22 research outputs found

    Rapid sea ice changes in the future Barents Sea

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    Observed and future winter Arctic sea ice loss is strongest in the Barents Sea. However, the anthropogenic signal of the sea ice decline is superimposed by pronounced internal variability that represents a large source of uncertainty in future climate projections. A notable manifestation of internal variability is rapid ice change events (RICEs) that greatly exceed the anthropogenic trend. These RICEs are associated with large displacements of the sea ice edge which could potentially have both local and remote impacts on the climate system. In this study we present the first investigation of the frequency and drivers of RICEs in the future Barents Sea, using multi-member ensemble simulations from CMIP5 and CMIP6. A majority of RICEs are triggered by trends in ocean heat transport or surface heat fluxes. Ice loss events are associated with increasing trends in ocean heat transport and decreasing trends in surface heat loss. RICEs are a common feature of the future Barents Sea until the region becomes close to ice-free. As their evolution over time is closely tied to the average sea ice conditions, rapid ice changes in the Barents Sea may serve as a precursor for future changes in adjacent seas.publishedVersio

    The Seasonal and Regional Transition to an Ice-Free Arctic

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    The Arctic sea ice cover is currently retreating and will continue its retreat in a warming world. However, the loss of sea ice is neither regionally nor seasonally uniform. Here, we present the first regional and seasonal assessment of future Arctic sea ice loss in CMIP6 models under low (SSP126) and high (SSP585) emission scenarios, thus spanning the range of future change. We find that Arctic sea ice loss—at present predominantly limited to the summer season—will under SSP585 take place in all regions and all months. The summer sea ice is lost in all the shelf seas regardless of emission scenario, whereas ice-free conditions in winter before the end of this century only occur in the Barents Sea. The seasonal transition to ice-free conditions is found to spread through the Atlantic and Pacific regions, with change starting in the Barents Sea and Chukchi Sea, respectively.publishedVersio

    Mechanisms of regional winter sea-ice variability in a warming arctic

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    The Arctic winter sea ice cover is in retreat overlaid by large internal variability. Changes to sea ice are driven by exchange of heat, momentum, and freshwater within and between the ocean and the atmosphere. Using a combination of observations and output from the Community Earth System Model Large Ensemble, we analyze and contrast present and future drivers of the regional winter sea ice cover. Consistent with observations and previous studies, we find that for the recent decades ocean heat transport though the Barents Sea and Bering Strait is a major source of sea ice variability in the Atlantic and Pacific sectors of the Arctic, respectively. Future projections show a gradually expanding footprint of Pacific and Atlantic inflows highlighting the importance of future Atlantification and Pacification of the Arctic Ocean. While the dominant hemispheric modes of winter atmospheric circulation are only weakly connected to the sea ice, we find distinct local atmospheric circulation patterns associated with present and future regional sea ice variability in the Atlantic and Pacific sectors, consistent with heat and moisture transport from lower latitudes. Even if the total freshwater input from rivers is projected to increase substantially, its influence on simulated sea ice is small in the context of internal variability.publishedVersio

    Antarctic Sea Ice Area in CMIP6

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    Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios

    Framework and baseline examination of the German National Cohort (NAKO)

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    The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5

    Arctic Sea Ice in CMIP6

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    Mechanisms of regional winter sea-ice variability in a warming arctic

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    The Arctic winter sea ice cover is in retreat overlaid by large internal variability. Changes to sea ice are driven by exchange of heat, momentum, and freshwater within and between the ocean and the atmosphere. Using a combination of observations and output from the Community Earth System Model Large Ensemble, we analyze and contrast present and future drivers of the regional winter sea ice cover. Consistent with observations and previous studies, we find that for the recent decades ocean heat transport though the Barents Sea and Bering Strait is a major source of sea ice variability in the Atlantic and Pacific sectors of the Arctic, respectively. Future projections show a gradually expanding footprint of Pacific and Atlantic inflows highlighting the importance of future Atlantification and Pacification of the Arctic Ocean. While the dominant hemispheric modes of winter atmospheric circulation are only weakly connected to the sea ice, we find distinct local atmospheric circulation patterns associated with present and future regional sea ice variability in the Atlantic and Pacific sectors, consistent with heat and moisture transport from lower latitudes. Even if the total freshwater input from rivers is projected to increase substantially, its influence on simulated sea ice is small in the context of internal variability

    The Seasonal and Regional Transition to an Ice-Free Arctic

    No full text
    The Arctic sea ice cover is currently retreating and will continue its retreat in a warming world. However, the loss of sea ice is neither regionally nor seasonally uniform. Here, we present the first regional and seasonal assessment of future Arctic sea ice loss in CMIP6 models under low (SSP126) and high (SSP585) emission scenarios, thus spanning the range of future change. We find that Arctic sea ice loss—at present predominantly limited to the summer season—will under SSP585 take place in all regions and all months. The summer sea ice is lost in all the shelf seas regardless of emission scenario, whereas ice-free conditions in winter before the end of this century only occur in the Barents Sea. The seasonal transition to ice-free conditions is found to spread through the Atlantic and Pacific regions, with change starting in the Barents Sea and Chukchi Sea, respectively

    Rise and fall of sea ice production in the Arctic Ocean’s ice factories

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    The volume, extent and age of Arctic sea ice is in decline, yet winter sea ice production appears to have been increasing, despite Arctic warming being most intense during winter. Previous work suggests that further warming will at some point lead to a decline in ice production, however a consistent explanation of both rise and fall is hitherto missing. Here, we investigate these driving factors through a simple linear model for ice production. We focus on the Kara and Laptev seas-sometimes referred to as Arctic “ice factories” for their outsized role in ice production, and train the model on internal variability across the Community Earth System Model’s Large Ensemble (CESM-LE). The linear model is highly skilful at explaining internal variability and can also explain the forced rise-then-fall of ice production, providing insight into the competing drivers of change. We apply our linear model to the same climate variables from observation-based data; the resulting estimate of ice production over recent decades suggests that, just as in CESM-LE, we are currently passing the peak of ice production in the Kara and Laptev seas.publishedVersio

    Forced and internal components of observed Arctic sea-ice changes

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    The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea-ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea-ice variability and trends, and they thus help to disentangle the role of forced and internal sea-ice changes over the satellite record. In particular, we identify a mode of decadal ocean–atmosphere–sea-ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30 % of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012 but accounts for at most 10 % of the decline since 1979. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea-ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments.ISSN:1994-0416ISSN:1994-042
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