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We investigate how sea ice decline in summer and warmer ocean and surface temperatures in winter affect sea ice growth in the Arctic. Sea ice volume changes are estimated from satellite observations during winter from 2002 to 2019 and partitioned into thermodynamic growth and dynamic volume change. Both components are compared to validated sea ice-ocean models forced by reanalysis data to extend observations back to 1980 and to understand the mechanisms that cause the observed trends and variability. We find that a negative feedback driven by the increasing sea ice retreat in summer yields increasing thermodynamic ice growth during winter in the Arctic marginal seas eastward from the Laptev Sea to the Beaufort Sea. However, in the Barents and Kara Seas, this feedback seems to be overpowered by the impact of increasing oceanic heat flux and air temperatures, resulting in negative trends in thermodynamic ice growth of -2 km3month-1yr-1 on average over 2002-2019 derived from satellite observations.

Single-column sea ice models are used to focus on the thermodynamic evolution of the ice. Generally these models are forced by atmospheric reanalysis in absence of atmospheric in situ observations. Here we assess the sea ice thickness (SIT) simulated by a single-column model (ICEPACK) with in situ observations obtained off Zhongshan Station for the austral winter of 2016. In the reanalysis the surface air temperature is about 1 °C lower, the total precipitation is about 2 mm day−1 larger, and the surface wind speed is about 2 m s−1 higher compared to the in situ observations, respectively. Using sensitivity experiments we evaluate the simulation bias in sea ice thickness due to the uncertainty in the individual atmospheric forcing variables. We show that the unrealistic precipitation in the reanalysis leads to a bias of 14.5 cm in sea ice thickness and of 17.3 cm in snow depth. In addition, our data show that increasing snow depth works to gradually inhibits the growth of sea ice associated with thermal blanketing by the snow due to changing the vertical heat flux. Conversely, given suitable conditions, the sea ice thickness may grow suddenly when the snow load gives rise to flooding and leads to snow-ice formation. A potential mechanism to explain the different characteristics of the precipitation bias on snow and sea ice is discussed. The flooding process for landfast sea ice might cause different effect compared to pack ice, thus need to be reconsidered in ICEPACK. Meanwhile, the overestimation in surface wind speed in reanalysis is likely responsible for the underestimation in simulated snow depth, however this had little influence on the modelled ice thickness.

The uniqueness of optimal parameter sets of an Arctic sea ice simulation is investigated. A set of parameter optimization experiments is performed using an automatic parameter optimization system, which simultaneously optimizes 15 dynamic and thermodynamic process parameters. The system employs a stochastic approach (genetic algorithm) to find the global minimum of a cost function. The cost function is defined by the model–observation misfit and observational uncertainties of three sea ice properties (concentration, thickness, drift) covering the entire Arctic Ocean over more than two decades. A total of 11 independent optimizations are carried out to examine the uniqueness of the minimum of the cost function and the associated optimal parameter sets. All 11 optimizations asymptotically reduce the value of the cost functions toward an apparent global minimum and provide strikingly similar sea ice fields. The corresponding optimal parameters, however, exhibit a large spread, showing the existence of multiple optimal solutions. The result shows that the utilized sea ice observations, even though covering more than two decades, cannot constrain the process parameters toward a unique solution. A correlation analysis shows that the optimal parameters are interrelated and covariant. A principal component analysis reveals that the first three (six) principal components explain 70% (90%) of the total variance of the optimal parameter sets, indicating a contraction of the parameter space. Analysis of the associated ocean fields exhibits a large spread of these fields over the 11 optimized parameter sets, suggesting an importance of ocean properties to achieve a dynamically consistent view of the coupled sea ice–ocean system.

Improvement and optimization of numerical sea ice models are of great relevance for understanding the role of sea ice in the climate system. They are also a prerequisite for meaningful prediction. To improve the simulated sea ice properties, we develop an objective parameter optimization system for a coupled sea ice–ocean model based on a genetic algorithm. To take the interrelation of dynamic and thermodynamic model parameters into account, the system is set up to optimize 15 model parameters simultaneously. The optimization is minimizing a cost function composed of the model–observation misfit of three sea ice quantities (concentration, drift, and thickness). The system is applied for a domain covering the entire Arctic and northern North Atlantic Ocean with an optimization window of about two decades (1990–2012). It successfully improves the simulated sea ice properties not only during the period of optimization but also in a validation period (2013–16). The similarity of the final values of the cost function and the resulting sea ice fields from a set of 11 independent optimizations suggest that the obtained sea ice fields are close to the best possible achievable by the current model setup, which allows us to identify limitations of the model formulation. The optimized parameters are applied for a simulation with a higher-resolution model to examine a portability of the parameters. The result shows good portability, while at the same time, it shows the importance of the oceanic conditions for the portability.

Reliable and detailed snow data are limited in the Arctic. We aim at overcoming this issue by addressing two questions: (1) Can the reanalysis ERA5 replace limited in situ measurements in high latitudes to drive snow models? (2) Can the Alpine model Crocus simulate reliably Arctic snow depth and stratigraphy? We compare atmospheric in situ measurements and ERA5 reanalysis and evaluate simulated and measured snow depth, density and specific surface area (SSA) in northeast Greenland (October 2014–October 2018). To account for differences between Alpine and Arctic region, we introduce a new parametrisation for the density of new snow.Our results show a good agreement between in situ and ERA5 atmospheric variables except for precipitation, wind speed and direction. ERA5’s resolution is too coarse to resolve the topography in the study area adequately, leading presumably to the detected biases. Nevertheless, measured snow depth agrees better with ERA5 forced simulations than forced with in situ measurements.Crocus can simulate satisfactory the evolution of snow depth, but simulations of SSA and density profiles for both forcings are biased compared to field measurements. Adjusting the new snow density parametrisation leads to improvements in the simulated snow stratigraphy. In conclusion, ERA5 can be used instead of in situ measurements to force snow models but the use of Crocus in the Arctic is affected by limitations likely due to the missing vertical water vapour transport and snow redistribution during strong winds. These limitations strongly affect the accuracy of the vertical profiles of physical snow properties.

With rapid sea-ice decline, ocean warming and increasing Atlantic inflow, the ecosystem of the Central Arctic Ocean (CAO) is experiencing an unprecedented, potentially disruptive transformation. While this transformation is affecting the biodiversity of marine communities and the ecosystem functions they fulfil, major knowledge gaps about the distribution of pelagic macrofauna (zooplankton and fish) complicate the assessment of the impact of this transformation on biodiversity and marine resources. The largest blind spot remains in the central Arctic Basin, which has been difficult to sample with large sampling gear such as fishing nets due to a year-round ice coverage. However, in the face of increasing human activities and international efforts to implement marine management in the CAO, it becomes important to monitor pelagic fauna in this remote area. One possibility to enable a better sampling of pelagic macrofauna is to use sea-ice thethered autonomous observatories. Within the British/German project EcoLight, we developed a new autonomous sea-ice observatory comprising an ASL Acoustic Zooplankton and Fish Profiler (AZFP). The device has 4 frequencies targeting different size classes of animals. It samples automatically at predefined intervals and transmits the data to a server in Europe via Iridium. It is possible to change the sampling parameters via a remote connection at any time. The AZFP buoy was deployed in the CAO in September 2020, shortly before the end of the MOSAiC expedition. Since then, the buoy has been recording the vertical zooplankton distribution in the water column under the ice. First data show a light-induced change of the vertical distribution of scatterers, transitioning from deep distribution during the polar day, through a short period of diel vertical migration during the twilight period, to a constant presence of scatterers in the surface layer in the polar night. Furthermore, AZFP data suggest an enhancement of zooplankton between the upper pycnocline and ~50 m depth during in an eddie transition. The data collected by the EcoLight AZFP buoy constitute the first hydroacoustic record of zooplankton distribution near the North Pole sampled with a fully autonomous system in the absence of disturbing light sources. They demonstrate the feasibility of year-round automated monitoring of macrofauna in the CAO in relation to environmental properties. Similar autonomous devices may serve as key elements in the future monitoring of biological resources in the CAO and other inaccessible areas.

Sea ice in Baffin Bay plays an important role in the deep water formation in the Labrador Sea and contributes to the variation of the Atlantic meridional overturning circulation (AMOC) on larger scales. To quantify the sea ice volume variations in Baffin Bay, a major driver of the deep water formation, three state-of-the-art sea ice models (CMST, NAOSIM, and PIOMAS) are investigated in the melt and freezing season from 2011 to 2016. An ensemble of three estimates of the sea ice volume fluxes in Baffin Bay is generated from the three modeled sea ice thickness and NSIDC satellite derived ice drift data. Results show that the net increase of the ensemble mean sea ice volume (SIV) in Baffin Bay occurs from October to April with the largest SIV increase in December (116 ± 16 km3 month−1) and the reduction occurs from May to September with the largest SIV decline in July (−160 ± 32 km3 month−1). The maximum SIV inflow occurs in winter in all the model data consistently. The ensemble mean SIV inflow (322 ± 4 km3) reaches its maximum in winter 2013 caused by high ice velocities while the largest SIV outflow (244 ± 61 km3) occurs in spring of 2014. The long-term annual mean ice volume inflow and outflow are 437(± 53) km3 and 339(± 68) km3, respectively. Our analysis also reveals that on average, sea ice in Baffin Bay melts from May to October with a net reduction of 335 km3 in volume while it freezes from November to April with a net increase of 251 km3.

The volume, characteristics and sources of freshwater circulating in the Arctic Ocean vary in time and are expected to change under a declining sea ice cover, influencing the physical environment and Arctic ecosystem. Relatively fresh (S = 32) Pacific Water, which enters the Arctic Ocean via the Bering Strait makes up a significant part of the liquid freshwater exiting the Arctic Ocean through Fram Strait. If transported to the Nordic Seas and North Atlantic via the East- and West Greenland Currents freshwater from the Pacific could have an effect on convection and dense water formation in those regions.More than 30 repeated sections of nutrient measurements have been collected across Fram Strait between 1980 and 2019. The fraction of Pacific Water along these repeated sections can be estimated from the ratio of nitrate to phosphate. The time-series of repeated Fram Strait sections indicates that the fraction of Pacific Water passing out of the Arctic Ocean has changed significantly over the last 30 years. Pacific water fractions remained high from 1980 to 1998, but in 1999 Pacific water almost disappeared from Fram Strait, reappearing from 2011 to 2012, when there was a peak in freshwater export though Fram Strait.Several hypotheses suggest how variations in the large-scale atmospheric circulation over the Arctic Ocean may influence the transport and pathways of Pacific Water. We show how anomalies in reanalysis wind fields are associated with the reappearance of Pacific Water in Fram Strait in recent years. Repeated sections across Fram Strait are compared with sea ice back-trajectories in the Polar Pathfinder 4 product and a simulated Pacific Water tracer in the NAOSIM numerical model to investigate likely Pacific water pathways through the Arctic Ocean and upstream drivers of changes observed in Fram Strait.

When the air is very cold, water at the surface of the ocean freezes, forming sea ice. Parts of the Arctic Ocean are covered by sea ice during the entire year. Often, snow falls onto the sea ice. Despite the cold, many plants and animals can live in the Arctic Ocean, some in the water, and some even in the sea ice. Particularly, algae can live in small bubbles in the sea ice. Like other plants, algae need energy to grow. This energy comes from food and sunlight. But how can the sunlight reach these little algae living inside the sea ice? From the sun, the light must pass through the atmosphere, the snow, and finally the sea ice itself. In this article, we describe how ice algae can live in this special environment and we explain what influences how much light reaches the algae to make them grow.

Warm water of open ocean origin on the continental shelf of the Amundsen and Bellingshausen Seas causes the highest basal melt rates reported for Antarctic ice shelves with severe consequences for the ice shelf/ice sheet dynamics. Ice shelves fringing the broad continental shelf in the Weddell and Ross Seas melt at rates orders of magnitude smaller. However, simulations using coupled ice–ocean models forced with the atmospheric output of the HadCM3 SRES-A1B scenario run (CO2 concentration in the atmosphere reaches 700 ppmv by the year 2100 and stays at that level for an additional 100 years) show that the circulation in the southern Weddell Sea changes during the twenty-first century. Derivatives of Circumpolar Deep Water are directed southward underneath the Filchner–Ronne Ice Shelf, warming the cavity and dramatically increasing basal melting. To find out whether the open ocean will always continue to power the melting, the authors extend their simulations, applying twentieth-century atmospheric forcing, both alone and together with prescribed basal mass flux at the end of (or during) the SRES-A1B scenario run. The results identify a tipping point in the southern Weddell Sea: once warm water flushes the ice shelf cavity a positive meltwater feedback enhances the shelf circulation and the onshore transport of open ocean heat. The process is irreversible with a recurrence to twentieth-century atmospheric forcing and can only be halted through prescribing a return to twentieth-century basal melt rates. This finding might have strong implications for the stability of the Antarctic ice sheet.

Of the wide variety of dumped objects containing radioactive materials in the Arctic seas, the submarine K-27 constitutes a major risk due to the large amount of highly enriched uranium onboard and its location in shallow waters. As the matter of potential operations involving raising of the submarine have entered the public arena, a priori assessment of the contamination in the Arctic marine environment that could result after a possible accident during such operations is a matter of some interest. The dispersion of contaminants within the Arctic has been assessed using a large scale hydrodynamic model for a series of plausible accident scenarios and locations under different oceanographic regimes. Results indicate that, depending primarily on the nature of a release (i.e. instantaneous or continuous), large areas of the Arctic marine environment will exhibit contamination to varying degrees.

There is increasing concern regarding the issue of dumped nuclear waste in the Arctic Seas and in particular dumped objects with Spent Nuclear Fuel (SNF). Amongst dumped objects in the Arctic, the dumped Russian submarine K-27 has received great attention as it contains two reactors with highly enriched fuel and lies at a depth of about 30 m under water. To address these concerns a health and environmental impact assessment has been undertaken. Marine dispersion of potentially released radionuclides as a consequence of different hypothetical accident scenarios was modelled using the model NAOSIM. The outputs from the dispersion modelling have been used as inputs to food-chain transfer and environmental dosimetry models. The annual effective doses for subsistence fishing communities of the Barents-Kara seas region do not exceed 0.6 mSv for hypothetical accidents located at Stepovogo fjord or the Barents Sea. For high rate consumers of fish in Norway, following a potential accident at the Gremikha Bay, annual effects doses would be at around 0.15 mSv. Accumulated doses (over 90 days) for various organisms and for all release scenarios considered were never in excess of 150 μGy. The levels of 137Cs derived for marine organism in areas close to Norway were not values that would likely cause concern from a regulatory perspective although for subsistence fishing communities close to the considered accident locations, it is not inconceivable that some restrictions on fishing etc. would need to be introduced.

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 which combines the gap-free spatial coverage of the passive microwave sea ice concentrations and the 1 km resolution of the thermal infrared sea ice concentrations. 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 as sea ice concentration between 60 % and 80 %. They are not resolved by the coarser passive microwave sea ice concentration product. 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 beneath 0 °C and thus more than 20 °C above the average. Two estimates of thermodynamic growth yield accumulated growth of 60 and 65 cm at the end of March. This compares well with airborne sea ice thickness measurements. 33 km3 of sea ice were produced thermodynamically.

The transport of nuclear or radioactive materials and the presence of nuclear powered vessels pose risks to the Northern Seas in terms of potential impacts to man and environment as well socio-economic impacts. Management of incidents involving actual or potential releases to the marine environment are potentially difficult due to the complexity of the environment into which the release may occur and difficulties in quantifying risk to both man and environment. In order to address this, a state of the art oceanographic model was used to characterize the underlying variability for a specific radionuclide release scenario. The resultant probabilistic data were used as inputs to transfer and dose models providing an indication of potential impacts for man and environment This characterization was then employed to facilitate a rapid means of quantifying risk to man and the environment that included and addressed this variability. The radionuclide specific risk indices derived can be applied by simply multiplying the reported values by the magnitude of the source term and thereafter summing over all radionuclides to provide an indication of total risk.

We present the prototype of a a flexible modelling system for Arctic Mission Benefit Analysis (ArcMBA) that evaluates in a mathematically rigorous fashion the observational constraints imposed by individual and groups of EO data products in using the quantitative network design (QND) approach. The assessment of the observation impact (added value) is performed in terms of the uncertainty reduction in a four-week forecast of sea ice and snow volumes (SIV and SNV) for three regions along the Northern Sea Route (NSR) by a coupled model of the sea ice-ocean system, which is extended by observation operators that link the simulated variables to equivalents of sea ice thickness (SIT), sea ice freeboard (SIFB), radar freeboard (RFB), laser freeboard (LFB), and snow depth (SND) products.

Empirical error functions for 6 different low-resolution Arctic sea-ice drift products are presented on monthly time-scales. To assess the error statistics of the Eulerian ice-drift products, we use high-resolution Lagrangian sea-ice drift obtained from synthetic aperture radar (SAR) images. We processed the Lagrangian drift to Eulerian drift vectors and used them as a reference for the error assessment. Unlike sea-ice buoy trajectory data traditionally used for that purpose, SAR offers a much larger number of data, which enables us to do a thorough assessment of the error statistics of the Eulerian products under different ice conditions. We find that the error statistics differ between the products and between the seasons. For some products the error is dependent on ice drift speed, while for others the error is rather dependent on ice concentration or on both. The summer ice drifts have roughly a two times larger error than the winter drifts, and show significant mean biases. The calculated empirical error functions allow us to derive uncertainty maps for the respective products. These maps can be used for model validation and data assimilation.

Time-space varying uncertainty maps of monthly mean Arctic summer ice drift are presented. To assess the error statistics of two low-resolution Eulerian ice drift products, we use high-resolution Lagrangian ice motion derived from synthetic aperture radar (SAR) imagery. The Lagrangian trajectories from the SAR data are converted to an Eulerian format to serve as reference for the error assessment of the Eulerian products. The statistical error associated with the conversion is suppressed to an acceptable level by applying a threshold for averaging. By using the SAR ice drift as a reference, we formulate the uncertainty of monthly mean ice drift as an empirical function of drift speed and ice concentration. The empirical functions are applied to derive uncertainty maps of Arctic ice drift fields. The estimated uncertainty maps reasonably capture an increase of uncertainty with the progress of summer melting season. The uncertainties range from 1.0 cm s−1 to 2.0 cm s−1, which indicates that the low-resolution Eulerian products for summer seasons are of practical use for climate studies, model validation and data assimilation, if their uncertainties are appropriately taken into account.

An intercomparison of four low-resolution remotely sensed ice-drift products in the Arctic Ocean is presented. The purpose of the study is to examine the uncertainty in space and time of these different drift products. The comparison is based on monthly mean ice drifts from October 2002 to December 2006. The ice drifts were also compared with available buoy data. The result shows that the differences of the drift vectors are not spatially uniform, but are covariant with ice concentration and thickness. In high (low) ice-concentration areas, the differences are small (large), and in thick (thin) ice-thickness areas, the differences are small (large). A comparison with the drift deduced from buoys reveals that the error of the drift speed depends on the magnitude of the drift speed: larger drift speeds have larger errors. Based on the intercomparison of the products and comparison with buoy data, uncertainties of the monthly mean drift are estimated. The estimated uncertainty maps reasonably reflect the difference between the products in relation to ice concentration and the bias from the buoy drift in relation to drift speed. Examinations of distinctive features of Arctic sea ice motion demonstrate that the transpolar drift speed differs among the products by 13% (0.32 cm s−1) on average, and ice drift curl in the Amerasian Basin differs by up to 24% (3.3 × 104 m2 s−1). These uncertainties should be taken into account if these products are used, particularly for model validation and data assimilation within the Arctic.

Freshwater in the Arctic Ocean plays an important role in the regional ocean circulation, sea ice, and global climate. From salinity observed by a variety of platforms, we are able, for the first time, to estimate a statistically reliable liquid freshwater trend from monthly gridded fields over all upper Arctic Ocean basins. From 1992 to 2012 this trend was 600±300 km3 yr−1. A numerical model agrees very well with the observed freshwater changes. A decrease in salinity made up about two thirds of the freshwater trend and a thickening of the upper layer up to one third. The Arctic Ocean Oscillation index, a measure for the regional wind stress curl, correlated well with our freshwater time series. No clear relation to Arctic Oscillation or Arctic Dipole indices could be found. Following other observational studies, an increased Bering Strait freshwater import to the Arctic Ocean, a decreased Davis Strait export, and enhanced net sea ice melt could have played an important role in the freshwater trend we observed.

[1] Sea ice and snow on sea ice to a large extent determine the surface heat budget in the Arctic Ocean. In spite of the advances in modeling sea-ice thermodynamics, a good number of models still rely on simple parameterizations of the thermodynamics of ice and snow. Based on simulations with an Arctic sea-ice model coupled to an ocean general circulation model, we analyzed the impact of changing two sea-ice parameterizations: (1) the prescribed ice thickness distribution (ITD) for surface heat budget calculations, and (2) the description of the snow layer. For the former, we prescribed a realistic ITD derived from airborne electromagnetic induction sounding measurements. For the latter, two different types of parameterizations were tested: (1) snow thickness independent of the sea-ice thickness below, and (2) a distribution proportional to the prescribed ITD. Our results show that changing the ITD from seven uniform categories to fifteen nonuniform categories derived from field measurements, and distributing the snow layer according to the ITD, leads to an increase in average Arctic-wide ice thickness by 0.56 m and an increase by 1 m in the Canadian Arctic Archipelago and Canadian Basin. This increase is found to be a direct consequence of 524 km3 extra thermodynamic growth during the months of ice formation (January, February, and March). Our results emphasize that these parameterizations are a key factor in sea-ice modeling to improve the representation of the sea-ice energy balance.

Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean--sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (\unit{\mu}GA) as an example of a stochastic approach. The opt\imizations were performed by minimizing a cost function composed of model--data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation (``smoothed code'' versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the \unit{\mu}GA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (\unit{\mu}GA) is of practical use for parameter optimization of a coupled ocean--sea ice model with a medium-sized horizontal resolution of 50\,km\,$\times$\,50\,km as used in this study.

Due to the lack of data, the extent, thickness and drift patterns of sea ice and icebergs in the glacial Arctic remains poorly constrained. Earlier studies are contradictory proposing either a cessation of the marine cryosphere or an ice drift system operating like present-day. Here we examine the marine Arctic cryosphere during the Last Glacial Maximum (LGM) using a high-resolution, regional ocean-sea ice model. Whereas modern sea ice in the western Arctic Basin can circulate in the Beaufort Gyre for decades, our model studies present an extreme shortcut of glacial ice drift. In more detail, our results show a clockwise sea-ice drift in the western Arctic Basin that merges into a direct trans-Arctic path towards Fram Strait. This is consistent with dated ice plow marks on the seafloor, which show the orientation of iceberg drift in this direction. Also ice-transported iron-oxide grains deposited in Fram Strait, can be matched by their chemical composition to similar grains found in potential sources from the entire circum-Arctic. The model results indicate that the pattern of Arctic sea-ice drift during the LGM is established by wind fields and seems to be a general feature of the glacial ocean. Our model results do not indicate a cessation in ice drift during the LGM.

Unprecedented summer-season sampling of the Arctic Ocean during the period 2006–2008 makes possible a quasi-synoptic estimate of liquid freshwater (LFW) inventories in the Arctic Ocean basins. In comparison to observations from 1992 to 1999, LFW content relative to a salinity of 35 in the layer from the surface to the 34 isohaline increased by 8400±2000 km3 in the Arctic Ocean (water depth greater than 500 m). This is close to the annual export of freshwater (liquid and solid) from the Arctic Ocean reported in the literature. Observations and a model simulation show regional variations in LFW were both due to changes in the depth of the lower halocline, often forced by regional wind-induced Ekman pumping, and a mean freshening of the water column above this depth, associated with an increased net sea ice melt and advection of increased amounts of river water from the Siberian shelves. Over the whole Arctic Ocean, changes in the observed mean salinity above the 34 isohaline dominated estimated changes in LFW content; the contribution to LFW change by bounding isohaline depth changes was less than a quarter of the salinity contribution, and non-linear effects due to both factors were negligible.

Compartment models are widely used for the evaluation of radiological consequences to man and biota in the marine environment over large spatial and long temporal scales. The model developed at the Norwegian Radiation Protection Authority (NRPA) is based on a compartment modelling approach that includes terms describing dispersion of radionuclides into oceanic space with time (non-instantaneous mixing in oceanic space). In this paper the latest modification of the NRPA model will be presented. The main improvement concerns the "time of availability" parameters (i.e. the times at which dispersed radionuclides reach compartment boundaries). The modifications have been implemented through the use of a comprehensive 99 Tc data set collected under the course of the project "RADNOR" and through comparison with the results of simulations provided by the 3D hydrodynamic NAOSIM model. The present version of the NRPA model describes the dispersion of 99 Tc in the Arctic Ocean and seas with a significantly improved precision for some marine regions. Results of the calculations indicate that defined "time of availability" parameters are in good agreement with transit times observed in the actual marine environment.

Pacific Water (PW) enters the Arctic Ocean through Bering Strait and brings in heat, fresh water, and nutrients from the northern Bering Sea. The circulation of PW in the central Arctic Ocean is only partially understood due to the lack of observations. In this paper, pathways of PW are investigated using simulations with six state‐of‐the art regional and global Ocean General Circulation Models (OGCMs). In the simulations, PW is tracked by a passive tracer, released in Bering Strait. Simulated PW spreads from the Bering Strait region in three major branches. One of them starts in the Barrow Canyon, bringing PW along the continental slope of Alaska into the Canadian Straits and then into Baffin Bay. The second begins in the vicinity of the Herald Canyon and transports PW along the continental slope of the East Siberian Sea into the Transpolar Drift, and then through Fram Strait and the Greenland Sea. The third branch begins near the Herald Shoal and the central Chukchi shelf and brings PW into the Beaufort Gyre. In the models, the wind, acting via Ekman pumping, drives the seasonal and interannual variability of PW in the Canadian Basin of the Arctic Ocean. The wind affects the simulated PW pathways by changing the vertical shear of the relative vorticity of the ocean flow in the Canada Basin., Key Points: Pathways of the Arctic Pacific Water are investigated in ocean modelsVariability of the Pacific Water due to wind is examinedMechanisms of the Pacific Water variability are suggested

In order to investigate the causes of sea ice volume variations, two simulations have been performed using two different sea ice-ocean models driven by NCEP-NCAR reanalysis data over the period 1955-97. In both models, the largest changes in ice thickness occur in the central Arctic. The anomalous exchanges of sea ice, air, and water between the North Atlantic and the Arctic play a large role in explaining ice volume variations. In particular, the anomaly of oceanic heat transport between Iceland and Norway could alone explain a large part of the simulated ice volume changes. The time evolution of the ice volume appears well correlated with the low-frequency variations of the North Atlantic Oscillation (NAO). Nevertheless, the link between NAO and ice volume changes could operate through different mechanisms between the first and second half of the simulation. The influence of the NAO on the meridional heat transport in the North Atlantic and in the Nordic Seas hold during the whole simulation. Besides, the link between NAO and Fram Strait ice export, which is another important source of ice volume variability, is valid only for the second half of the simulation.

Within the framework of the Arctic Ocean Model Intercomparison Project results from several coupled sea ice–ocean models are compared in order to investigate vertically integrated properties of the Arctic Ocean. Annual means and seasonal ranges of streamfunction, freshwater and heat content are shown. For streamfunction the entire water column is integrated. For heat and freshwater content integration is over the upper 1000 m. The study represents a step toward identifying differences among model approaches and will serve as a base for upcoming studies where all models will be executed with common forcing. In this first stage only readily available outputs are compared, while forcing as well as numerical parameterizations differ. The intercomparison shows streamfunctions differing in pattern and by several Sverdrups in magnitude. Differences occur as well for the seasonal range, where streamfunction is subject to large variability.

The sensitivity of the Baltic Sea salinity to the freshwater supply is investigated using a 3-dimensional (3D) coupled sea-ice-ocean model. Today's climate is characterized by an average salinity of about 7.4 parts per thousand. and a freshwater supply, including river runoff and net precipitation, of about 16 000 m(3) s(-1). As recent results of some regional climate models have suggested a significant increase in precipitation in the Baltic catchment area due to anthropogenic climate change, in this study the response of salinity in the Baltic Sea to changing freshwater inflow is investigated. Of special interest is the possibility of the Baltic Sea becoming a freshwater sea with 0 parts per thousand salinity in the future. Therefore, model simulations with modified river runoff and precipitation for 1902-1998 were performed. The model is forced with daily sea-level observations in the Kattegat, monthly basin-wide discharge data, and reconstructed atmospheric surface data. The reconstruction utilizes a statistical model to calculate daily sea-level pressure, and monthly surface-air temperature, dew-point temperature, precipitation, and cloud-cover fields. It is assumed that the Kattegat deepwater salinity of about 33 parts per thousand. will not change regardless of the changed freshwater supply. In most of the experiments the final stratification is almost in a steady state after 100 yr. We found that even for a freshwater supply increased by 100% compared to 1902-1998 the Baltic Sea cannot be classified as a freshwater sea. A pronounced halocline still separates the upper and lower layers in the Baltic Proper, limiting the impact of direct wind mixing to the surface layer. A calculated phase diagram suggests that the relationship between freshwater supply and average salinity of the final steady state is non-linear. The results of the 3D model are in agreement with an analytical steady-state model assumed to work for freshwater changes smaller than 30 %. The latter model was applied in scenarios for the average salinity of the Baltic Sea.

The relation between sea ice drift and cyclone activity in the Fram Strait region was studied by both in situ observations and long-term time series. In a 1999 field campaign, the atmospheric forcing and the ice drift were determined using a research aircraft and drifting ice buoys. One cyclone entered the experimental area and caused a temporal increase in ice drift speed. Long-term studies are based on 16 years of cyclone statistics and model, satellite and sonar ice drift estimates. The actual impact of a cyclone depends on its particular track through Fram Strait. On the average, cyclones increase the Arctic ice export through Fram Strait.

Output from six regional sea ice-ocean climate model simulations of the arctic seas is compared to investigate the models' ability to accurately reproduce the observed late winter mean sea surface salinity. The results indicate general agreement within the Nordic seas, strong differences on the arctic continental shelves, and the presence of a climate drift that leads to a high salinity bias in most models within the Beaufort Gyre. The latter is highly sensitive to the wind forcing and to the simulation of freshwater sources on the shelves and elsewhere.

A 15-yr simulation of an ocean general circulation model, exposed to atmospheric forcing as provided by the ECMWF reanalysis 1979‐93, is analyzed with respect to the statistics of the surface circulation of the North Sea on timescales of days to several weeks in winter. The first two EOFs of surface circulation are found to represent the bulk of the variability (72%). They are broadly consistent with the limited observational record. The first EOF represents regimes with one gyre flushing the entire North Sea, either with clockwise orientation (15% of time) or with counterclockwise orientation (30% of time). These regimes are excited by northeasterly and, respectively, southwesterly wind. The second EOF is representative for two opposite regimes with two bipolar patterns in the northern and southern part of the North Sea (45% of time). For a certain range of both EOFs coefficients, the North Sea circulation ceases (10% of time). The circulation of the North Sea in winter is highly variable; the regimes change frequently. Only 40% of the one-gyre regimes persist for longer than 5 days, and the bipolar pattern regimes rarely extend for more than 5 days.

Two models of the North Sea are compared with respect to their performance in the assessment of sea level changes in a changing climate: the OPYC model, originally designed as a global ocean model and run in a regional version, and the HAMSOM, which was built as a shelf sea model and applied to an extended region in a simplified version. Both models agree very well in their hindcast skill as measured by correlation and explained variance. The reaction of both models to the '2 〈 CO2' and 'control' runs of the time slice experiments of the DKRZ (German Climate Computing Center) is also very similar and indicates an increase of up to 30 cm of winter mean sea levels and no significant (compared with the variability in the past) impact on the intra-monthly 90% quantiles. It is concluded that sea level is a rather robust parameter that could still be assessed with some confidence if both models were simplified further.

Anthropogenic radionuclides released into European coastal waters from nuclear fuel reprocessing plants at Sellafield (UK) and La Hague (France) flow northward through the Nordic Seas and label Atlantic Water (AW) entering the Arctic Ocean. Transport of the soluble radionuclide 129I through the Arctic Ocean has been simulated using a numerical model for the period from 1970 to 2010. The simulated tracer distributions closely conform to 129I measurements made across the Arctic Ocean during the mid-1990s and 2000s and clearly illustrate the dramatic changes in oceanic circulation which occurred during this time. The largest changes in surface circulation were associated with the transition from a negative to a positive phase of the Arctic Oscillation in the early 1990s and the subsequent return to a weak phase in the late 1990s and early 2000s. Model and experimental results indicate that a new circulation regime evolved in the late 2000s when a period of intense, anti-cyclonic surface stress led to a strengthening of the Beaufort Gyre. We submit that this resulted in a suppression of the counter-rotating boundary current of mid-depth Atlantic Water (AW) below the Beaufort Gyre, with upper AW in the Canada Basin showing signs of a reversal from cyclonic to anti-cyclonic flow. These results are consistent with the development of a new AW circulation scheme involving a separation between flow at intermediate depths in the Eurasian and Canada Basins which could eventually result in alteration of the source water characteristics of Arctic intermediate depth water in the Nordic seas.

The Arctic freshwater (FW) has been the focus of many modeling studies, due to the potential impact of Arctic FW on the deep water formation in the North Atlantic. A comparison of the hindcasts from ten ocean-sea ice models shows that the simulation of the Arctic FW budget is quite different in the investigated models. While they agree on the general sink and source terms of the Arctic FW budget, the long-term means as well as the variability of the FW export vary among models. The best model-to-model agreement is found for the interannual and seasonal variability of the solid FW export and the solid FW storage, which also agree well with observations. For the interannual and seasonal variability of the liquid FW export, the agreement among models is better for the Canadian Arctic Archipelago (CAA) than for Fram Strait. The reason for this is that models are more consistent in simulating volume flux anomalies than salinity anomalies and volume-flux anomalies dominate the liquid FW export variability in the CAA but not in Fram Strait. The seasonal cycle of the liquid FW export generally shows a better agreement among models than the interannual variability, and compared to observations the models capture the seasonality of the liquid FW export rather well. In order to improve future simulations of the Arctic FW budget, the simulation of the salinity field needs to be improved, so that model results on the variability of the liquid FW export and storage become more robust.

The Antarctic ice sheet loses mass at its fringes bordering the Southern Ocean. At this boundary, warm circumpolar water can override the continental slope front, reaching the grounding line through submarine glacial troughs and causing high rates of melting at the deep ice-shelf bases. The interplay between ocean currents and continental bathymetry is therefore likely to influence future rates of ice-mass loss. Here we show that a redirection of the coastal current into the Filchner Trough and underneath the Filchner-Ronne Ice Shelf during the second half of the twenty-first century would lead to increased movement of warm waters into the deep southern ice-shelf cavity. Water temperatures in the cavity would increase by more than 2 degrees Celsius and boost average basal melting from 0.2 metres, or 82 billion tonnes, per year to almost 4 metres, or 1,600 billion tonnes, per year. Our results, which are based on the output of a coupled ice-ocean model forced by a range of atmospheric outputs from the HadCM3 climate model, suggest that the changes would be caused primarily by an increase in ocean surface stress in the southeastern Weddell Sea due to thinning of the formerly consolidated sea-ice cover. The projected ice loss at the base of the Filchner-Ronne Ice Shelf represents 80 per cent of the present Antarctic surface mass balance. Thus, the quantification of basal mass loss under changing climate conditions is important for projections regarding the dynamics of Antarctic ice streams and ice shelves, and global sea level rise.

[1] Two anomalously warm inflow pulses into the Atlantic Water Layer of the Arctic Ocean have occurred since the late 1980s. As a consequence temperatures of the Arctic basins at 200–800 m depth have increased considerably in comparison to earlier decades. The warm inflow pulses also had a low density. Owing to the decadal time scale of the circulation in the Atlantic Water Layer large pools of anomalously light water have thereby formed in the Arctic Ocean. These will slowly drain back south into the Nordic Seas. We submit that they will be able to influence the overflows into the Atlantic across the Greenland-Scotland ridges. The Atlantic meridional overturning is fed by these overflows. Our model experiments indicate that the low-density anomalies from the Arctic Ocean may be able to reduce the Denmark Strait overflow 15–25 years after the entrance of the original signal through Fram Strait into the Arctic Ocean. The actual size of the reduction depends on the exact path and speed of the anomalies inside the Arctic proper and on local processes in the Arctic Ocean and the Nordic Sea.

[1] The past two decades saw a steady decrease of summer Arctic sea ice extent. The 2007 value was yet considerably lower than expected from extrapolating the long-term trend. We present a quantitative analysis of this extraordinary event based on the adjoint of a coupled ocean-sea ice model. This new approach allows to efficiently assess the sensitivity of the ice-covered area in September 2007 with respect to any potential influence factor. We can trace back 86% of the ice area reduction to only four of these factors: May and June wind conditions, September 2-meter temperature, and March ice thickness. Two thirds of the reduction are determined by factors that are already known at the end of June, suggesting a high potential for an early prediction.

[1] Antarctic marginal seas are susceptible to significant decadal variability as revealed by the analysis of a 200-year integration of a regional ice-ocean model forced with the atmospheric output of the IPCC climate model ECHAM5-MPIOM. The strongest signal occurs on the southern and western Weddell Sea continental shelf where changes in bottom salinity are initiated by a variable sea ice cover and modification of surface waters near the Greenwich meridian. Related zonal shifts of the western rim current guide deep waters with different temperature out of the Weddell Sea. With a deep boundary current the temperature signal propagates westward through southern Drake Passage and along the upper continental rise in the southeast Pacific thereby influencing the hydrographic conditions on the continental shelf of Bellingshausen, Amundsen, and Ross Seas.

[1] The ability to simulate the past variability of the sea ice-ocean system is of fundamental interest for the identification of key processes and the evaluation of scenarios of future developments. To achieve this goal atmospheric surface fields are reconstructed by statistical means for the period 1900 to 1997 and applied to a coupled sea ice-ocean model of the North Atlantic/Arctic Ocean. We devised a statistical model using a redundancy analysis to reconstruct the atmospheric fields. Several sets of predictor and predictand fields are used for reconstructions on different time scales. The predictor fields are instrumental records available as gridded or station data sets of sea level pressure and surface air temperature. The predictands are surface fields from the NCAR/NCEP reanalysis. Spatial patterns are selected by maximizing predictand variance during a “learning” period. The reliability of these patterns is tested in a validation period. The ensemble of reconstructions is checked for robustness by mutual comparison and an “optimal” reconstruction is selected. Results of the simulations with the sea ice-ocean model are compared with historical sea ice extent observations for the Arctic and Nordic Seas. The results obtained with the “optimal” reconstruction are shown to be highly consistent with these historical data. An analysis of simulated trends of the “early 20th century warming” and the recent warming in the Arctic complete the manuscript.