Local simulations of snow redistribution by wind with an intermediate-complexity snow cover model driven by different wind downscaling methods

2021 ◽  
Author(s):  
Louis Quéno ◽  
Paul Morin ◽  
Rebecca Mott ◽  
Tobias Jonas
Keyword(s):  
Snow Cover ◽  
Transport Processes ◽  
Swiss Alps ◽  
Small Scale ◽  
Mountain Range ◽  
Model Framework ◽  
Intermediate Complexity ◽  
Operational Modelling ◽  
Snow Transport ◽  
Large Domains

<p>In mountainous terrain, wind-driven transport of deposited snow affects the overall distribution of snow, and can have a significant effect on snowmelt patterns even at coarser resolution.  In an operational modelling perspective, a compromise must be found to represent this complex small-scale process with enough accuracy while mitigating the computational costs of snow cover simulations over large domains. To achieve this compromise, we implemented the SNOWTRAN-3D snow transport module within the FSM intermediate complexity snow cover model. We included a new layering scheme and a historical variable of past snow wetting, but without resolving the snow microstructure. Simulations are run and evaluated over a small mountain range in the Swiss Alps at 25 to 100 m resolution. Being implemented in the model framework of the SLF operational snow hydrology service (OSHD), simulations further benefit from snow data assimilation techniques to provide improved estimates of solid precipitation fields. As complex wind patterns in mountains are the key processes driving snow transport, we tested statistical and dynamical methods to downscale 1 km resolution COSMO winds to better reflect topographically-induced flow patterns. These simulations are a first step working towards the integration of wind transport processes over large domains in an intermediate-complexity and -resolution operational modelling framework.</p>

scholarly journals Understanding snow-transport processes shaping the mountain snow-cover

2010 ◽  
Vol 4 (4) ◽  
pp. 545-559 ◽  
Author(s):  
R. Mott ◽  
M. Schirmer ◽  
M. Bavay ◽  
T. Grünewald ◽  
M. Lehning
Keyword(s):  
Snow Cover ◽  
Laser Scanning ◽  
Transport Processes ◽  
Snow Surface ◽  
North West ◽  
Deposition Patterns ◽  
Regional Prediction ◽  
Prevailing Wind Direction ◽  
Snow Transport ◽  
Snow Deposition

Abstract. Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow-transport processes on different scales and to analyze some major drift events caused by north-west storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m) were computed with the atmospheric model Advanced Regional Prediction System (ARPS) and used as input for a model of snow-surface processes (Alpine3D) to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during north-west storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snow-surface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow-deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns, particularly two huge cross-slope cornice-like drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven). In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

scholarly journals Pulsed carbon export from mountains by earthquake-triggered landslides explored in a reduced-complexity model

2021 ◽  
Vol 9 (4) ◽  
pp. 823-844
Author(s):  
Thomas Croissant ◽  
Robert G. Hilton ◽  
Gen K. Li ◽  
Jamie Howarth ◽  
Jin Wang ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Annual Runoff ◽  
Transport Processes ◽  
Mountain Range ◽  
Biogeochemical Processes ◽  
Organic Matter Degradation ◽  
Carbon Export ◽  
Model Framework ◽  
Mountain Ranges

Abstract. In mountain ranges, earthquakes can trigger widespread landsliding and mobilize large amounts of organic carbon by eroding soil and vegetation from hillslopes. Following a major earthquake, the landslide-mobilized organic carbon can be exported from river catchments by physical sediment transport processes or stored within the landscape where it may be degraded by heterotrophic respiration. The competition between these physical and biogeochemical processes governs a net transfer of carbon between the atmosphere and sedimentary organic matter, yet their relative importance following a large landslide-triggering earthquake remains poorly constrained. Here, we propose a model framework to quantify the post-seismic redistribution of soil-derived organic carbon. The approach combines predictions based on empirical observations of co-seismic sediment mobilization with a description of the physical and biogeochemical processes involved after an earthquake. Earthquake-triggered landslide populations are generated by randomly sampling a landslide area distribution, a proportion of which is initially connected to the fluvial network. Initially disconnected landslide deposits are transported downslope and connected to rivers at a constant velocity in the post-seismic period. Disconnected landslide deposits lose organic carbon by heterotrophic oxidation, while connected deposits lose organic carbon synchronously by both oxidation and river export. The modeling approach is numerically efficient and allows us to explore a large range of parameter values that exert a control on the fate of organic carbon in the upland erosional system. We explore the role of the climatic context (in terms of mean annual runoff and runoff variability) and rates of organic matter degradation using single pool and multi-pool models. Our results highlight the fact that the redistribution of organic carbon is strongly controlled by the annual runoff and the extent of landslide connection, but less so by the choice of organic matter degradation model. In the context of mountain ranges typical of the southwestern Pacific region, we find that model configurations allow more than 90 % of the landslide-mobilized carbon to be exported from mountain catchments. A simulation of earthquake cycles suggests efficient transfer of organic carbon out of a mountain range during the first decade of the post-seismic period. Pulsed erosion of organic matter by earthquake-triggered landslides is therefore an effective process to promote carbon sequestration in sedimentary deposits over thousands of years.

scholarly journals How much can we save? Impact of different emission scenarios on future snow cover in the Alps

2017 ◽  
Vol 11 (1) ◽  
pp. 517-529 ◽  
Author(s):  
Christoph Marty ◽  
Sebastian Schlögl ◽  
Mathias Bavay ◽  
Michael Lehning
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Swiss Alps ◽  
Small Scale ◽  
Emission Scenarios ◽  
Scenario Period ◽  
Temperature And Precipitation ◽  
Elevation Zone ◽  
Time Periods ◽  
Intervention Scenario

Abstract. This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at a 200 m horizontal resolution for the reference period (1999–2012). Future temperature and precipitation changes have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2 °C target) and for three future time periods (2020–2049, 2045–2074, 2070–2099). By applying simple daily change values to measured time series of temperature and precipitation, small-scale climate scenarios have been calculated for the median estimate and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-intervention scenarios demonstrate a decrease of about 50 % even for elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to 1 month later and ends 1 to 3 months earlier in this last scenario period. The resulting snow cover changes may be roughly equivalent to an elevation shift of 500–800 or 700–1000 m for the two non-intervention emission scenarios. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and only 0–2 snow days are predicted in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period but clearly demonstrate a stabilization thereafter, comprising much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).

scholarly journals Pulsed carbon export from mountains by earthquake-triggered landslides explored in a reduced-complexity model

2020 ◽  
Author(s):  
Thomas Croissant ◽  
Robert G. Hilton ◽  
Gen Li ◽  
Jamie Howarth ◽  
Jin Wang ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Annual Runoff ◽  
Transport Processes ◽  
Mountain Range ◽  
Biogeochemical Processes ◽  
Organic Matter Degradation ◽  
Carbon Export ◽  
Model Framework ◽  
Mountain Ranges

Abstract. In mountain ranges, earthquakes can trigger widespread landsliding and mobilise large amounts of organic carbon by eroding soil and vegetation from hillslopes. Following a major earthquake, the landslide-mobilised organic carbon can be exported from river catchments by physical sediment transport processes, or stored within the landscape where it may be degraded by heterotrophic respiration. The competition between these physical and biogeochemical processes governs a net transfer of carbon between the atmosphere and sedimentary organic matter, yet their relative importance following a large landslide-triggering earthquake remains poorly constrained. Here, we propose a model framework to quantify the post-seismic redistribution of soil-derived organic carbon. The approach combines predictions based on empirical observations of co-seismic sediment mobilisation, with a description of the physical and biogeochemical processes involved after the earthquake. Earthquake-triggered landslide populations are generated by randomly sampling a landslide area distribution, a proportion of which is initially connected to the fluvial network. Initially disconnected landslide deposits are transported downslope and connected to rivers at a constant velocity in the post-seismic period. Disconnected landslide deposits lose organic carbon by heterotrophic oxidation, while connected deposits lose organic carbon synchronously by both oxidation and river export. The modelling approach is numerically efficient and allows us to explore a large range of parameter values that exert a control on the fate of organic carbon in the upland erosional system. We explore the role of the climatic context (in terms of mean annual runoff and runoff variability) and rates of organic matter degradation using single and multi-pool models. Our results highlight that the redistribution of organic carbon is strongly controlled by the annual runoff and the extent of landslide connection, but less so by the choice of organic matter degradation model. In the context of mountain ranges typical of the southwest Pacific region, we find that model configurations allow for more than 90 % of the landslide-mobilized carbon to be exported from mountain catchments. A simulation of earthquake cycles suggests efficient transfer of organic carbon out of a mountain range during the first decade of the post-seismic period. Pulsed erosion of organic matter by earthquake-triggered landslides therefore offers an effective process to promote carbon sequestration in sedimentary deposits over thousands of years.

scholarly journals How much can we save? Impact of different emission scenarios on future snow cover in the Alps

2016 ◽  
Author(s):  
Christoph Marty ◽  
Sebastian Schlögl ◽  
Mathias Bavay ◽  
Lehning Michael
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Swiss Alps ◽  
Small Scale ◽  
Emission Scenarios ◽  
Scenario Period ◽  
Temperature And Precipitation ◽  
Elevation Zone ◽  
Time Periods ◽  
Intervention Scenario

Abstract. This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at 200 m horizontal resolution for the reference period (1999–2012). Future temperature and precipitation change have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2° C target) and for three future time periods (2020–2049, 2045–2074, 2070–2099). By applying simple daily change values to measured time series of temperature and precipitation series small-scale climate scenarios have been calculated for the ensemble mean and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-interventions scenarios demonstrate a decrease of about 50 % even for the elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to one month later and ends one to three month earlier in this last scenario period. The resultant snow cover changes may roughly be equivalent to an elevation shift of 500–800 m or 700–1000 m for the two non-intervention emissions scenario. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and is predicted to only 0–2 snow days in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period, but clearly demonstrate much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).

scholarly journals Understanding snow-transport processes shaping the mountain snow-cover

2010 ◽  
Vol 4 (3) ◽  
pp. 865-900 ◽  
Author(s):  
R. Mott ◽  
M. Schirmer ◽  
M. Bavay ◽  
T. Grünewald ◽  
M. Lehning
Keyword(s):  
Snow Cover ◽  
Laser Scanning ◽  
Transport Processes ◽  
Snow Surface ◽  
North West ◽  
Deposition Patterns ◽  
Regional Prediction ◽  
Prevailing Wind Direction ◽  
Snow Transport ◽  
Snow Deposition

Abstract. Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow transport processes on different scales and to analyze some major drift events caused by North-West storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m) were therefore computed with the atmospheric model Advanced Regional Prediction System (ARPS) and used as input for a model of snow surface processes (Alpine3D) to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during North-West storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snow surface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns we found, particularly two huge cross-slope cornice-like drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven). In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

Experiments on wind-driven heat exchange processes over melting snow

2021 ◽  
Author(s):  
Michael Haugeneder ◽  
Tobias Jonas ◽  
Dylan Reynolds ◽  
Michael Lehning ◽  
Rebecca Mott
Keyword(s):  
Snow Cover ◽  
Surface Wind ◽  
Infrared Camera ◽  
Snow Accumulation ◽  
Internal Boundary ◽  
Small Scale ◽  
Snow Melt ◽  
Two Dimensional ◽  
Atmospheric Conditions ◽  
Near Surface

<p>Snowmelt runoff predictions in alpine catchments are challenging because of the high spatial variability of t<span>he snow cover driven by </span>various snow accumulation and ablation processes. In spring, the coexistence of bare and snow-covered ground engages a number of processes such as the enhanced lateral advection of heat over partial snow cover, the development of internal boundary layers, and atmospheric decoupling effects due to increasing stability at the snow cover. The interdependency of atmospheric conditions, topographic settings and snow coverage remains a challenge to accurately account for these processes in snow melt models.<br>In this experimental study, we used an Infrared Camera (VarioCam) pointing at thin synthetic projection screens with negligible heat capacity. Using the surface temperature of the screen as a proxy for the air temperature, we obtained a two-dimensional instantaneous measurement. Screens were installed across the transition between snow-free and snow-covered areas. With IR-measurements taken at 10Hz, we capture<span> the dynamics of turbulent temperature fluctuations</span><span> </span>over the patchy snow cover at high spatial and temporal resolution. From this data we were able to obtain high-frequency, two-dimensional windfield estimations adjacent to the surface.</p><p>Preliminary results show the formation of a stable internal boundary layer (SIBL), which was temporally highly variable. Our data suggest that the SIBL height is very shallow and strongly sensitive to the mean near-surface wind speed. Only strong gusts were capable of penetrating through this SIBL leading to an enhanced energy input to the snow surface.</p><p>With these type of results from our experiments and further measurements this spring we aim to better understand small scale energy transfer processes over patch snow cover and it’s dependency on the atmospheric conditions, enabling to improve parameterizations of these processes in coarser-resolution snow melt models.</p>

The future of ski resorts in the Swiss Alps: using DMDU to identify tipping points

2021 ◽  
Author(s):  
Saeid Ashraf Vaghefi ◽  
Veruska Muccione ◽  
Kees C.H. van Ginkel ◽  
Marjolijn Haasnoot
Keyword(s):  
Snow Cover ◽  
Climate Models ◽  
Swiss Alps ◽  
Tipping Points ◽  
Annual Variability ◽  
Ski Resorts ◽  
The Future ◽  
Total Profit ◽  
Climate Uncertainty ◽  
Snow Conditions

<p>The future of ski resorts in the Swiss Alps is highly uncertain. Being dependent on snow cover conditions, winter sport tourism is highly susceptible to changes in temperature and precipitation. With the observed warming of the European Alps being well above global average warming, snow cover in Switzerland is projected to shrink at a rapid pace. Climate uncertainty originates from greenhouse gas emission trajectories (RCPs) and differences between climate models. Beyond climate uncertainty, the snow conditions are strongly subject to intra-annual variability. Series of unfavorable years have already led to the financial collapse of several low-altitude ski resorts. Such abrupt collapses with a large impact on the regional economy can be referred to as climate change induced socio-economic tipping points. To some degree, tipping points may be avoided by adaptation measures such as artificial snowmaking, although these measures are also subject to physical and economical constraints. In this study, we use a variety of exploratory modeling techniques to identify tipping points in a coupled physical-economic model applied to six representative ski resorts in the Swiss Alps. New high-resolution climate projections (CH2018) are used to represent climate uncertainty. To improve the coverage of the uncertainty space and accounting for the intra-annual variability of the climate models, a resampling technique was used to produce new climate realizations. A snow process model is used to simulate daily snow-cover in each of the ski resorts. The likelihood of survival of each resort is evaluated from the number of days with good snow conditions for skiing compared to the minimum thresholds obtained from the literature. Economically, the good snow days are translated into the total profit of ski resorts per season of operation. Multiple unfavorable years of total profit may lead to a tipping point. We use scenario discovery to identify the conditions under which these tipping points occur, and reflect on their implications for the future of snow tourism in the Swiss Alps.</p>

scholarly journals Sensitivity analysis of a wetland methane emission model based on temperate and arctic wetland sites

2009 ◽  
Vol 6 (12) ◽  
pp. 3035-3051 ◽  
Author(s):  
J. van Huissteden ◽  
A. M. R. Petrescu ◽  
D. M. D. Hendriks ◽  
K. T. Rebel
Keyword(s):  
Temporal Variability ◽  
Global Scale ◽  
Transport Processes ◽  
Small Scale ◽  
Soil Parameters ◽  
Wetland Soil ◽  
Emission Model ◽  
Ch4 Emission ◽  
Model Based ◽  
Ch4 Transport

Abstract. Modelling of wetland CH4 fluxes using wetland soil emission models is used to determine the size of this natural source of CH4 emission on local to global scale. Most process models of CH4 formation and soil-atmosphere CH4 transport processes operate on a plot scale. For large scale emission modelling (regional to global scale) upscaling of this type of model requires thorough analysis of the sensitivity of these models to parameter uncertainty. We applied the GLUE (Generalized Likelihood Uncertainty Analysis) methodology to a well-known CH4 emission model, the Walter-Heimann model, as implemented in the PEATLAND-VU model. The model is tested using data from two temperate wetland sites and one arctic site. The tests include experiments with different objective functions, which quantify the fit of the model results to the data. The results indicate that the model 1) in most cases is capable of estimating CH4 fluxes better than an estimate based on the data avarage, but does not clearly outcompete a regression model based on local data; 2) is capable of reproducing larger scale (seasonal) temporal variability in the data, but not the small-scale (daily) temporal variability; 3) is not strongly sensitive to soil parameters, 4) is sensitive to parameters determining CH4 transport and oxidation in vegetation, and the temperature sensitivity of the microbial population. The GLUE method also allowed testing of several smaller modifications of the original model. We conclude that upscaling of this plot-based wetland CH4 emission model is feasible, but considerable improvements of wetland CH4 modelling will result from improvement of wetland vegetation data.

scholarly journals Distributed snow and rock temperature modelling in steep rock walls using Alpine3D

2017 ◽  
Vol 11 (1) ◽  
pp. 585-607 ◽  
Author(s):  
Anna Haberkorn ◽  
Nander Wever ◽  
Martin Hoelzle ◽  
Marcia Phillips ◽  
Robert Kenner ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Snow Depth ◽  
Spatial Scales ◽  
Swiss Alps ◽  
Balance Model ◽  
Near Surface ◽  
Surface Rock ◽  
Depth Data ◽  
Rock Temperature

Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.

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