Description: In mountainous regions, snow accumulation on the ground is crucial for mountain hydrology and water resources. The present study investigates the link between the spatial variability in snowfall and in snow accumulation in the Swiss Alps. A mobile polarimetric X-band radar deployed in the area of Davos (Switzerland) collected valuable and continuous information on small scale precipitation for the winter seasons of 2009/10 and 2010/11. Local measurements of snow accumulation were collected with Airborne Laser-Scanning (ALS) for the winters of 2007/08 and 2008/09. The spatial distribution of snow accumulation exhibits a strong inter-annual consistency that can be generalized over the winters in the area. This unique configuration makes the comparison of the variability in total snowfall amount estimated from radar and in snow accumulation possible over the diverse winter periods. As expected, the spatial variability, quantified by means of the variogram, is shown to be larger in snow accumulation than in snowfall. However, the variability of snowfall is also significant, especially over the mountain tops, leads to preferential deposition during snowfall and needs further investigation. The higher variability at the ground is mainly caused by snow transport.

Description: Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, thermal conductivity, permeability, gas diffusivity and optical properties. Inasmuch as possible, equations to parameterize these properties as functions of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth arediscussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.

Description: The widely-used detailed SNOWPACK model has undergone constant development over the years. A notable recent extension is the introduction of a Richards Equation (RE) solver as an alternative for the bucket-type approach for describing water transport in the snow and soil layers. In addition, continuous updates of snow settling and new snow density parametrisations have changed model behaviour. This study presents a detailed evaluation of model performance against a comprehensive multi-year data set from Weissfluhjoch near Davos, Switzerland. The data set is collected by automatic meteorological and snowpack measurements and manual snow profiles. During the main winter season, snow height (RMSE: 〈4.2 cm), snow water equivalent (SWE, RMSE: 〈40 mm w.e.), snow temperature distributions (typical deviation with measurements: 〈1.0 °C) and snow density (typical deviation with observations: 〈50 kg m−3) as well as their temporal evolution are well simulated in the model and the influence of the two water transport schemes is small. The RE approach reproduces internal differences over capillary barriers but fails to predict enough grain growth since the growth routines have been calibrated using the bucket scheme in the original SNOWPACK model. The agreement in both density and grain size is sufficient to parametrise the hydraulic properties. In the melt season, a more pronounced underestimation of typically 200 mm w.e. in SWE is found. The discrepancies between the simulations and the field data are generally larger than the differences between the two water transport schemes. Nevertheless, the detailed comparison of the internal snowpack structure shows that the timing of internal temperature and water dynamics is adequately and better represented with the new RE approach when compared to the conventional bucket scheme. On the contrary, the progress of the meltwater front in the snowpack as detected by radar and the temporal evolution of the vertical distribution of melt forms in manually observed snow profiles do not support this conclusion. This discrepancy suggests that the implementation of RE partly mimics preferential flow effects.

Description: Preferential deposition of snow precipitation, snow transport and snow sublimation modify the mass which gets incorporated into or removed from the seasonal or perennial snow cover. These processes happen at very small scales from snow grain size to larger turbulent eddies and are therefore inaccessible to direct and scale-resolved physics-based modelling in large scale climatological and meteorological models. In extreme environments, these processes are hypothesized, however, to be a major driver of the overall surface mass balance for snow and ice. This contribution presents a variety of modelling strategies to overcome the scale gap. Modelling strategies include bulk approximation, statistical and stationary wind modelling and large eddy simulation. Modelling is supported by measuring local and spatial meteorology and more specifically fluxes and snow distribution. Using a combination of such measurements and the diverse modelling methods it is shown, when and where simple approximations fail. For example, surface flux parameterizations fail during blowing snow. We further suggest how to adequately incorporate these processes in weather models such as the CRYOWRF model and present results that demonstrate the influence of blowing and drifting snow on the surface mass balance in Antarctica, the Alps and High Mountain Asia. We consider the feed-back of blowing snow onto the atmospheric boundary layer and show how it influences local effects such as through katabatic winds.

Description: Simulations of snow-atmosphere interactions are often the domain of complex, modern atmospheric models. These models have assisted our understanding of the physical processes behind snow-atmosphere interactions and have demonstrated capability of simulating atmospheric processes which affect seasonal snow. However, computational limitations have limited the use of fully coupled snow-atmosphere models to case studies. The High-resolution Intermediate Complexity Atmospheric Research (HICAR) model presents a computationally efficient platform through which some snow-atmosphere process can be simulated at the hectometer scale and at seasonal time scales. In particular, ridge-scale snow depth patterns influenced by preferential deposition and leeside eddies are resolved by the model. This is done while still utilizing 804x fewer computational resources than the Weather Research and Forecasting (WRF) model. Here we present a validation of the HICAR model using snow depth data and distributed wind data collected during Winter 2022/2023 in complex terrain in the Swiss Alps. These results show that HICAR can downscale both winds and precipitation to within the same accuracy as WRF. Thus, HICAR offers the ability to dynamically downscale forcing data to the target resolution of snow model simulations or for detailed studies under future climate scenarios. To this point, results from a study using a one-way coupling strategy between HICAR and an intermediate complexity snow model with snow redistribution will also be presented, showing the importance of different accumulation processes across scales. Remaining challenges and caveats of this modeling strategy, including the representation of turbulent mixing and dependency on input data, will also be discussed.

Description: In spring, when the mountainous snow cover becomes patchy, the strong multi-scale surface heterogeneity influences atmospheric heat exchange processes. At valley scale, thermally driven winds advect warm air towards snow-covered regions at higher elevations. Additionally, the difference in albedo between bare ground and adjacent snow patches causes strong surface temperature differences on a (sub-)meter scale. Consequently, the structure of the near-surface boundary layer is spatio-temporally highly variable. During spring 2021, we recorded data in a comprehensive field campaign in the Dischma valley close to Davos (CH). The dataset includes multiple eddy-covariance measurements at different measurement heights. The topographic setting allows to group the measurements into up valley and down valley flow systems. Using a multi-resolution spectral decomposition of turbulent flux variables, we investigate the structure and dynamics of near-surface turbulence. During up valley flows, the advection of warm air induces stable internal boundary layers (SIBL) adjacent to snow patches with near-neutral static stability above. The strong stability withing the SIBL eventually leads to decoupling of the near-surface turbulence from the submeso-scale motions aloft. In contrast, during down valley flows, stability dampens turbulence similarly at all measurement heights. In concert with those findings, measurements utilizing the IR-screen setup during the same campaign yield high spatio-temporally resolved air temperature profiles during phases of different stability. Furthermore, the screen measurements visualize the near-surface boundary layer dynamics. In the next step, we will use the gained process understanding to test new physical parameterizations especially for warm air advection in hectometer scale coupled snow-atmosphere models.

Description: The position of the near-surface zero isotherm (ZIL) plays a key role in many physical and biological processes in the polar regions. Some of the processes that undergo important changes are the rain-snow phase transition, the thawing and freezing of the active layer of permafrost, glacier mass variations, and changes in biological activity. For that reason, the monthly mean ZIL position can be used as an indicator to monitor climate change in the Antarctic Peninsula and the changes that are expected to occur. We characterized the position of the ZIL using near-surface temperature in the ERA5 reanalysis after evaluating its performance in reproducing its arrival and regression against observations over the Antarctic Peninsula. Using this data set, we quantify a southward change in the ZIL of 23.9 km decade〈sup〉-1〈/sup〉 from 1957 to 2020. This rate is faster than the global mean rate of temperature change which has been estimated at 4.2 km decade〈sup〉-1〈/sup〉. A congruence analysis attributes part of this southward shift, 10.8 km decade〈sup〉-1〈/sup〉, to the SAM. We also analyze the projections of the ZIL in the CMIP6 models during the 21st century. Although the position of the ZIL presents great variability between the different simulations, its trends are consistent and show a retreat of 23 ± 17 km decade〈sup〉-1〈/sup〉 and 56 ± 26 km decade〈sup〉-1〈/sup〉 under the SSP2-4.5 and SSP5-8.5 scenarios, respectively.

Description: Wind-blowing snow reshapes the snow patterns in high mountain areas and results in a significant impact on local energy balance and hydrological processes. High Mountain Asia, with the most abundant snow budget outside of polar regions, contributes a huge uncertainty to the estimation of terrestrial snow mass balance due to the interactions of blowing snow processes and complex terrain. In this work, we present a framework combining field observations, remote sensing, and high-resolution modeling to predict the snow cover evolution in the typical basins of High Mountain Asia. A mobile 3-D comprehensive observation system including radar systems, automatic weather station, and snow particle counters, was built to characterize the characteristics of wind – temperature – humidity – blowing snow flux profiles, as well as the resulting snow distribution patterns. Snow redistribution, blowing snow sublimation, snow cornice formation, and snow avalanche are processes considered in the framework. The field observations were compared to both remote sensing data and high-resolution modeling with CRYOWRF, a new modeling framework for atmospheric flow simulations for Cryospheric-regions, which couples the state-of-the-art and widely used atmospheric model WRF with the detailed snow cover model SNOWPACK. Our work has the potential to contribute to precise estimates of snow distribution in mountains.

Description: In polar regions, and specifically in continental Antarctica, the local surface mass and energy balances can be largely controlled by snow transport in form of drifting and blowing snow particles, and sublimation both from the snow or ice surface and from the airborne snow particles. Adverse conditions in such extreme environments make continuous and reliable measurements of snow drift and sublimation a challenge, especially during the period of polar night and in absence of maintenance. Additionally, existing state-of-the-art snow mass and moisture flux measurement systems have relatively large power requirements, often resulting in spurious values or data gaps due to insufficient power supply from the autonomous wind and solar based power systems. In this contribution, we present observations of drifting snow events and latent heat fluxes obtained from collocated installations of classical eddy covariance instrumentation, optical snow particle counters, and acoustic particle flux devices deployed in Queen Maud Land, East Antarctica. We investigate the coherence of the optical and low-power acoustic snow drift measurements and compare them to numerical simulations of mass fluxes at the sensor sites. Furthermore, to mitigate the problems of potential power failure, low-power, fast-response humidity sensors are tested in laboratory and field settings to obtain latent heat flux estimates at largely reduced power consumption in comparison to eddy covariance measurements using infra-red gas analysers. Promising or successful novel systems may be a viable alternative for recording continuous time series of sublimation, in particular in the polar night season, and at significantly lower cost.