Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover and fast ice decay

Ice retreat in the eastern Eurasian Arctic is a consequence of atmospheric and oceanic processes and regional feedback mechanisms acting on the ice cover, both in winter and summer. A correct representation of these processes in numerical models is important, since it will improve predictions of sea ice anomalies along the Northeast Passage and beyond. In this study, we highlight the importance of winter ice dynamics for local summer sea ice anomalies in thickness, volume and extent. By means of airborne sea ice thickness surveys made over pack ice areas in the south-eastern Laptev Sea, we show that years of offshore-directed sea ice transport have a thinning effect on the late-winter sea ice cover. To confirm the preconditioning effect of enhanced offshore advection in late winter on the summer sea ice cover, we perform a sensitivity study using a numerical model. Results verify that the preconditioning effect plays a bigger role for the regional ice extent. Furthermore, they indicate an increase in volume export from the Laptev Sea as a consequence of enhanced offshore advection, which has far-reaching consequences for the entire Arctic sea ice mass balance. Moreover we show that ice dynamics in winter not only preconditions local summer ice extent, but also accelerate fast-ice decay

Selected Aspect of the Arctic Sea Ice Motion and Its influence on the ocean

A faithful simulation of the sea ice drift in a coupled sea ice-ocean model is one of the key prerequisites for a reliable simulation of the sea ice, ocean and atmosphere interactions. To achieve this goal we should continue improving model physics and constructing parameterizations for relevant sub-gird processes. Also a validation of the simulations against the observational data is essential. The main aim of this work is to demonstrate the importance of the sea ice motion for the underlaying ocean. In the scope of the ongoing and anticipated Arctic climate change it has been demonstrated that the changes in the atmosphere and ocean have large impacts on the sea ice cover. At present, it is still unclear if the changes in the sea ice motion itself can also have a feedback effect on the ocean. In this work we hypothesize that a change in the sea ice motion can cause significant changes in the ocean properties and circulation. To test the hypothesis we use two sensitivity studies that help to isolate sea ice motion processes and quantify the contribution of the process to the Arctic climate system. Our main results show that the immobile landfast ice in the model simulation shifts the flaw polynya, location of strong winter sea ice and brine production away from the coast in the more saline ocean waters and more brine reaches the Arctic halocline. This strengthens the halocline that shields cold surface waters and sea ice from the warm Atlantic Water layer underneath. In addition we find that a general change in the sea ice internal strength leads to substantial changes in the ocean properties and circulation. Under weaker and more mobile sea ice Atlantic Water layer temperatures are reduced by 0.2 K. The Eurasian basin circulation in the Atlantic Water layer is increased and this leads to the volume transports adjustments at the Arctic Straits. This effect shows that the Arctic sea ice properties and motion are not only important for the Arctic ocean, but may have consequences also for the global ocean circulation

Sea Ice Mass Balance Buoys (IMBs): Introduction to working group and Data Processing Intercomparison Study

IMBs are autonomous instruments able to continuously monitor the growth and melt of sea ice and its snow cover at a single point on an ice floe. Complementing field expeditions, remote sensing observations and modelling studies, these in-situ data are crucial to assess the mass balance and seasonal evolution of sea ice and snow in the polar oceans. Established subtypes of IMBs combine coarse-resolution temperature profiles through air, snow, ice and ocean with ultrasonic pingers to detect snow accumulation and ice thermodynamic growth. Recent technological advancements enable the use of high-resolution temperature chains, which are also able to identify the surrounding medium through a „heating cycle“. The temperature change during this heating cycle provides additional information on the internal properties and processes of the ice. However, a unified data processing technique to reliably and accurately determine sea ice thickness and snow depth from this kind of data is still missing, and an unambiguous interpretation remains a challenge. Following the need to improve techniques for remotely measuring sea ice mass balance, an international IMB working group has recently been established. The main goals are 1) to coordinate IMB deployments, 2) to enhance current IMB data processing and –interpretation techniques, and 3) to provide standardized IMB data products to a broader community. Here we present first results from two different data processing algorithms, applied to selected IMB datasets from the Arctic and Antarctic. Their performance with regard to sea ice thickness and snow depth retrieval is evaluated, and an uncertainty is determined. Although there are many challenges and caveats in IMB data processing and -interpretation techniques, such datasets bear great potential and yield plenty of useful information about sea ice properties and processes. It is planned to include many more algorithms from contributors within the working group, and we explicitly invite other interested scientists to join this promising effort

Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture

We provide sea ice classification maps of a subweekly time series of single (horizontal–horizontal, HH) polarization X-band TerraSAR-X scanning synthetic aperture radar (TSX SC) images from November 2019 to March 2020, covering the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This classified time series benefits from the wide spatial coverage and relatively high spatial resolution of TSX SC data and is a useful basic dataset for future MOSAiC studies on physical sea ice processes and ocean and climate modeling. Sea ice is classified into leads, young ice with different backscatter intensities, and first-year ice (FYI) or multiyear ice (MYI) with different degrees of deformation. We establish the per-class incidence angle (IA) dependencies of TSX SC intensities and gray-level co-occurrence matrix (GLCM) textures and use a classifier that corrects for the class-specific decreasing backscatter with increasing IAs, with both HH intensities and textures as input features. Optimal parameters for texture calculation are derived to achieve good class separation while maintaining maximum spatial detail and minimizing textural collinearity. Class probabilities yielded by the classifier are adjusted by Markov random field contextual smoothing to produce classification results. The texture-based classification process yields an average overall accuracy of 83.70 % and good correspondence to geometric ice surface roughness derived from in situ ice thickness measurements (correspondence consistently close to or higher than 80 %). A positive logarithmic relationship is found between geometric ice surface roughness and TSX SC HH backscatter intensity, similar to previous C- and L-band studies. Areal fractions of classes representing ice openings (leads and young ice) show prominent increases in middle to late November 2019 and March 2020, corresponding well to ice-opening time series derived from in situ data in this study and those derived from satellite synthetic aperture radar (SAR) and optical data in other MOSAiC studies

Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N-ICE2015 North of Svalbard

In recent years, sea-ice conditions in the Arctic Ocean changed substantially toward a younger and thinner sea-ice cover. To capture the scope of these changes and identify the differences between individual regions, in situ observations from expeditions are a valuable data source. We present a continuous time series of in situ measurements from the N-ICE2015 expedition from January to June 2015 in the Arctic Basin north of Svalbard, comprising snow buoy and ice mass balance buoy data and local and regional data gained from electromagnetic induction (EM) surveys and snow probe measurements from four distinct drifts. The observed mean snow depth of 0.53 m for April to early June is 73% above the average value of 0.30 m from historical and recent observations in this region, covering the years 1955–2017. The modal total ice and snow thicknesses, of 1.6 and 1.7 m measured with ground-based EM and airborne EM measurements in April, May, and June 2015, respectively, lie below the values ranging from 1.8 to 2.7 m, reported in historical observations from the same region and time of year. The thick snow cover slows thermodynamic growth of the underlying sea ice. In combination with a thin sea-ice cover this leads to an imbalance between snow and ice thickness, which causes widespread negative freeboard with subsequent flooding and a potential for snow-ice formation. With certainty, 29% of randomly located drill holes on level ice had negative freeboard

The Future of the Arctic: What Does It Mean for Sea Ice and Small Creatures?

The warming of our planet is changing the Arctic dramatically. The area covered by sea-ice is shrinking and the ice that is left is younger and thinner. We took part in an expedition to the Arctic, to study how these changes affect organisms living in and under the ice. Following this expedition, we found that storms can more easily break the thinner ice. Storms form cracks in the sea ice, allowing sunlight to pass into the water below, which makes algal growth possible. Algae are microscopic “plants” that grow in water or sea ice. Storms also brought thick heavy snow, which pushed the ice surface below the water. This flooded the snow and created slush. We discovered that this slush is another good habitat for algae. If Arctic sea ice continues to thin, and storms become more common, we expect that these algal habitats will become more important in the future

Contribution of deformation to sea-ice mass balance: a case study from an N-ICE2015 storm

The fastest and most efficient process of gaining sea ice volume is through the mechanical redistribution of mass as a consequence of deformation events. During the ice growth season divergent motion produces leads where new ice grows thermodynamically, while convergent motion fractures the ice and either piles the resultant ice blocks into ridges or rafts one floe under the other. Here we present an exceptionally detailed airborne dataset from a 9km2 area of first and second year ice in the Transpolar Drift north of Svalbard that allowed us to estimate the redistribution of mass from an observed deformation event. To achieve this level of detail we analyzed changes in sea ice freeboard acquired from two airborne laser scanner surveys just before and right after a deformation event brought on by a passing low pressure system. A linear regression model based on divergence during this storm can explain 64% of freeboard variability. Over the survey region we estimated that about 1.3% of level sea ice volume was pressed together into deformed ice and the new ice formed in leads in a week after the deformation event would increase the sea ice volume by 0.5%. As the region is impacted by about 15 storms each winter a simple linear extrapolation would result in about 7% volume increase and 20% deformed ice fraction at the end of the seaso

Thin ice and storms: Sea ice deformation from buoy arrays deployed during N-ICE2015

Arctic sea ice has displayed significant thinning as well as an increase in drift speed in recent years. Taken together this suggests an associated rise in sea ice deformation rate. A winter and spring expedition to the sea ice covered region north of Svalbard – the Norwegian young sea ICE 2015 expedition (N-ICE2015) - gave an opportunity to deploy extensive buoy arrays and to monitor the deformation of the first- and second-year ice now common in the majority of the Arctic Basin. During the 5-month long expedition, the ice cover underwent several strong deformation events, including a powerful storm in early February that damaged the ice cover irreversibly. The values of total deformation measured during N-ICE2015 exceed previously measured values in the Arctic Basin at similar scales: At 100 km scale, N-ICE2015 values averaged above 0.1, day−1, compared to rates of 0.08 day −1 or less for previous buoy arrays. The exponent of the power law between the deformation length scale and total deformation developed over the season from 0.37 to 0.54 with an abrupt increase immediately after the early February storm, indicating a weakened ice cover with more free drift of the sea ice floes. Our results point to a general increase in deformation associated with the younger and thinner Arctic sea ice and to a potentially destructive role of winter storms

Different mechanisms of Arctic first-year sea-ice ridge consolidation observed during the MOSAiC expedition

Sea-ice ridges constitute a large fraction of the ice volume in the Arctic Ocean, yet we know little about the evolution of these ice masses. Here we examine the thermal and morphological evolution of an Arctic firstyear sea-ice ridge, from its formation to advanced melt. Initially the mean keel depth was 5.6 m and mean sail height was 0.7 m. The initial rubble macroporosity (fraction of seawater filled voids) was estimated at 29% from ice drilling and 43%–46% from buoy temperature. From January until mid-April, the ridge consolidated slowly by heat loss to the atmosphere and the total consolidated layer growth during this phase was 0.7 m. From mid-April to mid-June, there was a sudden increase of ridge consolidation rate despite no increase in conductive heat flux. We surmise this change was related to decreased macroporosity due to transport of snow-slush to the ridge keel rubble via adjacent open leads. In this period, the mean thickness of the consolidated layer increased by 2.1 m. At the peak of melt in June–July we suggest that the consolidation was related to the refreezing of surface snow and ice meltwater and of ridge keel meltwater (the latter only about 15% of total consolidation). We used the morphology parameters of the ridge to calculate its hydrostatic equilibrium and obtained a more accurate estimate of the actual consolidation of the keel, correcting from 2.2 m to 2.8 m for average keel consolidation. This approach also allowed us to estimate that the average keel melt of 0.3 m, in June–July, was accompanied by a decrease in ridge draft of 0.9 m. An ice mass balance buoy in the ridge indicated total consolidation of 2.8 m, of which 2.1 m was related to the rapid mode of consolidation from April to June. By mid-June, consolidation resulted in a drastic decrease of the macroporosity of the interior of keel while the flanks had little or no change in macroporosity. These results are important to understanding the role of ridge keels as meltwater sources and sinks and as sanctuary for ice-associated organisms in Arctic pack ice