In this paper, we study centennial trends of climate and snow cover within the Ossola valley, in the Western Italian Alps. We pursue different tests (Mann Kendall MK, bulk, and sequential/progressive MKprog, Linear Regression, also with change point detection, and moving window average MW) on two datasets, namely (i) dataset1, daily temperature, precipitation, snow depth for 9 stations in the area, during 1930-2018, and (ii) dataset2, snow depth and density, measured twice a month (from February 1(st) to June 1(st)) for 47 stations during 2007-2023. We also verify correlation with glacier retreat nearby. In dataset1, we highlight a positive trend for minimum temperature with MK, and Linear Regression. Using MKprog/MW, a negative change of snow cover depth, and duration starting from the late 1980s is found. In dataset2, despite the annual variability in snow cover and 2022-2023 winter drought, we assess the maximum snow water equivalent (SWE) to be delayed with respect to maximum snow depth at high altitude (over a month above 2.700 m a.s.l.), highlighting the effect of settling in decreasing snow depth during spring. We also present a formula linking through Linear Regression the Day of the Year of SWE peak to altitude, relevant to assess the onset of thaw season. Due to the high altitude of the stations, and the paradigmatic nature of the Ossola Valley, hosting Toce River, a main contributor to the Lake Maggiore of Italy, our results are of interest, and can be used as a benchmark for the Italian Alps.

Centenary (1930-2023) climate, and snow cover changes in the Western Alps of Italy. The Ossola valley

Dresti, C;Bocchiola, D
2023-01-01

Abstract

In this paper, we study centennial trends of climate and snow cover within the Ossola valley, in the Western Italian Alps. We pursue different tests (Mann Kendall MK, bulk, and sequential/progressive MKprog, Linear Regression, also with change point detection, and moving window average MW) on two datasets, namely (i) dataset1, daily temperature, precipitation, snow depth for 9 stations in the area, during 1930-2018, and (ii) dataset2, snow depth and density, measured twice a month (from February 1(st) to June 1(st)) for 47 stations during 2007-2023. We also verify correlation with glacier retreat nearby. In dataset1, we highlight a positive trend for minimum temperature with MK, and Linear Regression. Using MKprog/MW, a negative change of snow cover depth, and duration starting from the late 1980s is found. In dataset2, despite the annual variability in snow cover and 2022-2023 winter drought, we assess the maximum snow water equivalent (SWE) to be delayed with respect to maximum snow depth at high altitude (over a month above 2.700 m a.s.l.), highlighting the effect of settling in decreasing snow depth during spring. We also present a formula linking through Linear Regression the Day of the Year of SWE peak to altitude, relevant to assess the onset of thaw season. Due to the high altitude of the stations, and the paradigmatic nature of the Ossola Valley, hosting Toce River, a main contributor to the Lake Maggiore of Italy, our results are of interest, and can be used as a benchmark for the Italian Alps.
2023
Snow cover
Italian Alps
Snow density
Snow water equivalent
Climate time series
Climate change
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1256330
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