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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.

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.

We have equipped the unstructured‐mesh global sea‐ice and ocean model FESOM2 with a set of physical parameterizations derived from the single‐column sea‐ice model Icepack. The update has substantially broadened the range of physical processes that can be represented by the model. The new features are directly implemented on the unstructured FESOM2 mesh, and thereby benefit from the flexibility that comes with it in terms of spatial resolution. A subset of the parameter space of three model configurations, with increasing complexity, has been calibrated with an iterative Green's function optimization method to test the impact of the model update on the sea‐ice representation. Furthermore, to explore the sensitivity of the results to different atmospheric forcings, each model configuration was calibrated separately for the NCEP‐CFSR/CFSv2 and ERA5 forcings. The results suggest that a complex model formulation leads to a better agreement between modeled and the observed sea‐ice concentration and snow thickness, while differences are smaller for sea‐ice thickness and drift speed. However, the choice of the atmospheric forcing also impacts the agreement of the FESOM2 simulations and observations, with NCEP‐CFSR/CFSv2 being particularly beneficial for the simulated sea‐ice concentration and ERA5 for sea‐ice drift speed. In this respect, our results indicate that parameter calibration can better compensate for differences among atmospheric forcings in a simpler model (i.e., sea‐ice has no heat capacity) than in more realistic formulations with a prognostic sea‐ice thickness distribution and sea ice enthalpy., Plain Language Summary: The role of model complexity in determining the performance of sea‐ice numerical simulations is still not completely understood. Some studies suggest that a more sophisticated description of the sea‐ice physics leads to simulations that agree better with sea‐ice observations. Others, however, fail to establish a link between complex model formulations and improved model performance. Here, we investigate this open question by analyzing a set of sea‐ice simulations performed with a revised and improved sea‐ice model that features substantial modularity in terms of model complexity. Ten model parameters in three different model configurations are optimized to improve the agreement between model results and observations, allowing a fair comparison between model configurations with varying complexity. The model optimization is repeated for two different atmospheric forcings to shed light on the relationship between model complexity and other sources of uncertainty in the sea‐ice simulations, such as those associated with the atmospheric conditions. The results suggest that a more complex formulation of our model can lead to a more appropriate representation of sea ice concentration and snow thickness, while it is less relevant for sea‐ice thickness and drift., Key Points: Increased sea‐ice model complexity can improve the simulated sea‐ice concentration and snow thickness Sea‐ice thickness and drift are only weakly affected by model complexity Parameter calibration can better compensate for differences between atmospheric forcings in a simpler model, Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347, European Commission (EC) http://dx.doi.org/10.13039/501100000780, US Department of Energy (DOE)

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.

International audience; There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017–2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.

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.

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.

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.

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 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.

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.

The inflow of water from the Atlantic Ocean has long been known to be an essential source of heat and salt for the Nordic Seas and the Arctic Ocean (Hansen and Osterhus 2000). However, only in the period of the projects VEINS (Variability of Exchanges in the Northern Seas) and ASOF (Arctic /Subarctic Ocean Flux Study) a coordinated effort to quantify the oceanic lateral fluxes in the Arctic/Subarctic domain has been attempted. In VEINS and ASOF, the simultaneous observation of the fluxes linking the Nordic Seas with adjacent oceans was combined with numerical modelling, providing an opportunity to synthesise the observations in a larger-scale context. In older literature on the oceanography of the Nordic Seas and the Arctic Ocean temporal variability had largely been ignored. An exception is the oceanic response to seasonally and interannually variable wind fields (e.g. Proshutinsky and Johnson 1997 and references therein). Only very few investigations have addressed variability of temperature and salinity fields due to variable fluxes at the upper boundaries or the lateral gateways. This changed dramatically in the recent decade after Quadfasel et al. (1991) had measured a significant increase of temperatures in the eastward Atlantic Water (AW) boundary current on the northern Barents Sea slope, relative to historical values. Then, it was not clear whether the observed warming was part of a long-term trend or an expression of low-frequency oscillations in the inflow water properties. Subsequent analysis of temperature and salinity observations in the West Spitsbergen Current (WSC) had shown that signals approaching from the south were fluctuating interannually (Grotefendt et al. 1998; Saloranta et al. 2001; Furevik 2001). However, a possible link of the fluctuating signals in the WSC with the patchy

International audience; The coincidence of rapid change in Arctic climate (the extreme 2007 decline in sea ice and recent unprecedented warming) and enhanced observational activities during the International Polar Year (IPY 2007-2008) offers hope that these changes will be documented in great detail. However, in order to explain changes in the Arctic and predict its future dynamics, models of the Arctic climatic system are needed to reproduce past and present states and to predict future transformations. Results from existing models are not always satisfactory [e.g., Stroeve et al., 2007] because there are significant uncertainties in model forcing, parameterization of physical processes, and internal model parameters.

[1] A series of sensitivity experiments using a coupled regional atmosphere-ocean-ice model of the Arctic has been conducted in order to identify the requirements needed to reproduce observed sea-ice conditions and to address uncertainties in the description of Arctic processes. The ability of the coupled model to reproduce observed summer ice retreat depends largely on a quasi-realistic ice volume at the beginning of the melting period, determined by the relationship between winter growth and summer decay of ice. While summer ice decay is strongly affected by the parameterization of the sea-ice albedo, winter ice growth depends significantly on the parameterization of lateral freezing. Reciprocal model biases due to uncertainties in the atmospheric energy fluxes can be compensated to a certain extent. However, potential underlying weaknesses of the model cannot be eliminated that way. Since lateral freezing also determines the ice concentration during winter, and thus the heat loss of the ocean and the near-surface air temperature, the model tuning possibilities are limited. A large uncertainty in the model relates to the simulation of long-wave radiation most likely as a result of overestimated cloud cover. The results suggest that uncertainties in the descriptions for Arctic clouds, snow, and sea-ice albedo, and lateral freezing and melting of sea ice, including the treatment of snow, are responsible for large deviations in the simulation of Arctic sea ice in coupled models. Improved descriptions of these processes are needed to reduce model biases and to enhance the credibility of future climate change projections.

[1] Observations indicate that the occurrence of dense upper-ocean water masses coincides with periods of intense deep-water formation in the Greenland Sea. This paper focuses on the upper-ocean hydrography of the area and its simulation in models. We analyze properties that reside below the summer mixed layer at 200 m and carry the winter mixing signal. The analysis employs numerical simulations from four different models, all of which are forced as specified by the Arctic Ocean Model Intercomparison Project (AOMIP). The models exhibit varying degrees of success in simulating upper-ocean properties observed in the Greenland Sea, including very dense, saline water masses in the 1950s, 1960s, and 1970s. Two of the models predict the importance of salinity in determining the maximum density in the upper waters of the central gyre. The circulation pattern of Atlantic Water was captured well by two high-resolution models as measured by temperature-salinity-density relationships. The simulated temporal variability of Atlantic Water properties was less satisfactory, particularly in the case of salinity.

The article of record as published may be found at http://dx.doi.org/10.1029/2006JC003642 As a part of the Arctic Ocean Model Intercomparison Project, results from 10 Arctic ocean/ice models are intercompared over the period 1970 through 1999. Models' monthly mean outputs are laterally integrated over two subdomains (Amerasian and Eurasian basins), then examined as functions of depth and time. Differences in such fields as averaged temperature and salinity arise from models' differences in parameterizations and numerical methods and from different domain sizes, with anomalies that develop at lower latitudes carried into the Arctic. A systematic deficiency is seen as AOMIP models tend to produce thermally stratified upper layers rather than the “cold halocline”, suggesting missing physics perhaps related to vertical mixing or to shelf‐basin exchanges. Flow fields pose a challenge for intercomparison. We introduce topostrophy, the vertical component of V×∇D where V is monthly mean velocity and ∇D is the gradient of total depth, characterizing the tendency to follow topographic slopes. Positive topostrophy expresses a tendency for cyclonic “rim currents”. Systematic differences of models' circulations are found to depend strongly upon assumed roles of unresolved eddies. National Science Foundation Office of Polar Programs International Arctic Research Center, University of Alaska Fairbanks U.S. Department of Energy, Climate Change Prediction Program Center for Computational Sciences at Oak Ridge National Laboratory NSF/ARCSS, by the NASA Global Modeling and Analysis, Radiation Sciences, Cryospheric Sciences Programs Russian Foundation for Basic Research OPP-0002239 OPP-0327664

[1] We use a subset of models from the coordinated experiment of the Arctic Ocean Model Intercomparison Project (AOMIP) to analyze differences in intensity and sense of rotation of Atlantic Water circulation. We focus on the interpretation of the potential vorticity (PV) balance. Results differ drastically for the Eurasian and the Amerasian Basins of the Arctic Ocean. We find indications that in the Eurasian Basin the lateral net flux of PV is a significant factor for the determination of the sense of rotation of Atlantic Water circulation on timescales beyond pentades. The main source of high PV causing cyclonic circulation in the Eurasian Basin is the Barents Sea, where the seasonal cycle of surface buoyancy fluxes forms stratified water that leaves the shelf and feeds the Atlantic Water Layer (AWL) in the Arctic Basins. However, in the Amerasian Basin vertical PV fluxes are the more important factor. These are closely related to wind field changes. We find an intense response of the AWL flow to wind forcing, approximated by the sea level pressure difference between the Bering Sea and the central Canadian Basin, which describes about half the variance of AWL flow of the Amerasian Basin. An experiment driven with a repeated atmospheric climatology exhibits an extreme case where a permanent high pressure system over the Beaufort Sea dominates the circulation in the Amerasian Basin, demonstrating the potential of the Beaufort Gyre to adjust in such a way as to suppress a cyclonic AWL flow in the Amerasian Basin. In more realistic cases the Beaufort Gyre still modulates the Amerasian Basin AWL circulation significantly.

This study was motivated by a strong warming signal seen in mooring-based and oceanographic survey data collected in 2004 in the Eurasian Basin of the Arctic Ocean. The source of this and earlier Arctic Ocean changes lies in interactions between polar and sub-polar basins. Evidence suggests such changes are abrupt, or pulse-like, taking the form of propagating anomalies that can be traced to higher-latitudes. For example, an anomaly found in 2004 in the eastern Eurasian Basin took ∼1.5 years to propagate from the Norwegian Sea to the Fram Strait region, and additional ∼4.5–5 years to reach the Laptev Sea slope. While the causes of the observed changes will require further investigation, our conclusions are consistent with prevailing ideas suggesting the Arctic Ocean is in transition towards a new, warmer state.

The complexity of the state-of-the-art Ocean General Circulation Models (OGCMs) has increased and the quality of the model systems has improved considerably over the last decades. The improvement is caused by a variety of factors ranging from improved representation of key physical and dynamical processes, parallel development of at least three classes of OGCM systems, accurate and cost-effective numerical schemes, an unprecedented increase in computational resources, and the availability of synoptic, multidecadal atmospheric forcing fields. The implications of these improvements are that the present generation of OGCMs can, for the first time, complement available ocean observations and be used to guide forthcoming ocean observation strategies. OGCMs are also extensively used as laboratories for assessing cause-relationships for observed changes in the marine climate system, and to assess how the ocean system may change in response to, for instance, anomalous air-sea fluxes of heat, freshwater, and momentum. The Nordic Seas are a particularly challenging region for OGCMs because of characteristic length scales of only a few to about 10 km, a variety of complex and interrelated ocean processes, and extreme air-sea fluxes. This paper gives an overview of the status of the prognostic modelling of the Nordic Seas marine climate system. To exemplify the status, we present output from two widely different state-of-the-art OGCM systems. We also address processes that are still inadequately described in the current generation of OGCMs, thus providing guidelines for the future development of model systems particularly tailored for the Nordic Seas region.

[1] A large pool of freshwater formed of ice and runoff is hosted by the Arctic Ocean. It exits through the Canadian Archipelago and Fram Strait to enter the North Atlantic deep water production regions. Using a numerical model and observations we trace a strong freshwater release to subpolar waters in the mid-1990s. In contrast to the ice export driven 1970's ‘Great Salinity Anomaly’ its source was a large additional liquid freshwater release from the Arctic Ocean. In fact it was a consequence of a change of the Arctic Ocean's thermohaline structure in response to the very intense North Atlantic Oscillation in the early 1990s. Our results show a strong link of large-scale Arctic Ocean changes with the freshwater flux to subpolar waters.

[1] The impact of North Atlantic Current (NAC) volume, heat, and salt transport variability onto the Nordic Seas and the Arctic Ocean is investigated using numerical hindcast and sensitivity experiments. The ocean-sea ice model reproduces observed propagation pathways and speeds of SST anomalies. Signals reaching the entrance to the Nordic Seas between Iceland and Scotland originate partly in the lower-latitude North Atlantic. Response experiments with different prescribed conditions at 50°N show that changes in the barotropic flow across 50°N have no impact on the seas north of the Greenland-Scotland Ridge because of the strong deformation of the f/H field. A temperature anomaly inserted in the upper 500 m at 50°N, on the other hand, has a widespread effect on the temperature distribution and the circulation in the high-latitude North Atlantic. NAC induced variability in the Nordic Seas and locally induced variability have similar magnitude. The local atmospheric influence and the complexity of North Atlantic-Nordic Seas advection pathways make it unlikely that detection of signal propagation in the NAC could lead to a prediction of oceanic conditions in the Nordic Seas and the Arctic Ocean with several years lead time.

Monthly energetics of the Arctic Ocean are estimated based on results from six different coupled ice-ocean models. The components of the kinetic, potential and available potential energies, energy conversion and forcing rates are studied. The energy balances derived from the models differ significantly in the abyss, notably regarding the conversion of potential and kinetic energies. The models produce arctic boundary undercurrents controlled by the non-geostrophic components of the momentum equation, like advection and friction. Discrepancies exist where the modeled boundary currents are located and how completely the flow circulates around the Arctic Ocean. Two models produce cyclonic circulation, which is strongest at the depths of 300–800 m. The initial stratification, based on observations, contains a marked gradient of the available potential energy between the Eurasian and Canadian Basins with two corresponding circulation cells. The stratification is modified by the modeled circulation systematically so that this gradient vanishes. The models aim to produce a closer match toward the expected circulation, but result in a deviation from the observed, initial stratification.

Convection in the Greenland and Labrador seas is compared using a sea-ice-ocean model forced with NCEP reanalysis atmospheric data for the period 1948-2001. Model-derived convection rates for the Greenland Sea and the Labrador Sea show good agreement with previous estimates. Composites based on convection indices are used to identify important forcing processes and the relationship to oceanic, atmospheric, and sea-ice fields. Convection in the Labrador Sea is dominated by large-scale atmospheric forcing, especially by the heat fluxes associated with the North Atlantic Oscillation (NAO). On the other hand, we find no robust correlation between Greenland Sea convection and the NAO. In the model, local sea-ice formation, wind direction, and associated sea-ice drift are important parameters affecting convection in the Greenland Sea.

[1] The regional coupled atmosphere-ice-ocean model HIRHAM-MOM has been developed to simulate the Arctic climate. The model has been applied for the year 1990, which was characterized by anomalous ice retreat along the eastern Arctic coasts. Many observed features of the anomalous atmospheric circulation and sea ice concentration pattern during spring to early summer are reproduced by the model. It was even able to generate the extreme summer sea ice conditions in the Eurasian Arctic and the associated high surface air temperatures. The model shows less success in simulating the large ice retreat in the Siberian Arctic in late summer. This is explained mainly by deviations in the simulated atmospheric circulations. Results from an ocean-ice-alone model confirm that the atmospheric forcing dominates the simulated ice retreat. On the other hand, a sensitivity study with the atmosphere-alone model shows the impact of the sea ice conditions on the atmospheric circulation. Only with the accurate satellite-derived sea ice data is the model able to reproduce the anomalous late summer atmospheric pressure patterns.

[1] Hindcast simulations for the period 1902–1998 have been performed using a three-dimensional coupled ice-ocean model for the Baltic Sea. Daily sea level observations in Kattegat, monthly basin-wide discharge data, and reconstructed atmospheric surface data have been used to force the Baltic Sea model. 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. Sensitivity experiments have been performed to explore the impact of the freshwater and saltwater inflow variability on the salinity of the Baltic Sea. The decadal variability of the average salinity is explained partly by decadal volume variations of the accumulated freshwater inflow from river runoff and net precipitation and partly by decadal variations of the large-scale sea level pressure over Scandinavia. During the last century two exceptionally long stagnation periods are found, the 1920s to 1930s and the 1980s to 1990s. During these periods, precipitation, runoff, and westerly winds were stronger, and salt transports into the Baltic were smaller than normal. As the response timescale on freshwater forcing of the Baltic Sea is about 35 years, seasonal and year-to-year changes of the freshwater inflow are too short to affect the average salinity significantly. We found that the impact of river regulation, which changes the discharge seasonality, is negligible.

Ice cover data simulated by a coupled sea ice-oceanmodel of the North Atlantic and the Arctic Ocean are compared withsatellite observations for the period 1978 to 2001. The capability ofthe model in reproducing the long-term mean state and the inter-seasonalvariability is demonstrated. The main modes of variability of thesatellite data and the simulation in the summer and winter half yearsare highly similar.Using NCEP/NCAR reanalysis data and the results from the sea ice-oceanmodel, we describe the relationship with atmospheric and oceanicvariables for the first two modes of sea-ice concentration variabilityin winter and in summer. The first winter mode shows a time delayedresponse to the Arctic Oscillation due to advection of heatanomalies in the ocean. The second winter mode is dominated by anevent in the late 1990s that is characterized by anomalously highpressure over the eastern Arctic. The first summer mode isstrongly influenced by the Arctic Oscillation of the previouswinter. The second summer mode is caused by anomalous air temperaturein the Arctic. This mode shows a distinctive trend and is related to anice extent reduction of about 4 10^5 km^2 over the 23 years ofanalysis.

[1] A statistical model is developed to reconstruct atmospheric surface data for the period 1902–1998 to force a coupled sea ice-ocean model of the Baltic Sea. As the response timescale of the Baltic Sea on freshwater inflow is of the order of 30–40 years, climate relevant model studies should cover at least century-long simulations. Such an observational atmospheric data set is not available yet. We devised a statistical model using a ‘‘redundancy analysis’’ to reconstruct daily sea level pressure (SLP) and monthly surface air temperature (SAT), dew-point temperature, precipitation, and cloud cover of the Baltic. The predictor fields are daily SLP at 19 stations and monthly coarse gridded SAT and precipitation available for the period 1902 to 1998. The second input is a gridded atmospheric data set, with high resolution in space and time, based on synoptic stations, which is available for the period 1970–2001. Spatial patterns are selected by maximizing predictand variance during the ‘‘learning’’ period 1980–1998. The remainder period 1970–1979 is used for validation. We found the highest skill of the statistical model for SLP and the lowest skill for cloud cover. For wintertime the dominant modes of variability on the interannual to interdecadal timescales of the reconstruction are discussed. It is shown that the wintertime variability of SLP, SAT, and precipitation is related to well-known atmospheric patterns of the Northern Hemisphere: the North Atlantic Oscillation, the Scandinavia pattern, the East Atlantic/West Russia pattern, and the Barents Sea Oscillation. INDEX TERMS: 4215 Oceanography: General: Climate and interannual variability (3309); 4235 Oceanography: General: Estuarine processes; 4243 Oceanography: General: Marginal and semienclosed seas; 4255 Oceanography: General: Numerical modeling; KEYWORDS: Baltic Sea, climate reconstruction, redundancy analysis, sea iceocean modeling, major Baltic inflows Citation: Kauker, F., and H. E. M. Meier, Modeling decadal variability of the Baltic Sea: 1. Reconstructing atmospheric surface data for the period 1902 – 1998, J. Geophys. Res., 108(C8), 3267, doi:10.1029/2003JC001797, 2003.