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      Arctic amplification is caused by sea-ice loss under increasing CO 2

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      Nature Communications
      Nature Publishing Group UK

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          Abstract

          Warming in the Arctic has been much faster than the rest of the world in both observations and model simulations, a phenomenon known as the Arctic amplification (AA) whose cause is still under debate. By analyzing data and model simulations, here we show that large AA occurs only from October to April and only over areas with significant sea-ice loss. AA largely disappears when Arctic sea ice is fixed or melts away. Periods with larger AA are associated with larger sea-ice loss, and models with bigger sea-ice loss produce larger AA. Increased outgoing longwave radiation and heat fluxes from the newly opened waters cause AA, whereas all other processes can only indirectly contribute to AA by melting sea-ice. We conclude that sea-ice loss is necessary for the existence of large AA and that models need to simulate Arctic sea ice realistically in order to correctly simulate Arctic warming under increasing CO 2.

          Abstract

          The cause of Arctic amplification is still heavily debated. Here the authors present climate change simulations to show that sea-ice loss is essential for the existence of Arctic amplification.

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            The ERA-Interim reanalysis: configuration and performance of the data assimilation system

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                Author and article information

                Contributors
                adai@albany.edu
                ldh@mail.iap.ac.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                10 January 2019
                10 January 2019
                2019
                : 10
                : 121
                Affiliations
                [1 ]ISNI 0000 0001 2151 7947, GRID grid.265850.c, Department of Atmospheric & Environmental Sciences, , University at Albany, SUNY, ; Albany, NY 12222 USA
                [2 ]ISNI 0000000119573309, GRID grid.9227.e, CAS RCE-TEA, Institute of Atmospheric Physics, , Chinese Academy of Sciences, ; Beijing, 100029 China
                [3 ]ISNI 0000000119573309, GRID grid.9227.e, LASG, Institute of Atmospheric Physics, , Chinese Academy of Sciences, ; Beijing, 100029 China
                Author information
                http://orcid.org/0000-0002-5371-917X
                Article
                7954
                10.1038/s41467-018-07954-9
                6328634
                30631051
                da5f1bbb-a92e-484d-a676-a24b1a0348f8
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 15 February 2017
                : 28 November 2018
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