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      Acceleration of western Arctic sea ice loss linked to the Pacific North American pattern

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          Abstract

          Recent rapid Arctic sea-ice reduction has been well documented in observations, reconstructions and model simulations. However, the rate of sea ice loss is highly variable in both time and space. The western Arctic has seen the fastest sea-ice decline, with substantial interannual and decadal variability, but the underlying mechanism remains unclear. Here we demonstrate, through both observations and model simulations, that the Pacific North American (PNA) pattern is an important driver of western Arctic sea-ice variability, accounting for more than 25% of the interannual variance. Our results suggest that the recent persistent positive PNA pattern has led to increased heat and moisture fluxes from local processes and from advection of North Pacific airmasses into the western Arctic. These changes have increased lower-tropospheric temperature, humidity and downwelling longwave radiation in the western Arctic, accelerating sea-ice decline. Our results indicate that the PNA pattern is important for projections of Arctic climate changes, and that greenhouse warming and the resultant persistent positive PNA trend is likely to increase Arctic sea-ice loss.

          Abstract

          The fastest sea-ice decline has been observed in the western Arctic, but the underlying mechanisms are still unclear. Here, the authors show that the Pacific North American pattern plays an important role in western Arctic sea-ice variability.

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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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              Classification, Seasonality and Persistence of Low-Frequency Atmospheric Circulation Patterns

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                Author and article information

                Contributors
                liuzf406@gmail.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 March 2021
                9 March 2021
                2021
                : 12
                : 1519
                Affiliations
                [1 ]GRID grid.24516.34, ISNI 0000000123704535, State Key Laboratory of Marine Geology, , Tongji University, ; Shanghai, China
                [2 ]GRID grid.462844.8, ISNI 0000 0001 2308 1657, Laboratoire de Météorologie Dynamique, IPSL, CNRS, , Sorbonne Université, ; Paris, France
                [3 ]GRID grid.462844.8, ISNI 0000 0001 2308 1657, Laboratoire d’Océanographie et du Climat (LOCEAN), IPSL, CNRS, IRD, , Sorbonne Université, ; Paris, France
                [4 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Department of Civil and Environmental Engineering, , National University of Singapore, ; Singapore, Singapore
                [5 ]GRID grid.214458.e, ISNI 0000000086837370, Department of Earth and Environmental Sciences, , University of Michigan, ; Ann Arbor, MI USA
                [6 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, , Sun Yat-sen University, ; Guangzhou, China
                [7 ]Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
                [8 ]GRID grid.9227.e, ISNI 0000000119573309, Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, , Chinese Academy of Sciences, ; Beijing, China
                [9 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, Department of Earth System Science, , Tsinghua University, ; Beijing, China
                [10 ]GRID grid.223827.e, ISNI 0000 0001 2193 0096, Department of Geology and Geophysics, , University of Utah, ; Salt Lake City, USA
                Author information
                http://orcid.org/0000-0002-2321-1543
                http://orcid.org/0000-0001-7038-6189
                http://orcid.org/0000-0001-5104-4271
                http://orcid.org/0000-0002-6287-8527
                http://orcid.org/0000-0002-0848-4973
                http://orcid.org/0000-0002-6928-3104
                Article
                21830
                10.1038/s41467-021-21830-z
                7943814
                33750823
                7c6329c3-9a39-4ff9-9de2-ad0398abbfec
                © The Author(s) 2021

                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
                : 18 March 2020
                : 9 February 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 41876039
                Award ID: 42025602
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                atmospheric science,ocean sciences
                Uncategorized
                atmospheric science, ocean sciences

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