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      Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments

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          Abstract

          Ongoing climate change is causing fundamental changes in the Arctic, some of which can be hazardous to nature and human activity. In the context of Earth surface systems, warming climate may lead to rising ground temperatures and thaw of permafrost. This Data Descriptor presents circumpolar permafrost maps and geohazard indices depicting zones of varying potential for development of hazards related to near-surface permafrost degradation, such as ground subsidence. Statistical models were used to predict ground temperature and the thickness of the seasonally thawed (active) layer using geospatial data on environmental conditions at 30 arc-second resolution. These predictions, together with data on factors (ground ice content, soil grain size and slope gradient) affecting permafrost stability, were used to formulate geohazard indices. Using climate-forcing scenarios (Representative Concentration Pathways 2.6, 4.5 and 8.5), permafrost extent and hazard potential were projected for the 2041–2060 and 2061–2080 time periods. The resulting data (seven permafrost and 24 geohazard maps) are relevant to near-future infrastructure risk assessments and for targeting localized geohazard analyses.

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          Most cited references71

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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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            A scaling method for priorities in hierarchical structures

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              Decision making with the analytic hierarchy process

                Author and article information

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                12 March 2019
                2019
                : 6
                : 190037
                Affiliations
                [1 ]Geography Research Unit, University of Oulu , Oulu, Finland
                [2 ]Department of Geosciences and Geography, University of Helsinki , Helsinki, Finland
                [3 ]Finnish Meteorological Institute , Helsinki, Finland
                [4 ]Department of Geosciences, University of Oslo , Oslo, Norway
                [5 ]Geophysical Institute, University of Alaska Fairbanks , Fairbanks, Alaska, USA
                [6 ]Department of Cryosophy, Tyumen State University , Tyumen, Russia
                [7 ]Department of Geography, Environment, and Spatial Sciences, Michigan State University , East Lansing, Michigan, USA
                [8 ]Department of Earth, Environmental, and Geographical Sciences, Northern Michigan University , Marquette, Michigan, USA
                Author notes
                []

                J.H. and M.L. developed the original idea. O.K. led the data compilation and hazard index formulation in communication with J.H., M.L. and J.A., and wrote the first draft of the manuscript. J.A. led the statistical modelling. All authors contributed to the final study design and commented on the manuscript.

                Author information
                http://orcid.org/0000-0003-2429-4595
                http://orcid.org/0000-0001-6819-4911
                http://orcid.org/0000-0001-6203-5143
                http://orcid.org/0000-0001-5156-3653
                Article
                sdata201937
                10.1038/sdata.2019.37
                6413688
                30860499
                fc21c8fe-0647-4bc7-b985-c05676fdce92
                Copyright © 2019, The Author(s)

                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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.

                History
                : 14 March 2018
                : 25 January 2019
                Categories
                Data Descriptor

                cryospheric science,climate and earth system modelling,natural hazards

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