Variability Of Sea Ice Extent Research Articles

Arctic and Barents Sea ice extent variability and trends in 1979–2022

The aim of the paper is to assess interannual and decadal variability of the Barents Sea and Arctic ice extent in various seasons for the period from 1979 to 2022.The material for the study was satellite data on the Barents Sea and Arctic ice extent, climate indices, oceanographic data obtained during surveys in the Barents Sea by PINRO and other available information on hydrometeorological conditions of the sea in 1979–2022.Methods of descriptive statistics as well as comparative, correlation, regression, harmonic and cluster analyses were applied.Results: The year-to-year changes in the Barents Sea and Arctic ice extent in various seasons are described for 1979–2022. The modern climate changes, manifested in substantial warming of air and water masses in the Arctic, resulted in a considerable ice extent reduction in the studied areas in recent decades. Well-marked negative trends took place in all months and seasons. The annual mean ice extent was decreasing at a rate of 532 thousand km2 per decade in the Arctic, and at a rate of 105 thousand km2 per decade in the Barents Sea. Over the past 40 years, the ice extent in the Arctic has decreased by 14%, and in the Barents Sea — by half (by 51%), while the ice-free period duration has increased in the Barents Sea from one to three months. Hydrometeorological parameters were identified that are most closely related to the ice extent in the Arctic (|r| ≥ 0.40) and Barents Sea (|r| ≥ 0.60). Reliable regression models were developed that explain 45.2 and 88.0% of its variability, respectively. The contribution of individual factors to the ice extent variability explained by regression equations was quantitatively assessed, and the leading role of air temperature was noted.Practical significance: The obtained results are useful for a better understanding of the climate processes occurring in the Arctic and Barents Sea in recent decades and can be used to assess the impact of climate changes on the main objects of Russian fishery in these areas.

Factors influencing haulout behaviour of non-breeding weddell seals (Leptonychotes weddellii) at Cape Royds, Antarctica

The Weddell seal (Leptonychotes weddellii) is a fast-ice obligate species that plays an important role as both predator and prey within the high-latitude, coastal Southern Ocean. Weddell seals are affected by pressures of marine resource extraction and variation in sea-ice extent and characteristics that are affected by climate. Thus, monitoring their population dynamics provides an indicator of the effectiveness of fisheries management, and impacts of changing climate in the high latitude Southern Ocean ecosystem. Satellite imagery is increasingly being used to monitor the populations of this species, but assessment techniques require a better understanding of the environmental factors influencing the likelihood that individuals will be on the sea-ice and therefore visible in a satellite image. Addressing that goal, we captured 5054 trail camera photos during spring 2017 in the 24-h light at Cape Royds, Antarctica, and then counted seals on the fast ice every 30 min over 59 days. Using a generalised additive model (63% deviance explained) we described the haulout behaviour of non-breeding Weddell seals according to time of day, date, air temperature, pressure, solar radiation, and wind speed. We found that the seals’ haulout cycle is driven to a significant degree by weather variables, primarily temperature and wind speed. Quantifying these haulout patterns can be used to determine the time of day, and under what conditions, that most seals are hauled out. Integrating environmental parameters to correct time-of-day patterns would allow better cross-site abundance comparisons, leading to better Weddell seal population estimates for the Ross Sea region and the wider coastal Antarctica.

Ornithogenic sedimentary profiles of n-alkanes and PAHs constrain breeding penguin population dynamics at Cape Bird, Ross Island, Antarctica, over the past 1,500 years

Ornithogenic sediment may contain important paleoecological information concerning past bird population dynamics. In this paper, we analyse the distribution of n-alkanes and polycyclic aromatic hydrocarbons (PAHs) in two sedimentary profiles collected from abandoned penguin colonies at Cape Bird, Ross Island, Antarctica. The geochronology of the sediment profiles was determined using 210Pb and AMS 14C dating techniques, and spans the past 1500 years. We observe low levels of n-alkanes (0.93–2.67 μg g−1) and PAHs (20.5–46.8 ng g−1) concentrations dominated by short-chain n-alkanes, low-molecular-weight and alkyl PAHs. Principal Component Analysis (PCA) shows that the PC 1 scores for n-alkanes and PAHs are significantly correlated with the input intensity of penguin guano and penguin bioelements. Using these proxies in combination with Generalized Additive Model (GAM), we reveal that breeding penguin population growth reaches a historical peak during the Medieval Climate Anomaly (MCA) prior to 1550 CE. This growth in population size corresponds to the extent of sea ice cover and the activity of the local atmospheric-ocean circulation. Warming induced by El Niño and the positive phase of the Southern Annular Mode, along with the expansion of ice-free zones and increased oceanic nutrient and food availability, are considered primary factors contributing to the growth of breeding penguin populations. Additionally, variations in sea ice extent and Amundsen Sea Low significantly influence penguin population dynamics. Our study suggests that n-alkanes and PAHs may be valuable organic proxies for reconstructing historical changes in breeding penguin populations, with the local sea ice extent and atmospheric-oceanic circulation exerting a major influence on Antarctic penguin population dynamics.

Sea surface temperature anomalies related to the Antarctic sea ice extent variability in the past four decades

Sea surface temperature anomalies related to the Antarctic sea ice extent variability in the past four decades

Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model

Abstract. Using a state-of-the-art coupled general circulation model, physical processes underlying Antarctic sea ice multidecadal variability and predictability are investigated. Our model simulations constrained by atmospheric reanalysis and observed sea surface temperature broadly capture a multidecadal variability in the observed sea ice extent (SIE) with a low sea ice state (late 1970s–1990s) and a high sea ice state (2000s–early 2010s), although the model overestimates the SIE decrease in the Weddell Sea around the 1980s. The low sea ice state is largely due to the deepening of the mixed layer and the associated deep convection that brings subsurface warm water to the surface. During the high sea ice period (post-2000s), the deep convection substantially weakens, so surface wind variability plays a greater role in the SIE variability. Decadal retrospective forecasts started from the above model simulations demonstrate that the Antarctic sea ice multidecadal variability can be skillfully predicted 6–10 years in advance, showing a moderate correlation with the observation. Ensemble members with a deeper mixed layer and stronger deep convection tend to predict a larger sea ice decrease in the 1980s, whereas members with a larger surface wind variability tend to predict a larger sea ice increase after the 2000s. Therefore, skillful simulation and prediction of the Antarctic sea ice multidecadal variability require accurate simulation and prediction of the mixed layer, deep convection, and surface wind variability in the model.

Interannual differences in sea ice regime in the north-western Barents Sea cause major changes in summer pelagic production and export mechanisms

The Barents Sea is a highly dynamic and productive marine ecosystem and a hotspot of global warming. Variability in sea ice extent is a common feature in the Barents Sea with substantial movements of the sea ice edge on short-term, seasonal to interannual time scales. Historically the northern Barents Sea (north of 75°N) has been ice-covered in winter, but recently it has become the area with most winter ice loss in the Arctic, and year-round ice-free conditions are predicted for the second half of the 21st century. These environmental changes have significant implications for the marine ecosystem. In this study we used contrasting sea ice regimes in August 2018 and August 2019 to explore the response of phytoplankton and bacterial production, microbial abundance, and vertical carbon flux in the north-western Barents Sea (between 76°N and 83°N) to the variability of sea ice. While the study area was ice-free in August 2018, extensive areas north of 79°N were ice-covered in 2019. When the northern parts of the transect were still ice covered, diatoms and other larger phytoplankton were dominant and highest abundances were observed following the receding ice edge. In contrast, under ice-free conditions in 2018, the pelagic ecosystem resembled a post-bloom stage of the seasonal succession with higher abundance of small phytoplankton and heterotrophic protists and low vertical flux throughout the water column. While phytoplankton biomass, bacterial production and downward vertical flux of particulate organic carbon in the upper 60 m were on average higher in 2019, primary production and carbon export below the euphotic layer were comparable between both years. However, overall highest primary production, bacterial production and abundance of both photosynthetic and heterotrophic microorganisms were observed in surface waters (upper 30 m) in 2019, connected to the retreating ice edge, where also vertical particle flux was higher and characterized by a strong attenuation curve. The results clearly demonstrate that differences in ice cover affect the phenology of pelagic primary production and associated biological processes in the Barents Sea.

Characteristics of seafloor ambient noise under different sea ice concentrations in the northern Chukchi Sea: Results from the N11 CHINARE ocean‐bottom seismic experiment

AbstractSeafloor ambient noise in the Arctic Ocean is related to sea ice. The characteristics of low‐frequency seafloor ambient noise (<10 Hz) in the northern Chukchi Sea have rarely been reported. Here, we investigated the seafloor ambient noise recorded using ocean‐bottom seismometers in the northern Chukchi Sea under four different sea ice‐concentration periods from 3 to 23 August 2020, in the 11th Chinese National Arctic Research Expedition. The causes and mechanisms of the changes in seafloor ambient noise that correspond to the variation in sea ice concentration were discussed. The energy of infragravity waves and primary microseisms is weak compared with other oceans. Combined with the analysis of land station, we argue that the variations in sea ice extent have little effect on the energy of the primary microseisms and infragravity waves. The power of secondary microseisms is growth with the loss of sea ice and is influenced by storms. We find that a high concentration of sea ice can impede the process of storm‐sea surface interaction, which in turn affects the power of microseisms inspired by storm.

South Asian Monsoon Variability and Arctic Sea Ice Extent Linkages During the Late Pliocene

AbstractThe influence of a warming‐induced reduction in Arctic sea ice extent (SIE) on the South Asian monsoon (SoAM) is not well understood. The mid‐Piacenzian Warm Period (MPWP, 3.264–3.025 million years ago, Ma), the most recent warm climate event when the Earth's CO2 levels were similar to the present, is considered an analog for future global warming. We present a multi‐proxy high‐resolution record of SoAM variability during the late Pliocene (∼3.4–2.7 Ma) using denitrification, productivity, weathering, and terrestrial influx proxies from the eastern Arabian Sea (International Ocean Discovery Program Expedition 355). The proxy‐based SoAM reconstruction is independently verified using a hybrid model‐proxy data set (Oscillayers). We identify two distinct intervals of monsoon intensification—during the MPWP and at 2.9 Ma. The SoAM variability appears to result from an interplay between dynamic (Insolation, Arctic SIE variability, and southern tropical Indian Ocean surface temperature variability due to Indonesian Throughflow changes) and thermodynamic effects (global temperature change due to pCO2 variability). Using a late Pliocene Arctic spring sea ice concentration reconstruction, we find that lower (higher) Arctic SIE leads to stronger (weaker) late Pliocene SoAM via asymmetric interhemispheric energy export and through modulating jet stream flow and meridional circulation. Our finding of strengthened SoAM during the MPWP corroborates model results and implies that more intense precipitation is expected over South Asia with continued climate warming.

The mechanism linking the variability of the Antarctic sea ice extent in the Indian Ocean sector to Indian summer monsoon rainfall.

The study investigates the mechanism of teleconnection between the variability of sea ice extent (SIE) in the Indian Ocean sector of the Southern Ocean and the variability of Indian summer monsoon rainfall. We utilized reanalysis, satellite, in-situ observation data, and model output from the coupled model intercomparison project phase 5 (CMIP5) from 1979 to 2013. The empirical orthogonal function (EOF) and correlation analysis show that the first and third modes of principal component (PC1 and PC3) of SIE in the Indian Ocean sector during April–May–June (AMJ) are significantly correlated with the second mode of principal component (PC2) of Indian summer monsoon rainfall. The reanalysis data revealed that the changes in the SIE in the Indian Ocean sector excite meridional wave train responses along the Indian Ocean for both principal component modes. Positive (negative) SIE anomalies based on first and third EOFs (EOF1 and EOF3), contribute to the strengthening (weakening) of the Polar, Ferrel, and Hadley cells, inducing stronger (weaker) convective activity over the Indian latitudes. The stronger (weaker) convective activity over the Indian region leads to more (less) rainfall over the region during high (low) ice phase years. Furthermore, a stronger (weaker) polar jet during the high (low) ice phase is also noted. The selected CMIP5 models captured certain atmospheric teleconnection features found in the reanalysis. During AMJ, the SIE simulated by the NorESM1-M model was significantly positively correlated with Indian summer monsoon rainfall, whereas the IPSL-CM54-LR model showed a negative correlation.

Rotational drift in Antarctic sea ice: pronounced cyclonic features and differences between data products

Abstract. Sea ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an indicator to evaluate the impact of climate change on polar regions. However, concentration-based measurements of ice variability do not allow the discrimination of the relative contributions made by thermodynamic and dynamic processes, prompting the need to use sea ice drift products and develop methods to quantify changes in sea ice dynamics that would indicate trends in the ice characteristics. Here, we present a new method to automate the detection of rotational drift features in Antarctic sea ice from space at spatial and temporal scales comparable to that of polar weather. This analysis focusses on drift features in the Atlantic sector of the Southern Ocean in the period 2013–2020 using currently available satellite ice motion products from EUMETSAT OSI SAF. We observe a large discrepancy between cyclonic and anticyclonic drift features, with cyclonic features typically exhibiting larger drift intensity and spatial variability according to all products. The mean intensity of the 95th percentile of cyclonic features is 1.5–2.0 times larger for cyclonic features than anticyclonic features. The spatial variability of cyclonic features increased with intensity, indicating that the most intense cyclonic features are also the least homogenous. There is good agreement between products in detecting anticyclonic features; however, larger disagreement is evident for cyclonic features, with the merged product showing the most intense 95th percentile threshold and largest spatial variability, likely due to the more extended coverage of valid vorticity points. A time series analysis of the 95th percentile shows an abrupt intensification of cyclonic features from 2014–2017, which coincides with the record decline in Antarctic sea ice extent since winter of 2015. Our results indicate the need for systematic assessments of sea ice drift products against dedicated observational experiments in the weather-dominated Atlantic sector. Such information will allow us to confirm whether the detected increase in cyclonic vorticity is linked to rapidly changing atmospheric changes driven by sea ice dynamics and establish the measure of rotational sea ice drift as a potential indicator of weather-driven variability in Antarctic sea ice.

Satellite-Based Data Assimilation System for the Initialization of Arctic Sea Ice Concentration and Thickness Using CICE5

The satellite-derived sea ice concentration (SIC) and thickness (SIT) observation over the Arctic region are assimilated by implementing the Ensemble Optimal Interpolation (EnOI) into the Community Ice CodE version 5.1.2 (CICE5) model. The assimilated observations are derived from Special Sensor Microwave Imager/Sounder (SSMIS) for the SIC, European Space Agency's (ESA) Soil Moisture and Ocean Salinity mission (SMOS) for the SIT of the thin ice, and ESA's CryoSat-2 satellite for the SIT of the thick ice. The SIC, and SIT observations are assimilated during 2000–2019, and 2011–2019, respectively. The quality of the reanalysis is evaluated by comparing with observation and modeled data. Three data assimilation experiments are conducted: noDA without data assimilation, Ver1 with SIC assimilation, and Ver2 with SIC and SIT assimilation. The climatological bias of the SIC in noDA was reduced in Ver1 by 29% in marginal ice zones during boreal winter, and 82% in pan-Arctic ocean during boreal summer. The quality of simulating the interannual variation of sea ice extent (SIE) is improved in all months particularly during boreal summer. The root-mean-square errors (RMSEs) of SIE anomaly in August are significantly reduced compared to noDA. However, the interannual variations of SIT is unrealistic in Ver1 which requires the additional assimilation of the SIT observation. The climatological bias of SIT over the Arctic was further reduced in Ver2 by 28% during boreal winter compared to that in Ver1. The interannual variability of SIT anomalies is realistically simulated in Ver2 by reducing the RMSEs of SIT anomalies by 33% in February, and 28% in August by compared to that in Ver1. The dominant interannual variation extracted by empirical orthogonal function (EOF) of SIT anomalies in Ver2 is better simulated than Ver1. The additional assimilation of SIT improves not only SIT, but also SIC. The climatological bias of SIE and the errors in leading EOF of SIC anomalies in Ver2 is further reduced compared to those in Ver1 during boreal winter. However, improvements led by assimilating additional SIT observation is not clear during boreal summer, possible due to the lack of available SIT observation during this season.

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.

Revisiting Antarctic sea-ice decadal variability since 1980

Sea-ice extent (SIE) satellite data has been stored and studied over the past four decades. Antarctica’s SIE has recently attained both its maximum (2014) and its minimum (2017) values, which raised questions regarding how SIE variability is evolving. Here we discuss a new approach to improve our understanding of SIE variability for the 1982–1993 and 2006–2017 periods. Using a probability density function and examining the mean and standard deviation of SIE distributions as a function of seasonality. Results show that the whole Southern Ocean presented both mean and standard deviation growth in all seasons. The largest SIE distribution difference for Southern Ocean between 1982–1993 and 2006–2017 periods was observed in July, August and September (JAS), during which all individual Sea sectors presented growth of the SIE mean. Not only different Sea sectors showed different variations, but the SIE data distributions from the same Sea sector yielded different changes with differing seasons. January, February and March (JFM) together with April, May and June were the seasons with the largest SIE decadal variability for Weddell, Indian, Amundsen and West Pacific Sea Sectors, while the Ross Sea showed greater SIE variability during JAS and October November, December. This methodology showed consistent results with the traditional SIE trend calculation and introduced a new quantification index for evaluating the differences between two distributions not necessarily connected in time.

Short-Term Meteorological and Environmental Signals Recorded in a Firn Core from a High-Accumulation Site on Plateau Laclavere, Antarctic Peninsula

High-accumulation sites are crucial for understanding the patterns and mechanisms of climate and environmental change in Antarctica since they allow gaining high-resolution proxy records from firn and ice. Here, we present new glacio- and isotope-geochemical data at sub-annual resolution from a firn core retrieved from an ice cap on Plateau Laclavere (LCL), northern Antarctic Peninsula, covering the period 2012–2015. The signals of two volcanic eruptions and two forest fire events in South America could be identified in the non-sea-salt sulphur and black carbon records, respectively. Mean annual snow accumulation on LCL amounts to 2500 kg m−2 a−1 and exhibits low inter-annual variability. Time series of δ18O, δD and d excess show no seasonal cyclicity, which may result from (1) a reduced annual temperature amplitude due to the maritime climate and (2) post-depositional processes. The firn core stratigraphy indicates strong surface melt on LCL during austral summers 2013 and 2015, likely related to large-scale warm-air advection from lower latitudes and temporal variations in sea ice extent in the Bellingshausen-Amundsen Sea. The LCL ice cap is a highly valuable natural archive since it captures regional meteorological and environmental signals as well as their connection to the South American continent.

High‐Frequency Sea Ice Variability in Observations and Models

AbstractWe characterize high‐frequency variability of sea ice extent (HFVSIE) in observations and climate models. We find that HFVSIE in models is biased low with respect to observations, especially at synoptic timescales (<20 days) in the Arctic year‐round and at monthly timescales (30–60 days) in Antarctica in winter. Models show large spread in HFVSIE, especially in Antarctica. This spread is partly explained by sea ice mean‐state while model biases in sea level pressure (SLP) and wind variability do not appear to play a major role in HFVSIE spread. Extreme sea ice extent (SIE) changes are associated with SLP anomaly dipoles aligned with the sea ice edge and winds directed on‐ice (off‐ice) during SIE loss (gain) events. In observations, these events are also associated with distinct ocean wave states during the cold season, when waves are greater (smaller) and travel toward (away from) the sea ice edge during SIE loss (gain) events.

Impact of Winds and Southern Ocean SSTs on Antarctic Sea Ice Trends and Variability

AbstractAntarctic sea ice extent (SIE) has slightly increased over the satellite observational period (1979 to the present) despite global warming. Several mechanisms have been invoked to explain this trend, such as changes in winds, precipitation, or ocean stratification, yet there is no widespread consensus. Additionally, fully coupled Earth system models run under historic and anthropogenic forcing generally fail to simulate positive SIE trends over this time period. In this work, we quantify the role of winds and Southern Ocean SSTs on sea ice trends and variability with an Earth system model run under historic and anthropogenic forcing that nudges winds over the polar regions and Southern Ocean SSTs north of the sea ice to observations from 1979 to 2018. Simulations with nudged winds alone capture the observed interannual variability in SIE and the observed long-term trends from the early 1990s onward, yet for the longer 1979–2018 period they simulate a negative SIE trend, in part due to faster-than-observed warming at the global and hemispheric scale in the model. Simulations with both nudged winds and SSTs show no significant SIE trends over 1979–2018, in agreement with observations. At the regional scale, simulated sea ice shows higher skill compared to the pan-Antarctic scale both in capturing trends and interannual variability in all nudged simulations. We additionally find negligible impact of the initial conditions in 1979 on long-term trends.

Changes in the role of Pacific decadal oscillation on sea ice extent variability across the mid-1990s

Characteristics of sea ice extent (SIE) have been rapidly changing in the Pacific Arctic sector (PAS) in recent years. The SIE variability in PAS during the late spring and early summer (i.e., April–May–June, AMJ) plays a key role in determining the SIE during the following fall when SIE is at a minimum. We find that the Pacific Decadal Oscillation (PDO), which is the most dominant variability of sea surface temperature (SST) on the low-frequency timescales, differently influences the SIE in PAS during AMJ before and after the mid-1990s. While a positive phase of PDO during the previous winter acts to increases SIE during AMJ before the mid-1990s, it acts to decrease SIE during AMJ after the mid-1990s. Further analysis indicates that atmospheric circulation associated with PDO differently influences the variability of SIE in the PAS during AMJ by modulating poleward moisture transport across the Alaska or the Far East Asia peninsula. This results in the change in the relationship of PDO and SIE in the PAS before and after the mid-1990s.

Life on the ice-edge: Paleoenvironmental significance of the radiolarian species Amphimelissa setosa in the northern hemisphere

The high-latitude Northern Hemisphere is a key region in the global climate balance. Variations in sea-ice extent affect biological productivity, CO2 exchange and carbon drawdown. Marine proxies indicative of proximity of the ice-marginal zone are therefore essential to understand these processes. Amphimelissa setosa is nowadays a dominant radiolarian species in the Arctic basin and very abundant in the high-latitude North Atlantic. This species, now absent from the North Pacific, has been widely used as a qualitative proxy of modern and past environmental conditions in the high-latitude Northern Hemisphere. Using our new and published data on the distribution of A. setosa in plankton, sediment trap, surface sediment and downcore samples, we provide a quantitative ecological context for the occurrence of this species. We find that the optimal depth and season of A. setosa in the modern North Atlantic and the Chukchi Sea are 160 m and the late boreal summer/early fall (August–October), respectively. A regression model combining environmental variables (temperature, salinity, silicate and chlorophyll-a concentrations, apparent oxygen utilization, sea-ice) at that season and depth, are able to explain 43% of the distribution of this species in surface sediments. Based on these new findings, we conclude that the presence of A. setosa in surface sediments is closely related to high primary production in the proximity of the sea-ice and areas of ice rafting. The onset of this species started at ca. 1.5 Ma in the North Pacific, linked to a gradual cooling, increased silica availability and southward advance of the ice-margins since the Early Pleistocene. Amphimelissa setosa’s decline in this region was likely caused by the development of a quasi-permanent halocline, perennial sea-ice and depletion of silica during marine isotope stage 4. In the high-latitude North Atlantic, the relative abundance of A. setosa appears to be related to cooling and supply of dissolved silica from the continent during ice-rafting events. The comprehensive approach taken in this study suggest that A. setosa is a useful proxy to explore past variations in the ice-cover in the high-latitude Northern Hemisphere.

Climate-driven benthic invertebrate activity and biogeochemical functioning across the Barents Sea polar front.

Arctic marine ecosystems are undergoing rapid correction in response to multiple expressions of climate change, but the consequences of altered biodiversity for the sequestration, transformation and storage of nutrients are poorly constrained. Here, we determine the bioturbation activity of sediment-dwelling invertebrate communities over two consecutive summers that contrasted in sea-ice extent along a transect intersecting the polar front. We find a clear separation in community composition at the polar front that marks a transition in the type and amount of bioturbation activity, and associated nutrient concentrations, sufficient to distinguish a southern high from a northern low. While patterns in community structure reflect proximity to arctic versus boreal conditions, our observations strongly suggest that faunal activity is moderated by seasonal variations in sea ice extent that influence food supply to the benthos. Our observations help visualize how a climate-driven reorganization of the Barents Sea benthic ecosystem may be expressed, and emphasize the rapidity with which an entire region could experience a functional transformation. As strong benthic-pelagic coupling is typical across most parts of the Arctic shelf, the response of these ecosystems to a changing climate will have important ramifications for ecosystem functioning and the trophic structure of the entire food web. This article is part of the theme issue 'The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

Marine20—The Marine Radiocarbon Age Calibration Curve (0–55,000 cal BP)

ABSTRACTThe concentration of radiocarbon (14C) differs between ocean and atmosphere. Radiocarbon determinations from samples which obtained their14C in the marine environment therefore need a marine-specific calibration curve and cannot be calibrated directly against the atmospheric-based IntCal20 curve. This paper presents Marine20, an update to the internationally agreed marine radiocarbon age calibration curve that provides a non-polar global-average marine record of radiocarbon from 0–55 cal kBP and serves as a baseline for regional oceanic variation. Marine20 is intended for calibration of marine radiocarbon samples from non-polar regions; it is not suitable for calibration in polar regions where variability in sea ice extent, ocean upwelling and air-sea gas exchange may have caused larger changes to concentrations of marine radiocarbon. The Marine20 curve is based upon 500 simulations with an ocean/atmosphere/biosphere box-model of the global carbon cycle that has been forced by posterior realizations of our Northern Hemispheric atmospheric IntCal2014C curve and reconstructed changes in CO2obtained from ice core data. These forcings enable us to incorporate carbon cycle dynamics and temporal changes in the atmospheric14C level. The box-model simulations of the global-average marine radiocarbon reservoir age are similar to those of a more complex three-dimensional ocean general circulation model. However, simplicity and speed of the box model allow us to use a Monte Carlo approach to rigorously propagate the uncertainty in both the historic concentration of atmospheric14C and other key parameters of the carbon cycle through to our final Marine20 calibration curve. This robust propagation of uncertainty is fundamental to providing reliable precision for the radiocarbon age calibration of marine based samples. We make a first step towards deconvolving the contributions of different processes to the total uncertainty; discuss the main differences of Marine20 from the previous age calibration curve Marine13; and identify the limitations of our approach together with key areas for further work. The updated values forΔR, the regional marine radiocarbon reservoir age corrections required to calibrate against Marine20, can be found at the data basehttp://calib.org/marine/.