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      Climate controls on snow reliability in French Alps ski resorts

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          Abstract

          Ski tourism is a major sector of mountain regions economy, which is under the threat of long-term climate change. Snow management, and in particular grooming and artificial snowmaking, has become a routine component of ski resort operations, holding potential for counteracting the detrimental effect of natural snow decline. However, conventional snowmaking can only operate under specific meteorological conditions. Whether snowmaking is a relevant adaptation measure under future climate change is a widely debated issue in mountainous regions, with major implications on the supply side of this tourism industry. This often lacks comprehensive scientific studies for informing public and private decisions in this sector. Here we show how climate change influences the operating conditions of one of the main ski tourism markets worldwide, the French Alps. Our study addresses snow reliability in 129 ski resorts in the French Alps in the 21st century, using a dedicated snowpack model explicitly accounting for grooming and snowmaking driven by a large ensemble of adjusted and downscaled regional climate projections, and using a geospatial model of ski resorts organization. A 45% snowmaking fractional coverage, representative of the infrastructures in the early 2020s, is projected to improve snow reliability over grooming-only snow conditions, both during the reference period 1986–2005 and below 2 °C global warming since pre-industrial. Beyond 3 °C of global warming, with 45% snowmaking coverage, snow conditions would become frequently unreliable and induce higher water requirements.

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          EURO-CORDEX: new high-resolution climate change projections for European impact research

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            Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble

            EURO-CORDEX is an international climate downscaling initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble is presented. The study documents the performance of the individual models in representing the basic spatiotemporal patterns of the European climate for the period 1989–2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS data set as observational reference. The ensemble consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight subdomains of the European continent. Results are compared to those for the ERA40-driven ENSEMBLES simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies nonnegligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 °C, while precipitation biases are typically located in the ±40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and southeastern Europe reflect common model biases. For seasonal mean quantities averaged over large European subdomains, no clear benefit of an increased spatial resolution (12 vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX ensemble mostly correspond to those of the ENSEMBLES simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments.
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              The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2

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                Author and article information

                Contributors
                samuel.morin@meteo.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 May 2019
                29 May 2019
                2019
                : 9
                : 8043
                Affiliations
                [1 ]Univ. Grenoble Alpes, Irstea, UR LESSEM, 38000 Grenoble, France
                [2 ]ISNI 0000 0001 2112 9282, GRID grid.4444.0, Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Études de la Neige, ; 38000 Grenoble, France
                [3 ]ISNI 0000 0004 0387 1602, GRID grid.10097.3f, Barcelona Supercomputing Center, ; Barcelona, Spain
                [4 ]ISNI 0000 0001 2353 1689, GRID grid.11417.32, CNRM, Université de Toulouse, Météo-France, CNRS, ; 31000 Toulouse, France
                [5 ]Univ. Grenoble Alpes, Irstea, UR ETNA, 38000 Grenoble, France
                Author information
                http://orcid.org/0000-0003-0603-0780
                http://orcid.org/0000-0002-1880-8820
                http://orcid.org/0000-0002-1781-687X
                Article
                44068
                10.1038/s41598-019-44068-8
                6541717
                31142772
                ad2642bc-7fa7-4ded-a503-14e3274fec00
                © 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
                : 22 March 2019
                : 8 May 2019
                Funding
                Funded by: Ministère de la Transition Ecologique et Solidaire, programme GICC (ADAMONT).
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                climate change,cryospheric science
                Uncategorized
                climate change, cryospheric science

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