Sea Ice Research Articles

From Polar Day to Polar Night: A Comprehensive Sun and Star Photometer Study of Trends in Arctic Aerosol Properties in Ny-Ålesund, Svalbard

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources.

First Observational Evidence That Dust‐Driven Cloud Phase Changes Cool the Surface Over Summertime Arctic Sea Ice

AbstractCloud phase has important impacts on Arctic surface temperatures, and circumstantial evidence suggests that dust aerosols have strong regional impacts on Arctic cloud phase. We used 7 years of satellite observations and model and reanalysis products to control for co‐varying meteorology, and to assess how dust and other aerosols impact cloud phase and cloud radiative effects over the summertime sea ice. We focus on clouds at 3 km, where dust modeling is most accurate. There is strong indication that dust aerosols caused about 4.5% of clouds below −15°C to change phase, with smaller effects at higher temperatures. Sulfate has a smaller impact on cloud phase. Dust is associated with cloud‐mediated surface cooling of up to a 6.3 W m−2 below single‐layer clouds at ∼3 km in June. This is the first observational study to constrain likely dust‐related cloud radiative effects over the summertime Arctic sea ice.

A moderator of tropical impacts on climate in Canadian Arctic Archipelago during boreal summer

The Canadian Arctic Archipelago consists of important international trade routes, and local surface air temperatures (SAT) greatly control sea ice melting in situ during boreal summer (June-July-August-September). However, the drivers of the Arctic Archipelago summer SAT variability have not yet been fully elucidated. Here, we find that the impact of tropical Indo-Pacific convection on the Arctic Archipelago SAT through induced poleward-propagating Rossby wave train is strongly modulated by Russian Arctic sea surface temperature anomalies (SSTA). Negative Russian Arctic SSTA lead to a weakened East Asia westerly jet via equatorward Rossby wave activity. The weakened westerly jet enhances the meridional gradient of the potential vorticity over the North Pacific, guiding the poleward-propagating Rossby wave to the Arctic Archipelago and therefore affecting the local SAT. Conversely, positive Russian Arctic SSTA impede the northward-propagating Rossby wave via enhancing the East Asia westerly jet, resulting in a weakened relationship between the tropical Indo-Pacific convection and Arctic Archipelago SAT. The present study proposes a mechanism whereby changes in the Tropical-Arctic connection stem from thermal conditions elsewhere in the Arctic, through shaping poleward-propagating Rossby waves by changing the background mean flow.

Projected Antarctic sea ice change contributes to increased occurrence of strong El Niño

Current climate models suggested that Antarctic sea ice cover would decrease substantially under cumulative CO2 emission, but little is known whether large decrease in Antarctic sea ice can influence the occurrence of strong El Niño. Using time slice coupled and uncoupled model experiments, we show that in response to half reduction of Antarctic sea ice projected near the end of the 21st century, the frequency of strong El Niño would be increased by ~40%. It is contributed by enhanced thermocline, Ekman, and zonal advective positive feedbacks that are partly offset by enhanced thermodynamic damping. The strong warming and weakened westerly winds in the southeastern Pacific generate an anomalous Rossby wave propagating into the eastern subtropical and tropical Pacific, favoring stronger El Nino, and air-sea coupling and ocean feedbacks play a critical role in the teleconnection. Unexpectedly, compare to halved Antarctic sea ice, the ice-free Antarctic leads to a decrease in the frequency of strong El Niño, which is largely due to a substantial increase in thermodynamic damping. We also show that a large portion of the increase of strong El Niño events under greenhouse warming might be connected with Antarctic sea-ice loss, though increased greenhouse gas plays an important role.

Capacity of a set of CMIP6 models to simulate Arctic sea ice drift

Abstract Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

Antarctic sea ice surface temperature bias in atmospheric reanalyses induced by the combined effects of sea ice and clouds

Sea-ice surface temperature from atmospheric reanalysis has been used as an indicator of ice melt and climate change. However, its performance in atmospheric reanalyses is not fully understood in Antarctica. Here, we quantified biases in six widely-used reanalyses using satellite observations, and found strong and persistent warm biases in most reanalyses examined. Further analysis of the biases revealed two main culprits: incorrect cloud properties, and inappropriate sea-ice representation in the reanalysis products. We found that overestimated cloud simulation can contribute more than 4 K warm bias, with ERA5 exhibiting the largest warm bias. Even in reanalysis with smaller biases, this accuracy is achieved through a compensatory relationship between relatively lower cloud fraction bias and overestimated sea ice insulation effect. A dynamic downscaling simulation shows that differences in sea-ice representation can contribute a 2.3 K warm bias. The representation of ice concentration is the primary driver of the spatial distribution of biases by modulating the coupling between sea ice and clouds, as well as surface heat conduction. The lack of a snow layer in all reanalyses examined also has an impact on biases.

Two-dimensional thermal and dynamical strain in landfast sea ice from InSAR: results from a new analytical inverse method and field observations

Abstract Observing continuous strain in sea ice at geophysical scales of tens of meters to kilometers requires displacement measurements made with millimeter-scale precision. Satellite-based interferometric synthetic aperture radar (InSAR) provides such precise measurements of relative surface displacement over broad spatial areas at regular intervals and, unlike point displacement measurements, it allows confident delineation of continuously deforming regions. However, InSAR only captures the 1-D component of surface displacement parallel to a radar's lines-of-sight. Additional analysis is required to translate between these 1-D observations and the horizontal or vertical displacements they arose from. Previous studies utilize an iterative inverse model to constrain estimates of horizontal surface displacement from InSAR. Here we build upon that work outlining a new analytical inverse modeling method for quantifying displacement and strain over continuous regions of sea ice and provide comparison between model results and independent displacement observations. We demonstrate the inverse method over both landfast and drifting ice along the Alaskan coastline. These intercomparisons highlight environments in which displacements inverted from interferograms may be used as an independent estimator of surface strain, as well as the potential for the outlined inverse methods to be used in conjunction with other observing methods.

High-resolution regional sea-ice model based on the discrete element method with boundary conditions from a large-scale model for ice drift

Abstract Understanding sea-ice dynamics at the floe scale is crucial to comprehend polar climate systems. While continuum models are commonly used to simulate large-scale sea-ice dynamics, they have limitations in accurately representing sea-ice behaviour at small scales. DEMs, on the other hand, are well-suited for modelling the behaviour of individual ice floes but face limitations due to computational constraints. To address the limitations of both approaches while combining their strengths, we explored the feasibility of using a DEM within a continuum model, where the latter provides boundary conditions for a rectangular high-resolution DEM domain. This paper presents a feasibility study where a discrete model of a 100 × 100 km2 icefield was created using high-resolution optical satellite imagery. Sea-ice dynamics were simulated in the DEM considering environmental forces and integrating large-scale ice-drift velocities as boundary conditions. Model predictions were compared with satellite observations for ice drift and deformation parameters. This numerical approach showed potential for offering accurate, high-resolution predictions of sea ice, particularly in coastal areas and near islands, and may find applications in ice navigation and climate studies. However, further development of the DEM, along with upgrades to the coupled ocean models providing data for the ice component, may be necessary. Additionally, challenges remain to develop a two-way coupling between the DEM and a continuum model, which may be needed to improve the accuracy of large-scale simulations.

Incidence angle dependency and seasonal evolution of L and C-band SAR backscatter over landfast sea ice

Abstract We estimate sea-ice type specific incidence angle (IA) dependencies for dual polarized (HH/HV) L and C-band synthetic aperture radar (SAR) for the winter, melt onset and advanced melt seasons for level and deformed ice, using time-series of Advanced Land Observing Satellite-2 (ALOS-2) and Sentinel-1 imagery off the north-east coast of Greenland. The IA dependencies are used to radiometrically correct the L and C-band backscatter time-series, which enables analysis of their seasonal evolution. From this, we observe that the L-band backscatter intensity increases for both ice types at the transition from winter to melt onset. We use these results to estimate ice type separability and to train an IA aware Bayesian classifier at both frequencies. These results show that while both frequencies are capable of distinguishing level and deformed ice during the winter, only L-band SAR can reliably make this separation during the melt onset season. During the advanced melt season, the overall classification accuracies are similarly low for L and C-band. This study demonstrates the potential of L-band SAR for sea-ice mapping, which is highly relevant in the light of several upcoming L-band SAR missions.

Atmospheric variability drives anomalies in the Bering Sea air-sea heat exchange

Abstract High-latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air-sea coupling plays a dominant role in driving Bering Sea upper ocean thermal variability, and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air-sea heat fluxes in the Bering Sea over the period 2010-2022 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September-April, and is primarily a result of near-surface air temperature and specific humidity anomalies. The air-mass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability, and are a result of anomalous cloud coverage, anomalous lower tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper ocean temperature variability through mediation of the surface heat fluxes during the analysis period.

A Bayesian Model for 20th Century Antarctic Sea Ice Extent Reconstruction

AbstractAntarctic sea ice, a key component in the complex Antarctic climate system, is an important driver and indicator of the global climate. In the relatively short satellite‐observed period from 1979 to 2022 the sea ice extent has continuously increased (contrasting a major decrease in Arctic sea ice) up to a dramatic decrease between 2014 and 2017. Recent years have seen record sea ice lows in February 2022–February 2023. We use a statistical ensemble reconstruction of Antarctic sea ice to put the observed changes into the historical context of the entire 20th century. We propose a seasonal Vector Auto‐Regressive Moving Average (VARMA) model fit in a Bayesian framework using regularized horseshoe priors on the regression coefficients to create a stochastic ensemble reconstruction of monthly Antarctic Sea ice extent from 1900 to 1979. This novel model produces a set of 2,500 plausible sea ice extent reconstructions for the sea ice by sector that incorporate the autocorrelation structure of sea ice over time as well as the dependence of sea ice between the sectors. These fully observed reconstructions exhibit plausible month‐to‐month changes in reconstructed sea ice as well as plausible interactions between the sectors and the total. We reconstruct an overall higher sea ice extent earlier in the 20th century with a relatively sharp decline in the 1970s. These trends agree well with previous reconstructions of Antarctic sea ice based on ice core data, whaling locations, and climatological data, as well as early satellite observations in the reconstruction period.

Thermodynamic and Dynamic Variations in Sea Ice Thickness of the Ross Sea, Antarctica, Driven by Atmospheric Circulation

AbstractAtmospheric circulation has significant impacts on sea ice drifting patterns and mass balance, as wind drag induces pressure ridges and leads on the sea ice surface. In this study, the spatiotemporal distributions of these dynamic sea ice deformation features in the Ross Sea are examined using ICESat‐2 (IS2) ATL10 freeboard data (2019–2022). The temporal variation of the modal sea ice thickness (SIT), caused by thermodynamic ice growth and sea ice advection, varies from 0.7–1.0 m in April to 1.0–1.6 m in July–September and decreases thereafter in the northwest (NW) and northeast (NE) sectors. This temporal variation of modal SIT agrees with the air temperature (correlation coefficients >0.5). The southwest (SW) sector shows a consistently low modal SIT (<1.0 m) because of the production of new ice in polynyas and continuous northward sea ice drift. Meanwhile, the southeast (SE) sector shows the thickest ice in Octobers 2019 and 2020 because of the advection of thick ice from the Amundsen Sea, which was reduced in 2021 and 2022. In terms of dynamic sea ice deformation, the SE sector shows the largest deformation because of the wind‐driven convergence of sea ice movement. However, such intense deformation in the SE sector diminished in 2021 and 2022 due to the dominance of strong southerly wind associated with the Amundsen Sea Low (ASL). This study emphasizes the potential of IS2 sea ice products to assess the role of atmospheric driving forces on thermodynamic and dynamic sea ice changes.

Calibration of Arctic ice core bromine enrichment records for past sea ice reconstructions

Bromine in ice cores has been proposed as a qualitative sea ice proxy to produce sea ice reconstructions for the polar regions. Here we report the first statistical validation of this proxy with satellite sea ice observations by combining bromine enrichment (with respect to seawater, Brenr) records from three Greenlandic ice cores (SIGMA-A, NU and RECAP) with satellite sea ice imagery, over three decades. We find that during the 1984–2016 satellite-era, ice core Brenr values are significantly correlated with first-year sea ice formed in the Baffin Bay and Labrador Sea supporting that the gas-phase bromine enrichment processes, preferentially occurring over the sea ice surface, are the main driver for the Brenr signal in ice cores. Moreover, in assessing Brenr's capability to record historical sea ice variability, we compare 20th-century Arctic Sea ice historical and proxy records with our reconstructions, based on an autoregressive–moving-average (ARMA) model, finding overall good agreement. While further enhancements are warranted, including site-specific calibrations and a comprehensive investigation into bromine transport-related concerns, this study presents a new method to quantitatively reconstruct past seasonal sea ice variability through bromine enrichment in ice cores.

Survival strategies of microalgae in response to fluctuating brine environments in Saroma-ko Lagoon sea ice, Hokkaido, Japan.

This study investigated the changes in sea ice temperature, microalgae species distribution, shape changes, and photosynthetic activity observed in the first-year ice that forms in winter in Saroma-ko Lagoon, Hokkaido, Japan. Temperatures at the bottom of the ice remained constant at -1.7°C, near the freezing point, while they varied between -6 and -1°C with diel fluctuations at the surface layer. Carefully collected algal samples showed high photosynthetic quantum yield and acclimation to the light intensities of individual ice layers; this indicates that the algal photosynthetic activity responds to dynamic changes in the ice environment, such as variations in temperature, salinity, and brine space. The algal communities consisted of more than 95% diatoms. Smaller algal cells were distributed in the upper layer of the sea ice compared to the lower layers. Chaetoceros sp., the dominant small-cell species, was evenly distributed throughout the layers. In contrast, Detonula confervacea, the dominant large-cell species, was unevenly distributed in the lower layer, with smaller colony size and cell volume in the upper layer. The shape differences observed in this species were thought to be a response to the changing environment within the first-year sea ice.

A Probabilistic Approach to Correct for Oblique Biases in Sea Ice Parametrization from Shipborne Cameras

Abstract This work investigates the perception bias caused by ice floes occluding open water regions behind them when analyzing sea ice from shipborne cameras. We propose a method to model this effect by predicting an occlusion probability for a given surface region based on a stochastic representation of the sea ice fields. We further show how the proposed framework can be used to design an unbiased estimator for image-based sea ice concentration by correcting for these occlusions. The occlusion model and proposed sea ice concentration estimator have been verified through simulated experiments. Results from the experiments showed that predictions from the occlusion model align with the simulated observations and that the proposed estimator remains unbiased for all environments tested. The contributions of this study can be used in algorithms for automated identification and characterization of ice environments from surface ships and are thus an essential step towards improved autonomy in Arctic navigation.

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.

The Characteristics of Different Apparent Optical Property Parameters in Non‐Destructively Estimating Absorptive Substances Within Sea Ice: A Case Study in Liaodong Bay

AbstractAbsorptive substances (AS) embedded in sea ice can alter irradiance transmission, exerting a significant influence on oceanic biogeochemical processes. Their quantification is thus essential, and a regression model based on the normalized difference index of transmittance (T(λ)) has been widely used for retrieving ice algal biomass. However, the potentials of albedo (α(λ)) and the diffuse attenuation coefficient (Kd(λ)) in AS estimation have not been explored. To fill this gap, sea ice optical properties observed in Liaodong Bay in 2009, 2010, 2013, and 2022 were used to investigate the characteristics of α(λ), T(λ), and Kd(λ) in non‐destructively estimating As through sensitivity analyses based on the Hydrolight radiative transfer model. The effects derived from AS vertical distribution, scattering coefficient and ice thickness were studied specifically. Ultimately, a significant relationship between α(λ) and the total absorption coefficient of AS was derived (R2 = 0.79) for Liaodong Bay sea ice. Sensitivity analyses revealed that it could only retrieve AS in the upper 15–20 cm, which was influenced by variations in ice thickness and scattering coefficient. In contrast, T(λ) could retrieve AS throughout the ice column and is less affected by scattering variation; but it is significantly affected by the vertical distribution of AS in the upper layer. Kd(λ) has the best potential in AS estimation, but for sea ice thinner than 30 cm, the effect of variation in ice thickness could not be neglected, similar to T(λ). Knowledge of this is helpful for the future development of AS estimation.

Analysis of Dynamic Changes in Sea Ice Concentration in Northeast Passage during Navigation Period

With global warming and the gradual melting of Arctic sea ice, the navigation duration of the Northeast Passage (NEP) is gradually increasing. The dynamic changes in sea ice concentration (SIC) during navigation time are a critical factor affecting the navigation of the passage. This study uses multiple linear regression and random forest to analyze the navigation windows of the NEP from 1979 to 2022 and examines the critical factors affecting the dynamic changes in the SIC. The results suggest that there are 25 years of navigable windows from 1979 to 2022. The average start date of navigable windows is approximately between late July and early August, while the end date is approximately early and mid-October, with considerable variation in the duration of navigable windows. The explanatory power of RF is significantly better than MLR, while LMG is better at identifying extreme events, and RF is more suitable for assessing the combined effects of all variables on the sea ice concentration. This study also found that the 2 m temperature is the main influencing factor, and the sea ice movement, sea level pressure and 10 m wind speed also play a role in a specific period. By integrating traditional statistical methods with machine learning techniques, this study reveals the dynamic changes of the SIC during the navigation period of the NEP and identifies its driving factors. This provides a scientific reference for the development and utilization of the Arctic Passage.

Calving Dynamics and the Potential Impact of Mélange Buttressing at the Western Calving Front of Thwaites Glacier, West Antarctica

AbstractThe western region of the wide Thwaites Glacier terminus is characterized by a near‐vertical calving front. The grounding line at this western calving front (WCF) rests on a relatively high ridge, behind which exists a reverse‐sloping bed; retreat of the grounding line into this over‐deepening basin could therefore expose deep calving faces that may be subject to ice‐cliff failure. Here, we use the 3D Helsinki Discrete Element Model to identify the factors that control the calving dynamics in this location. We then focus on the ability of mélange to influence these dynamics given the wide embayment in which Thwaites Glacier terminates. We find that calving along the WCF is currently influenced by ice flow across the grounding line and consequent longitudinal tensile stress and rift formation. Calving is slowed in simulations that are initiated with a highly constricted mélange, with a thicker mélange suppressing calving entirely. We liken the constrained simulations to a scenario in which mélange piles behind a large grounded iceberg. In a future which may see calving become a more dominant control on the retreat of Thwaites Glacier, this type of blockage will be necessary for robust force chains to develop and transmit resistive forces to the terminus. The ability of the mélange to hinder calving at this location will be determined by the presence and rigidity of binding land‐fast sea ice and iceberg keel depths. Therefore, it is necessary to represent calving, mélange and sea ice in a single framework to predict the fate of Thwaites Glacier.

Interaction between three key species in the sea ice-reduced Arctic Barents Sea system.

Population dynamics depend on trophic interactions that are affected by climate change. The rise in sea temperature is associated with the disappearance of sea ice in the Arctic. In the Arctic part of the Barents Sea, Atlantic cod, capelin and polar cod are three fish populations that interact and are confronted with climate-induced sea ice reductions. The first is a major predator in the system, while the last two are key species in Arctic and sub-Arctic ecosystems, respectively. There are still many unknowns regarding how predicted environmental change may influence the joint dynamics of these populations. Using time series from a 32 year long survey, we developed a state-space model that jointly modelled the dynamics of cod, capelin and polar cod. Using a hindcast scenario approach, we projected the effect of reduced sea ice on these populations. We show that the impact of sea ice reduction and concomitant sea temperature increase may lead to a decrease of polar cod abundance at the benefit of capelin but not of cod which may decrease, resulting in strong changes in the food web. Our analyses show that climate change in the Arcto-boreal system can generate different species assemblages and new trophic interactions, which is the knowledge needed for effective management measures.