Low Ice Concentration Research Articles

Sea ice decline drives biogeographical shifts of key Calanus species in the central Arctic Ocean.

In recent decades, the central Arctic Ocean has been experiencing dramatic decline in sea ice coverage, thickness and extent, which is expected to have a tremendous impact on all levels of Arctic marine life. Here, we analyze the regional and temporal changes in pan-Arctic distribution and population structure of the key zooplankton species Calanus glacialis and C. hyperboreus in relation to recent changes in ice conditions, based on historical (1993-1998) and recent (2007-2016) zooplankton collections and satellite-based sea ice observations. We found strong correlations between Calanus abundance/population structure and a number of sea ice parameters. These relationships were particularly strong for C. glacialis, with higher numbers being observed at locations with a lower ice concentration, a shorter distance to the ice edge, and more days of open water. Interestingly, early stages of C. hyperboreus followed the same trends, suggesting that these two species substantially overlap in their core distribution area in the Arctic Ocean. Calanus glacialis and C. hyperboreus have been historically classified as shelf versus basin species, yet we conclude that both species can inhabit a wide range of bottom depths and their distribution in the Arctic Ocean is largely shaped by sea ice dynamics. Our data suggest that the core distribution patterns of these key zooplankton are shifting northwards with retreating sea ice and changing climate conditions.

Juvenile bearded seal response to a decade of sea ice change in the Bering, Chukchi, and Beaufort seas

Significant reductions in sea ice in the Pacific Arctic have occurred over the last 2 decades. Comparing the results of similarly conducted studies, but from different time periods, can increase our understanding of how marine mammals are responding to this change. We modeled the habitat selection and movement behavior of juvenile bearded seals Erignathus barbatus tagged with satellite transmitters in the Bering, Chukchi, and Beaufort seas during 2014-2018, a period of rapid decline in sea ice cover. We compared our results to an earlier study of juvenile bearded seals tagged in the Chukchi Sea during 2004-2009, a period of relatively stable sea ice coverage, and found differences. Seals in the earlier period strongly selected habitat near the ice edge and intermediate ice concentrations (50-60%) in both winter and spring. Seals in the later period strongly selected habitat away from the ice edge, showed no selection for any ice concentration in winter, and weakly selected low ice concentrations in spring (<50%). The likely explanation for these differences is changes in sea ice habitat because the shift away from the ice edge corresponds with a shift in the distribution of intermediate ice concentrations that seals prefer. During the later period, seals still used intermediate ice, which occurred farther from the ice edge and was now the average ice concentration available to them, masking any preference for intermediate ice in the habitat selection model. This change in sea ice conditions, although significant, may not currently be detrimental for juvenile bearded seals.

Change Points Detected in Decadal and Seasonal Trends of Outlet Glacier Terminus Positions across West Greenland

We investigated the change in terminus position between 1985 and 2015 of 17 marine-terminating glaciers that drain into Disko and Uummannaq Bays, West Greenland, by manually digitizing over 5000 individual frontal positions from over 1200 Landsat images. We find that 15 of 17 glacier termini retreated over the study period, with ~80% of this retreat occurring since 2000. Increased frequency of Landsat observations since 2000 allowed for further investigation of the seasonal variability in terminus position. We identified 10 actively retreating glaciers based on a significant positive relationship between glaciers with cumulative retreat >300 m since 2000 and their average annual amplitude (seasonal range) in terminus position. Finally, using the Detecting Breakpoints and Estimating Segments in Trend (DBEST) program, we investigated whether the 2000–2015 trends in terminus position were explained by the occurrence of change points (significant trend transitions). Based on the change point analysis, we found that nine of 10 glaciers identified as actively retreating also underwent two or three periods of change, during which their terminus positions were characterized by increases in cumulative retreat. Previous literature suggests potential relationships between our identified change dates with anomalous ocean conditions, such as low sea ice concentration and high sea surface temperatures, and our change durations with individual fjord geometry.

Experimental study of ship resistance in artificial ice floes

In this paper, a model-scale ship towing experiment is conducted to investigate the ship resistance in small ice floes. Instead of using refrigerated model ice, artificial ice floes made of Polypropylene (PP) is used in the tests based on the assumption that the dominant motion modes of small ice floes in water are rigid-body ones. The control parameters are further tailored to define the sizes and shapes of the artificial ice floes, whose specific compositions are determined based on the information from field observations. These ice floes are then randomly placed on the water surface in the Laboratory to approximate the realistic characteristics of ship resistance caused by small ice floes in practical conditions. The influences of Sea ice concentration, floes shapes and floes sizes on ship resistance vs velocity are investigated. Experimental results close to those obtained from other authors have been obtained, which indicates the feasibility of using PP-material artificial ice floes to measure ship resistance in waters covered with small ice floes subjected to low ice concentrations. Interesting phenomena observed in the experimental tests are also reported and analyzed.

Sea ice, temperature, and prey effects on annual variations in mean lengths of a key Arctic fish, Boreogadus saida, in the Barents Sea

Abstract Oceanographic conditions in the Arctic are changing, with sea ice cover decreasing and sea temperatures increasing. Our understanding of the effects on marine populations in the area is, however, limited. Here, we focus on the Barents Sea stock of polar cod (Boreogadus saida). Polar cod is a key fish species for the transfer of energy from zooplankton to higher trophic levels in the Arctic food web. We analyse the relationships between 30-year data series on the length-at-age of polar cod cohorts (ages 0–4) and sea surface temperature, sea ice concentration, prey biomasses, predator indices, and length-at-age the previous year using multiple linear regression. Results for several ages showed that high length-at-age is significantly associated with low sea ice concentration and high length-at-age the previous year. Only length-at-age for age 1 shows a positive significant relationship with prey biomass. Our results suggest that retreating sea ice has positive effects on the growth of polar cod in the Barents Sea despite previous observations of a stagnating stock biomass and decreasing stock abundance. Our results contribute to identifying mechanisms by which climate variability affects the polar cod population, with implications for our understanding of how future climate change may affect Arctic ecosystems.

The New Minimum of Sea Ice Concentration in the Central Arctic in 2016

In view of the extremely low sea ice concentration (SIC) appeared at high latitudes of the Arctic in the summer of 2010, the changes of SIC in the central Arctic from 2010 to 2017 were investigated in this paper based on the AMSR-E/AMSR-2 SIC products retrieved by the NT2 algorithm. The results show that the extremely low sea ice concentration in the central Arctic not only occurred in 2010 but also occurred again in 2016, and the daily average sea ice concentration (ASIC) reached a minimum of 0.70, which was significantly lower than the value of 0.78 in 2010 and became a new historical low record. A large area of sea ice in the sector 150°E–180° in 2010 disappeared in 2016, which was the most important difference to produce the new minimum. Also, the ice edge in 2016 retreated into the 85°N circle, whereas in 2010 it was far from the central Arctic. In 2010 and 2016, there were high correlations between the wind stress curl and the relative variation rate of ASIC , which indicates that wind stress curl (WSC) drove the divergence of sea ice. It directly leads to the decrease in the SIC and is the main cause of the extremely low SIC events. The results in this paper show that the decline of Arctic sea ice is represented by not only the reduction of sea ice coverage but also the reduction of SICs. The central Arctic has always been covered by large amount of sea ices, so the drastic reduction of SIC will not only change the structure of the ice field, but also lead to critical climatic effects that deserve further attention.

Accuracy and inter-analyst agreement of visually estimated sea ice concentrations in Canadian Ice Service ice charts using single-polarization RADARSAT-2

Abstract. This study compares the accuracy of visually estimated ice concentrations by eight analysts at the Canadian Ice Service with three standards: (i) ice concentrations calculated from automated image segmentation, (ii) ice concentrations calculated from automated image segmentation that were validated by the analysts, and (iii) the modal ice concentration estimate by the group. A total of 76 predefined areas in 67 RADARSAT-2 images are used in this study. Analysts overestimate ice concentrations when compared to all three standards, most notably for low ice concentrations (1/10–3/10). The spread of ice concentration estimates is highest for middle concentrations (5/10, 6/10) and smallest for the 9/10 ice concentration. The overestimation in low concentrations and high variability in middle concentrations introduce uncertainty into the ice concentration distribution in ice charts. The uncertainty may have downstream implications for numerical modelling and sea ice climatology. Inter-analyst agreement is also measured to determine which classifier's ice concentration estimates (analyst or automated image segmentation) disagreed the most. It was found that one of the eight analysts disagreed the most, followed second by the automated segmentation algorithm. This suggests high agreement in ice concentration estimates between analysts at the Canadian Ice Service. The high agreement, but consistent overestimation, results in an overall accuracy of ice concentration estimates in polygons to be 39 %, 95 % CI [34 %, 43 %], for an exact match in the ice concentration estimate with calculated ice concentration from segmentation and, 84 %, 95 % CI [80 %, 87 %], for the ±1 ice concentration category. Only images with high contrast between ice and open water and well-defined floes are used: true accuracy is expected to be lower than what is found in this study.

Trends in the Stability of Antarctic Coastal Polynyas and the Role of Topographic Forcing Factors

Polynyas are an important factor in the Antarctic and Arctic climate, and their changes are related to the ecosystems in the polar regions. The phenomenon of polynyas is influenced by the combination of inherent persistence and dynamic factors. The dynamics of polynyas are greatly affected by temporal dynamical factors, and it is difficult to objectively reflect the internal characteristics of their formation. Separating the two factors effectively is necessary in order to explore their essence. The Special Sensor Microwave/Imager (SSM/I) passive microwave sensor has been making observations of Antarctica for more than 20 years, but it is difficult for existing current sea ice concentration (SIC) products to objectively reflect how the inherent persistence factors affect the formation of polynyas. In this paper, we proposed a long-term multiple spatial smoothing method to remove the influence of dynamic factors and obtain stable annual SIC products. A halo located on the border of areas of low and high ice concentration around the Antarctic coast, which has a strong similarity with the local seabed in outline, was found using the spatially smoothed SIC products and seabed. The relationship of the polynya location to the wind and topography is a long-understood relationship; here, we quantify that where there is an abrupt slope and wind transitions, new polynyas are best generated. A combination of image expansion and threshold segmentation was used to extract the extent of sea ice and coastal polynyas. The adjusted record of changes in the extent of coastal polynyas and sea ice in the Southern Ocean indicate that there is a negative correlation between them.

The biogeography and ecology of common diatom species in the northern North Atlantic, and their implications for paleoceanographic reconstructions

Abstract Sound knowledge of present-day diatom species and their environments is crucial when attempting to reconstruct past climate and environmental changes based on fossil assemblages. For the North Atlantic region, the biogeography and ecology of many diatom taxa that are used as indicator-species in paleoceanographic studies are still not well known. Using information contained in large diatom-environment calibration datasets can greatly increase our knowledge on diatom taxa and improve the accuracy of paleoenvironmental reconstructions. A diatom calibration dataset including 183 surface sediment samples from the northern North Atlantic was used to explore the distribution and ecology of 21 common Northern Hemisphere diatom taxa. We define the ecological responses of these species to April sea ice concentrations and August sea surface temperatures (aSSTs) using Huisman-Olff-Fresco (HOF)-response curves, provide distribution maps, temperature optima and ranges, and high-quality light microscope images. Based on the results, we find species clearly associated with cold, warm and temperate waters. All species have a statistically significant relationship with aSST, and 15 species with sea ice. Of these, Actinocyclus curvatulus, Fragilariopsis oceanica and Porosira glacialis are most abundant at high sea ice concentrations, whereas Coscinodiscus radiatus, Shionodiscus oestrupii, Thalassionema nitzschioides, Thalassiosira angulata, Thalassiosira nordenskioeldii and Thalassiosira pacifica are associated with low sea ice concentrations/ice-free conditions. Interestingly, some species frequently used as sea ice indicators, such as Fragilariopsis cylindrus, show similar abundances at high and low sea ice concentrations with no statistically significant relationship to sea ice.

The co-distribution of Arctic cod and its seabird predators across the marginal ice zone in Baffin Bay

Arctic cod (Boreogadus saida) is the dominant pelagic fish in Arctic seas and a staple food of many arctic predators including several seabird species. Marginal ice zones are known as important feeding locations for seabirds. The hypothesis that thick-billed murre (Uria lomvia), northern fulmar (Fulmarus glacialis) and black-legged kittiwake (Rissa tridactyla) congregate in areas of high Arctic cod food resource and low ice concentration was tested at different spatial scales. Arctic cod biomass was estimated by hydroacoustics as a resource proxy, and seabirds were counted and sampled for stomach analysis along eight longitudinal transects across the marginal ice zone in southern Baffin Bay in June–July 2016. With increasing length, the epipelagic age-0 Arctic cod migrated from open waters to ice-covered areas. Subsequently, age-1 and age-2 Arctic cod tended to concentrate in a subsurface layer (40–100 m) within the epipelagic layer. Arctic cod 5.7–16.1 cm long (late age-0 to age-5) were the main fish prey of the three seabird species, which preferentially captured age-1 cod (6–11.5 cm). At large spatial scale (western versus eastern Baffin Bay), thick-billed murre, northern fulmar and their Arctic cod resource proxy were generally more abundant on the western ice-covered side of Baffin Bay. No clear spatial match was found, however, when comparing seabird abundances and their food-resource proxy in different ice concentrations across the marginal ice zone or at small scale (5 km). At medium scale (12.5 km), only murre density was influenced positively by its Arctic cod resource. A lack of schooling behavior and a successful strategy to avoid predation by hiding under the ice could explain the absence of any strong spatial match between Arctic cod and its seabird predators at these different scales.

An improved dual-polarized ratio algorithm for sea ice concentration retrieval from passive microwave satellite data and inter-comparison with ASI, ABA and NT2

The dual-polarized ratio algorithm (DPR) for the retrieval of Arctic sea ice concentration from Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data was improved using a contrast ratio (CR) parameter. In contrast to three other algorithms (Artist Sea Ice algorithm, ASI; NASA-Team 2 algorithm, NT2; and AMSR-E Bootstrap algorithm, ABA), this algorithm does not use a series of tie-points or a priori values of brightness temperature of sea-ice constituents, such as open water and 100% sea ice. Instead, it is based on a ratio ( α ) of horizontally and vertically polarized sea ice emissivity at 36.5 GHz, which can be automatically determined by the CR. α exhibited a clear seasonal cycle: changing slowly during winter, rapidly at other times, and reaching a minimum during summer. The DPR was improved using a seasonal α. The systematic differences in the Arctic sea ice area over the complete AMSR-E period (2002–2011) were -0.8%±2.0% between the improved DPR and ASI; -1.3%±1.7% between the improved DPR and ABA; and -0.7%±1.9% between the improved DPR and NT2. The improved DPR and ASI (or ABA) had small seasonal differences. The seasonal differences between the improved DPR and NT2 decreased, except in summer. The improved DPR identified extremely low ice concentration regions in the Pacific sector of the central Arctic (north of 83°N) around August 12, 2010, which was confirmed by the Chinese National Arctic Research Expedition. A series of high-resolution MODIS images (250 m×250 m) of the Beaufort Sea during summer were used to assess the four algorithms. According to mean bias and standard deviations, the improved DPR algorithm performed equally well with the other three sea ice concentration algorithms. The improved DPR can provide reasonable sea ice concentration data, especially during summer.

Atmospheric Correction of Sea Ice Concentration Retrieval for 89 GHz AMSR-E Observations

An improved sea ice concentration (SIC) retrieval algorithm named ASI2 that uses weather corrected polarization difference (PD) of brightness temperatures (TBs) at 89 GHz measured by AMSR-E/2 is developed. Effects of wind, total water vapor, liquid water path, and surface temperature on the TBs are evaluated through a radiative transfer model. TBs of open ocean yield higher sensitivity to the atmospheric water due to its low emissivity, whereas that of sea ice is more influenced by the surface conditions such as temperature and ice type. The weather effects are corrected by simulating changes in TBs caused by the atmospheric water absorption/emission and wind roughened ocean surface using numerical weather prediction reanalysis data fields as atmospheric profiles. ASI2 is validated on a collection of AMSR-E observations over open water and 100% SIC. The correction significantly reduces the standard deviation and bias of SIC over open water, yet yields little change over 100% SIC. Combined with an improved weather filter based on the corrected TBs at lower frequencies, ASI2 allows retrieval of low ice concentration and resolves a more exact ice concentration gradient across the ice edge compared to the original ASI algorithm.

Record low sea-ice concentration in the central Arctic during summer 2010

The Arctic sea-ice extent has shown a declining trend over the past 30 years. Ice coverage reached historic minima in 2007 and again in 2012. This trend has recently been assessed to be unique over at least the last 1450 years. In the summer of 2010, a very low sea-ice concentration (SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack ice at lower latitudes. This striking low ice concentration—referred to here as a record low ice concentration in the central Arctic (CARLIC)—is unique in our analysis period of 2003–15, and has not been previously reported in the literature. The CARLIC was not the result of ice melt, because sea ice was still quite thick based on in-situ ice thickness measurements. Instead, divergent ice drift appears to have been responsible for the CARLIC. A high correlation between SIC and wind stress curl suggests that the sea ice drift during the summer of 2010 responded strongly to the regional wind forcing. The drift trajectories of ice buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector, which appeared to benefit the CARLIC in 2010. Under these conditions, more solar energy can penetrate into the open water, increasing melt through increased heat flux to the ocean. We speculate that this divergence of sea ice could occur more often in the coming decades, and impact on hemispheric SIC and feed back to the climate.

Stratospheric Ozone Depletion: An Unlikely Driver of the Regional Trends in Antarctic Sea Ice in Austral Fall in the Late Twentieth Century

AbstractIt has been suggested that recent regional trends in Antarctic sea ice might have been caused by the formation of the ozone hole in the late twentieth century. Here we explore this by examining two ensembles of a climate model over the ozone hole formation period (1955–2005). One ensemble includes all known historical forcings; the other is identical except for ozone levels, which are fixed at 1955 levels. We demonstrate that the model is able to capture, on interannual and decadal timescales, the observed statistical relationship between summer Amundsen Sea Low strength (when ozone loss causes a robust deepening) and fall sea ice concentrations (when observed trends are largest). In spite of this, the modeled regional trends caused by ozone depletion are found to be almost exactly opposite to the observed ones. We deduce that the regional character of observed sea ice trends is likely not caused by ozone depletion.

Sea-ice production in the northern Japan Sea

Sinking of the dense water plays a significant role in the global climate system by driving thermohaline (overturning) circulation and biogeochemical cycles. Deep water convection occurs also in the Japan Sea, and the convection has been considered to be mainly caused by intense cooling of the sea surface. Another possible cause of the convection is brine rejection associated with high sea-ice production in a coastal polynya (thin sea-ice) area in the northern Japan Sea. We have developed an algorithm which detects the thin ice area and estimates the thickness using passive microwave satellite data. Based on a heat flux calculation with the satellite-derived ice thickness, the total sea-ice production in winter (December–March) averaged over 2002/03–2010/11 is estimated to be 4.27 × 1010m3. This indicates that the ice production was underestimated by about half in a previous study in which the polynya was unrealistically treated as a low ice concentration area. The main determinant factor for the total ice production is the surface air temperature in early winter (December–January), which shows a rapid warming trend of 0.7°C/decade for this 40-years. Based on a linear regression approach, the total ice production is estimated to have decreased by ~5%/decade due to air temperature warming. If brine rejection due to the ice production contributes to the deep water formation in the Japan Sea, this is consistent with the fact that the deep water formation has been decreasing for the last 50–100 years.

Ice and ocean velocity in the Arctic marginal ice zone: Ice roughness and momentum transfer

The interplay between sea ice concentration, sea ice roughness, ocean stratification, and momentum transfer to the ice and ocean is subject to seasonal and decadal variations that are crucial to understanding the present and future air-ice-ocean system in the Arctic. In this study, continuous observations in the Canada Basin from March through December 2014 were used to investigate spatial differences and temporal changes in under-ice roughness and momentum transfer as the ice cover evolved seasonally. Observations of wind, ice, and ocean properties from four clusters of drifting instrument systems were complemented by direct drill-hole measurements and instrumented overhead flights by NASA operation IceBridge in March, as well as satellite remote sensing imagery about the instrument clusters. Spatially, directly estimated ice-ocean drag coefficients varied by a factor of three with rougher ice associated with smaller multi-year ice floe sizes embedded within the first-year-ice/multi-year-ice conglomerate. Temporal differences in the ice-ocean drag coefficient of 20–30% were observed prior to the mixed layer shoaling in summer and were associated with ice concentrations falling below 100%. The ice-ocean drag coefficient parameterization was found to be invalid in September with low ice concentrations and small ice floe sizes. Maximum momentum transfer to the ice occurred for moderate ice concentrations, and transfer to the ocean for the lowest ice concentrations and shallowest stratification. Wind work and ocean work on the ice were the dominant terms in the kinetic energy budget of the ice throughout the melt season, consistent with free drift conditions. Overall, ice topography, ice concentration, and the shallow summer mixed layer all influenced mixed layer currents and the transfer of momentum within the air-ice-ocean system. The observed changes in momentum transfer show that care must be taken to determine appropriate parameterizations of momentum transfer, and imply that the future Arctic system could become increasingly seasonal.

Sea Ice Concentration Estimation During Melt From Dual-Pol SAR Scenes Using Deep Convolutional Neural Networks: A Case Study

High-resolution ice concentration maps are of great interest for ship navigation and ice hazard forecasting. In this case study, a convolutional neural network (CNN) has been used to estimate ice concentration using synthetic aperture radar (SAR) scenes captured during the melt season. These dual-pol RADARSAT-2 satellite images are used as input, and the ice concentration is the direct output from the CNN. With no feature extraction or segmentation postprocessing, the absolute mean errors of the generated ice concentration maps are less than 10% on average when compared with manual interpretation of the ice state by ice experts. The CNN is demonstrated to produce ice concentration maps with more detail than produced operationally. Reasonable ice concentration estimations are made in melt regions and in regions of low ice concentration.

High‐frequency gravity waves and homogeneous ice nucleation in tropical tropopause layer cirrus

AbstractThe impact of high‐frequency gravity waves on homogeneous‐freezing ice nucleation in cold cirrus clouds is examined using parcel model simulations driven by superpressure balloon measurements of temperature variability experienced by air parcels in the tropical tropopause region. We find that the primary influence of high‐frequency waves is to generate rapid cooling events that drive production of numerous ice crystals. Quenching of ice nucleation events by temperature tendency reversal in the highest‐frequency waves does occasionally produce low ice concentrations, but the overall impact of high‐frequency waves is to increase the occurrence of high ice concentrations. The simulated ice concentrations are considerably higher than indicated by in situ measurements of cirrus in the tropical tropopause region. One‐dimensional simulations suggest that although sedimentation reduces mean ice concentrations, a discrepancy of about a factor of 3 with observed ice concentrations remains. Reconciliation of numerical simulations with the observed ice concentrations will require inclusion of physical processes such as heterogeneous nucleation and entrainment.

A hypothesis on variability of surface water <italic>p</italic>CO<sub>2</sub> under the rapid sea-ice retreat during summer in the Arctic Ocean

The Arctic Ocean has been recognized to play an active role in global carbon cycle due to its potential to disproportionally take up CO2 from the atmosphere especially under a dwindling ice extent. It is estimated that the Arctic Ocean will be responsible for up to 5%–14% of the total global oceanic CO2 uptake even though it comprises only 3% of the world ocean surface area. Over the past decade, the sea ice in the Arctic Ocean has significantly retreated during summer. The rapid sea ice retreat is thought to cause corresponding changes in the distribution of p CO2 in the surface waters of Arctic Ocean. However, the response of carbon dynamics to a changing Arctic Ocean remains poorly quantified. It has been postulated that an ice-free condition in the Arctic Ocean basins would allow for uptake of a substantial amount of carbon dioxide (CO2) from the atmosphere as a result of sea ice melt and increasing primary productivity. However, the other direct observation-based study of high-resolution survey of sea-surface CO2 concentration across the Canada Basin, showing a great high p CO2 relative to earlier observations and predicted that the Arctic Ocean basin will not become a large atmospheric CO2 sink under ice-free conditions. Due to the existing quite different views, thus, there is an implication of observation-based learning in the variations of the surface seawater p CO2 under a scenario of rapid sea ice melting. In the summer of 2008, during the 3rd Chinese National Arctic Research Expedition (CHINARE) cruise, significant variability of p CO2 in surface water has been observed along a trans-Arctic section of 150°–160°W from the Chukchi Sea slope to 88°N in the western Arctic Ocean. We propose a hypothesis of “low-low-high” variation trend in surface water p CO2 levels along a decreasing ice-cover gradient across three different zones in the Arctic Ocean under a rapid sea ice melting scenario in the summer. Specifically, there are (1) “low” p CO2 levels of ~270–280 μ atm in the sea ice-covered zone (north of 84°N) with a high ice concentration >70%; (2) “low” p CO2 of ~250–270 μ atm in a sea ice melting zone (78°–81°N) with a medium ice extent of around 50%; and (3) “high” p CO2 of ~320–365 μ atm in an ice-free zone (72°–77°N) with a low ice concentration of p CO2 variation trend could be attributed to different driving forces. The low p CO2 in the heavily ice-covered northern basin is likely influenced by a combination of several processes, including mixing of various source waters, CO2 fixation by ice algae, ice-water gas exchange, and temperature change, although their relative roles remain to be quantified. The low p CO2 observed in the partially ice-covered northern Canada Basin could be primarily derived from biological CO2 fixation and the dissolution of CaCO3 precipitates, both of which consume CO2. Primary productivity enhanced by the early melting of sea ice plays an important role in the decreased sea-surface p CO2. In addition, sea ice melting also promotes the dissolution of authigenic CaCO3 in the form of ikaite within the sea ice. Finally, results of tracer data and model simulations suggest that the rapid CO2 invasion from the atmosphere and low biological export of CO2 owing to a shallow mixed-layer depth, strong subsurface water stratification, and limited nutrient supply to the surface water are both responsible for the observed high p CO2 values in the ice-free southern Canada Basin.

Towards ensemble data assimilation for the Environment Canada Regional Ice Prediction System

A short‐range high‐resolution sea ice prediction system has been developed at Environment Canada. This study describes the first steps towards transitioning this system from a simple deterministic data assimilation system based on the three‐dimensional variational (3D‐Var) approach into a data assimilation system based on an ensemble of ensemble‐variational (EnVar) analyses. First, an ensemble of 3D‐Var analyses using static background‐error covariances is implemented and used to evaluate different strategies for simulating model uncertainties during the ensemble forecast step; these range from perturbing parameters within the sea ice model to completely disabling the sea ice dynamics or thermodynamics in some of the ensemble members. The experiments show a good ensemble spread–error relationship in areas with low or high ice concentration, though more work is needed to better simulate uncertainties in areas with intermediate ice concentration. Second, results from idealized experiments with EnVar analyses using ensemble covariances are presented. They demonstrate the potential improvement of sea ice analyses from using state‐dependent multivariate ensemble covariances when assimilating ice concentration observations to correct both ice concentration and unobserved variables such as ice thickness and ocean temperature.