Snow model comparison to simulate snow depth evolution and sublimation at point scale in the semi-arid Andes of Chile

International audiencePhysically based snow models provide valuable information on snow cover evolution and are therefore key to provide water availability projections. Yet, uncertainties related to snow modelling remain large as a result of differences in the representation of snow physics and meteorological forcing. While many studies focus on evaluating these uncertainties, no snow model comparison has been done in environments where sublimation is the main ablation process. This study evaluates a case study in the semi-arid Andes of Chile and aims to compare two snow models with different complexities, SNOWPACK and SnowModel, at a local point over one snow season and to evaluate their sensitivity relative to parameterisation and forcing. For that purpose, the two models are forced with (i) the most ideal set of input parameters, (ii) an ensemble of different physical parameterisations, and (iii) an ensemble of biased forcing. Results indicate large uncertainties depending on forcing, the snow roughness length z0, albedo parameterisation, and fresh snow density parameterisation. The uncertainty caused by the forcing is directly related to the bias chosen. Even though the models show significant differences in their physical complexity, the snow model choice is of least importance, as the sensitivity of both models to the forcing data was on the same order of magnitude and highly influenced by the precipitation uncertainties. The sublimation ratio ranges are in agreement for the two models: 36.4 % to 80.7 % for SnowModel and 36.3 % to 86.0 % for SNOWPACK, and are related to the albedo parameterisation and snow roughness length choice for the two models

The Stability of a Permanent Terrestrial Laser Scanning System – a Case Study with Hourly Scans

ISSN:1682-1750ISSN:2194-9034ISSN:1682-177

Investigating wind-driven Snow Redistribution Processes over an Alpine Glacier with high-resolution Terrestrial Laser Scans and Large-eddy Simulations

Wind-driven snow redistribution affects the glacier mass balance by eroding or depositing mass from or to different parts of the glacier’s surface. High-resolution observations are used to test the ability of large eddy simulations as a tool for distributed mass balance modeling. We present a case study of observed and simulated snow redistribution over Hintereisferner glacier (Ötztal Alps, Austria) between 6 and 9 February 2021. Observations consist of three high-resolution Digital Elevation Models (∆x=1 m) derived from terrestrial laser scans taken shortly before, directly after, and 15 hours after snowfall. The scans are complemented by data sets from three onsite weather stations. After the snow fall event the snowpack decreased by 0.08 m on average over the glacier and typical snow redistribution patterns were observed. The decrease of the snow depth is to be attributed to both post-snowfall compaction and redistribution of snow. Simulations were performed with the WRF model at ∆x=48 m with a newly implemented snow drift module. The spatial patterns of the simulated snow redistribution agree well with the observed generalized patterns. Snow redistribution contributed -0.026 m to the surface elevation decrease over the glacier surface on 8 Feb, resulting in a mass loss of -3.9 kg m−2, which is in the same order of magnitude as the observations. With the single case study we cannot yet extrapolate to the impact of post-snowfall events on the seasonal glacier mass balance, but the study shows that the snow drift module in WRF is a powerful tool to improve knowledge on snow redistribution over glaciers and that the model setup can be applied to other mountain glaciers

Uncertainty assessment of a permanent long-range terrestrial laser scanning system for the quantification of snow dynamics on Hintereisferner (Austria)

A permanently installed terrestrial laser scanner (TLS) helps to investigate surface changes at high spatio-temporal resolution. Previous studies show that the annual and seasonal glacier volume, and subsequently the mass balance, can be measured by TLSs. This study systematically identifies and quantifies uncertainties and their sources of the permanent long-range TLS system at Hintereisferner glacier (Ötztal Alps, Austria) in order to assess its potential and limitations for detecting glaciologically relevant small-scale surface elevation changes, such as snowfall and redistribution events. Five uncertainty sources are analyzed: the registration method, the influence of the instrument and hardware limitations of the TLS, the effect of atmospheric conditions on the laser beam, the scanning geometry, and the uncertainty caused by rasterization. The instrument and hardware limitations cause the largest uncertainty to the TLS data, followed by the scanning geometry and influence of varying atmospheric conditions on the laser beam. The magnitude of each uncertainty source depends on the distance (range) between the TLS and the target surface, showing a strong decrease of the obtained spatial resolution and a concurrent increase in uncertainty with increasing distance. An automated registration method results in an uncertainty of ±0.50 m at grids of 100 by 100 m. After post-processing, a 0.1-m vertical accuracy can be obtained allowing the detection of surface changes of respective magnitudes and especially making it possible to quantify snow dynamics at Hintereisferner.ISSN:2296-646

Snowdrift scheme in the Weather Research and Forecasting model

Wind-driven redistribution of snow is one of the key factors leading to heterogeneous accumulation of snow at small scales. Understanding these processes is, therefore, of great importance to many glaciological and hydrological questions. High-quality information on the wind field is necessary to realistically represent drifting snow. Here, we introduce a novel, intermediate-complexity drifting and blowing snow module for the Weather Research and Forecasting (WRF) model that integrates seamlessly into the standard WRF infrastructure. The module also accounts for snow particle sublimation and considers the thermodynamic feedback on the atmospheric fields. The module was tested in an idealized model environment. The simple and computationally efficient implementation allows this module to be used for small-scale and large-scale simulations in polar and glaciated regions