Changes In Arctic Sea Ice Research Articles

Estimation of Arctic sea ice thickness from CryoSat-2 altimetry data

ABSTRACT Arctic sea ice change is one of the critical factors affecting the global climate environment; hence, it is crucial to obtain sea ice thickness with high accuracy while studying polar and global climate change. In the process of using altimetry data to estimate sea ice thickness, the mean sea surface height will bring greater uncertainty to the extraction of sea ice freeboard, which will affect the accuracy of sea ice thickness. Also, the influence of snow cover on radar signal penetration will bring greater uncertainty to sea ice thickness. In this paper, we present a processing chain for sea ice thickness estimation. First, we compare the effect of four different MSS models on the freeboard estimation. Then, considering the incomplete penetration of radar signals and the different speeds of radar signals penetrating the snow layer and the vacuum, the traditional sea ice thickness model is optimized to obtain the sea ice thickness. Compared with the Operation IceBridge (OIB) sea ice thickness, the accuracy of sea ice thickness obtained by the optimized model is better than 0.350 m, with a root mean square error of 0.260 m and a mean bias of 0.048 m. The comparison results show that the combination of the latest DTU18 MSS model and sea ice thickness optimization model effectively improve the accuracy of sea ice thickness.

Unraveling the Arctic Sea Ice Change since the Middle of the Twentieth Century

Changes in Arctic sea ice since the middle of the last century are explored in this study. Both observations and climate model simulations show an overall sea ice expansion during 1953–1970 but a general sea ice decline afterward. Anthropogenic aerosols, nature forcing and atmospheric ozone changes are found to contribute to the sea ice expansion in the early period. Their effects are strong generally in late boreal summer. On the other hand, greenhouse gas warming has a dominant effect on diminishing Arctic sea ice cover during 1971–2005, especially in September. Internal climate variability also plays a role in the Arctic sea ice change during 1953–1970. However, it cannot solely explain the Arctic sea ice decline since the 1970s.

Radiative Effects and Costing Assessment of Arctic Sea Ice Albedo Changes

The rapid loss of Arctic Sea ice cover and thickness diminishes the surface albedo, which increases the ocean’s absorption of solar heat and exacerbates the Arctic amplification effect. According to the most recent research from the Intergovernmental Panel on Climate Change, the Sixth Assessment Report (IPCC, AR6), the extent of summer sea ice is anticipated to decrease below 1 million km2 by the 2050s as a result of the extreme climate. Nevertheless, past and future changes in sea ice albedo radiative forcing and the resulting economic cost remain to be explored in systematic and multi-disciplinary manners. In this study, we first analyze the evolution of Arctic sea ice radiative forcing (SIRF) from 1982 to 2100 using a radiative kernel method based on albedo data from the Polar Pathfinder-Extent (APP-x) and Coupled Model Intercomparison Project 5 (CMIP5). Then, the SIRF is converted to CO2 equivalent emissions via the Dynamic Integrated Model of Climate and Economy (DICE) model. Finally, the associated costs are calculated using the substitute cost method, based on the social cost of carbon to achieve the Paris Agreement targets. The results show that the average Arctic SIRF was −0.75 ± 0.1 W·m−2 between 1982 and 2020, and increased by 0.12 W·m−2 during this period. The SIRF in April–June accounts for nearly 77% of the average annual value, with a maximum absolute value of –3.2 W·m−2 in May. Through model transformation, it is shown that the Arctic SIRF rising leads to global warming comparable to the effect of an increase of 34.5 Gt of CO2 in the atmosphere relative to pre-industrialization, and results in a loss of 24.4–48.8 trillion USD for climate regulation service (CRS). From 2020 to 2100, in the representative concentration pathway (RCP) 8.5, the Arctic SIRF is projected to increase by 0.31 W·m−2. Combined with the discount rate, the estimated average annual cost over the period ranges from 6.7–13.3 trillion USD. These findings provide a systematic understanding of the radiative effect of Arctic sea ice change on the global climate and the corresponding economic cost.

Inferring Changes in Arctic Sea Ice through a Spatio-Temporal Logistic Autoregression Fitted to Remote-Sensing Data

Arctic sea ice extent (SIE) has drawn increasing attention from scientists in recent years because of its fast decline in the Boreal summer and early fall. The measurement of SIE is derived from remote sensing data and is both a lagged and leading indicator of climate change. To characterize at a local level the decline in SIE, we use remote-sensing data at 25 km resolution to fit a spatio-temporal logistic autoregressive model of the sea-ice evolution in the Arctic region. The model incorporates last year’s ice/water binary observations at nearby grid cells in an autoregressive manner with autoregressive coefficients that vary both in space and time. Using the model-based estimates of ice/water probabilities in the Arctic region, we propose several graphical summaries to visualize the spatio-temporal changes in Arctic sea ice beyond what can be visualized with the single time series of SIE. In ever-higher latitude bands, we observe a consistently declining temporal trend of sea ice in the early fall. We also observe a clear decline in and contraction of the sea ice’s distribution between 70∘N–75∘N, and of most concern is that this may reflect the future behavior of sea ice at ever-higher latitudes under climate change.

New insight into the influence of the Greenland high on summer Arctic sea ice

The Greenland high (GL-high) coincides with a local center of action of the summer North Atlantic Oscillation and is known to have significant influence on Greenland ice sheet melting and summer Arctic sea ice. However, the mechanism behind the influence on regional Arctic sea ice is not yet clear. In this study, using reanalysis datasets and satellite observations, the influence of the GL-high in early summer on Arctic sea ice variability, and the mechanism behind it, are investigated. In response to an intensified GL-high, sea ice over the Beaufort Sea shows significant decline in both concentration and thickness from June through September. This decline in sea ice is primarily due to thermodynamic and mechanical redistribution processes. Firstly, the intensified GL-high increases subsidence over the Canadian Basin, leading to an increase in surface air temperature by adiabatic heating, and a substantial decrease in cloud cover and thus increased downward shortwave radiation. Secondly, the intensified GL-high increases easterly wind frequency and wind speed over the Beaufort Sea, pushing sea ice over the Canadian Basin away from the coastlines. Both processes contribute to an increase in open water areas, amplifying ice–albedo feedback and leading to sea ice decline. The mechanism identified here differs from previous studies that focused on northward moisture and heat transport and the associated increase in downward longwave radiation over the Arctic. The impact of the GL-high on the regional sea ice (also Arctic sea ice extent) can persist from June into fall, providing an important source for seasonal prediction of Arctic sea ice. The GL-high has an upward trend and reached a record high in 2012 that coincided with a record minimum summer Arctic sea ice extent, and has strong implications for summer Arctic sea ice changes.

Impacts of active satellite sensors' low-level cloud detection limitations on cloud radiative forcing in the Arctic

Abstract. Previous studies revealed that satellites sensors with the best detection capability identify 25 %–40 % and 0 %–25 % fewer clouds below 0.5 and between 0.5–1.0 km, respectively, over the Arctic. Quantifying the impacts of cloud detection limitations on the radiation flux are critical especially over the Arctic Ocean considering the dramatic changes in Arctic sea ice. In this study, the proxies of the space-based radar, CloudSat, and lidar, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), cloud masks are derived based on simulated radar reflectivity with QuickBeam and cloud optical thickness using retrieved cloud properties from surface-based radar and lidar during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. Limitations in low-level cloud detection by the space-based active sensors, and the impact of these limitations on the radiation fluxes at the surface and the top of the atmosphere (TOA), are estimated with radiative transfer model Streamer. The results show that the combined CloudSat and CALIPSO product generally detects all clouds above 1 km, while detecting 25 % (9 %) fewer in absolute values below 600 m (600 m to 1 km) than surface observations. These detection limitations lead to uncertainties in the monthly mean cloud radiative forcing (CRF), with maximum absolute monthly mean values of 2.5 and 3.4 Wm−2 at the surface and TOA, respectively. Cloud information from only CALIPSO or CloudSat lead to larger cloud detection differences compared to the surface observations and larger CRF uncertainties with absolute monthly means larger than 10.0 Wm−2 at the surface and TOA. The uncertainties for individual cases are larger – up to 30 Wm−2. These uncertainties need to be considered when radiation flux products from CloudSat and CALIPSO are used in climate and weather studies.

Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice

In order to satisfy the demand of key sea ice parameters, including melt pond depth Hp and underlying ice thickness Hi, in studies of Arctic sea ice change in summer, four algorithms of retrieving Hp and Hi were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of Hp. For the retrieval of Hi, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more accurate. The retrieval results of Hi for Lu18 agreed better with field measurements for thin ice (Hi < 1 m) than that for thick ice, but those results of Hp were not satisfactory. The König20 algorithm was only suitable for clear sky conditions, and underestimated Hp, while showing a good agreement with Hp < 0.15 m. For Arctic applications, Malinka18 and Zhang21 algorithms provided a basis and reference for the satellite optical data such as WoeldView2 to retrieve Hp and Hi. Malimka18 also showed the ability to retrieve Hi, except for the Lu18 algorithm if pond color captured by helicopters and unmanned aerial vehicles were available. This study identifies the optimal algorithm for retrieval of Hp and Hi under different conditions, which have the potential to provide necessary data for numerical simulations of Arctic sea ice changes in summer.

Causal Links Between Arctic Sea Ice and Its Potential Drivers Based on the Rate of Information Transfer

AbstractArctic sea ice has substantially changed over the past four decades, with a large decrease in sea‐ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble. This ensemble consists of 50 members realized with the EC‐Earth3 global climate model and covers the period 1970‐2100. We apply for the first time the Liang‐Kleeman information flow method to analyze the cause‐effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea‐ice area and volume on air temperature and ocean heat transport through the twenty‐first century.

Impact of Microstructure on Solar Radiation Transfer Within Sea Ice During Summer in the Arctic: A Model Sensitivity Study

The recent rapid changes in Arctic sea ice have occurred not only in ice thickness and extent, but also in the microstructure of ice. To understand the role of microstructure on partitioning of incident solar shortwave radiation within the ice and upper ocean, this study investigated the sensitivity of the optical properties of summer sea ice on ice microstructures such as the volume fraction, size, and vertical distribution of gas bubbles, brine pockets, and particulate matter (PM). The results show that gas bubbles are the predominant scatterers within sea ice. Their effects on the scattering coefficient and ice albedo are 5 and 20 times stronger respectively than the effect of brine pockets. Albedo and transmittance of ice decrease with higher concentration and larger size of PM particles. A 4-cm top layer of ice with high PM concentration (50 g/m3) results in a 10% increase in radiation absorption. The role of ice microstructure in the partitioning of radiation transfer is more important for seasonal than for multiyear ice, and more important for ponded than for snow-covered ice. Varying ice microstructure can obviously alter solar radiation transfer in the ice-ocean system, even with a constant ice thickness. Our results suggest that numerical models should take the variable microstructure of sea ice into account to improve model accuracy and to understand the interaction between internal variations in Arctic sea ice and the ocean, especially in summer.

A New Perspective on Four Decades of Changes in Arctic Sea Ice from Satellite Observations

Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations—the extended AVHRR Polar Pathfinder (APP-x)—trends in sea ice concentration, ice extent, ice thickness, and ice volume in the Arctic from 1982 to 2020 are investigated. Results show that the Arctic has become less ice-covered in all seasons, especially in summer and autumn. Arctic sea ice thickness has been decreasing at a rate of −3.24 cm per year, resulting in an approximate 52% reduction in thickness from 2.35 m in 1982 to 1.13 m in 2020. Arctic sea ice volume has been decreasing at a rate of −467.7 km3 per year, resulting in an approximate 63% reduction in volume, from 27,590.4 km3 in 1982 to 10,305.5 km3 in 2020. These trends are further examined from a new perspective, where the Arctic Ocean is classified into open water, perennial, and seasonal sea ice-covered areas based on sea ice persistence. The loss of the perennial sea ice-covered area is a major factor in the total sea ice loss in all seasons. If the current rates of sea ice changes in extent, concentration, and thickness continue, the Arctic is expected to have ice-free summers by the early 2060s.

Trans-Arctic shipping routes expanding faster than the model projections

Rapid declines in Arctic sea ice coverage over the past four decades have increased the commercial feasibility of trans-Arctic routes. However, the historical changes in navigability of trans-Arctic routes remain unclear, and projections by global circulation models (GCMs) contain large uncertainties since they cannot simulate long-term Arctic sea ice changes. In this study, we determined the changes in trans-Arctic routes from 1979 to 2019 by combining two harmonized high-quality daily sea ice products. We found that the trans-Arctic routes are becoming navigable much faster than projected by the GCMs. The navigation season for open water (OW) vessels along the Northeast Passage (NEP) has lengthened from occasionally navigable in the 1980 s to 92 ± 15 days in the 2010 s. In contrast, previous GCM projections have suggested that navigability would not be achieved until the mid-21st century. The 90-day safety shipping area for OW vessels expanded by 35% during 1979–2018, reaching 8.28 million km2 in 2018, indicating an increasing rate of 0.08 ± 0.01 million km2 per year. The shortest trans-Arctic routes were also shifted further north than the model projections. Regular ships have been able to safely travel north along the islands in the NEP and transit through the M’Clure Strait in the Canadian Arctic Archipelago during the 2010 s, while previous studies have projected that this would not be feasible until the mid-21st century. We also found that the improved navigability of trans-Arctic routes enables commercial ships to transport approximately 33–66% (at the same load factor) more goods from East Asia to Europe during the Arctic shipping season than by the traditional Suez Canal route. These findings highlight the need for aggressive actions to develop mandatory rules that promote navigation safety and strengthen environmental protection in the Arctic.

The Roles of Sea Ice Export, Atmospheric and Oceanic Factors in the Seasonal and Regional Variability of Arctic Sea Ice during 1979–2020

The seasonal and regional variability of Arctic sea ice area (SIA) and thickness (SIT) were investigated between 1979 and 2020 for the Atlantic sector (AS), Pacific sector (PS) and Barents–Kara Seas (BKSs). We applied the SIA data from remote sensing observations and SIT data from numerical model calculations. We found the large summer variability of SIA and SIT in AS and PS compared with those in winter. The opposite feature was seen in the BKSs. The annual declining rates of SIA and SIT were the largest in PS (−1.73 × 104 km2 yr−1) and AS (−3.36 × 10−2 m yr−1), respectively. The SIA variability was modest for winter PS and the northern Canadian Arctic Archipelago of AS. The annual and winter SIA flux from PS to AS gradually increased in 1979–2020; the summer SIA flux accounted for 11% of the PS summer SIA decline. The annual and seasonal SIA outflow through the Fram Strait during 1979–2020 steadily increased while for annual and winter SIA export, the increase mainly occurred in 1979–2000; the summer SIA outflow was only 1.45% equivalent to the decrease in the entire Arctic summer SIA. We concluded that sea ice export was not a major impact factor on the seasonal and regional decline of SIA and SIT except for the individual years. The near surface air temperature (SAT) and sea surface temperature (SST) were responsible for the retreat and thinning of the sea ice. The dramatic increase in SAT in winter resulted in a strong decrease in winter sea ice in BKS. The outgoing longwave radiation had significant negative correlations with SIA and SIT and positive correlations with SAT and SST. The Atlantic multi-decadal oscillation, related to the North Atlantic Ocean’s SST anomalies, had significant negative correlations with SIA and SIT. The SIT had higher correlations with the atmospheric and oceanic factors compared with SIA, which indicates that SIT is important for predictions of Arctic sea ice and climate change.

Effects of Water Vapor and Cloud Fraction in AIRS Retrievals on Arctic Sea Ice Variability

Using the precipitable water vapor (PWV) and cloud fraction (CF) measurements from the Atmospheric Infrared Sounder (AIRS), this study investigates the potential feedback on Arctic sea ice concentration (SIC) caused by variations in PWV and total CF, as well as CFs at low, middle and high levels during December 2002–November 2020. We find that increases in PWV and total CF generally coincide with the Arctic sea ice decline in each season, and both PWV and total CF anomalies are typically correlated with SIC anomalies in all seasons except for the PWV anomalies in summer. Additionally, during all seasons except summer, the low CF generally exhibits closer connection than the middle and high CFs with the trend in total CF and sea ice, and the correlation of SIC with total CF anomalies is governed by that with low CF anomalies. The sensitivities of SIC to changes in PWV and total CF are typically negative, and they are generally consistent with each other in each season. Moreover, the negative sensitivities of SIC to low, middle and high CFs are greatest and most extensive in summer. The contribution of PWV is typically much greater and more extensive than that of total CF to Arctic sea ice change in all seasons. Among the CFs at different levels, the positive contribution of low CF is typically most extensive in winter and spring, while the contributions of high and middle CFs are relatively greater in summer and autumn.

Sea ice in the northern North Atlantic through the Holocene: Evidence from ice cores and marine sediment records

Sea ice plays a pivotal role in Earth's climate and its past reconstruction is crucial to investigate the connections and feedbacks with the other components of the climate system. Among the available archives that store information of past sea ice are marine and ice cores. Recent studies on the IP25 biomarker extracted from marine sediments has shown great skill to infer past changes of Arctic sea ice. In ice matrixes, sodium, bromine and iodine have shown potential to store the fingerprint of sea ice presence. The development of an unambiguous sea ice proxy from ice cores, however, has proven to be a challenging task especially in the Arctic realm.In this work we analyze the sodium, bromine and iodine records in the RECAP ice core, coastal eastern Greenland, to investigate the sea ice variability in the northern North Atlantic Ocean through the last 11,000 years of the current interglacial, i.e. the Holocene. We compare the RECAP records with marine sea ice proxy records available from the northern North Atlantic.We suggest that RECAP sodium concentrations can be associated with variability of sea ice extent, while the bromine-to-sodium ratios and iodine are associated respectively with seasonal sea ice and bioproductivity from open ocean and fresh sea ice surfaces.According to our interpretation, we find that sea ice was at its lowest extent and seasonal in nature during the early Holocene in all regions of the North Atlantic. Increasing sea ice signals are seen from ca. 8–9 ka b2k, in line with long-term Holocene cooling. The increasing sea ice trend appears uninterrupted in the Fram Strait and North Iceland while reaching a maximum ca. 5 ka b2k in the East Greenland region. Sea ice modifications during the last 5000 years display great variability in East Greenland with intermediate conditions between the early and mid Holocene, possibly associated with local fjord dynamics. The last sea ice maximum was reached across all regions 1000 years b2k.

Response of Northern Hemisphere weather and climate to Arctic sea ice decline: Resolution independence in Polar Amplification Model Intercomparison Project (PAMIP) simulations

AbstractThe impact of Arctic sea ice decline on the weather and climate in mid-latitudes is still much debated, with observation suggesting a strong and models a much weaker link. In this study, we use the atmospheric model OpenIFS, in a set of model experiments following the protocol outlined in the Polar Amplification Model Intercomparison Project (PAMIP), to investigate whether the simulated atmospheric response to future changes in Arctic sea ice fundamentally depends on model resolution. More specifically, we increase the horizontal resolution of the model from 125km to 39km with 91 vertical levels; in a second step resolution is further increased to 16km with 137 levels in the vertical. The model does produce a response to sea ice decline with a weaker mid latitude Atlantic jet and increased blocking in the high latitude Atlantic, but no sensitivity to resolution can be detected with 100 members. Furthermore we find that the ensemble convergence toward the mean is not impacted by the model resolutions considered here.

Stratospheric winds trigger cold spells.

Changes in Arctic sea ice and snow cover can alter wind patterns at high altitudes.

Persistent freshening of the Arctic Ocean and changes in the North Atlantic salinity caused by Arctic sea ice decline

Arctic sea ice has been declining over past several decades with the largest ice loss occurring in summer. This implies a strengthening of the sea ice seasonal cycle. Here, we examine global ocean salinity response to such changes of Arctic sea ice using simulations wherein we impose a radiative heat imbalance at the sea ice surface, inducing a sea ice decline comparable to the observed. The imposed perturbation leads to enhanced seasonal melting and a rapid retreat of Arctic sea ice within the first 5–10 years. We then observe a gradual freshening of the upper Arctic ocean that continues for about a century. The freshening is most pronounced within the central Arctic, including the Beaufort gyre, and is attributed to excess surface freshwater associated with the stronger seasonal sea ice melting, as well as a greater upper-ocean freshwater storage due to changes in ocean circulation. The freshening of the Nordic Seas can also occur via a distillation-like process in which denser saline waters with increased salinity are exported to the subtropical/tropical North Atlantic by meridional overturning circulation. Thus, enhanced seasonal sea ice melting in a warmer climate can lead to a persistent Arctic freshening with large impacts on the global salinity distribution.

Pacific circulation response to eastern Arctic sea ice reduction in seasonal forecast simulations

Recent studies point to the sensitivity of mid-latitude winter climate to Arctic sea ice variability. However, there remain contradictory results in terms of character and timing of Northern Hemisphere large-scale circulation features to Arctic sea ice changes. This study assesses the impact of realistic late autumn eastern Arctic sea ice anomalies on atmospheric wintertime circulation at mid-latitudes, pointing to a hidden potential for seasonal predictability. ​Using a dynamical seasonal prediction system, an ensemble of seasonal forecast simulations of 23 historical winter seasons is run with reduced November sea ice cover in the Barents-Kara Seas, and is compared to the respective control seasonal hindcast simulations set. ​A non energy-conserving approach is adopted for achieving the desired sea ice loss, with artificial heat being added conditionally to the ocean surface heat fluxes so as to inhibit the formation of sea ice during November. Our results point to a robust atmospheric circulation response in the North Pacific sector, similar to previous findings on the multidecadal timescale. Specifically, an anticyclonic anomaly at upper and lower levels is identified over the eastern midlatitude North Pacific, leading to dry conditions over the North American southwest coast. The responses are related to a re-organization (weakening) of west-Pacific tropical convection and interactions with the tropical Hadley circulation. ​A possible interaction of the poleward-shifted Pacific eddy-driven jet stream and the Hadley cell is discussed​. ​The winter circulation response in the Euro-Atlantic sector is ephemeral in character and statistically significant in January only, corroborating previous findings of an intermittent and non-stationary Arctic sea ice-NAO link during boreal winter. These results ​aid our understanding of the seasonal impacts of reduced eastern Arctic sea ice on the midlatitude atmospheric circulation with implications for seasonal predictability in wintertime.

Fingerprint of COVID-19 in Arctic sea ice changes

Fingerprint of COVID-19 in Arctic sea ice changes

Observed Statistical Connections Overestimate the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate

AbstractDisentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called Atmospheric Model Intercomparison Project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents–Kara sea ice and Eurasian surface temperature, and between winter Chukchi–Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November–December Barents–Kara sea ice, a weakened winter stratospheric polar vortex, and a shift toward the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-yr-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent or are substantially weaker in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.