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Understanding the changes of Fram Strait sea ice volume export and responsible processes is crucial due to their climate relevance. In this paper, we disentangled the processes driving the interannual variability and trends of the Fram Strait sea ice volume export in the early 21st century (2001-2019) by using dedicated numerical simulations with the support of observations. The significant decreasing trend in the sea ice volume export is caused by the persistent thinning trend of Arctic sea ice, while the interannual variability of the volume export is predominantly determined by winds. The interannual variability of the volume export can be mainly attributed to the variation in sea ice drift at Fram Strait, while the variation in Fram Strait sea ice thickness also plays an important role. As a result, the atmospheric mode that can better represent the wind variability driving the variability of both the sea ice drift and thickness at Fram Strait can better explain the variability of the sea ice volume export. The wintertime Arctic Oscillation (AO) and Fram Strait sea ice volume export continue to have a strong linkage in the early 21st century. The persistent thinning of Arctic sea ice preconditions events of anomalously low Fram Strait sea ice volume export. One of the extreme events in recent years occurred in 2017/2018. Variation in winds alone would not have caused such an extreme event without the persistent Arctic sea ice thinning. Plain Language Summary A strong freshening in the upper ocean of the northern North Atlantic was observed in the 1970s. This event was caused by very high export of sea ice volume through Fram Strait at the end of the 1960s and was the first well-documented Great Salinity Anomaly (GSA). GSAs can have strong impacts on the ocean circulation in the North Atlantic and may also affect weather. With persistent sea ice thinning in the Arctic Ocean, the export of Arctic sea ice through Fram Strait into the North Atlantic has fallen significantly in the early 21st century. An extreme event of very low sea ice volume export through Fram Strait in recent years is found in this study. This event is due to a combination of winds that tend to reduce sea ice export and the ongoing thinning of Arctic sea ice over past decades. As we expect that Arctic sea ice will continue to decline in a warming world, even stronger events can be anticipated later. Will such events of low sea ice export cause a "positive" GSA, with higher surface salinities in the northern North Atlantic and significant impacts on ocean circulation? This remains to be better monitored and understood. [ABSTRACT FROM AUTHOR]

The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term "the new Arctic." Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources--inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ ice surface--and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and mid-depth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions. [ABSTRACT FROM AUTHOR]

Numerical models of the atmosphere, oceans, and sea ice are divided into horizontal grid cells that can range in size from a few kilometers to hundreds of kilometers. In these models, many surface-level variables are assumed to be uniform over a grid cell. Using a year of in situ data from the experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA), the authors investigate the accuracy of this assumption of gridcell uniformity for the surface-level variables pressure, air temperature, wind speed, humidity, and incoming longwave radiation. The paper bases its analysis on three statistics: the monthly average and, for each season, the spatial correlation function and the spatial bias. For five SHEBA sites, which had a maximum separation of 12 km, the analysis supports the assumption of gridcell uniformity in pressure, air temperature, wind speed, and humidity in all seasons. In winter, when the incidence of fractional cloudiness is largest, the incoming longwave radiation may not be uniform over a grid cell. In other seasons, the bimodal distribution in cloud cover-either clear skies or total cloud cover-tends to homogenize the incoming radiation at scales of 12 km and less. [ABSTRACT FROM AUTHOR]

The climate model projections of ice reductions lead to the idea that new trans-Arctic shipping routes linking the Atlantic and Pacific Oceans could be open. In order to support and enhance the polar components of GMDSS five new METAREAs have been established by IMO in 2011. The responsibilities for the issuing and transmission of the meteorological marine safety information are presented in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we present the inclusion of an online dynamical downscaling of heat and moisture within the model of intermediate complexity iLOVECLIM v1.1. We describe the followed methodology to generate temperature and precipitation fields on a 40 km x 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is non grid-specific and conserves energy and moisture. We show that we are able to generate a high resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Whilst the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature includes ice sheet model coupling and high-resolution land surface model. [ABSTRACT FROM AUTHOR]

High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice and melt ponds is time-consuming and labor-intensive. In this study, an object-based classification algorithm is developed to automatically extract sea ice and melt ponds efficiently from 163 aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the Arctic Pacific Sector. The photographs are selected from 599 cloud-free photographs based on their image quality and representativeness in the marginal ice zone (MIZ). The algorithm includes three major steps: (1) the image segmentation groups the neighboring pixels into objects according to the similarity of spectral and textural information; (2) the random forest ensemble classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice along ice edges), shadow, and ice/snow; and (3) the polygon neighbor analysis further separates melt ponds and submerged ice from the GSI according to their spatial relationships. The overall classification accuracy for the four general classes is 95.5% based on 178 ground reference objects. Furthermore, the producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection through 98 independent reference objects. For the 163 photos examined, a total of 19,438 melt ponds larger than 1 m 2 are detected, with a pond density of 867.2 km − 2 , mean pond size of 32.6 ± 0.03 m 2 , and mean pond fraction of 0.06 ± 0.006; a total of 42,468 ice floes are detected, with the mean floe size of 173.3 ± 0.1 m 2 (majority in 1–30 m 2 ) and mean ice concentration of 46.1 ± 0.5% (ranging from 18.6–98.6%). These results matched well with ship-based visual observations in the MIZ in the same area and time. The method presented in the paper can be applied to data sets of high spatial resolution Arctic sea ice photographs for deriving detailed sea ice concentration, floe size, and melt pond distributions over wider regions, and extracting sea ice physical parameters and their corresponding changes between years. [ABSTRACT FROM AUTHOR]

Climate change is especially strong in the region of the Arctic Ocean, and will have an important impact on its thermo‐haline structure. We analyze the results of a hindcast simulation of a new 3D ocean model of the Arctic and North Atlantic oceans for the period 1970–2019. We compared the time period 1970–1999 with the time period 2010–2019. The comparison showed that there is a decrease of stratification between the two periods over most of the shallow Arctic shelf seas and in the core of the Transpolar Ice Drift. Fresh water inputs to the ocean surface decline, and inputs of momentum to the ocean increase, which can explain the decrease in stratification. The comparison also showed that the mixed layer becomes deeper during winter, in response to the weakened stratification owing to increased vertical mixing. The comparison of summer mixed layer depths between the two time periods follows a deepening pattern that is less evident. Regional exceptions include the Nansen Basin and the part of the Canadian Basin bordering the Canadian Archipelago, where the mixed layer shoals. Trends of freshwater fluxes imply that the changes of haline stratification in these regions are also influenced by other processes, for example, horizontal advection of fresh water, increased mixing and changes in the underlaying water masses. Runoff increase toward the Arctic Ocean can locally decrease but also increase salinity, and has an impact on stratification which can be explained by coastal dynamics. The results emphasize the non‐linear nature of Arctic Ocean dynamics. Plain Language Summary: We analyzed the results of an ocean model simulation for the Arctic and North Atlantic oceans for the period 1970–2019. Our model is in line with the recent observed changes in the Arctic Ocean and allows, in contrast to the rather sparse observations, a detailed assessment of stratification changes. These changes will affect the Arctic ecosystem and are also believed to affect the large scale ocean circulation. We show that major changes in upper ocean conditions are caused by changes in the fresh water supply by sea ice and varying effect of the wind on regions that are now becoming ice‐free. We also study the effect of changes in river runoff into the Arctic Ocean. Our study shows that an increase in river runoff can change the coastal circulation and results, paradoxically, in regions of higher salinity. These results point to the importance of modeling tools when it comes to a better understanding of ocean processes in a changing climate. Key Points: Results from a hindcast simulation of the Arctic Ocean for the period 1970–2019 show strong changes in stratificationThe changes in stratification are explained by altered surface stress and freshwater fluxesTrends in river runoff have little effect on the mixed layer depth but change the Arctic coastal circulation [ABSTRACT FROM AUTHOR]

Phytoplankton in the Arctic Ocean are subject to nitrogen limitation in the summer, however, how severely the nitrogen stress affects phytoplankton physiology remains largely unknown. In the summers of 2015–2018, we examined the distribution of phytoplankton photophysiological properties across two contrasting regions of the Arctic Ocean with distinctly different levels of nitrogen availability in the upper water column. We quantified the extent of nitrogen stress using a highly sensitive fluorescence induction and relaxation system to obtain continuous underway measurements and via discrete sample analyses of phytoplankton physiology, as well as nutrient enrichment incubations. The results revealed vast regions in the Chukchi Sea where phytoplankton photosynthesis was severely nitrogen‐stressed. Thereby, the maximum quantum yield of photochemistry in photosystem II showed only a small decrease (12 ± 9%) relative to its nutrient‐replete values, while the maximum photosynthetic electron transport rates under saturating irradiance were impaired to a greater extent (40 ± 17%). This phytoplankton photosynthesis response is indicative of a severe nitrogen limitation, which results in dramatic reduction in growth and net primary production rates. Nutrient enrichment incubations also revealed a marked increase in large‐size phytoplankton growth (>10 μm) after the nitrogen stress was alleviated, suggesting that the larger cells were more susceptible to nitrogen stress. These results are important for understanding how regional nitrogen fluxes control variability in the primary production and phytoplankton community structure and how these processes might change with rapid climate changes in the Arctic Ocean. Plain Language Summary: Nutrient availability is the main bottom‐up controls of phytoplankton physiology and growth in the upper ocean. The distribution of nutrient limitation in the global ocean varies greatly in space and time, so phytoplankton responses to this factor are essential for understanding the marine ecosystem. Although nitrogen limitation was previously shown in the Arctic Ocean in the summer, how nitrogen stress affects phytoplankton physiology remains largely unknown. This study investigates, with high spatial resolution, the distribution of phytoplankton physiological status and quantifies the effects of nitrogen stress in the western Arctic Ocean. Our results revealed severe nitrogen limitation in the summer that results in dramatic reduction in growth and net primary production in this region of the ocean. Therefore, alterations in nitrogen fluxes along with climate change in the Arctic Ocean would be important for controlling phytoplankton growth and primary production in this region. Key Points: Regional nitrogen availability in the Arctic Ocean is an important factor determining the physiological status of phytoplanktonSevere nitrogen limitation reduces gross photosynthetic rates of phytoplankton in the western Arctic Ocean in summer by approximately 40%Large‐sized phytoplankton are more susceptible to nitrogen stress in the Arctic Ocean [ABSTRACT FROM AUTHOR]

The impact of April sea-ice thickness (SIT) initialization on the predictability of September sea-ice extent (SIE) is investigated based on a series of perfect model ensemble experiments using the MIROC5.2 climate model. Ensembles with April SIT initialization can accurately predict the September SIE for greater lead times than in cases without the initialization – up to 2 years ahead. The persistence of SIT correctly initialized in April contributes to the skilful prediction of SIE in the first September. On the other hand, errors in the initialization of SIT in April cause errors in the predicted sea-ice concentration and thickness in the Pacific sector from July to September and consequently influence the predictive skill with respect to SIE in September. The present study suggests that initialization of the April SIT in the Pacific sector significantly improves the accuracy of the September SIE forecasts by decreasing the errors in sea-ice fields from July to September. [ABSTRACT FROM AUTHOR]

With Arctic summer sea ice potentially disappearing halfway through this century, the surface albedo and insulating effects of Arctic sea ice will decrease considerably. The ongoing Arctic sea ice retreat also affects the strength of the Planck, lapse rate, cloud, and surface albedo feedbacks together with changes in the heat exchange between the ocean and the atmosphere, but their combined effect on climate sensitivity has not been quantified. This study presents an estimate of all Arctic sea ice related climate feedbacks combined. We use a new method to keep Arctic sea ice at its present-day (PD) distribution under a changing climate in a 50-yr CO2 doubling simulation, using a fully coupled global climate model (EC-Earth, version 2.3). We nudge the Arctic Ocean to the (monthly dependent) year 2000 mean temperature and minimum salinity fields on a mask representing PD sea ice cover. We are able to preserve about 95% of the PD mean March and 77% of the September PD Arctic sea ice extent by applying this method. Using simulations with and without nudging, we estimate the climate response associated with Arctic sea ice changes. The Arctic sea ice feedback globally equals 0.28 ± 0.15 W m−2 K−1. The total sea ice feedback thus amplifies the climate response for a doubling of CO2, in line with earlier findings. Our estimate of the Arctic sea ice feedback agrees reasonably well with earlier CMIP5 global climate feedback estimates and shows that the Arctic sea ice exerts a considerable effect on the Arctic and global climate sensitivity. [ABSTRACT FROM AUTHOR]

The diminishing Arctic sea ice pack has been widely studied, but previous research has mostly focused on time-mean changes in sea ice rather than on short-term variations that also have important physical and societal consequences. In this study we test the hypothesis that future interannual Arctic sea ice area variability will increase by utilizing 40 independent simulations from the Community Earth System Model's Large Ensemble (CESM-LE) for the 1920–2100 period and augment this with simulations from 12 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both CESM-LE and CMIP5 models project that ice area variability will indeed grow substantially but not monotonically in every month. There is also a strong seasonal dependence in the magnitude and timing of future variability increases that is robust among CESM ensemble members. The variability generally correlates with the average ice retreat rate, before there is an eventual disappearance in both terms as the ice pack becomes seasonal in summer and autumn by late century. The peak in variability correlates best with the total area of ice between 0.2 and 0.6 m monthly thickness, indicating that substantial future thinning of the ice pack is required before variability maximizes. Within this range, the most favorable thickness for high areal variability depends on the season, especially whether ice growth or ice retreat processes dominate. Our findings suggest that thermodynamic melting (top, bottom, lateral) and growth (frazil, congelation) processes are more important than dynamical mechanisms, namely ice export and ridging, in controlling ice area variability. [ABSTRACT FROM AUTHOR]

Midlatitude anthropogenic mercury (Hg) emissions and discharge reach the Arctic Ocean (AO) by atmospheric and oceanic transport. Recent studies suggest that Arctic river Hg inputs have been a potentially overlooked source of Hg to the AO. Observations on Hg in Eurasian rivers, which represent 80% of freshwater inputs to the AO, are quasi-inexistent, however, putting firm understanding of the Arctic Hg cycle on hold. Here, we present comprehensive seasonal observations on dissolved Hg (DHg) and particulate Hg (PHg) concentrations and fluxes for two large Eurasian rivers, the Yenisei and the Severnaya Dvina. We find large DHg and PHg fluxes during the spring flood, followed by a second pulse during the fall flood. We observe well-defined water vs. Hg runoff relationships for Eurasian and North American Hg fluxes to the AO and for Canadian Hg fluxes into the larger Hudson Bay area. Extrapolation to pan-Arctic rivers and watersheds gives a total Hg river flux to the AO of 44 ° 4 Mg per year (1σ), in agreement with the recent model-based estimates of 16 to 46 Mg per year and Hg/dissolved organic carbon (DOC) observation-based estimate of 50 Mg per year. The river Hg budget, together with recent observations on tundra Hg uptake and AO Hg dynamics, provide a consistent view of the Arctic Hg cycle in which continental ecosystems traffic anthropogenic Hg emissions to the AO via rivers, and the AO exports Hg to the atmosphere, to the Atlantic Ocean, and to AO marine sediments. [ABSTRACT FROM AUTHOR]

A key parameterization in sea ice models describes the subgrid scale ice thickness distribution. Based on only a few observations, the ice thickness distribution model was shown to be consistent with field data and to improve the simulation's large‐scale properties. The available submarine and airborne observations enable to evaluate in greater detail the ability of a pan‐Arctic sea ice‐ocean model with an ice thickness distribution parameterization to reproduce observed thickness distributions in different regions and seasons. Many observations are reproduced accurately. Some cases of poorly simulated modes and tails of the distributions are tentatively attributed to simplified thermodynamics and inaccurate deformation fields. Variability on decadal timescales, however, is generally underestimated. Thickness distributions in individual grid cells of the model show similar differences between regions and seasons as observed regional mean distributions, but the modeled grid‐scale variability is lower than observed. Simulated modal thicknesses of first‐year ice are only insufficiently different from those of multiyear ice. The modal thickness proves to be a useful metric for quantifying model biases in both dynamics and thermodynamics. In addition to improving basin‐wide mean variables, the ice thickness distribution parameterization provides reliable and valuable additional subgrid scale data. At the same time the low climate sensitivity of the parameterization may affect longer simulations with strong climate change aspects. Plain Language Summary: Sea ice is part of the climate system: computer models of sea ice are necessary for climate simulation. Many processes that shape sea ice in the Arctic Ocean cannot be represented in a computer model. For example, a sea ice model cannot distinguish between different ice thicknesses that are observed in a given area, but requires a submodel to calculate these ice thickness distributions, a model within the model. Any submodel must be tested against observations before it can be used with confidence. Here we repeat previous tests of the ice thickness distribution submodel, which had some data limitations, with a larger data set of new observations and a sea ice model of the entire Arctic Ocean. We find that the submodel works very well in many cases. Unfortunately, the model simulations do not agree with observed changes that happen slowly over 20 years and they do not contain as many small fluctuations as the observations. As a by‐product we find that we can learn a lot about computer models when we not only compare mean ice thickness to observations, but also the most frequent ice thickness. Key Points: Recent observations allow to evaluate ice thickness distributions in the Arctic on regional to local scalesA pan‐Arctic model simulates the observed regional and seasonal range of ice thickness distributions with some skillThe model underestimates the decadal variability of ice thickness distributions [ABSTRACT FROM AUTHOR]

Northward ocean heat transport and its variability influence the Arctic sea ice cover, contribute to surface warming or cooling, or simply warm or cool the Arctic Ocean interior. A simulation with the forced global ocean model NorESM20CR, aided by hydrographic observations since 1900, show large decadal fluctuations in the ocean heat transport, with the largest variations in the Atlantic sector. The simulated net poleward ocean heat transport over the last century is about 68 TW, and 88% of this occurs in the Barents Sea Opening (45 TW) and the Fram Strait (15 TW). Typical variations are 40 TW over time scales between 5 and 10 years, related to thermohaline and wind stress forcings. The mean heat transport in the Davis Strait is about 10 TW, and less than 5 TW flows north in the Bering Strait. The core temperature of the Atlantic Water (AW) entering the Arctic Ocean has increased in recent decades, consistent with an ongoing expansion of the Atlantic domain (Atlantification), but earlier warm events are also documented. The temperature of the northward‐flowing AW thus plays a vital role, with decadal variations of around 0.5 ∘C. The Nordic Seas atmosphere contributes with thermodynamic forcing, dampening the advected heat anomalies. In the Barents Sea, variations in the inflow volume flux dominate, while variations in temperature dominate the heat transport in the Fram Strait. There are significant trends over recent decades, also dominated by the Barents Sea that presently has 1 Sv higher volume transport and +1.0 ∘C warmer AW than the long‐term mean. Plain Language Summary: Ocean currents bring heat northward into the Arctic Ocean. This ocean heat influences the sea ice cover regionally and warms the Arctic Ocean surface and interior. Warm and salty Atlantic Water that enters the Arctic Ocean through the Fram Strait and the Barents Sea dominates the oceanic heat contribution to the Arctic Ocean in the 20th century. In this study, we have investigated how this ocean heat transport has varied over time and which physical mechanisms that influence these variations. Understanding these natural variations is important for explaining ongoing Arctic change today. Our main tool for investigation is a global ocean model driven by observed atmospheric variations, and we compare this model with observations of temperature and salinity in the Nordic Seas. We find that the ocean heat transport has varied on different time scales and that these variations are linked to changes in the wind systems in the Nordic Seas, atmosphere‐ocean heat exchanges, and, to some extent, local winds in the straits. Overall, the ocean heat transports and Atlantic Water temperatures have increased during recent decades. These changes are especially large at the Barents Sea entrance where the water has warmed about 1 ∘C. Key Points: Atlantic Ocean heat transport variability dominates in the Northern Hemisphere and on centennial scaleVolume transport changes due to wind stress curl and temperature due to advection and local forcingOcean heat transport in the Fram Strait is dominated by temperature variability but in the Barents Sea Opening by volume variability [ABSTRACT FROM AUTHOR]

Sea ice formation is accompanied by the rejection of salt which in nature tends to be mixed vertically by the formation of convective plumes. Here we analyze the influence of a salt plume parameterization in an atmosphere‐sea ice‐ocean model. Two 330‐yearlong simulations have been conducted with the AWI Climate Model. In the reference simulation, the rejected salt in the Arctic Ocean is added to the uppermost ocean layer. This approach is commonly used in climate modeling. In another experiment, employing salt plume parameterization, the rejected salt is vertically redistributed within the mixed layer based on a power law profile that mimics the penetration of salt plumes. We discuss the effects of this redistribution on the simulated mean state and on atmosphere–ocean linkages associated with the intensity of deepwater formation. We find that the salt plume parameterization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the Arctic. The salt plume parameterization considerably alters the interplay between the atmosphere and the ocean in the Nordic Seas. The parameterization modifies the ocean ventilation; however, resulting changes in temperature and salinity largely compensate each other in terms of density so that the overturning circulation is not significantly affected. Plain Language Summary: The process of salt rejection during the sea ice formation is not properly parameterized in the climate models. Here we implement the salt plume parameterization in an atmosphere‐ice‐ocean model and analyze its influence on the simulated mean state and associated atmosphere–ocean linkages. Salt plume parameterization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the Arctic. It is argued that salt plume parameterization alters the interplay between the atmosphere and the ocean in the Nordic Seas. Key Points: A salt plume parameterization for the Arctic Ocean has been implemented into the AWI Climate ModelThe salt plume parameterization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the ArcticIt is argued that the salt plume parameterization alters the interplay between the atmosphere and the ocean in the Nordic Seas [ABSTRACT FROM AUTHOR]

The appearance of winter deep mixed layers in the Arctic Ocean under a warming climate is investigated with the HiGEM coupled global climate model. In response to a four times increase of atmospheric CO2 levels with respect to present day conditions, the Arctic Basin becomes seasonally ice-free. Its surface becomes consequently warmer and, on average, slightly fresher. Locally, changes in surface salinity can be far larger (up to 4 psu) than the basin-scale average, and of a different sign. The Canadian Basin undergoes a strong freshening, while the Eurasian Basin undergoes strong salinification. These changes are driven by the spin up of the surface circulation, likely resulting from the increased transfer of momentum to the ocean as sea ice cover is reduced. Changes in the surface salinity field also result in a change in stratification, which is strongly enhanced in the Canadian Basin and reduced in the Eurasian Basin. Reduction, or even suppression, of the stratification in the Eurasian Basin produces an environment that is favourable for, and promotes the appearance of, deep convection near the sea ice edge, leading to a significant deepening of winter mixed layers in this region (down to 1000 m). As the Arctic Ocean is transitioning toward a summer ice-free regime, new dynamical ocean processes will appear in the region, with potentially important consequences for the Arctic Ocean itself and for climate, both locally and on larger scales. [ABSTRACT FROM AUTHOR]

This study evaluates different hypotheses of the origin of the Little Ice Age, focusing on the long-term response of Arctic sea ice and oceanic circulation to solar and volcanic perturbations. The authors analyze the Last Millennium Ensemble of climate model simulations carried out with the Community Earth System Model at the National Center for Atmospheric Research. The authors examine the duration and strength of volcanic perturbations, and the effects of initial and boundary conditions, such as the phase of the Atlantic multidecadal oscillation. They evaluate the impacts of these factors on decadal-to-multicentennial perturbations of the cryospheric, oceanic, and atmospheric components of the climate system. The authors show that, at least in the Last Millennium Ensemble, volcanic eruptions are followed by a decadal-scale positive response of the Atlantic multidecadal overturning circulation, followed by a centennial-scale enhancement of the Northern Hemispheric sea ice extent. It is hypothesized that a few mechanisms, not just one, may have to play a role in consistently explaining such a simulated climate response at both decadal and centennial time scales. The authors argue that large volcanic forcing is necessary to explain the origin and duration of Little Ice Age–like perturbations in the Last Millennium Ensemble. Other forcings might play a role as well. In particular, prolonged fluctuations in solar irradiance associated with solar minima potentially amplify the enhancement of the magnitude of volcanically triggered anomalies of Arctic sea ice extent. [ABSTRACT FROM AUTHOR]

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A new method, called contour shifting, is proposed for correcting the bias in forecasts of contours such as sea ice concentration above certain thresholds. Retrospective comparisons of observations and dynamical model forecasts are used to build a statistical spatiotemporal model of how predicted contours typically differ from observed contours. Forecasted contours from a dynamical model are then adjusted to correct for expected errors in their location. The statistical model changes over time to reflect the changing error patterns that result from reducing sea ice cover in the satellite era in both models and observations. For an evaluation period from 2001 to 2013, these bias-corrected forecasts are on average more accurate than the unadjusted dynamical model forecasts for all forecast months in the year at four different lead times. The total area, which is incorrectly categorized as containing sea ice or not, is reduced by 3.3 × 105 km2 (or 21.3%) on average. The root-mean-square error of forecasts of total sea ice area is also reduced for all lead times. [ABSTRACT FROM AUTHOR]

The Nordic Seas and the Barents Sea is the Atlantic Ocean's gateway to the Arctic Ocean, and the Gulf Stream's northern extension brings large amounts of heat into this region and modulates climate in northwestern Europe. We have investigated the predictive skill of initialized hindcast simulations performed with three state-of-the-art climate prediction models within the CMIP5-framework, focusing on sea surface temperature (SST) in the Nordic Seas and Barents Sea, but also on sea ice extent, and the subpolar North Atlantic upstream. The hindcasts are compared with observation-based SST for the period 1961-2010. All models have significant predictive skill in specific regions at certain lead times. However, among the three models there is little consistency concerning which regions that display predictive skill and at what lead times. For instance, in the eastern Nordic Seas, only one model has significant skill in predicting observed SST variability at longer lead times (7-10 years). This region is of particular promise in terms of predictability, as observed thermohaline anomalies progress from the subpolar North Atlantic to the Fram Strait within the time frame of a couple of years. In the same model, predictive skill appears to move northward along a similar route as forecast time progresses. We attribute this to the northward advection of SST anomalies, contributing to skill at longer lead times in the eastern Nordic Seas. The skill at these lead times in particular beats that of persistence forecast, again indicating the potential role of ocean circulation as a source for skill. Furthermore, we discuss possible explanations for the difference in skill among models, such as different model resolutions, initialization techniques, and model climatologies and variance. [ABSTRACT FROM AUTHOR]

We use a regionally coupled ocean-sea ice-atmosphere-hydrological discharge model to investigate the influence of changes in the atmospheric large-scale circulation on the interannual variability of the Arctic freshwater (FW) components. This model includes all sinks and sources of FW and allows for the analysis of a closed FW cycle in the Arctic. We show that few atmospheric winter modes explain large parts of the interannual variability of the Arctic FW cycle. A strong Icelandic low causing anomalous strong westerlies over the North Atlantic leads to warmer and wetter conditions over Eurasia. The ocean circulation is then characterized by a strong transpolar drift leading to increased export of FW in liquid and solid form into the North Atlantic. In contrast to this, a weaker than usual Icelandic low and a strong Siberian high is associated with a strong Beaufort Gyre and thus an accumulation of FW within the Arctic Ocean. Not only specific winter conditions but also increased precipitation in late spring and summer, caused by enhanced cyclone activity over land, lead to increased Eurasian runoff, which is responsible for most of the variability in Arctic river runoff. [ABSTRACT FROM AUTHOR]

Both Arctic sea ice loss and La Niña events can result in cold conditions in midlatitude Eurasia in winter. Since the two forcings sometimes occur simultaneously, determining whether they are independent of each other is undertaken first. The result suggests an overall independence. Considering possible interactions between them, their coordinated impacts on the Northern Hemisphere winter climate are then investigated based on observational data analyses, historical simulation analyses from one coupled model (MPI-ESM-LR) contributing to CMIP5, and atmospheric general circulation model sensitive experiments in ECHAM5. The results show that the impacts of the two forcings are overall linearly accumulated. In comparison with one single forcing, there is intensified cooling response in midlatitude Eurasia along with northern warmer-southern cooler dipolar temperature responses over North America. Despite the additive linearity, additive nonlinearity between the two forcings is identifiable. The nonlinearity causes midlatitude Eurasian cooling weakened by one-tenth to one-fifth as much as their individual impacts in combination. The underlying mechanisms for the weak additive nonlinearity are finally explored by transient adjustment AGCM runs with one single forcing or both the forcings switched on suddenly. The day-to-day evolution of responses suggests that the additive nonlinearity may arise initially from the forced wave dynamics and then be amplified because of the involvement of transient eddy feedbacks. [ABSTRACT FROM AUTHOR]

The authors explore possible temperature modifications of the Atlantic Water Layer (AWL) induced by climate change, performing simulations for 1970 to 2099 with a coupled ice-ocean Arctic model (CIOM). Surface fields to drive the CIOM were provided by the Canadian Regional Climate Model (CRCM), driven by outputs from the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) following the A1B climate change scenario. In the present climate, represented as 1990-2009, the CIOM can reliably reproduce the AWL compared to Polar Science Center Hydrographic Climatology (PHC) data. For the future climate, assuming the A1B climate change scenario, there is a significant increase in water volume transport into the central Arctic Ocean through Fram Strait due to the weakened atmospheric high pressure system over the western Arctic and an intensified atmospheric low pressure system over the Nordic seas. The AWL temperature tends to decrease from 0.36°C in the 2010s to 0.26°C in the 2060s. In the vertical, the warm Atlantic water core slightly expands before the 2030s, significantly shrinks after the 2050s, and essentially disappears by 2070-99, in the southern Beaufort Sea. The temperature decrease after 2030 is mainly due to the reduced heat fluxes in the Kara and Barents Seas. In the northeastern Barents and Kara Seas, the loss of sea ice increases the heat loss from the Atlantic water and reduces the water temperature near the bottom, contributing to decreased heat fluxes into the central Arctic Ocean, as well as decreased AWL temperature at central Arctic Ocean intermediate layers. In addition, the vertically integrated heat loss also plays an important role in the AWL cooling process. [ABSTRACT FROM AUTHOR]