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      Frequency of extreme precipitation increases extensively with event rareness under global warming

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          Abstract

          The intensity of the heaviest extreme precipitation events is known to increase with global warming. How often such events occur in a warmer world is however less well established, and the combined effect of changes in frequency and intensity on the total amount of rain falling as extreme precipitation is much less explored, in spite of potentially large societal impacts. Here, we employ observations and climate model simulations to document strong increases in the frequencies of extreme precipitation events occurring on decadal timescales. Based on observations we find that the total precipitation from these intense events almost doubles per degree of warming, mainly due to changes in frequency, while the intensity changes are relatively weak, in accordance to previous studies. This shift towards stronger total precipitation from extreme events is seen in observations and climate models, and increases with the strength – and hence the rareness – of the event. Based on these results, we project that if historical trends continue, the most intense precipitation events observed today are likely to almost double in occurrence for each degree of further global warming. Changes to extreme precipitation of this magnitude are dramatically stronger than the more widely communicated changes to global mean precipitation.

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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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            Constraints on future changes in climate and the hydrologic cycle.

            What can we say about changes in the hydrologic cycle on 50-year timescales when we cannot predict rainfall next week? Eventually, perhaps, a great deal: the overall climate response to increasing atmospheric concentrations of greenhouse gases may prove much simpler and more predictable than the chaos of short-term weather. Quantifying the diversity of possible responses is essential for any objective, probability-based climate forecast, and this task will require a new generation of climate modelling experiments, systematically exploring the range of model behaviour that is consistent with observations. It will be substantially harder to quantify the range of possible changes in the hydrologic cycle than in global-mean temperature, both because the observations are less complete and because the physical constraints are weaker.
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              The representative concentration pathways: an overview

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                Author and article information

                Contributors
                gunnar.myhre@cicero.oslo.no
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 November 2019
                5 November 2019
                2019
                : 9
                : 16063
                Affiliations
                [1 ]CICERO Center for International Climate Research – Oslo, 0318 Oslo, Norway
                [2 ]ISNI 0000 0001 2156 2780, GRID grid.5801.c, Institute for Atmospheric and Climate Science, ETH Zurich, ; 8092 Zurich, Switzerland
                [3 ]ISNI 0000 0001 0226 1499, GRID grid.82418.37, Norwegian Meteorological Institute, ; 0313 Oslo, Norway
                [4 ]NILU – Norwegian Institute for Air Research, Kjeller, Norway
                Author information
                http://orcid.org/0000-0002-4309-476X
                http://orcid.org/0000-0003-4650-1102
                http://orcid.org/0000-0003-3608-9468
                http://orcid.org/0000-0001-5233-8992
                http://orcid.org/0000-0003-4925-0046
                http://orcid.org/0000-0001-8013-1833
                http://orcid.org/0000-0002-0219-5345
                http://orcid.org/0000-0003-0074-3421
                http://orcid.org/0000-0003-1931-6737
                http://orcid.org/0000-0003-4493-4158
                http://orcid.org/0000-0002-2524-5755
                Article
                52277
                10.1038/s41598-019-52277-4
                6831572
                31690736
                ae5a732f-9d34-4494-aaa1-ea41dc8592f7
                © 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/.

                History
                : 2 July 2019
                : 15 October 2019
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                climate sciences,environmental social sciences
                Uncategorized
                climate sciences, environmental social sciences

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