Abstract
Abstract. The surface temperature controls the temporal evolution of the snowpack, playing a key role in metamorphism and snowmelt. It shows large spatial variations in mountainous areas because the surface energy budget is affected by the topography, for instance because of the modulation of the short-wave irradiance by the local slope and the shadows and the short-wave and long-wave re-illumination of the surface from surrounding slopes. These topographic effects are often neglected in large-scale models considering the surface to be flat and smooth. Here we aim at estimating the surface temperature of snow-covered mountainous terrain in clear-sky conditions in order to evaluate the relative importance of the different processes that control the spatial variations. For this, a modelling chain is implemented to compute the surface temperature in a kilometre-wide area from local radiometric and meteorological measurements at a single station. The first component of this chain is the Rough Surface Ray-Tracing (RSRT) model. Based on a photon transport Monte Carlo algorithm, this model quantifies the incident and reflected short-wave radiation on every facet of the mesh describing the snow-covered terrain. The second component is a surface scheme that estimates the terms of the surface energy budget from which the surface temperature is eventually estimated. To assess the modelling chain performance, we use in situ measurements of surface temperature and satellite thermal observations (Landsat 8) in the Col du Lautaret area, in the French Alps. The results of the simulations show (i) an agreement between the simulated and measured surface temperature at the station for a diurnal cycle in winter within 0.2 ∘C; (ii) that the spatial variations in surface temperature are on the order of 5 to 10 ∘C in the domain and are well represented by the model; and (iii) that the topographic effects ranked by importance are the modulation of solar irradiance by the local slope, followed by the altitudinal variations in air temperature (lapse rate), the re-illumination by long-wave thermal emission from surrounding terrain, and the spectral dependence of snow albedo. The changes in the downward long-wave flux because of variations in altitude and the absorption enhancement due to multiple bounces of photons in steep terrain play a less significant role. These results show the necessity of considering the topography to correctly assess the energy budget and the surface temperature of snow-covered complex terrain.
Highlights
The snow cover is rarely flat and smooth on Earth
The spatially resolved LST observations from Landsat 8 are first assessed in the study area before the evaluation of the model simulations against the local measurements and the satellite observations
This is normally achieved by means of normalized difference vegetation index (NDVI)-based classifications (Li et al, 2013) that can be adapted to snow-covered complex terrains with methods that rely on the snow cover area (Varade and Dikshit, 2020)
Summary
Undulations exist over a very large range of scales, from the centimetre to the kilometre scale. At the centimetre and metre scales, ripples, snow dunes, and erosion features (sastrugi) formed by wind usually coexist (Filhol and Sturm, 2015). At the decametre to kilometre scale range, the snow surface topography is mostly determined by the underlying soil or ice topography (Revuelto et al, 2018). Because of all these undulations, the surface temperature can vary by several degrees Celsius across a study area, even without significant differences in the near-surface meteorological forcing (incident radiation, wind, air temperature, humidity). Terrain slope and orientation and the presence of facing neighbouring slopes
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