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      Seasonal energy exchange in sea ice retreat regions contributes to differences in projected Arctic warming

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      1 , 2 ,
      Nature Communications
      Nature Publishing Group UK

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          Abstract

          Rapid and, in many cases, unprecedented Arctic climate changes are having far-reaching impacts on natural and human systems. Despite state-of-the-art climate models capturing the rapid nature of Arctic climate change, termed Arctic amplification, they significantly disagree on its magnitude. Using a regional, process-oriented surface energy budget analysis, we argue that differences in seasonal energy exchanges in sea ice retreat regions via increased absorption and storage of sunlight in summer and increased upward surface turbulent fluxes in fall/winter contribute to the inter-model spread. Models able to more widely disperse energy drawn from the surface in sea ice retreat regions warm more, suggesting that differences in the local Arctic atmospheric circulation response contribute to the inter-model spread. We find that the principle mechanisms driving the inter-model spread in Arctic amplification operate locally on regional scales, requiring an improved understanding of atmosphere-ocean-sea ice interactions in sea ice retreat regions to reduce the spread.

          Abstract

          State-of-the-art climate models disagree on the magnitude of Arctic climate change. Here the authors show that the principle processes driving the disagreement operate locally in sea ice retreat regions, necessitating comprehensive observations to improve our understanding of atmosphere-ocean-sea ice energy exchanges.

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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 Arctic’s rapidly shrinking sea ice cover: a research synthesis

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              Polar amplification of climate change in coupled models

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                Author and article information

                Contributors
                patrick.c.taylor@nasa.gov
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                27 November 2018
                27 November 2018
                2018
                : 9
                : 5017
                Affiliations
                [1 ]ISNI 0000 0004 0453 291X, GRID grid.427409.c, Science Systems Applications Inc, ; Hampton, VA 23666 USA
                [2 ]NASA Langley Research Center, Climate Science Branch, Hampton, VA 23681-2199 USA
                Article
                7061
                10.1038/s41467-018-07061-9
                6258731
                30479330
                a4ca8abf-64ee-4f9f-b998-b85315296d2d
                © The Author(s) 2018

                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/.

                History
                : 10 September 2017
                : 9 October 2018
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