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Sea ice plays a key role setting up a climate state of the Polar Oceans through moderating interactions between the ocean and atmosphere. As it is seen from satellite data, on the synoptic and sub-seasonal time-scales sea ice partly moves as a solid body – large areas of sea ice cover drift as single polygons – and partly deforms as a plastic material, shearing along the deformation lines – linear kinematic features (leads). Leads are important for the heat fluxes and also for navigational safety.In this study we focus on winter sea ice. Currently sea ice is thinning and more deformable; thinner ice is easier to crack. We compare the effect of different rheologies on sea ice and have developed a very high resolution (1 km) Arctic model, which allows for examining lead formation. The model shows a step change in behaviour compared to the previous high-resolution configuration (3 km). Specifically, we compare the EVP and EAP sea ice rheologies; these show substantial differences in the number and orientation of leads. EAP produces diamond patterns which has so far been difficult to create in models. The stand-alone sea ice model simulations will be coupled to ocean to examine eddy interaction.We acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821926 (IMMERSE project) and from the LTS-S CLASS Programme (grant NE/R015953/1). The work reflects only the authors’ view; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. This work also used the ARCHER-II UK National Supercomputing Service and JASMIN, the UK collaborative data analysis facility.

The Arctic can be seen as a two-layer ocean: thin (

Arctic sea ice is diminishing with climate warming1 at a rate unmatched for at least 1,000 years2. As the receding ice pack raises commercial interest in the Arctic3, it has become more variable and mobile4, which increases safety risks to maritime users5. Satellite observations of sea-ice thickness are currently unavailable during the crucial melt period from May to September, when they would be most valuable for applications such as seasonal forecasting6, owing to major challenges in the processing of altimetry data7. Here we use deep learning and numerical simulations of the CryoSat-2 radar altimeter response to overcome these challenges and generate a pan-Arctic sea-ice thickness dataset for the Arctic melt period. CryoSat-2 observations capture the spatial and the temporal patterns of ice melting rates recorded by independent sensors and match the time series of sea-ice volume modelled by the Pan-Arctic Ice Ocean Modelling and Assimilation System reanalysis8. Between 2011 and 2020, Arctic sea-ice thickness was 1.87 ± 0.10 m at the start of the melting season in May and 0.82 ± 0.11 m by the end of the melting season in August. Our year-round sea-ice thickness record unlocks opportunities for understanding Arctic climate feedbacks on different timescales. For instance, sea-ice volume observations from the early summer may extend the lead time of skilful August–October sea-ice forecasts by several months, at the peak of the Arctic shipping season.

The sea ice floe size distribution (FSD) is an important component for sea ice thermodynamic and dynamic processes, particularly in the marginal ice zone. Recently FSD-related processes have been incorporated in sea ice models, but the sparsity of existing observations limits the evaluation of FSD models, so hindering model improvements. In this study, three FSD models are selected for the evaluation – Waves-in-Ice module and Power law Floe Size Distribution (WIPoFSD) model and two branches of a fully prognostic floe size-thickness distribution model: CPOM-FSD and FSDv2-WAVE. These models are evaluated against a new FSD dataset derived from high-resolution satellite imagery in the Arctic. The evaluation shows an overall overestimation of floe perimeter density by the models against the observations. Comparison of the normalized distributions of the floe perimeter density with the observations show that the models exhibit much larger proportion for small floes (the radius < 10–30 m) but much smaller proportion for large floes (the radius > 30–50 m). Observations and the WIPoFSD model both show a negative correlation between sea ice concentration and the floe perimeter density, but the two prognostic models (CPOM-FSD and FSDv2-WAVE) show the opposite pattern. These differences between models and the observations may be attributed to limitations of the observations (e.g., the image resolution is not sufficient to detect small floes), or limitations of the model parameterisations, including the use of a global power-law exponent in the WIPoFSD model, as well as too-weak floe welding and enhanced wave fracture in the prognostic models.

Sea ice is composed of discrete units called floes. Observations show that these floes can adopt a range of sizes spanning orders of magnitude, from metres to tens of kilometres. Floe size impacts the nature and magnitude of interactions between the sea ice, ocean, and atmosphere including lateral melt rate and momentum and heat exchange. However, large-scale geophysical sea ice models employ a continuum approach and traditionally either assume floes adopt a constant size or do not include an explicit treatment of floe size. In this study we apply novel observations to analyse two alternative approaches to modelling a floe size distribution (FSD) within the state-of-the-art CICE sea ice model. The first model considered is a prognostic floe size–thickness distribution where the shape of the distribution is an emergent feature of the model and is not assumed a priori. The second model considered, the WIPoFSD (Waves-in-Ice module and Power law Floe Size Distribution) model, assumes floe size follows a power law with a constant exponent. We introduce a parameterisation motivated by idealised models of in-plane brittle fracture to the prognostic model and demonstrate that the inclusion of this scheme enables the prognostic model to achieve a reasonable match against the novel observations for mid-sized floes (100 m–2 km). While neither FSD model results in a significant improvement in the ability of CICE to simulate pan-Arctic metrics in a stand-alone sea ice configuration, larger impacts can be seen over regional scales in sea ice concentration and thickness. We find that the prognostic model particularly enhances sea ice melt in the early melt season, whereas for the WIPoFSD model this melt increase occurs primarily during the late melt season. We then show that these differences between the two FSD models can be explained by considering the effective floe size, a metric used to characterise a given FSD. Finally, we discuss the advantages and disadvantages to these different approaches to modelling the FSD. We note that although the WIPoFSD model is unable to represent potentially important features of annual FSD evolution seen with the prognostic model, it is less computationally expensive and produces a better fit to novel FSD observations derived from 2 m resolution MEDEA imagery, possibly making this a stronger candidate for inclusion in climate models.

Dense water is formed when sea ice around Antarctica drifts apart leaving open-water areas called polynyas. Both the processes of cooling sea water in contact with the atmosphere and salt accumulation in sea water during sea ice formation, lead to the sea water getting denser. The dense water formation in the oceans surrounding the Antarctic continent contributes to meridional overturning circulation, making it crucial to understand the changes in the Antarctic sea ice and oceans to improve model predictions. Using NEMO output from both a regional configuration and a coupled global configuration we ask how well are polynyas and deep water formation represented in the models? How do regional trends in sea ice affect the polynyas and deep water formation? In the model we find several types of polynya; including the open-water Great Weddell Sea Polynya and coastal polynyas. We have developed and applied an algorithm for classifying coastal polynyas based on sea ice concentration to identify and separate these from the open water polynya areas, in addition, we include sea ice thickness in the classification of coastal polynyas to select areas where the mixed-layer is deep, and surface salt flux is present. In the coastal polynyas the mixed-layer is deep and densification of the upper ocean is strong due to the surface salt flux. The Great Weddell Sea Polynya is also found to deepen the mixed-layer but the strong salt flux, found along the coast, is not present in the open-water polynya suggesting an alternative mechanism is taking place. The favourable ice divergence in the Weddell Sea builds over several years in both models but the Great Polynya itself does not reoccur after the 1980s. Coastal polynyas make up the largest area of the polynyas but show a negative trend in total area, possibly suggesting a diminishing role of these polynyas in future dense water formation. The study asserts different contributions of the two types of polynyas to deep water production.

The Arctic Ocean is of central importance for the global climate and ecosystems. It is undergoing rapid climate change, with a dramatic decrease in sea ice cover over recent decades. Surface advective pathways connect the transport of nutrients, freshwater, carbon and contaminants with their sources and sinks. Pathways of drifting material are deformed under velocity strain, due to atmosphere-ocean-ice coupling. Deformation is largest at fine space- and time-scales and is associated with a loss of potential predictability, analogous to weather often becoming unpredictable as synoptic-scale eddies interact and deform. However, neither satellite observations nor climate model projections resolve fine-scale ocean velocity structure. Here, we use a high-resolution ocean model hindcast and coarser satellite-derived ice velocities, to show: that ensemble-mean pathways within the Transpolar Drift during 2004–14 have large interannual variability and that both saddle-like flow structures and the presence of fine-scale velocity gradients are important for basin-wide connectivity and crossing time, pathway bifurcation, and also for predictability and dispersion (the latter are covered in an associated paper [1].The saddle-points in the flow and their neighbouring streamlines define flow separatrices, which partition the surface Arctic into separate regions of connected transport properties. The separatrix streamlines vary interannually and identify periods when the East Siberian Arctic Shelf, an important source of terragenic minerals, carbon and nutrients, is either connected or disconnected with Fram Strait and the North Atlantic. We explore the implications of this transport connectivity, with our new metric - the Separatrix Curvature Index – which in this context is arguably more informative than either the Arctic Oscillation or Arctic Ocean Oscillation indices.This work resulted from the Advective Pathways of nutrients and key Ecological sub- stances in the Arctic (APEAR) project (NE/R012865/1, NE/R012865/2, #03V01461), part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF). This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 820989 (project COMFORT). The work reflects only the authors' view; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. This work also used the ARCHER UK National Supercomputing Service and JASMIN, the UK collaborative data analysis facility. Satellitebased sea ice tracking was carried out as part of the Russian-German Research Cooperation QUARCCS funded by the German Ministry for Education and Research (BMBF) under grant 03F0777A. This study was carried out as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (AWI_PS122_1 and AF-MOSAiC-1_00) and the NERC Project “PRE-MELT” (Grant NE/T000546/1). We also acknowledge funding support received from the NERC National Capability programmes LTS-M ACSIS (North Atlantic climate system integrated study, grant NE/N018044/1) and LTS-S CLASS (Climate–Linked Atlantic Sector Science, grant NE/R015953/1). The authors would like to acknowledge the contribution of Maria Luneva to the discussions about the initial idea of the study and for highlighting the historical importance of observations from the Russian North Pole drifting stations. Sadly, Maria passed away suddenly in 2020 before the draft of the reported paper was written.[1] Wilson, C., Aksenov, Y., Rynders, S. et al. Significant variability of structure and predictability of Arctic Ocean surface pathways affects basinwide connectivity. Commun. Earth. Environ. 2, 164 (2021). https://doi.org/10.1038/s43247-021-00237-0.

Arctic coastal erosion is an environmental hazard expected to increase under climate change, due to decreasing sea ice protection along with increasing wave heights. In addition to the impact on land, this affects the marine environment, as coastal erosion is a source of organic matter, carbon and nutrients for the coastal waters and shelf seas in the Arctic. Following Barnhart et al., we adapted the White model for iceberg melt to calculate pan-coastal erosion rates. The approach combines ice, ocean and wave model output with permafrost model output and geological characteristics from observations. The calculated erosion rates show large spatial variability, similar to observations, as well as a large seasonal cycle. Additionally, it brings to light the increasing trend between the 1980s and 2010s, with a lengthening of the erosion season, plus inter-annual variability. Using observed nutrient ratios, the erosion rates are converted to biogeochemical sources, which can be used for marine ecosystem models. The approach could be used on-line in earth system models, providing both projections of future erosion rates as well as improved biogeochemistry projections. We acknowledge financial support from Advective Pathways of nutrients and key Ecological substances in the Arctic (APEAR) project (NE/R012865/1, NE/R012865/2, #03V01461), as part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF), and from the European Union’s Horizon 2020 research and innovation programme under project COMFORT (grant agreement no. 820989), for which the work reflects only the authors’ view; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains.

While reasonable knowledge of multidecadal Arctic freshwater storage variability exists, we have little knowledge of Arctic freshwater exports on similar time scales. A hydrographic time series from the Labrador Shelf, spanning seven decades at annual resolution, is here used to quantify Arctic Ocean freshwater export variability west of Greenland. Output from a high-resolution coupled ice–ocean model is used to establish the representativeness of those hydrographic sections. Clear annual to decadal variability emerges, with high freshwater transports during the 1950s and 1970s–80s, and low transports in the 1960s and from the mid-1990s to 2016, with typical amplitudes of 30 mSv (1 Sv = 106m3s−1). The variability in both the transports and cumulative volumes correlates well both with Arctic and North Atlantic freshwater storage changes on the same time scale. We refer to the “inshore branch” of the Labrador Current as the Labrador Coastal Current, because it is a dynamically and geographically distinct feature. It originates as the Hudson Bay outflow, and preserves variability from river runoff into the Hudson Bay catchment. We find a need for parallel, long-term freshwater transport measurements from Fram and Davis Straits to better understand Arctic freshwater export control mechanisms and partitioning of variability between routes west and east of Greenland, and a need for better knowledge and understanding of year-round (solid and liquid) freshwater fluxes on the Labrador shelf. Our results have implications for wider, coherent atmospheric control on freshwater fluxes and content across the Arctic Ocean and northern North Atlantic Ocean.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical models at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss.

Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present along-drift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean.

A growing number of studies are concluding that the resilience of the Arctic sea ice cover in a warming climate is essentially controlled by its thickness. Satellite radar and laser altimeters have allowed us to routinely monitor sea ice thickness across most of the Arctic Ocean for several decades. However, a key uncertainty remaining in the sea ice thickness retrieval is the error on the sea surface height (SSH) which is conventionally interpolated at ice floes from a limited number of lead observations along the altimeter's orbital track. Here, we use an objective mapping approach to determine sea surface height from all proximal lead samples located on the orbital track and from adjacent tracks within a neighborhood of 30–220 (mean 105) km. The patterns of the SSH signal's zonal, meridional, and temporal decorrelation length scales are obtained by analyzing the covariance of historic CryoSat-2 Arctic lead observations, which match the scales obtained from an equivalent analysis of high-resolution sea ice-ocean model fields. We use these length scales to determine an optimal SSH and error estimate for each sea ice floe location. By exploiting leads from adjacent tracks, we can increase the sea ice radar freeboard precision estimated at orbital crossovers by up to 20%. In regions of high SSH uncertainty, biases in CryoSat-2 radar freeboard can be reduced by 25% with respect to coincident airborne validation data. The new method is not restricted to a particular sensor or mode, so it can be generalized to all present and historic polar altimetry missions.

Arctic sea ice is diminishing with climate warming

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss., Accurate seasonal forecasts of sea ice are highly valuable, particularly in the context of sea ice loss due to global warming. A new machine learning tool for sea ice forecasting offers a substantial increase in accuracy over current physics-based dynamical model predictions.

The Beaufort Gyre is a key feature of the Arctic Ocean, acting as a reservoir for freshwater in the region. Depending on whether the prevailing atmospheric circulation in the Arctic is anticyclonic or cyclonic, either a net accumulation or release of freshwater occurs. The sources of freshwater to the Arctic Ocean are well established and include contributions from the North American and Eurasian Rivers, the Bering Strait Pacific water inflow, sea ice meltwater, and precipitation, but their contribution to the Beaufort Gyre freshwater accumulation varies with changes in the atmospheric circulation. Here we use a Lagrangian backward tracking technique in conjunction with the 1/12‐degree resolution Nucleus for European Modelling of the Ocean model to investigate how sources of freshwater to the Beaufort Gyre have changed in recent decades, focusing on increase in the Pacific water content in the gyre between the late 1980s and early 2000s. Using empirical orthogonal functions we analyze the change in the Arctic oceanic circulation that occurred between the 1980s and 2000s. We highlight a “waiting room” advective pathway that was present in the 1980s and provide evidence that this pathway was caused by a shift in the center of Ekman transport convergence in the Arctic. We discuss the role of these changes as a contributing factor to changes in the stratification, and hence potentially the biology, of the Beaufort Gyre region.

A growing number of studies are concluding that the resilience of the Arctic sea ice cover in a warming climate is essentially controlled by its thickness. Satellite radar and laser altimeters have...

Marginal ice zones are areas with many interactions between ocean, surface waves, sea ice and atmosphere. Increasing computational power makes it possible to perform increasingly complex simulations of marine systems, with more components of the climate system that are more interacting. We have produced a set of increasingly coupled simulations with NEMO, CICE and WW3, exchanging more and more variables. The configuration is global at 1 degree resolution. The focus is on wave attenuation in sea ice and the impact of using modelled wave height for ocean mixing due to breaking waves. The example simulations give an idea of the possible impact on the simulated state versus the still considerable computational cost.

The Arctic sea ice cover is not a continuous expanse of ice but is instead composed of individual sea ice floes. These floes can range in size from just a few metres to tens of kilometres. Floe size can influence a variety of processes, including lateral melt rates, momentum transfer within the sea ice-ocean-atmosphere system, surface moisture flux, and sea ice rheology. Sea ice models have traditionally defined floe size using a single parameter, if floe size is explicitly treated at all. There have been several recent efforts to incorporate models of the Floe Size Distribution (FSD) into sea ice models in order to explore both how the shape of the FSD emerges and evolves and its impact on the sea ice cover, including the seasonal retreat. Existing models have generally focused on ocean surface wave-floe interactions and thermodynamic melting and growth processes. However, in-situ observations have indicated the presence of mechanisms other than wave fracture involved in the fragmentation of floes, including brittle failure and melt-induced break up.In this study we consider two alternative FSD models within the CICE sea ice model: the first assumes the FSD follows a power law with a fixed exponent, with parameterisations of individual processes characterised using a variable FSD tracer; the second uses a prognostic approach, with the shape of the FSD an emergent characteristic of the model rather than imposed. We firstly use case studies to understand how similarities and differences in the impacts of the two FSD models on the sea ice emerge, including the different spatial and temporal variability of these impacts. We also consider whether the inclusion of FSD processes in sea ice models can enhance seasonal predictability. We will also demonstrate the need to include in-plane brittle fracture processes in FSD models and discuss the requirements needed within any parameterisation of the brittle failure mechanism.

We explore dense water cascading (DWC), a type of bottom‐trapped gravity current, on multidecadal time scales using a pan‐Arctic regional ocean‐ice model. DWC is particularly important in the Arctic Ocean as the main mechanism of ventilation of interior waters when open ocean convection is blocked by strong density stratification. We identify the locations where the most intense DWC events occur and evaluate the associated cross‐shelf mass, heat, and salt fluxes. We find that the modeled locations of cascading agree well with the sparse historical observations and that cascading is the dominant process responsible for cross‐shelf exchange in the boundary layers. Simulated DWC fluxes of 1.3 Sv (1 Sv = 106 m3/s) in the Central Arctic are comparable to Bering Strait inflow, with associated surface and benthic Ekman fluxes of 0.85 and 0.58 Sv. With ice decline, both surface Ekman flux and DWC fluxes are increasing at a rate of 0.023 and 0.0175 Sv/year, respectively. A detailed analysis of specific cascading sites around the Beaufort Gyre and adjacent regions shows that autumn upwelling of warm and saltier Atlantic waters on the shelf and subsequent cooling and mixing of uplifted waters trigger the cascading on the West Chukchi Sea shelf break. Lagrangian particle tracking of low salinity Pacific waters originating at the surface in the Bering Strait shows that these waters are modified by brine rejection and cooling, and through subsequent mixing become dense enough to reach depths of 160–200 m.

Earth system models enable a broad range of climate interactions that physical climate models are unable to simulate. However, the extent to which adding Earth system components changes or improves the simulation of the physical climate is not well understood. Here we present a broad multivariate evaluation of the North Atlantic climate system in historical simulations of the UK Earth System Model (UKESM1) performed for CMIP6. In particular, we focus on the mean state and the decadal time scale evolution of important variables that span the North Atlantic climate system. In general, UKESM1 performs well and realistically simulates many aspects of the North Atlantic climate system. Like the physical version of the model, we find that changes in external forcing, and particularly aerosol forcing, are an important driver of multidecadal change in UKESM1, especially for Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation. However, many of the shortcomings identified are similar to common biases found in physical climate models, including the physical climate model that underpins UKESM1. For example, the summer jet is too weak and too far poleward; decadal variability in the winter jet is underestimated; intraseasonal stratospheric polar vortex variability is poorly represented; and Arctic sea ice is too thick. Forced shortwave changes may be also too strong in UKESM1, which, given the important role of historical aerosol forcing in shaping the evolution of the North Atlantic in UKESM1, motivates further investigation. Therefore, physical model development, alongside Earth system development, remains crucial in order to improve climate simulations.

Lagrangian particle tracking and associated diagnostics may be used to examine advective pathways of material and to identify coherent structures in the flow. Lagrangian coherent structures are material transport barriers and act to separate different flow regimes.The drift of the International Multidisciplinary Observatory for the Study of Arctic Climate (MOSAiC) expedition onboard R/V Polarstern began in October 2019 and will continue for the full year. Our study has the goals to (i) characterise advective pathways and (ii) examine potential predictability of the MOSAiC drift. Eddies, jets and boundary currents feature large spatiotemporally varying velocity gradients. Since operational ocean forecasts have a limited time horizon (~weeks), we focused on hindcast to examine typical sea ice/ocean circulation scenarios for 2005-15. We applied off-line ARIANE particle tracking in an eddying 1/12 deg. global NEMO sea ice-ocean model to estimate the most likely drift pathways. Over 10,000 trajectories were initialised in October each year, started at the best estimated MOSAiC location, advected for one year and analysed for key coherent drift structures. The advection and deformation of the initial particle cluster provided information about MOSAiC drift predictability, but also elucidated transport processes of the biogeochemical tracers, such as nutrients and carbon, and spread of pollution and microplastics. We analysed observations from a newly curated dataset of the Arctic to examine various watermass properties, their origin, fate and connectivity.The MOSAiC surface drift trajectories depend on release time and location, but to leading-order, they are governed by the interannual variability of the wind and of the underlying ocean circulation. Mesoscale flow deformation is linked to a spreading of the cluster of particles and is associated with reduced potential predictability of separation of particles within the cluster (~ 450 km after 12 months). Gyre-scale flow affects the ensemble drift path over long times and influences whether particular coherent structures are encountered by the particles, their location and strength (in terms of velocity magnitude and gradient). Saddle-type structures play a major role in bifurcation of particle trajectories. In the examples studied, saddles north of Nares Strait, near Northern Greenland and Northern Iceland, topologically associated with streamline connectivity between gyres, coastal boundary currents and inflow/outflow at the Arctic gateways, were significant. On seasonal-interannual scales, the position and strength of the Beaufort Gyre, as well as an anomalous cyclonic gyre in the eastern basin, affected both the ensemble drift path and the coherent flow structures.The variability of ensemble drift path, cluster deformation and coherent flow structures across the full Arctic basin were often very different from the climatological advective behaviour of Trans-Polar Drift. For estimation of advective pathways and sea ice drift it is important to consider the varying flow from gyre-scale to mesoscale, where velocity gradients are large, and to identify robust Lagrangian measures for steady features.The study is supported from NE/R012865/1 (APEAR), part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF).

We explore dense water cascading (DWC; a type of bottom-trapped gravity current) on multi-decadal time scales using a pan-Arctic regional ocean-ice model. DWC is particularly important in the Arctic Ocean as the main mechanism of ventilation of interior waters when open ocean convection is blocked by strong density stratification. We identify the locations where the most intense DWC events occur and evaluate the associated cross-shelf mass, heat and salt fluxes. A detailed analysis of specific cascading sites around the Beaufort Gyre and adjacent regions is performed. We find that autumn upwelling of warm and saltier Atlantic waters on the shelf and subsequent cooling and mixing of uplifted waters trigger the cascading on the West Chukchi Sea shelf break. We also perform Lagragian particle tacking of low salinity Pacific waters originating at the surface in the Bering Strait; these waters are shown to be modified by brine rejection and cooling, and through subsequent mixing become dense enough to reach depths of 160-200m and below. We examine the role of cascading and shelf upwelling on the shelf waters transformation, pathways and spread of the biological important tracers (O18, Si., DIC snd DIN).

Sea ice exists as individual units of ice called floes. These floes can vary by orders of magnitude in diameter over small spatial scales. They are better described by a floe size distribution (FSD) rather than by a single diameter. Observations of the FSD are frequently fitted to a power law with a negative exponent. Floe size can influence several sea ice processes including the lateral melt rate, momentum exchange between the sea ice, ocean and atmosphere, and sea ice rheology. There have been several recent efforts to develop a model of the floe size distribution to include within sea ice models to improve the representation of floe size beyond a fixed single value. Some of these involve significant approximations about the shape and variability of the distribution whereas others adopt a more prognostic approach that does not restrict the shape of the distribution.In this study we compare the impacts of two alternative approaches to modelling the FSD within the CICE sea ice model. The first assumes floes follow a power law distribution with a constant exponent. Parameterisations of processes thought to influence the floe size distribution are expressed in terms of a variable FSD tracer. The second uses a prognostic floe size-thickness distribution. The sea ice area in individual floe size categories evolves independently such that the shape of distribution is an emergent behaviour rather than imposed. Here we compare the impact of the two modelling approaches on the thermodynamic evolution of the sea ice. We show that both predict an increase in lateral melt with a compensating reduction in basal melt. We find that the magnitude of this change is highly dependent on the form of the distribution for the smallest floes. We also explore the impact of both FSD models on the momentum exchange of the sea ice and find a large response in the spatial distribution of sea ice volume. Finally, we will discuss whether the results from the prognostic FSD model support the assumptions required to construct the power law derived FSD model.

We present analysis of Arctic sea ice and ocean dynamics in the ensemble of the UK Earth System Model (UK ESM1) simulations completed under the Coupled Model Intercomparison Project Phase 6 (CMIP6) protocol. The focus of the investigation is on the future changes in the Arctic sea ice and oceanic connections and on the impact of the nutrient advection on the Arctic marine biogeochemistry and ecosystems. Changes in the balance of the oceanic inflows from the North Atlantic and North Pacific Oceans are found to have a first order effect on the watermasses and nutrients balances in the central Arctic Ocean. The simulations show that the total primary production in the Arctic Ocean is increased by 100% in the 2090s as compared to the present climate. This is caused by higher nutrients availability in the Atlantic inflowing waters and prolonged ice- free season. The faster connections through the Arctic and milder oceanic environment allows species to survive through the winter and from the second half of the century the Arctic Ocean could become a key oceanic gateway connecting the global oceans. The study is supported from the project APEAR (NE/R012865/1) NERC-BMBF and from the NERC ACSIS Programme (NE/N018044/1).

Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 % and 80 % sea ice cover, is the region separating pack ice from the open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but sea ice models within climate models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a power law defined by an upper floe size cut-off, lower floe size cut-off, and power-law exponent. This distribution is also defined by a new tracer that varies in response to lateral melting, wave-induced break-up, freezing conditions, and advection. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed-layer model. We present results to show that the use of a power-law floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. We also find that the attenuation rate of waves propagating under the sea ice cover modulates the impact of wave break-up on the floe size distribution. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is a useful stepping stone for future development of floe size modelling.

Continuum sea ice models have been applied close to the presumed limits of their validity for many years, yet they remain compatible with current observations. The resolution requirements for sea ice models varies considerably depending on the application (e.g., large ensembles, paleoclimate simulations, short-range forecasting), and therefore continuum models will likely remain useful for many years to come. Meanwhile, it is highly desirable to explore the potential of DEMs. These models are expected to be more physically faithful at the highest resolutions envisioned for sea ice in ESMs, provided they incorporate all the required processes. DEMs may also prove more efficient for some new computer architectures. Such perspectives highlight the need for the sea ice modeling community to have a clear and consistent vision of the future evolution of HPC systems. Sea ice models are used for many different purposes and therefore benefit from modularity, which allows the activation or exclusion of parameterizations and code features. Thus, users can adjust model complexity to fit their specific application. Considering limited human resources among core sea ice modeling groups, engagement of the wider community has proven a very efficient way to advance large-scale sea ice models. However, there is still scope for further integration of the wider community in model development activities. An important feature of the Laugarvatn sea ice modeling workshop was the open minded atmosphere in which very different views were exchanged. The workshop successfully brought together model developers and users of sea ice models for Earth system modeling, operational forecasting and (re)analyses. International sea ice modeling workshops such as this foster collaboration and community engagement in the field of sea ice modeling. A recommendation from this workshop is that the exercise should be repeated every 2-3 years to maintain community engagement, exchange cutting-edge ideas, and reinforce collaborative momentum. © 2020 American Meteorological Society.

The fast development of the offshore energy industry becomes an essential component of resilient economies in most of the countries around the North Sea, addressing an increasing demand for cost-efficient and environmentally safe energy sources. Offshore wind farms are planned to be installed further away from the coasts to ensure stronger and more stable wind resources in this region. Oil and gas extraction infrastructures are also planned to move into deeper areas of the continental shelf and continental shelf slopes to explore new fields. These deeper areas of the ocean are characterised by harsh environmental conditions: stronger winds, larger waves and strong shelf slope currents, inducing considerably larger loads on offshore structures. This study brings together operational physical oceanography and the mathematics of fluid-structure interactions to estimate the likelihood of extreme environmental loads on offshore structures in the North Sea. We use the state-of-the-art Met Office high resolution ocean forecasting system, which provides high-frequency data on ocean and tidal currents, wave heights and periods and winds at a ~7 km horizontal resolution grid, spanning the North–West European Shelf. The Morison equation framework is used to calculate environmental loads on various types of offshore structures that are typically employed by the offshore industries in the North Sea. We use hourly data for a 2-year period to analyse the spatio-temporal variability of mean and extreme hydrodynamic loads and derive the relative contributions of currents, waves and winds in the region. The results indicate that waves dominate extreme hydrodynamic forces on the shallow shelf, whereas the current contribution is important at the shelf break and in the English Channel.

The rapid Arctic summer sea ice reduction in the last decade has lead to debates in the maritime industries on the possibility of an increase in cargo transportation in the region. Average sailing times on the North Sea Route along the Siberian Coast have fallen from 20 days in the 1990s to 11 days in 2012–2013, attributed to easing sea ice conditions along the Siberian coast. However, the economic risk of exploiting the Arctic shipping routes is substantial. Here a detailed high-resolution projection of ocean and sea ice to the end of the 21st century forced with the RCP8.5 IPCC emission scenario is used to examine navigability of the Arctic sea routes. In summer, opening of large areas of the Arctic Ocean previously covered by pack ice to the wind and surface waves leads to Arctic pack ice cover evolving into the Marginal Ice Zone. The emerging state of the Arctic Ocean features more fragmented thinner sea ice, stronger winds, ocean currents and waves. By the mid 21st century, summer season sailing times along the route via the North Pole are estimated to be 13–17 days, which could make this route as fast as the North Sea Route.

Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 and 80 % sea ice cover, is the region separating pack ice from open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but climate sea ice models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a truncated power law defined by three key parameters: minimum floe size, maximum floe size, and power law exponent. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed layer model. We present results to show that the use of a power law derived floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is suitable for applications where a simple but realistic floe size distribution model is required.

The Arctic Ocean simulated in 14 global ocean-sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE-II) is analyzed in this study. The focus is on the Arctic liquid freshwater (FW) sources and freshwater content (FWC). The models agree on the interannual variability of liquid FW transport at the gateways where the ocean volume transport determines the FW transport variability. The variation of liquid FWC is induced by both the surface FW flux (associated with sea ice production) and lateral liquid FW transport, which are in phase when averaged on decadal time scales. The liquid FWC shows an increase starting from the mid-1990s, caused by the reduction of both sea ice formation and liquid FW export, with the former being more significant in most of the models. The mean state of the FW budget is less consistently simulated than the temporal variability. The model ensemble means of liquid FW transport through the Arctic gateways compare well with observations. On average, the models have too high mean FWC, weaker upward trends of FWC in the recent decade than the observation, and low consistency in the temporal variation of FWC spatial distribution, which needs to be further explored for the purpose of model development.

Until recently, the Arctic Basin was generally considered to be a low productivity area and was afforded little attention in global- or even basin-scale ecosystem modelling studies. Due to anthropogenic climate change however, the sea ice cover of the Arctic Ocean is undergoing an unexpectedly fast retreat, exposing increasingly large areas of the basin to sunlight. As indicated by existing Arctic phenomena such as ice-edge blooms, this decline in sea-ice is liable to encourage pronounced growth of phytoplankton in summer and poses pressing questions concerning the future of Arctic ecosystems. It thus provides a strong impetus to modelling of this region. The Arctic Ocean is an area where plankton productivity is heavily influenced by physical factors. As these factors are strongly responding to climate change, we analyse here the results from simulations of the 1/4° resolution global ocean NEMO (Nucleus for European Modelling of the Ocean) model coupled with the MEDUSA (Model for Ecosystem Dynamics, carbon Utilisation, Sequestration and Acidification) biogeochemical model, with a particular focus on the Arctic Basin. Simulated productivity is consistent with the limited observations for the Arctic, with significant production occurring both under the sea-ice and at the thermocline, locations that are difficult to sample in the field. Results also indicate that a substantial fraction of the variability in Arctic primary production can be explained by two key physical factors: (i) the maximum penetration of winter mixing, which determines the amount of nutrients available for summer primary production, and (ii) short-wave radiation at the ocean surface, which controls the magnitude of phytoplankton blooms. A strong empirical correlation was found in the model output between primary production these two factors, highlighting the importance of physical processes in the Arctic Ocean.

Sea‐ice‐free summers are projected to become a prominent feature of the Arctic environment in the coming decades. From a shipping perspective, this means larger areas of open water in the summer, thinner and less compact ice all year round, and longer operating seasons. Therefore, the possibility for easier navigation along trans‐Arctic shipping routes arises. The Northern Sea Route (NSR) is one trans‐Arctic route, and it offers a potential 10 day shortcut between Western Europe and the Far East. More ships transiting the NSR means an increased risk of an accident, and associated oil spill, occurring. Previous research suggests that current infrastructure is insufficient for increased shipping. Therefore, should an oil spill occur, the window for a successful clean‐up will be short. In the event of a failed recovery, the long‐term fate of the unrecovered pollutants must be considered, at least until the next melt season when it could become accessible again. Here we investigate the role of oceanic advection in determining the long‐term fate of Arctic pollutants using a high‐resolution ocean model along with Lagrangian particle‐tracking to simulate the spread of pollutants. The resulting “advective footprints” of pollutants are proposed as an informative metric for analyzing such experiments. We characterize the circulation along different parts of the NSR, defining three main regions in the Eurasian Arctic, and relate the distinctive circulation pathways of each to the long‐term fate of spilled oil. We conclude that a detailed understanding of ocean circulation is critical for determining the long‐term fate of Arctic pollutants. Plain Language Summary The Earth's climate is changing and the Arctic Ocean is projected to experience ice free summers within decades. This would enable more commercial shipping, which in turn makes an Arctic shipping accident more likely. This could lead to oil (or other pollutants) being spilled into the ocean. Because of the harsh Arctic environment, an oil spill may not be successfully recovered, so we need to consider where it will go in the following months and years. We released virtual “particles” into a computer model of the ocean and tracked their progress for 2 years. In this time, particles traveled, on average, 1,223 km. This demonstrates that pan‐Arctic modeling is needed in the event of an unrecovered pollutant spill. Unrecovered oil from one season may be accessible the next spring. By analyzing the spread of our particles, we found that on average 676,917 km2 would need to be searched to find it, but that this is highly dependent on where the spill occurs. Finally, we noted that in some places, particularly the Barents Sea, there was a risk that spilled pollutants could become entrained into deep water, rendering them irrecoverable.

This paper presents the first estimate of the seasonal cycle of ocean and sea ice net heat and freshwater (FW) fluxes around the boundary of the Arctic Ocean. The ocean transports are estimated primarily using 138 moored instruments deployed in September 2005 to August 2006 across the four main Arctic gateways: Davis, Fram and Bering Straits, and the Barents Sea Opening (BSO). Sea ice transports are estimated from a sea ice assimilation product. Monthly velocity fields are calculated with a box inverse model that enforces volume and salinity conservation. The resulting net ocean and sea ice heat and FW fluxes (annual mean $\pm$ 1 standard deviation) are 175 $\pm$48 TW and 204 $\pm$85 mSv (respectively; 1 Sv = 10$^{6} m^{3} s^{-1}$). These boundary fluxes accurately represent the annual means of the relevant surface fluxes. Oceanic net heat transport variability is driven by temperature variability in upper part of the water column and by volume transport variability in the Atlantic Water layer. Oceanic net FW transport variability is dominated by Bering Strait velocity variability. The net water mass transformation in the Arctic entails a freshening and cooling of inflowing waters by 0.62$\pm$0.23 in salinity and 3.74$\pm$0.76C in temperature, respectively, and a reduction in density by 0.23$\pm$0.20 kg m$^{-3}$. The volume transport into the Arctic of waters associated with this water mass transformation is 11.3$\pm$1.2 Sv, and the export is -11.4$\pm$1.1 Sv. The boundary heat and FW fluxes provide a benchmark data set for the validation of numerical models and atmospheric re-analyses products., 64 pages, 12 figures, 5 tables, 24 pages supporting information. This manuscript is submitted to Journal of Physical Oceanography on November 2017 for a publication. Copyright in this work may be transferred to American Meteorological Society without further notice

The Atlantic Water flow from the Barents and Kara seas to the Arctic Ocean through the St. Anna Trough (SAT) is conditioned by interaction between Fram Strait branch water circulating in the SAT and Barents Sea branch water—both of Atlantic origin. Here we present data from an oceanographic mooring deployed on the eastern flank of the SAT from September 2009 to September 2010 as well as CTD (conductivity-temperature-depth) sections across the SAT. A distinct vertical density front over the SAT eastern slope deeper than ∼50 m is attributed to the outflow of Barents Sea branch water to the Arctic Ocean. In turn, the Barents Sea branch water flow to the Arctic Ocean is conditioned by two water masses defined by relative low and high fractions of the Atlantic Water. They are also traceable in the Nansen Basin downstream of the SAT entrance. A persistent northward current was recorded in the subsurface layer along the SAT eastern slope with a mean velocity of 18 cm s−1 at 134–218 m and 23 cm s−1 at 376–468 m. Observations and modeling suggest that the SAT flow has a significant density-driven component. It is therefore expected to respond to changes in the cross-trough density gradient conditioned by interaction between the Fram Strait and Barents Sea branches. Further modeling efforts are necessary to investigate hydrodynamic instability and eddy generation caused by the interaction between the SAT flow and the Arctic Ocean Fram Strait branch water boundary current.

The Arctic Circumpolar Boundary Current (ACBC) transports a vast amount of mass and heat around cyclonic gyres of the deep basins, acting as a narrow, topographically-controlled flow, confined to the continental margins. Current observations during 2002–2011 at seven moorings along the major Atlantic Water (AW) pathway, complemented by an extensive collection of measured temperatures and salinities as well as results of state-of-the-art numerical modeling, have been used to examine the spatial structure and temporal variability of the ACBC within the Eurasian Basin (EB). These observations and modeling results suggest a gradual, six-fold decrease of boundary current speed (from 24 to 4 cm/s) on the route between Fram Strait and the Lomonosov Ridge, accompanied by a transformation of the vertical flow structure from mainly barotropic in Fram Strait to baroclinic between the area north of Spitsbergen and the central Laptev Sea continental slope. The relative role of density-driven currents in maintaining AW circulation increases with the progression of the ACBC eastward from Fram Strait, so that baroclinic ACBC forcing dominates over the barotropic in the eastern EB. Mooring records have revealed that waters within the AW and the cold halocline layers circulate in roughly the same direction in the eastern EB. The seasonal signal, meanwhile, is the most powerful mode of variability in the EB, contributing up to ~70% of the total variability in currents (resolved by moorings records) within the eastern EB. Seasonal signal amplitudes for current speed and AW temperature both decrease with the eastward progression of AW flow from source regions, and demonstrate strong interannual modulation. In the 2000s, the state of the EB (e.g., circulation pattern, thermohaline conditions, and freshwater balance) experienced remarkable changes. Results showing anomalous circulation patterns for an extended period of 30 months in 2008–2010 for the eastern EB, and a two-core AW temperature structure that emerged in this region of the Arctic Ocean in the most recent decade, suggest a shift of the EB toward a new, more dynamic state. This also likely suggests that the EB interior will become more susceptible to future climate change. Evaluating properties of the ACBC, its temporal variability at time scales from a season to several years, and possible governing mechanisms, this study contributes to a better understanding of Arctic Ocean circulation.

Siberian river water is a first-order contribution to the Arctic freshwater budget, with the Ob, Yenisey, and Lena supplying nearly half of the total surface freshwater flux. However, few details are known regarding where, when, and how the freshwater transverses the vast Siberian shelf seas. This paper investigates the mechanism, variability, and pathways of the fresh Kara Sea outflow through Vilkitsky Strait toward the Laptev Sea. We utilize a high-resolution ocean model and recent shipboard observations to characterize the freshwater-laden Vilkitsky Strait Current (VSC), and shed new light on the little-studied region between the Kara and Laptev Seas, characterized by harsh ice conditions, contrasting water masses, straits, and a large submarine canyon. The VSC is 10–20 km wide, surface intensified, and varies seasonally (maximum from August to March) and interannually. Average freshwater (volume) transport is 500 ± 120 km3 a−1 (0.53 ± 0.08 Sv), with a baroclinic flow contribution of 50–90%. Interannual transport variability is explained by a storage-release mechanism, where blocking-favorable summer winds hamper the outflow and cause accumulation of freshwater in the Kara Sea. The year following a blocking event is characterized by enhanced transports driven by a baroclinic flow along the coast that is set up by increased freshwater volumes. Eventually, the VSC merges with a slope current and provides a major pathway for Eurasian river water toward the western Arctic along the Eurasian continental slope. Kara (and Laptev) Sea freshwater transport is not correlated with the Arctic Oscillation, but rather driven by regional summer pressure patterns.

Dedicated to the memory of our colleague Klaus Hochheim, who tragically lost his life in the Arctic expedition in September 2013. A distinct, subsurface density front along the eastern St. Anna Trough in the northern Kara Sea is inferred from hydrographic observations in 1996 and 2008–2010. Direct velocity measurements show a persistent northward subsurface current (~ 18 cm s−1) along the St. Anna Trough eastern flank. This sheared flow, carrying the outflow from the Barents and Kara seas to the Arctic Ocean, is also evident from shipboard observations as well as from geostrophic velocities and numerical model simulations. Although we cannot substantiate our conclusions by direct observation-based estimates of mixing rates in the area, we hypothesize that the enhanced vertical mixing along the St. Anna Trough eastern flank favors the upward heat loss from the intermediate warm Atlantic water layer. Modeling results support this hypothesis. The upward heat flux inferred from hydrographic data and model simulations is of O(30–100) W m−2. The region of lowered sea ice thickness and concentration seen both in sea ice remote sensing observations and model simulations marks the Atlantic water pathway in the St. Anna Trough and adjacent Nansen Basin continental margin. In fact, the sea ice shows a delayed freeze-up onset during fall and a reduction in the sea ice thickness during winter. This is consistent with our results on the enhanced Atlantic water heat loss along the Atlantic water pathway in the St. Anna Trough.