Turbulent exchange of heat and moisture plays an important role in snow cover dynamics in mountain regions and governs boundary layer dynamics. Having an accurate representation of turbulent fluxes is essential for predicting the snow hydrological cycle, avalanche hazards, and climate in cold regions. Although these processes are subject to great spatial and temporal variability, especially in complex terrain, measurements of heat, moisture, and momentum fluxes are almost exclusively point observations. To quantify the spatial variability, and assess the representativeness of the observations, numerical modeling of the atmosphere and surface is a useful tool. Nevertheless, there is considerable uncertainty regarding the accuracy of surface models in capturing turbulent fluxes, particularly in complex terrain with large spatial variability on small scales. These uncertainties can be attributed in part to (1) the use of parametrization schemes used in such models such as the Monin-Obukhov similarity theory, which has limitations in complex terrain because the assumptions of stationarity and spatial homogeneity are usually not fulfilled and (2) the errors in representing wind speeds and near-surface atmospheric gradients in the model simulations. In this study, we analyze the spatial and temporal variability of the energy exchange over snow during different meteorological events in mountain regions and the sources of errors in representing them. To verify common modelling approaches with observations, we performed model predictions of turbulent fluxes from the novel state-of-the-art model CRYOWRF in the region of Davos, Switzerland. CRYOWRF is developed by the Snow and Avalanche Research Centre SLF and is the atmospheric model WRF coupled to the surface model SNOWPACK. The turbulent fluxes at different model resolutions are compared to turbulent fluxes measured using high frequency measurements of wind, temperature, and moisture by the eddy covariance method and calculated with low frequency measurements using the Monin-Obukhov similarity theory. This model comparison and spatial analysis is carried out for three different meteorological events that are representative of the local climate of Davos, particularly föhn events.
The results from the model indicate that the fluxes vary strongly temporally and spatially. Depending on the weather pattern, elevation plays a large role in the variability of the turbulent fluxes which results in an elevation dependent correlation of turbulent fluxes with wind speed. This shows that locally measured turbulent heat fluxes are not representative of the whole mountain area. This has implications for the calculation of snow melt, sublimation, and accumulation across mountainous terrain and indicates that the spatial variability is important to account for. The resolution within the model also significantly influences the representation of turbulent fluxes, as coarser (1 km) resolutions greatly overestimate wind speeds compared to higher resolutions (200 m). This is due to fewer topography-wind interactions when topography is not accurately represented in the model, leading to an overestimation of turbulent fluxes.
Quiz question
Which topographical feature influences the spatial variability of turbulent fluxes in the model most?
Correct answer: Elevation
False Answer 1: Slope aspect
False Answer 2: Slope angle
Quiz question
Which topographical feature influences the spatial variability of turbulent fluxes in the model most?
Slope angle
Elevation
Slope aspect