In this study, the small-scale boundary layer dynamics and the energy balance over a fractional snow cover are numerically investigated. The atmospheric boundary layer flows over a patchy snow cover were calculated with an atmospheric model (Advanced Regional Prediction System) on a very high spatial resolution of 5 m. The numerical results revealed that the development of local flow patterns and the relative importance of boundary layer processes depend on the snow patch size distribution and the synoptic wind forcing. Energy balance calculations for quiescent wind situations demonstrated that well-developed katabatic winds exerted a major control on the energy balance over the patchy snow cover, leading to a maximum in the mean downward sensible heat flux over snow for high snow-cover fractions. This implies that if katabatic winds develop, total melt of snow patches may decrease for low snow-cover fractions despite an increasing ambient air temperature, which would not be predicted by most hydrological models. In contrast, stronger synoptic winds increased the effect of heat advection on the catchment’s melt behavior by enhancing the mean sensible heat flux over snow for lower snow-cover fractions. A sensitivity analysis to grid resolution suggested that the grid size is a critical factor for modeling the energy balance of a patchy snow cover. The comparison of simulation results from coarse (50 m) and fine (5 m) horizontal resolutions revealed a difference in the spatially averaged turbulent heat flux over snow of 40%–70% for synoptic cases and 95% for quiescent cases.

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Herein, a procedure permitting vertical nesting for one-way concurrent simulation is developed and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.

Abstract. 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 orographic 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.

Abstract. Snow distribution in complex alpine terrain and its evolution in the future climate is important in a variety of applications including hydro-power, avalanche forecasting and fresh water resources. However, the relative importance of processes such as cloud-dynamics and pure particle-flow interactions is still barely known and models are essential to investigate these processes. Here, we present very high resolution Weather Research and Forecasting model (WRF) simulations, which are initialized by 2.2 km resolution Consortium for Small-scale Modeling (COSMO) reanalysis (COSMO–WRF). To assess the ability of COSMO–WRF to represent spatial snow precipitation patterns, they are validated against operational weather radar measurements. Estimated WRF precipitation is generally higher than estimated radar precipitation, most likely due to an overestimation of orographic precipitation in the model. The high precipitation also leads to a higher spatial variability in the model at the scale of 10 km. Overall, an autocorrelation and scale analysis of radar and WRF precipitation patterns show that WRF captures the variability relative to the domain wide variability of precipitation patterns down to the scale of few kilometers, but misses quite substantial variability on the smallest scales of a few 100 meters. However, differences of precipitation between 2830 m above sea level and the ground indicate that near-surface processes are active in the model.

The dynamics that govern the evolution of nighttime flows in a deep valley, California's Owens Valley, are analyzed. Measurements from the Terrain-Induced Rotor Experiment (T-REX) reveal a pronounced valleywind system with often nonclassical flow evolution. Two cases with a weak high pressure ridge over the study area but very different valley flow evolution are presented. The first event is characterized by the appearance of a layer of southerly flow after midnight local time, sandwiched between a thermally driven low-level downvalley (northerly) flow and a synoptic northwesterly flow aloft. The second event is characterized by an unusually strong and deep downvalley jet, exceeding 15 m s 21 . The analysis is based on the T-REX measurement data and the output of high-resolution large-eddy simulations using the Advanced Regional Prediction System (ARPS). Using horizontal grid spacings of 1 km and 350 m, ARPS reproduces the observed flow features for these two cases very well. It is found that the low-level along-valley forcing of the valley wind is the result of a superposition of the local thermal forcing and a midlevel (2-2.5 km MSL) along-valley pressure forcing. The analysis shows that the large difference in valley flow evolution derives primarily from differences in the midlevel pressure forcing, and that the Owens Valley is particularly susceptible to these midlevel external influences because of its specific geometry. The results demonstrate the delicate interplay of forces that can combine to determine the valley flow structure on any given night.