Observed snow depth trends in the European Alps: 1971 to 2019

Author:

Matiu MichaelORCID,Crespi AliceORCID,Bertoldi GiacomoORCID,Carmagnola Carlo Maria,Marty ChristophORCID,Morin SamuelORCID,Schöner Wolfgang,Cat Berro Daniele,Chiogna GabrieleORCID,De Gregorio LudovicaORCID,Kotlarski Sven,Majone BrunoORCID,Resch Gernot,Terzago Silvia,Valt MauroORCID,Beozzo Walter,Cianfarra PaolaORCID,Gouttevin IsabelleORCID,Marcolini Giorgia,Notarnicola ClaudiaORCID,Petitta MarcelloORCID,Scherrer Simon C.ORCID,Strasser UlrichORCID,Winkler MichaelORCID,Zebisch MarcORCID,Cicogna Andrea,Cremonini Roberto,Debernardi Andrea,Faletto Mattia,Gaddo Mauro,Giovannini LorenzoORCID,Mercalli Luca,Soubeyroux Jean-Michel,Sušnik Andrea,Trenti Alberto,Urbani Stefano,Weilguni Viktor

Abstract

Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

Funder

Horizon 2020 Framework Programme

Deutsche Forschungsgemeinschaft

Publisher

Copernicus GmbH

Subject

Earth-Surface Processes,Water Science and Technology

Reference69 articles.

1. Aschauer, J., Bavay, M., Begert, M., and Marty, C.: Comparing methods for gap filling in historical snow depth time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020–17211, https://doi.org/10.5194/egusphere-egu2020-17211, 2020.

2. Auer, I., Böhm, R., Jurković, A., Orlik, A., Potzmann, R., Schöner, W., Ungersböck, M., Brunetti, M., Nanni, T., Maugeri, M., Briffa, K., Jones, P., Efthymiadis, D., Mestre, O., Moisselin, J.-M., Begert, M., Brazdil, R., Bochnicek, O., Cegnar, T., Gajić-Čapka, M., Zaninović, K., Majstorović, Ž., Szalai, S., Szentimrey, T., and Mercalli, L.: A new instrumental precipitation dataset for the greater alpine region for the period 1800–2002, Int. J. Climatol., 25, 139–166, https://doi.org/10.1002/joc.1135, 2005.

3. Auer, I., Böhm, R., Jurkovic, A., Lipa, W., Orlik, A., Potzmann, R., Schöner, W., Ungersböck, M., Matulla, C., Briffa, K., Jones, P., Efthymiadis, D., Brunetti, M., Nanni, T., Maugeri, M., Mercalli, L., Mestre, O., Moisselin, J.-M., Begert, M., Müller-Westermeier, G., Kveton, V., Bochnicek, O., Stastny, P., Lapin, M., Szalai, S., Szentimrey, T., Cegnar, T., Dolinar, M., Gajic-Capka, M., Zaninovic, K., Majstorovic, Z., and Nieplova, E.: HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region, Int. J. Climatol., 27, 17–46, https://doi.org/10.1002/joc.1377, 2007.

4. Bach, A. F., Schrier, G. van der, Melsen, L. A., Tank, A. M. G. K., and Teuling, A. J.: Widespread and Accelerated Decrease of Observed Mean and Extreme Snow Depth Over Europe, Geophys. Res. Lett., 45, 12312–12319, https://doi.org/10.1029/2018GL079799, 2018.

5. Bazile, E., Abida, R., Verelle, A., Le Moigne, P., and Szczypta, C.: MESCAN-SURFEX surface analysis, deliverable D2.8 of the UERRA project, Technical Report, European Commission, available at: http://uerra.eu/publications/deliverable-reports.html (last access: 5 March 2021), 2017.

Cited by 87 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3