Evaluation of homogenization methods for seasonal snow depth data in the Austrian Alps, 1930–2010. (30th April 2019)

• Record Type: Journal Article
• Authors: Marcolini, Giorgia; Koch, Roland; Chimani, Barbara; Schöner, Wolfgang; Bellin, Alberto; Disse, Markus; Chiogna, Gabriele
• Is Part Of: International journal of climatology. Volume 39:Number 11(2019)
• Page Start: 4514
• Page End: 4530
• Publication Date: 2019-04-30
• Subjects: Alps -- Austria -- homogenization -- HOMOP -- INTERP -- PRODIGE -- SNHT -- snow; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.6095
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract : Despite the importance of snow in alpine regions, little attention has been given to the homogenization of snow depth time series. Snow depth time series are generally characterized by high spatial heterogeneity and low correlation among the time series, and the homogenization thereof is therefore challenging. In this work, we present a comparison between two homogenization methods for mean seasonal snow depth time series available for Austria: the standard normal homogeneity test (SNHT) and HOMOP. The results of the two methods are generally in good agreement for high elevation sites. For low elevation sites, HOMOP often identifies suspicious breakpoints (that cannot be confirmed by metadata and only occur in relation to seasons with particularly low mean snow depth), while the SNHT classifies the time series as homogeneous. We therefore suggest applying both methods to verify the reliability of the detected breakpoints. The number of computed anomalies is more sensitive to inhomogeneities than trend analysis performed with the Mann–Kendall test. Nevertheless, the homogenized dataset shows an increased number of stations with negative snow depth trends and characterized by consecutive negative anomalies starting from the late 1980s and early 1990s, which was in agreement with the observations available for several stations in the Alps. In summary, homogenization of snow depth data is possible, relevant and should be carried out prior to performing climatological analysis. Abstract : The homogenization of snow depth time series (in the figure for the station of Bad Gastein, Austria) is very important to perform reliable climatological analysis and investigate the sensitivity of snow to the ongoing increasing temperatures in the Alps. In this work, we compared the homogenization methods HOMOP and standard normal homogeneity test using Austrian mean seasonal snow depth time series. The results are quite encouraging since the two methodologies agree in most of the cases, showing a good reliability in detecting breakpoints in the snow depth time series.