The European Alps are a major mountain range in Europe with a long history of dense in-situ observations of snow cover, whose analysis is hampered by the fragmentation of observer networks and the varying quality and availability of their data. Here we present a collation of in-situ observations of snow depth and depth of snowfall across the whole Alps. We employed novel quality checks and gap-filling procedures based on spatial correlation, which work in areas with a moderate to high density of stations. We show how the climatology of in-situ snow depth and remotely sensed snow cover duration matches the expected climatic forcing zones. These large-scale climatic zones not only influenced day-to-day variability but also long-term trends. A multivariate attribution study highlights the impact of temperature and precipitation variability on snowfall patterns in a smaller subregion. Finally, future snow cover information is derived from an ensemble of regional climate models.
Snow cover climatology and trends in the European Alps from in-situ observations, remote sensing, and regional climate models / Matiu, Michael; Crespi, Alice; Bertoldi, Giacomo; Maria Carmagnola, Carlo; Marty, Christoph; Morin, Samuel; Schöner, Wolfgang; Bozzoli, Michele; Majone, Bruno; Giovannini, Lorenzo; Zardi, Dino; Hanzer, Florian. - (2023). (Intervento presentato al convegno IUGG2023 tenutosi a Berlin, Germania nel 2023-07-11 - 2023-07-20) [10.57757/iugg23-1751].
Snow cover climatology and trends in the European Alps from in-situ observations, remote sensing, and regional climate models
Michael Matiu
;Michele Bozzoli;Bruno Majone;Lorenzo Giovannini;Dino Zardi;
2023-01-01
Abstract
The European Alps are a major mountain range in Europe with a long history of dense in-situ observations of snow cover, whose analysis is hampered by the fragmentation of observer networks and the varying quality and availability of their data. Here we present a collation of in-situ observations of snow depth and depth of snowfall across the whole Alps. We employed novel quality checks and gap-filling procedures based on spatial correlation, which work in areas with a moderate to high density of stations. We show how the climatology of in-situ snow depth and remotely sensed snow cover duration matches the expected climatic forcing zones. These large-scale climatic zones not only influenced day-to-day variability but also long-term trends. A multivariate attribution study highlights the impact of temperature and precipitation variability on snowfall patterns in a smaller subregion. Finally, future snow cover information is derived from an ensemble of regional climate models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione