Aiming at an alpine wide assessment of the temporal changes in the distribution of snow depth using quantile regression

Presentation held at ICAM 2019 in Riva del Garda:

Aiming at an alpine wide assessment of the temporal changes in the distribution of snow depth using quantile regression: Results from a case study in the southern alps

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Abstract

Snow plays a key role in the alpine ecosystem. Understanding and quantifying the changes in snow amounts in the past is a prerequisite to putting the simulated future changes in context. Our aim is to provide an alpine wide assessment of past changes in station observations of snow depth. To the best of our knowledge, no such assessment exists, because of difficulties in exchanging data across borders. Moreover, a meta-analysis of the existing national and regional studies is hampered by the various methodologies. Here, we present initial efforts and the proposed methodology for selected stations in South Tyrol (northern Italy). As a versatile method, quantile regression shall be used, which is a statistical tool that originates from econometrics and that allows to quantify the changes in the whole distribution of snow depth. In this way, asymmetric changes could be identified, such as different trends in extreme and average conditions. We would like to use the possibility of presenting this contribution to an expert audience, of which some might be interested in collaborating for a cross-national assessment of past snow changes. A unified alpine wide study would be able to put the past changes in snow depth not only in relation to altitude, but also to geography, for example by distinguishing between climatic zones (see e.g. the HISTALP project). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 795310.