Orographic effects on snow deposition patterns in mountainous terrain

Orographic lifting of air masses and other topographically modified flows induce cloud and precipitation formation at larger scales and preferential deposition of precipitation at smaller scales. In this study, we examine orographic effects on small-scale snowfall patterns in Alpine terrain. A polarimetric X-band radar was deployed in the area of Davos (Switzerland) to determine the spatial variability of precipitation. In order to relate measured precipitation fields to flow dynamics, we model flow fields with the atmospheric prediction model Advanced Regional Prediction System. Additionally, we compare radar reflectivity fields with snow accumulation at the surface as modeled by Alpine3D. We investigate the small-scale precipitation dynamics for one heavy snowfall event in March 2011 at a high resolution of 75 m. The analysis of the vertical and horizontal distribution of radar reflectivity at horizontal polarization and differential reflectivity shows polarimetric signatures of orographic snowfall enhancement near the summit region. Increasing radar reflectivity at horizontal polarization over the windward slopes toward the crest and downwind decreasing reflectivity over the leeward slopes is observed. The temporal variation of the location of maximum concentration of snow particles is partly attributed to the effect of preferential deposition of snowfall: For situations with strong horizontal winds, the concentration maximum is shifted from the ridge crest toward the leeward slopes. Qualitatively, we discuss the relative role of cloud microphysics such as the seeder-feeder mechanism versus atmospheric particle transport in generating the observed snow deposition at the ground. Key Points Orographic snowfall enhancement near the summit region Preferred snow deposition on leeward slopes Snow drift affects reflectivity patterns observed by radar

Identification of snow precipitation mechanisms and accumulation patterns over complex terrain with very high resolution radar data and terrestrial laser scans

Alexis Berne, Franziska Gerber, Jacopo Grazioli, Michael Lehning, Daniel Wolfensberger

Knowledge on changes in seasonal mountain snow water resources are essential e.g. for hydropower companies. Both, snow accumulation and ablation need to be investigated to make precise predictions of water stored in a seasonal snow cover. Only if the processes behind snow accumulation and ablation are understood with sufficient quantitative accuracy, the evolution of snow water resources under a changing climate can be addressed. It is known that different snow precipitation processes and snow redistribution are responsible for snow accumulation patterns in alpine terrain. In a small-scale analysis of radar data in the region of Davos, Mott et al. (2014) could identify different snow deposition patterns for homogeneous precipitation, seeder-feeder mechanism, preferential deposition and a combination of the seeder-feeder mechanism and preferential deposition. In addition to the snow precipitation mechanisms, snow redistribution due to snow-atmosphere interaction is essential to characterize snow accumulation patterns at small scales (Scipión et al., 2013). In this study we investigate small-scale patterns of precipitation for an extended area over the Dischma valley (Davos, CH) for the winter season 2014/2015. An X-band polarimetric radar was installed on a slope facing the Dischma valley and it conducted plane position indicator (PPI) scans at elevation angles of 7° and 10° (minimum distance to the ground is about 300m and 500m, respectively) and three range height indicator (RHI) scans along the Dischma valley and along the Landwasser valley (i.e. along Davos). These radar products are available with horizontal and vertical resolution of 75 meters and a high temporal resolution of 5 minutes. The specific spatial patterns revealed by the radar measurements allow to characterize the different types of winter precipitation as well as to identify cloud microphysical and dynamical processes that govern the precipitation distribution. The continuous radar measurements are also used to analyze the frequency of certain types of hydrometeors and precipitation genesis processes as well as snow precipitation patters, which are related to specific atmospheric situations. For a few snowfall events, we additionally analyze terrestrial laser scans (TLS) of steep rock faces with different orientations that were performed before and after the snow precipitation events. The results allow us to relate identified accumulation patterns to the identified precipitation patterns and confirm the importance of redistribution processes for accumulation in steep terrain.

2015

Investigation of snow melt dynamics and boundary layer processes over a melting snow surface

Sebastian Schlögl

In this thesis, we investigate the surface energy balance of a snow pack for a continuous and a patchy snow cover. Snow surface temperatures have been validated to assess the accuracy of the surface energy balance of a continuous snow pack for individual points. As the four radiation components contribute largest to the surface energy balance, accurate radiation measurements (typically only available for the shortwave radiation) are required for the model input. A model error (up to 5 K in snow surface temperatures) is introduced to the surface energy balance of a continuous snow pack by parametrizing the incoming longwave radiation, which is typically not measured. Turbulent heat fluxes are typically calculated in physics-based models with Monin-Obukhov bulk formulations and its parametrization contributes to model errors in the surface energy balance up to 2 K. The parametrization of the turbulent fluxes was found to be the largest error source in the case of measured incoming longwave radiation. Very stable atmospheric conditions over snow and a non-equilibrium boundary layer have a strong but very difficult to quantify influence on turbulent surface fluxes. Stability corrections were typically developed over non-snow surfaces and applied over snow in complex terrain, where several mandatory assumptions of the Monin-Obukhov bulk formulation are heavily violated. Therefore, our validation shows a much better model representation of the surface energy balance in idealized flat terrain in comparison with complex terrain. In this thesis, we develop new stability corrections over snow and assess the error of the Monin-Obukhov bulk formulation with 6 W m-2 and an additional error of 1-5 W m-2 due to state-of-the-art parametrizations of the stability correction. The energy balance of a snow pack significantly alters for heterogeneous land-surfaces in the late ablation period. Warm air from the bare ground can be efficiently transported over the snow patch and modifies the near-surface air temperature field. Terrestrial laser scanning measurements reveal that local snow ablation rates at the upwind edge of the snow patch are 25 % larger than further inside of the snow patch. The strong thermal contrast in surface temperatures in combination with calm wind conditions leads to the development of a stable internal boundary layer, which grows along the fetch and reduces turbulent mixing of warm air masses. Small-scale boundary layer dynamics are typically not resolved in hydrological models. Numerical simulations with the atmospheric model Advanced Regional Prediction System (ARPS) reveal a mean air temperature increase above the patchy snow cover of 2-5 K in comparison with a continuous snow cover, which could lead to an increase in daily mean snow ablation rates up to 30 %. Above-average snow ablation rates at the upwind edge of a snow patch could be resolved by the development of a temperature footprint approach. However, the effect of increasing near-surface mean air temperatures to snow ablation from lateral transport processes is small when considering an entire melting period. Uncertainties in measured precipitation, parametrized incoming longwave radiation and calculated turbulent fluxes with Monin-Obukhov bulk formulation lead to larger errors in modelled snow heights than neglecting lateral transport processes.

EPFL2018

Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain

Alexis Berne, Nikola Besic, Marco Gabella, Franziska Gerber, Michael Lehning, Varun Sharma

Snow distribution in complex alpine terrain and its evolution in the future climate is important in a variety of applications including hydropower, avalanche forecasting and freshwater resources. However, it is still challenging to quantitatively forecast precipitation, especially over complex terrain where the interaction between local wind and precipitation fields strongly affects snow distribution at the mountain ridge scale. Therefore, it is essential to retrieve high-resolution information about precipitation processes over complex terrain. Here, we present very-high-resolution Weather Research and Forecasting model (WRF) simulations (COSMO-WRF), which are initialized by 2.2 km resolution Consortium for Small-scale Modeling (COSMO) analysis. To assess the ability of COSMO-WRF to represent spatial snow precipitation patterns, they are validated against operational weather radar measurements. Estimated COSMO-WRF precipitation is generally higher than estimated radar precipitation, most likely due to an overestimation of oro-graphic precipitation enhancement in the model. The high precipitation amounts also lead to a higher spatial variability in the model compared to radar estimates. Overall, an autocorrelation and scale analysis of radar and COSMO-WRF precipitation patterns at a horizontal grid spacing of 450 m show that COSMO-WRF captures the spatial variability normalized by the domain-wide variability in precipitation patterns down to the scale of a few kilometers. However, simulated precipitation patterns systematically show a lower variability on the smallest scales of a few hundred meters compared to radar estimates. A comparison of spatial variability for different model resolutions gives evidence for an improved representation of local precipitation processes at a horizontal resolution of 50 m compared to 450 m. Additionally, differences of precipitation between 2830 m above sea level and the ground indicate that near-surface processes are active in the model.

2018