Sea Ice Processes Research Articles

The Role of Sea Ice Insulation Effects on the Probability of AMOC Transitions

Abstract Recent simulations performed with the Community Earth System Model (CESM) have suggested a crucial role of sea ice processes in Atlantic meridional overturning circulation (AMOC) hysteresis behavior under varying surface freshwater forcing. Here, we further investigate this issue using additional CESM simulations and a novel conceptual ocean–sea ice box model. The CESM simulations suggest that the presence of sea ice gives rise to the existence of statistical equilibria with a weak AMOC strength. This is confirmed in the conceptual model, which captures similar AMOC hysteresis behavior as in the CESM simulation and where steady states are computed versus freshwater forcing parameters. In the conceptual model, transition probabilities between the different equilibrium states are determined using rare event techniques. The transition probabilities from a strong AMOC state to a weak AMOC state increase when considering sea ice insulation effects and indicate that sea ice promotes these transitions. On the other hand, sea ice insulation effects strongly reduce the probabilities of the reverse transition from a weak AMOC state to a strong AMOC state and this implies that sea ice also limits AMOC recovery. The results here indicate that sea ice effects play a dominant role in AMOC hysteresis width and influence transition probabilities between the different equilibrium states. Significance Statement We develop a novel conceptual ocean–sea ice box model to explain AMOC hysteresis behavior recently found in a modern complex climate model (the Community Earth System Model) and determine how sea ice insulation effects influence the hysteresis width and the probability of AMOC transitions.

Stereooptical Methods of Sea Surface Processes Registration

This work presents the optical methods for measurements of physical parameters on sea surface also covered by ice by using stereo cameras. New method of images with sea ice processing is offered. It can detect areas of open water and sharp edges on ice, which influence on radar signal refraction. This method is based on area of interest detection on optical images, statistical parameters for each area calculation, classification and local level definition to recognize needed structures. By using stereo system perspective distortions can be corrected and physical parameters of wind waves and sea ice can be calculated. This method was probe on stereo images obtained from 90th voyage of R/V «Akademik Mstislav Keldysh» in the Laptev Sea.The results of ripple waves velocity measurements in case on open water by using development previously stereo method is presented. Comparison with Doppler shift of microwave signal is made.The methods presented in this paper are of interest in field experiments simultaneously with the use of coherent radar stations for the quantitative interpretation of radar data, as well as for remote monitoring of the sea surface and ice conditions methods development.

Tropical cyclone activity over western North Pacific favors Arctic sea ice increase.

Teleconnections between the tropics and the Arctic have attracted a lot of scientific interest. However, the mechanisms by which tropical synoptic-scale systems influence the variability of Arctic sea ice remain unknown. In this study, we highlight the impacts of tropical cyclone (TC) activity over the western North Pacific (WNP) on Arctic Sea Ice Concentration (SIC) using observational evidence and climate model simulation experiments. Our findings demonstrate significant positive correlations between Accumulated Cyclone Energy (ACE) in the WNP and SIC in the Arctic-Pacific Sector (APS), particularly when considering a 30-day lag. The TC activity over the WNP induces Rossby wave train propagation towards the Arctic, leading to anomalous cyclonic circulation over the upper troposphere of the APS. The anomalous cyclone over the Arctic, on one hand, signifies the deepening of the Arctic polar vortex and diminishes adiabatic warming over the APS, subsequently inducing cooling and drying of the lower Arctic air. This process reduces downward longwave radiation, promoting an increase in September APS SIC. On the other hand, the anomalous cyclone over the Arctic hinders the export of sea ice and local melting processes throughout the Fram Strait. These findings contribute to a deeper comprehension of tropics-Arctic teleconnections.

Data collation for climate-cooling gas dimethylsulfide in Antarctic snow, sea ice and underlying seawater

Dimethylsulfide (DMS) is a climatically active volatile sulfur compound found in Earth’s oceans and atmosphere that plays an important role in cloud formation. DMS originates from its precursor dimethylsulfoniopropionate (DMSP), which is produced by several classes of phytoplankton. Concentrations of DMS and DMSP in Antarctic sea ice, snow and underlying seawater are not well documented and there is currently no dataset available to find the existing data. The purpose of this project was to compile historical measurements into a publicly available dataset. A total of 220 samples collected since 1992 were compiled using the Antarctic Sea ice Processes and Climate program template, in accordance with the existing datasets for chlorophyll-a, macronutrients, and dissolved iron. Analyses performed on the completed DMS dataset showed that the spatial and temporal coverages are limited; there are barely any measurements in autumn and winter, nor in the Amundsen or Ross seas. These findings provide a basis for future sampling efforts in the Antarctic region.

Sea ice feedbacks cause more greenhouse cooling than greenhouse warming at high northern latitudes on multi-century timescales

Abstract In contrast to surface greenhouse warming, surface greenhouse cooling has been less explored, especially on multi-century timescales. Here, we assess the processes controlling the pacing and magnitude of the multi-century surface temperature response to instantaneously doubling and halving atmospheric carbon dioxide concentrations in a modern global coupled climate model. Over the first decades, surface greenhouse warming is larger and faster than surface greenhouse cooling both globally and at high northern latitudes (45–90° N). Yet, this initial multi-decadal response difference does not persist. After year 150, additional surface warming is negligible, but surface cooling and sea ice expansion continues. Notably, the equilibration timescale for high northern latitude surface cooling (∼437 years) is more than double the equivalent timescale for warming. The high northern latitude responses differ most at the sea ice edge. Under greenhouse cooling, the sea ice edge slowly creeps southward into the mid-latitude oceans amplified by positive lapse rate and surface albedo feedbacks. While greenhouse warming and sea ice loss at high northern latitudes occurs on multi-decadal timescales, greenhouse cooling and sea ice expansion occurs on multi-century timescales. Overall, this work shows the importance of multi-century timescales and sea ice processes for understanding high northern latitude climate responses.

Seasonal Variability in Baffin Bay

AbstractThree dominant characteristics and underlying dynamics of the seasonal cycle in Baffin Bay are discussed. The study is based on a regional, high‐resolution coupled sea ice‐ocean numerical model that complements our understanding drawn from observations. Subject to forcing from the atmosphere, sea ice, Greenland, and other ocean basins, the ocean circulation exhibits complex seasonal variations that influence Arctic freshwater storage and export. The basin‐scale barotropic circulation is generally stronger (weaker) in summer (winter). The interior recirculation (∼2 Sv) is primarily driven by oscillating along‐topography surface stress. The volume transport along the Baffin Island coast is also influenced by Arctic inflows (∼0.6 Sv) via Smith Sound and Lancaster Sound with maximum (minimum) in June‐August (October‐December). In addition to the barotropic variation, the Baffin Island Current also has changing vertical structure with the upper‐ocean baroclinicity weakened in winter‐spring. It is due to a cross‐shelf circulation associated with spatially variable ice‐ocean stresses that flattens isopycnals. Greenland runoff and sea ice processes dominate buoyancy forcing to Baffin Bay. Opposite to the runoff that freshens the west Greenland shelf, stronger salinification by ice formation compared to freshening by ice melt enables a net densification in the interior of Baffin Bay. Net sea ice formation in the past 30 years contributes to ∼25% of sea ice export via Davis Strait. The seasonal variability in baroclinicity and water mass transformation changes in recent decades based on the simulation.

Salinity and Stratification at the Sea Ice Edge (SASSIE): an oceanographic field campaign in the Beaufort Sea

Abstract. As our planet warms, Arctic sea ice coverage continues to decline, resulting in complex feedbacks with the climate system. The core objective of NASA's Salinity and Stratification at the Sea Ice Edge (SASSIE) mission is to understand how ocean salinity and near-surface stratification affect upper-ocean heat content and thus sea ice freeze and melt. SASSIE specifically focuses on the formation of Arctic Sea ice in autumn. The SASSIE field campaign in 2022 collected detailed observations of upper-ocean properties and meteorology near the sea ice edge in the Beaufort Sea using ship-based and piloted and drifting assets. The observations collected during SASSIE include vertical profiles of stratification up to the sea surface, air–sea fluxes, and ancillary measurements that are being used to better understand the role of salinity in coupled Arctic air–sea–ice processes. This publication provides a detailed overview of the activities during the 2022 SASSIE campaign and presents the publicly available datasets generated by this mission (available at https://podaac.jpl.nasa.gov/SASSIE, last access: 29 May 2024; DOIs for individual datasets in the “Data availability” section), introducing an accompanying repository that highlights the numerical routines used to generate the figures shown in this work.

Modeling freezing and BioGeoChemical processes in Antarctic sea ice

AbstractThe Antarctic sea ice, which undergoes annual freezing and melting, plays a significant role in the global climate cycle. Since satellite observations in the Antarctic region began, 2023 saw a historically unprecedented decrease in the extent of sea ice. Further ocean warming and future environmental conditions in the Southern Ocean will influence the extent and amount of ice in the Marginal Ice Zones (MIZ), the BioGeoChemical (BGC) cycles, and their interconnected relationships. The so‐called pancake floes are a composition of a porous sea ice matrix with interstitial brine, nutrients, and biological communities inside the pores. The ice formation and salinity are both dependent on the ambient temperature. To realistically model these multiphasic and multicomponent coupled processes, the extended Theory of Porous Media (eTPM) is used to develop Partial Differential Equations (PDEs) based high‐fidelity models capable of simulating the different seasonal variations in the region. All critical variables like salinity, ice volume fraction, and temperature, among others, are considered and have their equations of state. The phase transition phenomenon is approached through a micro‐macro linking scheme. In this paper, a phase‐field solidification model [4] coupled with salinity is used to model the microscale freezing processes and up‐scaled to the macroscale eTPM model. The evolution equations for the phase field model are derived following Landau‐Ginzburg order parameter gradient dynamics and mass conservation of salt allowing to model the salt trapped inside the pores. A BGC flux model for sea ice is set up to simulate the algal species present in the sea ice matrix. Ordinary differential equations (ODE) are employed to represent the diverse environmental factors involved in the growth and loss of distinct BGC components. Processes like photosynthesis are dependent on temperature and salinity, which are derived through an ODE‐PDE coupling with the eTPM model. Academic simulations and results are presented as validation for the mathematical model. These high‐fidelity models eventually lead to their incorporation into large‐scale global climate models.

The atmospheric connection between the Arctic and Eurasia is underestimated in simulations with prescribed sea ice

Numerous analyses have demonstrated the impact of Arctic sea ice loss on Eurasia during wintertime. However, dynamical models inconsistently support the observed Arctic-Eurasia connection. The critical physical processes causing discrepancies remain unclear. Here, through numerical simulation, we found that the Arctic-Eurasian connection is underestimated when the model is forced with prescribed sea ice concentrations. The suppressed turbulent heat flux over the Arctic sea ice surface, due to the oversimplified sea ice states, is likely an important physical process leading to model spread. By incorporating the reanalyzed turbulent heat flux into the model, we enhance the heat transfer and reproduce the Arctic-Eurasian connection. The weakened Siberian Storm Track and reduced baroclinicity favors the strengthened Siberian High through eddy feedback forcing. These findings highlight the vital role of turbulent heat flux related to sea ice loss, emphasizing the urgent need for enhanced model fidelity in representing the sea ice processes.

An Assessment of Convergence of Climate Reanalyses from Two Coupled Data Assimilation Systems with Identical High-Efficiency Filtering

Abstract Coupled data assimilation (CDA) uses coupled model dynamics and physics to extract observational information from measured data in multiple Earth system domains to reconstruct historical states of the Earth system, forming a reanalysis of climate variability. Due to imperfect numerical schemes in modeling dynamics and physics, models are usually biased from the real world. Such model bias is a critical obstacle in the reconstruction of historical variability by combining model and observations and, to some degree, causes divergence of CDA results because of individual model behavior in each system. Here, based on a multitime-scale high-efficiency filtering algorithm which includes a deep-ocean bias relaxing scheme, we first develop a high-efficiency online CDA system with the Community Earth System Model (CESM-MSHea-CDA). Then, together with the other previously established CDA system within the Coupled Model, version 2.1 (CM2-MSHea-CDA), that is developed by the Geophysical Fluid Dynamics Laboratory, we conduct climate reanalysis for the past 4 decades (1978–2018). Evaluations show that due to improved representation for multiscale background statistics and effective deep-ocean model bias relaxing, both CDA systems produce convergent estimation of variability for major climate signals such as variability of basin-scale ocean heat content, El Niño–Southern Oscillation (ENSO), and Pacific decadal oscillation (PDO). Particularly, both CDA systems generate similar time mean of global and Atlantic meridional overturning circulations that converge to the geostrophic velocity estimate from climatological temperature and salinity data. The CDA-estimated mass transport at typical measurement sections is mostly consistent with the observations. Significance Statement A coupled climate model simulates the interactions of the atmosphere, ocean, sea ice, and land processes and derives change and variations of the climate system by combining these components. Due to imperfect numerical schemes, a model usually has systematic biases to the real world. Coupled data assimilation (CDA) combines coupled model dynamics and physics with atmospheric and oceanic observations to reconstruct the historical states of Earth’s climate system, forming the analysis of climate change and variability. However, because of the existence of model errors and individual data assimilation algorithm behaviors, currently, the ocean variability of reanalysis produced by different numerical systems is basically divergent. Here, we first apply an identical coupled data assimilation algorithm and effective model error relaxing scheme to two widely used IPCC coupled models to establish two CDA systems. Then, we use both CDA systems to assimilate historical atmospheric and oceanic observations to form two sets of climate reanalyses for the past 4 decades. We found, by some degree, that the results of these multimodel coupled climate reanalyses converged to what historical states ought to be in observational estimation. These convergent climate reanalyses are expected to significantly increase our understanding of CDA and climate assessment.

Photosynthetic processes in Antarctic sea ice during the spring melt

AbstractHigh‐latitude oceans experience strong seasonality where low light limits photosynthetic activity most of the year. This limitation is pronounced for algae within and underlying sea ice, and these algae are uniquely acclimated to low light levels. During spring melt, however, light intensity and daylength increase drastically, triggering blooms of ice algae that play important roles in carbon cycling and ecosystem productivity. How the algae acclimate to this dynamic and heterogeneous environment is poorly understood. Here, we measured 14C‐carbon fixation rates, photophysiology, and ribulose 1,5‐bisphosphate carboxylase oxygenase (Rubisco) content of sea‐ice algae in coastal waters near the western Antarctic Peninsula during spring, ranging from a low‐light‐acclimated, bottom community to a light‐saturated bloom. Carbon fixation rates by sea‐ice algae were similar to other Antarctic sea‐ice measurements (2–49 mg C m−2 d−1), and there was little phytoplankton biomass in the underlying water at the time of sampling. Net‐to‐gross ratios of carbon fixation were generally high and showed no relationship with ice type. We found algal photophysiology and Rubisco concentrations varied in relation to the different types of ice, altering the balance between the photochemical and biochemical processes that constrain carbon fixation rates. For algae inhabiting the bottom layers of sea ice, rates of carbon fixation were largely constrained by light availability whereas in surface seawater, interior and rotten/brash ice, carbon fixation rates could be calculated with reasonable accuracy from measurements of Rubisco concentrations. This work provides additional insight and means to evaluate carbon fixation rates as sea ice continues to change in future.

Impacts of Projected Arctic Sea Ice Loss on Daily Weather Patterns over North America

Abstract Future Arctic sea ice loss has a known impact on Arctic amplification (AA) and mean atmospheric circulation. Furthermore, several studies have shown it leads to a decreased variance in temperature over North America. In this study, we analyze results from two fully coupled Community Earth System Model (CESM) Whole Atmosphere Community Climate Model (WACCM4) simulations with sea ice nudged to either the ensemble mean of WACCM historical runs averaged over the 1980–99 period for the control (CTL) or projected RCP8.5 values over the 2080–99 period for the experiment (EXP). Dominant large-scale meteorological patterns (LSMPs) are then identified using self-organizing maps applied to winter daily 500-hPa geopotential height anomalies () over North America. We investigate how sea ice loss (EXP − CTL) impacts the frequency of these LSMPs and, through composite analysis, the sensible weather associated with them. We find differences in LSMP frequency but no change in residency time, indicating there is no stagnation of the flow with sea ice loss. Sea ice loss also acts to de-amplify and/or shift the that characterize these LSMPs and their associated anomalies in potential temperature at 850 hPa. Impacts on precipitation anomalies are more localized and consistent with changes in anomalous sea level pressure. With this LSMP framework we provide new mechanistic insights, demonstrating a role for thermodynamic, dynamic, and diabatic processes in sea ice impacts on atmospheric variability. Understanding these processes from a synoptic perspective is critical as some LSMPs play an outsized role in producing the mean response to Arctic sea ice loss. Significance Statement The goal of this study is to understand how future Arctic sea ice loss might impact daily weather patterns over North America. We use a global climate model to produce one set of simulations where sea ice is similar to present conditions and another that represents conditions at the end of the twenty-first century. Daily patterns in large-scale circulation at roughly 5.5 km in altitude are then identified using a machine learning method. We find that sea ice loss tends to de-amplify these patterns and their associated impacts on temperature nearer the surface. Our methodology allows us to probe more deeply into the mechanisms responsible for these changes, which provides a new way to understand how sea ice loss can impact the daily weather we experience.

Sea Ice and Cloud Processes Mediating Compensation between Atmospheric and Oceanic Meridional Heat Transports across the CMIP6 Preindustrial Control Experiment

Abstract Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.

The Significance of the Melt-Pond Scheme in a CMIP6 Global Climate Model

Abstract The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments (“implicit” schemes) or prognostic melt-pond parameterizations (“explicit” schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere. Significance Statement This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change.

Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations

Sea ice thickness (SIT), which is a crucial and sensitive indicator of climate change in the Antarctic, has a substantial impact on atmosphere-sea-ice-ocean interactions. Despite the slight thinning in SIT and reduction in sea ice volume (SIV) in the Antarctic in the recent decade, challenges remain in quantifying their changes, primarily because of the limited availability of high-quality long-term observational data. Therefore, it is crucial to accurately simulate Antarctic SIT and to assess the SIT simulation capability of state-of-the-art climate models. In this study, we evaluated historical simulations of SIT by 51 climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) using Envisat (ES) and CryoSat-2 (CS2) observations. Results revealed that most models can capture the seasonal cycles in SIV and that the CMIP6 multimodel mean (MMM) can reproduce the increasing and decreasing trends in the SIV anomaly based on ES and CS2 data, although the magnitudes of the trends in the SIV anomaly are underestimated. Additionally, the intermodel spread in simulations of SIT and SIV was found to be reduced (by 43%) from CMIP5 to CMIP6. Nevertheless, based on the CMIP6 MMM, substantial underestimations in SIV of 57.52% and 59.66% were found compared to those derived from ES and CS2 observations, respectively. The most notable underestimation in SIT was located in the sea ice deformation zone surrounding the northwestern Weddell Sea, coastal areas of the Bellingshausen and Amundsen seas, and the eastern Ross Sea. The substantial bias in the simulated SIT might result from deficiencies in simulating critical physical processes such as ocean heat transport, dynamic sea ice processes, and sea ice-ocean interactions. Therefore, increasing the model resolution and improving the representation of sea ice dynamics and the physical processes controlling sea ice-ocean interactions are essential for improving the accuracy of Antarctic sea ice simulation.

Improvement of sea ice thermodynamics with variable sea ice salinity and melt pond parameterizations in an OGCM

Enhanced representation of sea ice processes in ocean modeling studies is required for advancing our understanding and prediction of the climate variability. In the present study, we improved the sea ice thermodynamics in an OGCM by introducing processes for variable sea ice salinity and melt ponds on sea ice. The former affects the latent heat and conductivity of sea ice as well as the salt budget in the ocean–sea ice system. We formulated salinification and desalination processes based on previous observational studies. Melt ponds enhance summertime surface melting by reducing the surface albedo. In our formulation of the melt pond thermodynamics, the shortwave radiation absorbed in the pond was partly released to the air and partly conducted to the underlying sea ice. By adopting these parameterizations, seasonal cycles of the sea ice salinity distributions in both hemispheres were generally reproduced. Simulated seasonal and interannual variations in the Arctic melt pond area and associated surface albedo reductions were basically consistent with observational estimates. The melt pond effect reduced the Arctic sea ice volume by about 1.5 × 103 km3 in the summer; half of this impact remained throughout the year. Our results suggest that the new parameterizations have the potential to improve the seasonal evolution of the sea ice thickness and concentration distributions, which would contribute to prediction studies.

On the drivers of regime shifts in the Antarctic marginal seas, exemplified by the Weddell Sea

Abstract. Recent studies have found evidence for a potential future tipping point, when the density of Antarctic continental shelf waters, specifically in the southern Weddell Sea, will allow for the onshore flow of warm waters of open ocean origin. A cold-to-warm regime shift in the adjacent ice shelf cavities entails a strong enhancement of ice shelf basal melt rates and could trigger instabilities in the ice sheet. From a suite of numerical experiments, aimed to force such a regime shift on the continental shelf, we identified the density balance between the shelf waters formed by sea ice production and the warmer water at the shelf break as the defining element of a tipping into a warm state. In our experiments, this process is reversible but there is evidence for hysteresis behaviour. Using HadCM3 20th-century output as atmospheric forcing, the resulting state of the Filchner–Ronne cavity depends on the initial state. In contrast, ERA Interim forcing pushes even a warm-initialized cavity into a cold state, i.e. it pushes the system back across the reversal threshold to the cold side. However, it turns out that for forcing data perturbations of a realistic magnitude, a unique and universal recipe for triggering a regime shift in Antarctic marginal seas was not found; instead, various ocean states can lead to an intrusion of off-shelf waters onto the continental shelf and into the cavities. Whether or not any given forcing or perturbation yields a density imbalance and thus allows for the inflow of warm water depends on the complex interplay between bottom topography, mean ocean state, sea ice processes, and atmospheric conditions.

Inorganic carbon and nutrient dynamics in the marginal ice zone of the Barents Sea: Seasonality and implications for ocean acidification

The Barents Sea is a productive Arctic shelf sea experiencing Atlantification with ocean warming, sea ice loss and increased influence of Atlantic Water. The impact of these changes on inorganic carbon and nutrient dynamics and ocean acidification are yet to be fully understood. Seasonal variability and drivers of inorganic carbon and nutrients were determined from south of the Polar Front at 76 °N in the Barents Sea to 82 °N in the Nansen Basin, Arctic Ocean, encompassing Atlantic and Arctic regimes in summer (August 2019), winter (December 2019), winter/spring (March 2021) and spring (May 2021). Summer sea-ice meltwater was the main driver reducing total alkalinity (AT) and dissolved inorganic carbon (CT), corresponding to 55 % and 81 % of the total changes ΔCT and ΔAT, respectively, in the surface layer. Primary production reduced CT (37 % of ΔCT) and nutrients, particularly in ice-free waters, increasing calcium carbonate (CaCO3) saturation for aragonite (Ωaragonite) from 1.3 in spring to 2.3 in summer. Net community production (NCP) in the upper 50 m was highest (1.3 molCm−2) in the Atlantic Water regimes and lowest (0.4 molCm−2) in the ice-covered Nansen Basin in summer. Mixing, organic matter remineralisation and CO2 uptake enriched AT, CT and nutrients to pre-condition the water column from winter to early spring. Formation and dissolution of CaCO3 from shells and ikaite in sea ice (5–13 % of ΔAT) represented a minor AT source from winter to spring. Highest NCP by spring (0.3 molCm−2) occurred in a transient Atlantic-like regime over the shelf slope. Atmospheric CO2 uptake contributed up to 37 % of ΔCT and the region was an annual CO2 sink. Sea-ice processes and deep winter convection lowered AT and Ωaragonite (1.12–1.14) to enhance the risk of acidification over the shelf. Future Atlantification may increase biological production, reduce meltwater dilution effects and counteract acidification in the Barents Sea. The observations reveal the importance of seasonal and spatial studies to capture variability in inorganic carbon and nutrient cycling, driven by numerous processes coupled to the ice-ocean system that may exacerbate or alleviate ocean acidification in Arctic shelf seas.

The Deep Arctic Ocean and Fram Strait in CMIP6 Models

Abstract Arctic sea ice loss has become a symbol of ongoing climate change, yet climate models still struggle to reproduce it accurately, let alone predict it. A reason for this is the increasingly clear role of the ocean, especially that of the “Atlantic layer,” on sea ice processes. We here quantify biases in that Atlantic layer and the Arctic Ocean deeper layers in 14 representative models that participated in phase 6 of the Climate Model Intercomparison Project. Compared to observational climatologies and hydrographic profiles, the modeled Atlantic layer core is on average too cold by −0.4°C and too deep by 400 m in the Nansen Basin. The Atlantic layer is too thick, extending to the seafloor in some models. Deep and bottom waters are in contrast too warm by 1.1° and 1.2°C. Furthermore, the modeled properties hardly change throughout the Arctic. We attribute these biases to an inaccurate representation of shelf processes: only three models seem to produce dense water overflows, at too few locations, and these do not sink deep enough. No model compensates with open ocean deep convection. Therefore, the properties are set by the inaccurate volume fluxes through Fram Strait, biased low by up to 6 Sv (1 Sv ≡ 106 m3 s−1), but coupled to a too-warm Fram Strait, resulting in a somewhat accurate heat inflow. These fluxes are related to biases in the Nordic seas, themselves previously attributed to inaccurate sea ice extent and atmospheric modes of variability, thus highlighting the need for overall improvements in the different model components and their coupling. Significance Statement Coupled climate models are routinely used for climate change projection and adaptation, but they are only as good as the data used to create them. And in the deep Arctic, those data are scarce. We determine how biased 14 of the most recent models are regarding the deep Arctic Ocean and the Arctic’s only deep gateway, Fram Strait (between Greenland and Svalbard). These models are very biased: too cold where they should be warm, too warm where they should be cold, not stratified enough, not in contact with the surface as they should, moving the wrong way around the Arctic, etc. Some problems are induced by biases in regions outside of the Arctic and/or from the sea ice models.

The Role of Atmospheric Rivers in Antarctic Sea Ice Variations

AbstractAntarctic sea ice variations are affected by moisture and heat from low‐ and mid‐latitudes, more than 90% of which are transported by atmospheric rivers (ARs). This study employs the ERA5 reanalysis and satellite observations to detect all the ARs over the Antarctic sea ice and analyze the general contributions of ARs on sea ice changes from 1979 to 2020. Though AR frequency is low in all seasons, ARs give rise to intense sea ice reduction at a rate of more than 10%/day in marginal ice zone. Thermodynamic processes of sea ice dominate the AR‐induced variations, associated with anomalous atmospheric conditions during ARs. Warm, moist and cloudy weather causes considerable melting by enhancing sensible heat flux in cold seasons but has restrictive influences in summer due to blocked solar radiation. Heavy precipitation during ARs is also nonnegligible, especially during the summer melt.