT FROM AUTHOR]

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Organic geochemical and micropaleontological analyses of surface sediments collected in the southern Drake Passage and the Bransfield Strait, Antarctic Peninsula, enable a proxy-based reconstruction of recent sea ice conditions in this climate sensitive area. The distribution of the sea ice biomarker IPSO25 supports earlier suggestions that the source diatoms seem to be common in near-coastal environments characterized by an annually recurring sea ice cover. We here propose and evaluate the combination of IPSO25 with a more unsaturated highly branched isoprenoid alkene and phytosterols and introduce the PIPSO25 index as a potentially semi-quantitative sea ice proxy. This organic geochemical approach is complemented with diatom data. PIPSO25 sea ice estimates are used to discriminate between areas characterized by permanently ice-free conditions, seasonal sea ice cover and extended sea ice cover. These trends are consistent with satellite sea ice data and winter sea ice concentrations estimated by diatom transfer functions. Minor offsets between proxy-based and satellite-based sea ice data are attributed to the different time intervals recorded within the sediments and the instrumental records from the study area, which experienced rapid environmental changes during the past 100 years. [ABSTRACT FROM AUTHOR]

To better understand recent changes of Arctic sea ice thickness and extent, it is important to distinguish between the contributions of winter growth and summer melt to the sea ice mass balance. In this study we present a Lagrangian approach to quantify summer sea ice melt in which multiyear ice (MYI) floes that were surveyed by airborne electromagnetic thickness sounding within Nares Strait during summer were backtracked, using satellite imagery, to a region in close proximity (3–20 km) to spring ice thickness surveys carried out in the Lincoln Sea. Typical modal total MYI thicknesses, including ~0.4‐m snow, ranged between 3.9 and 4.7 m in the Lincoln Sea during April. Ice‐only modal thicknesses were between 2.2 and 3.0 m in Nares Strait during August. Total thinning including snow and ice was 1.3 ± 0.1 m including 0.4 ± 0.09 m of snow melt and 0.9 ± 0.2 m of ice melt. This translates to a seasonal net heat input of 305 ± 69 MJ/m2 (262 ± 60 MJ/m2 for ice only) and seasonal net heat flux of 57 ± 13 W/m2 (45 ± 10 W/m2 for ice only), which is unlikely to be explained by solar radiation fluxes alone. Furthermore, our approach provides an improvement on traditional ice mass balance buoy estimates because it integrates melt over larger spatial scales, where melt can be highly variable due to differential melt experienced between melt ponds, bare ice, hummocks, and ridges. Plain Language Summary: Some of the oldest and thickest sea ice remains in a small region between Canada, Greenland and the North Pole, the so‐called "Last Ice Area", and will retain this ice longest into the future. Thus, continued monitoring of this unique sea ice habitat is crucial in order to document ongoing changes in the physical environment and to better predict the fate of many animals that depend on sea ice for survival (e.g., polar bears and seals). In this study, we compared sea ice thickness measurements from spring and summer to provide a better understanding of how the ice changes from season to season. Ice thickness changes provide important information on the Arctic Ocean's energy budget, a good indicator of the health of the Arctic Ocean. Our measurements are particularly important because they are the first of their kind over old, thick ice during summer in this unique region. We showed that 0.9 m of old sea ice melted from spring to summer. Although this is comparable to previous studies of old ice, it is important to continue these measurements in order document the expected ongoing changes to the sea ice environment and monitor the health of the Arctic Ocean. Key Points: MYI surveyed in the Lincoln Sea during spring had modal thicknesses of 3.9‐4.7 m, which thinned to 2.2‐3.0 m in summer in Nares StraitBacktracking individual floes with satellite images was used to reconstruct positions of the same ice fields surveyed in spring and summerEstimated sea ice melt was 0.9 +/‐ 0.2 m, slightly higher than observations by ice mass balance buoys for the same region [ABSTRACT FROM AUTHOR]

While variations of Baltic Sea ice extent and thickness have been extensively studied, there is little information about drift ice thickness, distribution, and its variability. In our study, we quantify the interannual variability of sea ice thickness in the Bay of Bothnia during the years 2003–2016. We use various different data sets: official ice charts, drilling data from the regular monitoring stations in the coastal fast ice zone, and helicopter and shipborne electromagnetic soundings. We analyze the different data sets and compare them to each other to characterize the interannual variability, to discuss the ratio of level and deformed ice, and to derive ice thickness distributions in the drift ice zone. In the fast ice zone the average ice thickness is 0.58±0.13 m. Deformed ice increases the variability of ice conditions in the drift ice zone, where the average ice thickness is 0.92±0.33 m. On average, the fraction of deformed ice is 50 % to 70 % of the total volume. In heavily ridged ice regions near the coast, mean ice thickness is approximately half a meter thicker than that of pure thermodynamically grown fast ice. Drift ice exhibits larger interannual variability than fast ice. [ABSTRACT FROM AUTHOR]

The Canadian Sea Ice and Snow Evolution (Can- SISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time. [ABSTRACT FROM AUTHOR]

Abstract: Spring melt pond fraction (fp) has been shown to influence September sea ice extent and, with a growing need to improve melt pond physics in climate and forecast models, observations at large spatial scales are needed. We present a novel technique for estimating fp on sea ice at high spatial resolution from the Sentinel‐1 satellite during the winter period leading up to spring melt. A strong correlation (r = −0.85) is found between winter radar backscatter and fp from first‐year and multiyear sea ice data collected in the Canadian Arctic Archipelago (CAA) in 2015. Observations made in the CAA in 2016 are used to validate a fp retrieval algorithm, and a fp prediction for the CAA in 2017 is made. The method is effective using the horizontal transmit and receive polarization channel only and shows promise for providing seasonal, pan‐Arctic, fp maps for improved understanding of melt pond distributions and forecast model skill. [ABSTRACT FROM AUTHOR]

Sea ice monitoring and classification is one of the main applications of Synthetic Aperture Radar (SAR) remote sensing. C-band SAR imagery is regarded as an optimal choice for sea ice applications; however, other SAR frequencies has not been extensively assessed. In this study, we evaluate the potential of fully polarimetric L-band SAR imagery for monitoring and classifying sea ice during dry winter conditions compared to fully polarimetric C-band SAR. Twelve polarimetric SAR parameters are derived using sets of C- and L-band SAR imagery and the capabilities of the derived parameters for the discrimination between First Year Ice (FYI) and Old Ice (OI), which is considered to be a mixture of Second Year Ice (SYI) and Multiyear Ice (MYI), are investigated. Feature vectors of effective C- and L-band polarimetric parameters are extracted and used for sea ice classification. Results indicate that C-band SAR provides high classification accuracy (98.99%) of FYI and OI in comparison to the obtained accuracy using L-band SAR (82.17% and 81.85%), as expected. However, L-band SAR was found to classify only the MYI floes as OI, while merging both FYI and SYI into one separate class. This comes in contrary to C-band SAR, which classifies as OI both MYI and SYI. This indicates a new potential for discriminating SYI from MYI by combining C- and L-band SAR in dry ice winter conditions. [ABSTRACT FROM AUTHOR]

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high-frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multisensor oceanographic time series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04 and DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, intersatellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m. [ABSTRACT FROM AUTHOR]

In April 2017, we collected unique, extensive in situ data of sea ice and snow thickness. At 10 sampling sites, located under a CryoSat-2 overpass, between Ellesmere Island and 87.1°N mean and modal total ice thicknesses ranged between 2 to 3.4 m and 1.8 to 2.9 m, respectively. Coincident snow thicknesses ranged between 0.3 to 0.47 m (mean) and 0.1 to 0.5 m (mode). The profile spanned the complete multiyear ice zone in the Lincoln Sea, into the first-year ice zone farther north. Complementary snow thickness measurements near the North Pole showed a mean thickness of 0.31 m. Compared with scarce measurements from other years, multiyear ice was up to 0.75 m thinner than in 2004, but not significantly different from 2011 and 2014. We found excellent agreement with a commonly used snow climatology and with published long-term ice thinning rates. There was reasonable agreement with CryoSat-2 thickness retrievals. [ABSTRACT FROM AUTHOR]

Snow thickness on sea ice is a largely undersampled parameter yet of importance for the sea ice mass balance and for satellite-based sea ice thickness estimates and thus our general understanding of global ice volume change. Traditional direct thickness measurements with meter sticks can provide accurate but only spot information, referred to as 'needles' due to their pinpoint focus and information, while airborne and satellite remote sensing snow products, referred to as 'the haystack,' have large uncertainties due to their scale. We demonstrate the remarkable accuracy and applicability of ground-penetrating radar (GPR) snow thickness measurements by comparing them with in situ meter stick data from two field campaigns to Antarctica in late winter/early spring. The efficiency and millimeter-to-centimeter accuracy of GPR enables practitioners to acquire extensive, semiregional data with the potential to upscale needles to the haystack and to potentially calibrate satellite remote sensing products that we confirm to derive roughly 30% of the in situ thickness. We find the radar wave propagation velocity in snow to be rather constant (± 6%), encouraging regional snow thickness surveys. Snow thinner than 10 cm is under the detection limit with the off-the-shelf GPR setup utilized in our study. [ABSTRACT FROM AUTHOR]

We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice. [ABSTRACT FROM AUTHOR]

With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice–associated production than generally assumed. [ABSTRACT FROM AUTHOR]

Bacterial communities in Arctic sea ice play an important role in the regulation of nutrient and energy dynamics in the Arctic Ocean. Sea ice has vertical gradients in temperature, brine salinity and volume, and light and UV levels. Multiyear ice (MYI) has at least two distinct ice layers: old fresh ice with limited permeability, and new saline ice, and may also include a surface melt pond layer. Here, we determine whether bacterial communities (1) differ with ice depth due to strong physical and chemical gradients, (2) are relatively homogenous within a layer, but differ between layers, or (3) do not vary with ice depth. Cores of MYI off northern Ellesmere Island, NU, Canada, were subsectioned in 30-cm intervals, and the bacterial assemblage structure was characterized using 16S rRNA gene pyrotag sequencing. Assemblages clustered into three distinct groups: top (0-30 cm); middle (30-150 cm); and bottom (150-236 cm). These layers correspond to the occurrence of refrozen melt pond ice, at least 2-year-old ice, and newly grown first-year ice at the bottom of the ice sheet, respectively. Thus, MYI houses multiple distinct bacterial assemblages, and in situ conditions appear to play a less important role in structuring microbial assemblages than the age or conditions of the ice at the time of formation. [ABSTRACT FROM AUTHOR]