Abstract
Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.
Highlights
In the European Alps, numerous rockfall events were observed in permafrost rock faces during the last decades (e.g. Fischer et al, 2012; Gruber et al, 2004b; Phillips et al, 2016b; Ravanel et al, 2010, 2013)
Note that mean annual near-surface rock temperature (MANSRT), r2, mean absolute error (MAE) and mean bias error (MBE) are always given for the study years 2012–2013/2013–2014, separated by a slash (e.g. MANSRT for 2012–2013/MANSRT for 2013–2014)
The potential to model the strongly heterogeneous snow cover and its influence on the rock thermal regime on two rugged, steep mountain rock walls has been studied at the Gemsstock ridge over a 2-year period
Summary
In the European Alps, numerous rockfall events were observed in permafrost rock faces during the last decades (e.g. Fischer et al, 2012; Gruber et al, 2004b; Phillips et al, 2016b; Ravanel et al, 2010, 2013). Measuring rock wall temperatures (e.g. Gruber et al, 2004a; Haberkorn et al, 2015a; Hasler et al, 2011; Magnin et al, 2015; PERMOS, 2013) and in a further step modelling the spatial permafrost distribution in steep rock walls is of great importance. Numerical model studies simulating rock temperatures of idealized rock walls have been carried out e.g. by Gruber et al (2004a), Noetzli and Gruber (2009) and Noetzli et Published by Copernicus Publications on behalf of the European Geosciences Union. Blöschl and Kirnbauer, 1992; Gruber Schmid and Sardemann, 2003; Winstral et al, 2002) They suggested that air temperature and solar radiation are sufficient to model rock surface temperatures in near-vertical, compact, homogeneous rock walls. The spatially variable snow cover is one of these driving factors
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