Articles | Volume 18, issue 6
https://doi.org/10.5194/tc-18-2783-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-2783-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy
Benjamin Bouchard
CORRESPONDING AUTHOR
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
CentrEau – Quebec Water Research Centre, Université Laval, Québec, G1V 0A6, Canada
Centre d'Études Nordiques, Université Laval, Québec, G1V 0A6, Canada
Daniel F. Nadeau
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
CentrEau – Quebec Water Research Centre, Université Laval, Québec, G1V 0A6, Canada
Florent Domine
Centre d'Études Nordiques, Université Laval, Québec, G1V 0A6, Canada
Department of Chemistry, Université Laval, Québec, G1V 0A6, Canada
Takuvik Joint International Laboratory, Université Laval (Canada) and CNRS-INSU (France), Québec, G1V 0A6, Canada
Nander Wever
WSL Institute for Snow and Avalanche Research (SLF), 7260 Davos Dorf, Switzerland
École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering, Lausanne, Switzerland
Adrien Michel
WSL Institute for Snow and Avalanche Research (SLF), 7260 Davos Dorf, Switzerland
École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering, Lausanne, Switzerland
Federal Office of Meteorology and Climatology, MeteoSwiss, Geneva, Switzerland
Michael Lehning
WSL Institute for Snow and Avalanche Research (SLF), 7260 Davos Dorf, Switzerland
École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering, Lausanne, Switzerland
Pierre-Erik Isabelle
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
CentrEau – Quebec Water Research Centre, Université Laval, Québec, G1V 0A6, Canada
Related authors
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, François Anctil, Tobias Jonas, and Étienne Tremblay
Hydrol. Earth Syst. Sci., 28, 2745–2765, https://doi.org/10.5194/hess-28-2745-2024, https://doi.org/10.5194/hess-28-2745-2024, 2024
Short summary
Short summary
Observations and simulations from an exceptionally low-snow and warm winter, which may become the new norm in the boreal forest of eastern Canada, show an earlier and slower snowmelt, reduced soil temperature, stronger vertical temperature gradients in the snowpack, and a significantly lower spring streamflow. The magnitude of these effects is either amplified or reduced with regard to the complex structure of the canopy.
Florent Domine, Mireille Quémener, Ludovick Bégin, Benjamin Bouchard, Valérie Dionne, Sébastien Jerczynski, Raphaël Larouche, Félix Lévesque-Desrosiers, Simon-Olivier Philibert, Marc-André Vigneault, Ghislain Picard, and Daniel C. Côté
EGUsphere, https://doi.org/10.5194/egusphere-2024-1582, https://doi.org/10.5194/egusphere-2024-1582, 2024
Short summary
Short summary
Shrubs buried in snow absorb solar radiation and reduce irradiance in the snowpack. This decreases photochemical reactions rates and emissions to the atmosphere. By monitoring irradiance in snowpacks with and without shrubs, we conclude that shrubs absorb solar radiation as much as 140 ppb of soot and reduce irradiance by a factor of two. Shrub expansion in the Arctic may therefore affect tropospheric composition during the snow season, with climatic effects.
Stephanie Mayer, Martin Hendrick, Adrien Michel, Bettina Richter, Jürg Schweizer, Heini Wernli, and Alec van Herwijnen
The Cryosphere, 18, 5495–5517, https://doi.org/10.5194/tc-18-5495-2024, https://doi.org/10.5194/tc-18-5495-2024, 2024
Short summary
Short summary
Understanding the impact of climate change on snow avalanche activity is crucial for safeguarding lives and infrastructure. Here, we project changes in avalanche activity in the Swiss Alps throughout the 21st century. Our findings reveal elevation-dependent patterns of change, indicating a decrease in dry-snow avalanches alongside an increase in wet-snow avalanches at elevations above the current treeline. These results underscore the necessity to revisit measures for avalanche risk mitigation.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
Short summary
Short summary
Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Hongxiang Yu, Michael Lehning, Guang Li, Benjamin Walter, Jianping Huang, and Ning Huang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2458, https://doi.org/10.5194/egusphere-2024-2458, 2024
Short summary
Short summary
Cornices are overhanging snow accumulations that form on mountain crests. Previous studies focused on how cornices collapse, little is known about why they form in the first place, specifically how snow particles adhere together to form the front end of the cornice. This study looked at the movement of snow particles around a developing cornice to understand how they gather, the speed and angle at which the snow particles hit the cornice surface, and how this affects the shape of the cornice.
Sonja Wahl, Benjamin Walter, Franziska Aemisegger, Luca Bianchi, and Michael Lehning
The Cryosphere, 18, 4493–4515, https://doi.org/10.5194/tc-18-4493-2024, https://doi.org/10.5194/tc-18-4493-2024, 2024
Short summary
Short summary
Wind-driven airborne transport of snow is a frequent phenomenon in snow-covered regions and a process difficult to study in the field as it is unfolding over large distances. Thus, we use a ring wind tunnel with infinite fetch positioned in a cold laboratory to study the evolution of the shape and size of airborne snow. With the help of stable water isotope analyses, we identify the hitherto unobserved process of airborne snow metamorphism that leads to snow particle rounding and growth.
Dylan Reynolds, Louis Quéno, Michael Lehning, Mahdi Jafari, Justine Berg, Tobias Jonas, Michael Haugeneder, and Rebecca Mott
The Cryosphere, 18, 4315–4333, https://doi.org/10.5194/tc-18-4315-2024, https://doi.org/10.5194/tc-18-4315-2024, 2024
Short summary
Short summary
Information about atmospheric variables is needed to produce simulations of mountain snowpacks. We present a model that can represent processes that shape mountain snowpack, focusing on the accumulation of snow. Simulations show that this model can simulate the complex path that a snowflake takes towards the ground and that this leads to differences in the distribution of snow by the end of winter. Overall, this model shows promise with regard to improving forecasts of snow in mountains.
Ella Gilbert, Denis Pishniak, José Abraham Torres, Andrew Orr, Michelle Maclennan, Nander Wever, and Kristiina Verro
EGUsphere, https://doi.org/10.5194/egusphere-2024-2111, https://doi.org/10.5194/egusphere-2024-2111, 2024
Short summary
Short summary
We use 3 sophisticated climate models to examine extreme precipitation in a critical region of West Antarctica. We found that rainfall probably occurred during the two cases we examined, and that it was generated by the interaction of air with steep topography. Our results show that kilometre scale models are useful tools for exploring extreme precipitation in this region, and that more observations of rainfall are needed.
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, François Anctil, Tobias Jonas, and Étienne Tremblay
Hydrol. Earth Syst. Sci., 28, 2745–2765, https://doi.org/10.5194/hess-28-2745-2024, https://doi.org/10.5194/hess-28-2745-2024, 2024
Short summary
Short summary
Observations and simulations from an exceptionally low-snow and warm winter, which may become the new norm in the boreal forest of eastern Canada, show an earlier and slower snowmelt, reduced soil temperature, stronger vertical temperature gradients in the snowpack, and a significantly lower spring streamflow. The magnitude of these effects is either amplified or reduced with regard to the complex structure of the canopy.
Florent Domine, Mireille Quémener, Ludovick Bégin, Benjamin Bouchard, Valérie Dionne, Sébastien Jerczynski, Raphaël Larouche, Félix Lévesque-Desrosiers, Simon-Olivier Philibert, Marc-André Vigneault, Ghislain Picard, and Daniel C. Côté
EGUsphere, https://doi.org/10.5194/egusphere-2024-1582, https://doi.org/10.5194/egusphere-2024-1582, 2024
Short summary
Short summary
Shrubs buried in snow absorb solar radiation and reduce irradiance in the snowpack. This decreases photochemical reactions rates and emissions to the atmosphere. By monitoring irradiance in snowpacks with and without shrubs, we conclude that shrubs absorb solar radiation as much as 140 ppb of soot and reduce irradiance by a factor of two. Shrub expansion in the Arctic may therefore affect tropospheric composition during the snow season, with climatic effects.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-78, https://doi.org/10.5194/hess-2024-78, 2024
Revised manuscript under review for HESS
Short summary
Short summary
Observations from a study site network in eastern Canada showed a temperature interval the overlapping probabilities for rain, snow or a mix of both. Models using random forest algorithms were developed to classify the precipitation phase using meteorological data to evaluate operational applications. They showed significantly improved phase classification compared to benchmarks, but misclassification led to costlier errors. However, accurate prediction of mixed phase remains a challenge.
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024, https://doi.org/10.5194/essd-16-1523-2024, 2024
Short summary
Short summary
The forest–tundra ecotone is the transition region between the boreal forest and Arctic tundra. It spans over 13 000 km across the Arctic and is evolving rapidly because of climate change. We provide extensive data sets of two sites 850 m apart, one in tundra and one in forest in this ecotone for use in various models. Data include meteorological and flux data and unique snow and soil physics data.
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068, https://doi.org/10.5194/gmd-16-5049-2023, https://doi.org/10.5194/gmd-16-5049-2023, 2023
Short summary
Short summary
The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Megan Thompson-Munson, Nander Wever, C. Max Stevens, Jan T. M. Lenaerts, and Brooke Medley
The Cryosphere, 17, 2185–2209, https://doi.org/10.5194/tc-17-2185-2023, https://doi.org/10.5194/tc-17-2185-2023, 2023
Short summary
Short summary
To better understand the Greenland Ice Sheet’s firn layer and its ability to buffer sea level rise by storing meltwater, we analyze firn density observations and output from two firn models. We find that both models, one physics-based and one semi-empirical, simulate realistic density and firn air content when compared to observations. The models differ in their representation of firn air content, highlighting the uncertainty in physical processes and the paucity of deep-firn measurements.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-298, https://doi.org/10.5194/gmd-2022-298, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better quality maps. The correction can then be extended backwards and forwards in time for periods when better quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the last 60 years at a resolution of one day and one kilometre. This is the first time that such a dataset has been produced.
Michelle L. Maclennan, Jan T. M. Lenaerts, Christine A. Shields, Andrew O. Hoffman, Nander Wever, Megan Thompson-Munson, Andrew C. Winters, Erin C. Pettit, Theodore A. Scambos, and Jonathan D. Wille
The Cryosphere, 17, 865–881, https://doi.org/10.5194/tc-17-865-2023, https://doi.org/10.5194/tc-17-865-2023, 2023
Short summary
Short summary
Atmospheric rivers are air masses that transport large amounts of moisture and heat towards the poles. Here, we use a combination of weather observations and models to quantify the amount of snowfall caused by atmospheric rivers in West Antarctica which is about 10 % of the total snowfall each year. We then examine a unique event that occurred in early February 2020, when three atmospheric rivers made landfall over West Antarctica in rapid succession, leading to heavy snowfall and surface melt.
Hongxiang Yu, Guang Li, Benjamin Walter, Michael Lehning, Jie Zhang, and Ning Huang
The Cryosphere, 17, 639–651, https://doi.org/10.5194/tc-17-639-2023, https://doi.org/10.5194/tc-17-639-2023, 2023
Short summary
Short summary
Snow cornices lead to the potential risk of causing snow avalanche hazards, which are still unknown so far. We carried out a wind tunnel experiment in a cold lab to investigate the environmental conditions for snow cornice accretion recorded by a camera. The length growth rate of the cornices reaches a maximum for wind speeds approximately 40 % higher than the threshold wind speed. Experimental results improve our understanding of the cornice formation process.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
Short summary
Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Nicole Clerx, Horst Machguth, Andrew Tedstone, Nicolas Jullien, Nander Wever, Rolf Weingartner, and Ole Roessler
The Cryosphere, 16, 4379–4401, https://doi.org/10.5194/tc-16-4379-2022, https://doi.org/10.5194/tc-16-4379-2022, 2022
Short summary
Short summary
Meltwater runoff is one of the main contributors to mass loss on the Greenland Ice Sheet that influences global sea level rise. However, it remains unclear where meltwater runs off and what processes cause this. We measured the velocity of meltwater flow through snow on the ice sheet, which ranged from 0.17–12.8 m h−1 for vertical percolation and from 1.3–15.1 m h−1 for lateral flow. This is an important step towards understanding where, when and why meltwater runoff occurs on the ice sheet.
Gauthier Vérin, Florent Domine, Marcel Babin, Ghislain Picard, and Laurent Arnaud
The Cryosphere, 16, 3431–3449, https://doi.org/10.5194/tc-16-3431-2022, https://doi.org/10.5194/tc-16-3431-2022, 2022
Short summary
Short summary
Snow physical properties on Arctic sea ice are monitored during the melt season. As snow grains grow, and the snowpack thickness is reduced, the surface albedo decreases. The extra absorbed energy accelerates melting. Radiative transfer modeling shows that more radiation is then transmitted to the snow–sea-ice interface. A sharp increase in transmitted radiation takes place when the snowpack thins significantly, and this coincides with the initiation of the phytoplankton bloom in the seawater.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
Short summary
Short summary
This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 3357–3373, https://doi.org/10.5194/tc-16-3357-2022, https://doi.org/10.5194/tc-16-3357-2022, 2022
Short summary
Short summary
We compared the snowpack at two sites separated by less than 1 km, one in shrub tundra and the other one within the boreal forest. Even though the snowpack was twice as thick at the forested site, we found evidence that the vertical transport of water vapor from the bottom of the snowpack to its surface was important at both sites. The snow model Crocus simulates no water vapor fluxes and consequently failed to correctly simulate the observed density profiles.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
Short summary
Short summary
High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Short summary
Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
Short summary
Short summary
This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Adrien Michel, Bettina Schaefli, Nander Wever, Harry Zekollari, Michael Lehning, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, https://doi.org/10.5194/hess-26-1063-2022, 2022
Short summary
Short summary
This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, François Anctil, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022, https://doi.org/10.5194/tc-16-127-2022, 2022
Short summary
Short summary
The surface energy budget is the sum of all incoming and outgoing energy fluxes at the Earth's surface and has a key role in the climate. We measured all these fluxes for an Arctic snowpack and found that most incoming energy from radiation is counterbalanced by thermal radiation and heat convection while sublimation was negligible. Overall, the snow model Crocus was able to simulate the observed energy fluxes well.
Achut Parajuli, Daniel F. Nadeau, François Anctil, and Marco Alves
The Cryosphere, 15, 5371–5386, https://doi.org/10.5194/tc-15-5371-2021, https://doi.org/10.5194/tc-15-5371-2021, 2021
Short summary
Short summary
Cold content is the energy required to attain an isothermal (0 °C) state and resulting in the snow surface melt. This study focuses on determining the multi-layer cold content (30 min time steps) relying on field measurements, snow temperature profile, and empirical formulation in four distinct forest sites of Montmorency Forest, eastern Canada. We present novel research where the effect of forest structure, local topography, and meteorological conditions on cold content variability is explored.
Maria Belke-Brea, Florent Domine, Ghislain Picard, Mathieu Barrere, and Laurent Arnaud
Biogeosciences, 18, 5851–5869, https://doi.org/10.5194/bg-18-5851-2021, https://doi.org/10.5194/bg-18-5851-2021, 2021
Short summary
Short summary
Expanding shrubs in the Arctic change snowpacks into a mix of snow, impurities and buried branches. Snow is a translucent medium into which light penetrates and gets partly absorbed by branches or impurities. Measurements of light attenuation in snow in Northern Quebec, Canada, showed (1) black-carbon-dominated light attenuation in snowpacks without shrubs and (2) buried branches influence radiation attenuation in snow locally, leading to melting and pockets of large crystals close to branches.
Florent Domine, Georg Lackner, Denis Sarrazin, Mathilde Poirier, and Maria Belke-Brea
Earth Syst. Sci. Data, 13, 4331–4348, https://doi.org/10.5194/essd-13-4331-2021, https://doi.org/10.5194/essd-13-4331-2021, 2021
Short summary
Short summary
Current sophisticated snow physics models were mostly designed for alpine conditions and cannot adequately simulate the physical properties of Arctic snowpacks. New snow models will require Arctic data sets for forcing and validation. We provide an extensive driving and testing data set from a high Arctic herb tundra site in Canada. Unique validating data include continuous time series of snow and soil thermal conductivity and temperature profiles. Field observations in spring are provided.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
Short summary
Short summary
A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Devon Dunmire, Alison F. Banwell, Nander Wever, Jan T. M. Lenaerts, and Rajashree Tri Datta
The Cryosphere, 15, 2983–3005, https://doi.org/10.5194/tc-15-2983-2021, https://doi.org/10.5194/tc-15-2983-2021, 2021
Short summary
Short summary
Here, we automatically detect buried lakes (meltwater lakes buried below layers of snow) across the Greenland Ice Sheet, providing insight into a poorly studied meltwater feature. For 2018 and 2019, we compare areal extent of buried lakes. We find greater buried lake extent in 2019, especially in northern Greenland, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that buried lakes form via different processes across Greenland.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 2739–2755, https://doi.org/10.5194/tc-15-2739-2021, https://doi.org/10.5194/tc-15-2739-2021, 2021
Short summary
Short summary
The thermal conductivity of snow is an important physical property governing the thermal regime of a snowpack and its substrate. We show that it strongly depends on the kinetics of water vapor sublimation and that previous experimental data suggest a rather fast kinetics. In such a case, neglecting water vapor leads to an underestimation of thermal conductivity by up to 50 % for light snow. Moreover, the diffusivity of water vapor in snow is then directly related to the thermal conductivity.
Marcel Haeberli, Daniel Baggenstos, Jochen Schmitt, Markus Grimmer, Adrien Michel, Thomas Kellerhals, and Hubertus Fischer
Clim. Past, 17, 843–867, https://doi.org/10.5194/cp-17-843-2021, https://doi.org/10.5194/cp-17-843-2021, 2021
Short summary
Short summary
Using the temperature-dependent solubility of noble gases in ocean water, we reconstruct global mean ocean temperature (MOT) over the last 700 kyr using noble gas ratios in air enclosed in polar ice cores. Our record shows that glacial MOT was about 3 °C cooler compared to the Holocene. Interglacials before 450 kyr ago were characterized by about 1.5 °C lower MOT than the Holocene. In addition, some interglacials show transient maxima in ocean temperature related to changes in ocean circulation.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
Short summary
Short summary
Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
J. Melchior van Wessem, Christian R. Steger, Nander Wever, and Michiel R. van den Broeke
The Cryosphere, 15, 695–714, https://doi.org/10.5194/tc-15-695-2021, https://doi.org/10.5194/tc-15-695-2021, 2021
Short summary
Short summary
This study presents the first modelled estimates of perennial firn aquifers (PFAs) in Antarctica. PFAs are subsurface meltwater bodies that do not refreeze in winter due to the isolating effects of the snow they are buried underneath. They were first identified in Greenland, but conditions for their existence are also present in the Antarctic Peninsula. These PFAs can have important effects on meltwater retention, ice shelf stability, and, consequently, sea level rise.
Kévin Fourteau, Florent Domine, and Pascal Hagenmuller
The Cryosphere, 15, 389–406, https://doi.org/10.5194/tc-15-389-2021, https://doi.org/10.5194/tc-15-389-2021, 2021
Short summary
Short summary
There has been a long controversy to determine whether the effective diffusion coefficient of water vapor in snow is superior to that in free air. Using theory and numerical modeling, we show that while water vapor diffuses more than inert gases thanks to its interaction with the ice, the effective diffusion coefficient of water vapor in snow remains inferior to that in free air. This suggests that other transport mechanisms are responsible for the large vapor fluxes observed in some snowpacks.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Louis Quéno, Charles Fierz, Alec van Herwijnen, Dylan Longridge, and Nander Wever
The Cryosphere, 14, 3449–3464, https://doi.org/10.5194/tc-14-3449-2020, https://doi.org/10.5194/tc-14-3449-2020, 2020
Short summary
Short summary
Deep ice layers may form in the snowpack due to preferential water flow with impacts on the snowpack mechanical, hydrological and thermodynamical properties. We studied their formation and evolution at a high-altitude alpine site, combining a comprehensive observation dataset at a daily frequency (with traditional snowpack observations, penetration resistance and radar measurements) and detailed snowpack modeling, including a new parameterization of ice formation in the 1-D SNOWPACK model.
Thore Kausch, Stef Lhermitte, Jan T. M. Lenaerts, Nander Wever, Mana Inoue, Frank Pattyn, Sainan Sun, Sarah Wauthy, Jean-Louis Tison, and Willem Jan van de Berg
The Cryosphere, 14, 3367–3380, https://doi.org/10.5194/tc-14-3367-2020, https://doi.org/10.5194/tc-14-3367-2020, 2020
Short summary
Short summary
Ice rises are elevated parts of the otherwise flat ice shelf. Here we study the impact of an Antarctic ice rise on the surrounding snow accumulation by combining field data and modeling. Our results show a clear difference in average yearly snow accumulation between the windward side, the leeward side and the peak of the ice rise due to differences in snowfall and wind erosion. This is relevant for the interpretation of ice core records, which are often drilled on the peak of an ice rise.
Benjamin Walter, Hendrik Huwald, Josué Gehring, Yves Bühler, and Michael Lehning
The Cryosphere, 14, 1779–1794, https://doi.org/10.5194/tc-14-1779-2020, https://doi.org/10.5194/tc-14-1779-2020, 2020
Short summary
Short summary
We applied a horizontally mounted low-cost precipitation radar to measure velocities, frequency of occurrence, travel distances and turbulence characteristics of blowing snow off a mountain ridge. Our analysis provides a first insight into the potential of radar measurements for determining blowing snow characteristics, improves our understanding of mountain ridge blowing snow events and serves as a valuable data basis for validating coupled numerical weather and snowpack simulations.
Philippe Massicotte, Rémi Amiraux, Marie-Pier Amyot, Philippe Archambault, Mathieu Ardyna, Laurent Arnaud, Lise Artigue, Cyril Aubry, Pierre Ayotte, Guislain Bécu, Simon Bélanger, Ronald Benner, Henry C. Bittig, Annick Bricaud, Éric Brossier, Flavienne Bruyant, Laurent Chauvaud, Debra Christiansen-Stowe, Hervé Claustre, Véronique Cornet-Barthaux, Pierre Coupel, Christine Cox, Aurelie Delaforge, Thibaud Dezutter, Céline Dimier, Florent Domine, Francis Dufour, Christiane Dufresne, Dany Dumont, Jens Ehn, Brent Else, Joannie Ferland, Marie-Hélène Forget, Louis Fortier, Martí Galí, Virginie Galindo, Morgane Gallinari, Nicole Garcia, Catherine Gérikas Ribeiro, Margaux Gourdal, Priscilla Gourvil, Clemence Goyens, Pierre-Luc Grondin, Pascal Guillot, Caroline Guilmette, Marie-Noëlle Houssais, Fabien Joux, Léo Lacour, Thomas Lacour, Augustin Lafond, José Lagunas, Catherine Lalande, Julien Laliberté, Simon Lambert-Girard, Jade Larivière, Johann Lavaud, Anita LeBaron, Karine Leblanc, Florence Le Gall, Justine Legras, Mélanie Lemire, Maurice Levasseur, Edouard Leymarie, Aude Leynaert, Adriana Lopes dos Santos, Antonio Lourenço, David Mah, Claudie Marec, Dominique Marie, Nicolas Martin, Constance Marty, Sabine Marty, Guillaume Massé, Atsushi Matsuoka, Lisa Matthes, Brivaela Moriceau, Pierre-Emmanuel Muller, Christopher-John Mundy, Griet Neukermans, Laurent Oziel, Christos Panagiotopoulos, Jean-Jacques Pangrazi, Ghislain Picard, Marc Picheral, France Pinczon du Sel, Nicole Pogorzelec, Ian Probert, Bernard Quéguiner, Patrick Raimbault, Joséphine Ras, Eric Rehm, Erin Reimer, Jean-François Rontani, Søren Rysgaard, Blanche Saint-Béat, Makoto Sampei, Julie Sansoulet, Catherine Schmechtig, Sabine Schmidt, Richard Sempéré, Caroline Sévigny, Yuan Shen, Margot Tragin, Jean-Éric Tremblay, Daniel Vaulot, Gauthier Verin, Frédéric Vivier, Anda Vladoiu, Jeremy Whitehead, and Marcel Babin
Earth Syst. Sci. Data, 12, 151–176, https://doi.org/10.5194/essd-12-151-2020, https://doi.org/10.5194/essd-12-151-2020, 2020
Short summary
Short summary
The Green Edge initiative was developed to understand the processes controlling the primary productivity and the fate of organic matter produced during the Arctic spring bloom (PSB). In this article, we present an overview of an extensive and comprehensive dataset acquired during two expeditions conducted in 2015 and 2016 on landfast ice southeast of Qikiqtarjuaq Island in Baffin Bay.
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
Short summary
Short summary
Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
Adrien Michel, Tristan Brauchli, Michael Lehning, Bettina Schaefli, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 24, 115–142, https://doi.org/10.5194/hess-24-115-2020, https://doi.org/10.5194/hess-24-115-2020, 2020
Short summary
Short summary
This study constitutes the first comprehensive analysis of river
temperature in Switzerland combined with discharge and key meteorological variables, such as air temperature and precipitation. It is also the first study to discuss the large-scale seasonal behaviour of stream temperature in Switzerland. This research shows the clear increase of river temperature in Switzerland over the last few decades and may serve as a solid reference for future climate change scenario simulations.
Varun Sharma, Louise Braud, and Michael Lehning
The Cryosphere, 13, 3239–3260, https://doi.org/10.5194/tc-13-3239-2019, https://doi.org/10.5194/tc-13-3239-2019, 2019
Short summary
Short summary
Snow surfaces, under the action of wind, form beautiful shapes such as waves and dunes. This study is the first ever study to simulate these shapes using a state-of-the-art numerical modelling tool. While these beautiful and ephemeral shapes on snow surfaces are fascinating from a purely aesthetic point of view, they are also critical in regulating the transfer of heat and mass between the atmosphere and snowpacks, thus being of huge importance to the Earth system.
Audrey Maheu, Islem Hajji, François Anctil, Daniel F. Nadeau, and René Therrien
Hydrol. Earth Syst. Sci., 23, 3843–3863, https://doi.org/10.5194/hess-23-3843-2019, https://doi.org/10.5194/hess-23-3843-2019, 2019
Short summary
Short summary
We tested a new method to simulate terrestrial evaporation in a hydrological model. Given physical constraints imposed by this model, it should help avoid the overestimation of terrestrial evaporation in climate change assessments. We show the good performance of the model by comparing simulated terrestrial evaporation to observations at three sites with different climates and vegetation. Overall, this research proposes a method that will improve our ability to make streamflow projections.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
Short summary
Short summary
Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Gauthier Verin, Florent Dominé, Marcel Babin, Ghislain Picard, and Laurent Arnaud
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-113, https://doi.org/10.5194/tc-2019-113, 2019
Publication in TC not foreseen
Short summary
Short summary
The results of two sampling campaigns conducted on landfast sea ice in Baffin Bay show that the melt season can be divided into four main phases during which surface albedo and snow properties show distinct signatures. A radiative transfer model was used to successfully reconstruct the albedo from snow properties. This modeling work highlights that only little changes on the very surface of the snowpack are able to dramatically change the albedo, a key element for the energy budget of sea ice.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
Short summary
Short summary
This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Varun Sharma, Francesco Comola, and Michael Lehning
The Cryosphere, 12, 3499–3509, https://doi.org/10.5194/tc-12-3499-2018, https://doi.org/10.5194/tc-12-3499-2018, 2018
Short summary
Short summary
The Thorpe-Mason (TM) model describes how an ice grain sublimates during aeolian transport. We revisit this classic model using simple numerical experiments and discover that for many common scenarios, the model is likely to underestimate the amount of ice loss. Extending this result to drifting and blowing snow using high-resolution turbulent flow simulations, the study shows that current estimates for ice loss due to sublimation in regions such as Antarctica need to be significantly updated.
Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning
The Cryosphere, 12, 3137–3160, https://doi.org/10.5194/tc-12-3137-2018, https://doi.org/10.5194/tc-12-3137-2018, 2018
Short summary
Short summary
A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.
Christian Gabriel Sommer, Nander Wever, Charles Fierz, and Michael Lehning
The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, https://doi.org/10.5194/tc-12-2923-2018, 2018
Short summary
Short summary
Wind packing is how wind produces hard crusts at the surface of the snowpack. This is relevant for the local mass balance in polar regions. However, not much is known about this process and it is difficult to capture its high spatial and temporal variability. A wind-packing event was measured in Antarctica. It could be quantified how drifting snow leads to wind packing and generates barchan dunes. The documentation of these deposition dynamics is an important step in understanding polar snow.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
Short summary
Short summary
This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Thomas Grünewald, Fabian Wolfsperger, and Michael Lehning
The Cryosphere, 12, 385–400, https://doi.org/10.5194/tc-12-385-2018, https://doi.org/10.5194/tc-12-385-2018, 2018
Short summary
Short summary
Snow farming is the conservation of snow during summer. Large snow piles are covered with a sawdust insulation layer, reducing melt and guaranteeing a specific amount of available snow in autumn, independent of the weather conditions. Snow volume changes in two heaps were monitored, showing that about a third of the snow was lost. Model simulations confirmed the large effect of the insulation on energy balance and melt. The model can now be used as a tool to examine future snow-farming projects.
Mathieu Barrere, Florent Domine, Bertrand Decharme, Samuel Morin, Vincent Vionnet, and Matthieu Lafaysse
Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, https://doi.org/10.5194/gmd-10-3461-2017, 2017
Short summary
Short summary
Global warming projections still suffer from a limited representation of the permafrost–carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Nander Wever, Francesco Comola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 21, 4053–4071, https://doi.org/10.5194/hess-21-4053-2017, https://doi.org/10.5194/hess-21-4053-2017, 2017
Short summary
Short summary
The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the
linkage between the snow cover, soil and discharge in the stream network. Simulations of soil moisture and streamflow were performed and compared with observations. It was found that discharge at the catchment outlet during intense rainfall or snowmelt periods correlates positively with the initial soil moisture state, in both measurements and simulations.
Gautier Davesne, Daniel Fortier, Florent Domine, and James T. Gray
The Cryosphere, 11, 1351–1370, https://doi.org/10.5194/tc-11-1351-2017, https://doi.org/10.5194/tc-11-1351-2017, 2017
Short summary
Short summary
This study presents data from Mont Jacques-Cartier, the highest summit in the Appalachians of south-eastern Canada, to demonstrate that the occurrence of contemporary permafrost body is associated with a very thin and wind-packed winter snow cover which brings local azonal topo-climatic conditions on the dome-shaped summit. This study is an important preliminary step in modelling the regional spatial distribution of permafrost on the highest summits in eastern North America.
Sebastian Würzer, Nander Wever, Roman Juras, Michael Lehning, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 1741–1756, https://doi.org/10.5194/hess-21-1741-2017, https://doi.org/10.5194/hess-21-1741-2017, 2017
Short summary
Short summary
We discuss a dual-domain water transport model in a physics-based snowpack model to account for preferential flow (PF) in addition to matrix flow. So far no operationally used snow model has explicitly accounted for PF. The new approach is compared to existing water transport models and validated against in situ data from sprinkling and natural rain-on-snow (ROS) events. Our work demonstrates the benefit of considering PF in modelling hourly snowpack runoff, especially during ROS conditions.
Anna Haberkorn, Nander Wever, Martin Hoelzle, Marcia Phillips, Robert Kenner, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 585–607, https://doi.org/10.5194/tc-11-585-2017, https://doi.org/10.5194/tc-11-585-2017, 2017
Short summary
Short summary
The effects of permafrost degradation on rock slope stability in the Alps affect people and infrastructure. Modelling the evolution of permafrost is therefore of great importance. However, the snow cover has generally not been taken into account in model studies of steep, rugged rock walls. Thus, we present a distributed model study on the influence of the snow cover on rock temperatures. The promising results are discussed against detailed rock temperature measurements and snow depth data.
Christoph Marty, Sebastian Schlögl, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 517–529, https://doi.org/10.5194/tc-11-517-2017, https://doi.org/10.5194/tc-11-517-2017, 2017
Short summary
Short summary
We simulate the future snow cover in the Alps with the help of a snow model, which is fed by projected temperature and precipitation changes from a large set of climate models. The results demonstrate that snow below 1000 m is probably a rare guest at the end of the century. Moreover, even above 3000 m the simulations show a drastic decrease in snow depth. However, the results reveal that the projected snow cover reduction can be mitigated by 50 % if we manage to keep global warming below 2°.
Aurélien Gallice, Mathias Bavay, Tristan Brauchli, Francesco Comola, Michael Lehning, and Hendrik Huwald
Geosci. Model Dev., 9, 4491–4519, https://doi.org/10.5194/gmd-9-4491-2016, https://doi.org/10.5194/gmd-9-4491-2016, 2016
Short summary
Short summary
This paper presents the improvements brought to an existing model for discharge and temperature prediction in Alpine streams. Compared to the original model version, it is now possible to choose between various alternatives to simulate certain parts of the water cycle, such as the technique used to transfer water along the stream network. The paper includes an example of application of the model over an Alpine catchment in Switzerland.
Florent Domine, Mathieu Barrere, and Samuel Morin
Biogeosciences, 13, 6471–6486, https://doi.org/10.5194/bg-13-6471-2016, https://doi.org/10.5194/bg-13-6471-2016, 2016
Short summary
Short summary
Warming-induced shrub growth in the Arctic traps snow and modifies snow properties, hence the permafrost thermal regime. In the Canadian high Arctic, we measured snow physical properties in the presence and absence of willow shrubs (Salix richardsonii). Shrubs dramatically reduce snow density and thermal conductivity, seriously limiting soil winter cooling. Simulations taking into account only winter changes show that shrub growth leads to a ground winter warming of up to 13 °C.
Nander Wever, Sebastian Würzer, Charles Fierz, and Michael Lehning
The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, https://doi.org/10.5194/tc-10-2731-2016, 2016
Short summary
Short summary
The study presents a dual domain approach to simulate liquid water flow in snow using the 1-D physics based snow cover model SNOWPACK. In this approach, the pore space is separated into a part for matrix flow and a part that represents preferential flow. Using this approach, water can percolate sub-freezing snow and form dense (ice) layers. A comparison with snow pits shows that some of the observed ice layers were reproduced by the model while others remain challenging to simulate.
Florent Domine, Mathieu Barrere, and Denis Sarrazin
The Cryosphere, 10, 2573–2588, https://doi.org/10.5194/tc-10-2573-2016, https://doi.org/10.5194/tc-10-2573-2016, 2016
Short summary
Short summary
The thermal conductivity (TC) of the snow and top soil greatly impacts the permafrost energy budget. We report the first winter-long monitoring of snow and soil TC in the high Arctic.
The data and field observations show the formation of a highly insulating basal depth hoar layer overlaid by a more conductive wind slab. Detailed snow physics models developed for alpine snow cannot reproduce observations because they neglect the strong upward vertical water vapor flux prevailing in Arctic snow.
Rebecca Mott, Enrico Paterna, Stefan Horender, Philip Crivelli, and Michael Lehning
The Cryosphere, 10, 445–458, https://doi.org/10.5194/tc-10-445-2016, https://doi.org/10.5194/tc-10-445-2016, 2016
Short summary
Short summary
For the first time, this contribution investigates atmospheric decoupling above melting snow in a wind tunnel study. High-resolution vertical profiles of
sensible heat fluxes are measured directly over the melting snow patch.
The study shows that atmospheric decoupling is strongly increased in topographic sheltering but only for low wind velocities. Then turbulent mixing close to the surface is strongly suppressed, facilitating the formation of cold-air pooling in local depressions.
N. Wever, L. Schmid, A. Heilig, O. Eisen, C. Fierz, and M. Lehning
The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, https://doi.org/10.5194/tc-9-2271-2015, 2015
Short summary
Short summary
A verification of the physics based SNOWPACK model with field observations showed that typical snowpack properties like density and temperature are adequately simulated. Also two water transport schemes were verified, showing that although Richards equation improves snowpack runoff and several aspects of the internal snowpack structure, the bucket scheme appeared to have a higher agreement with the snow microstructure. The choice of water transport scheme may depend on the intended application.
W. Steinkogler, B. Sovilla, and M. Lehning
The Cryosphere, 9, 1819–1830, https://doi.org/10.5194/tc-9-1819-2015, https://doi.org/10.5194/tc-9-1819-2015, 2015
Short summary
Short summary
Infrared radiation thermography (IRT) was used to assess the surface temperature of avalanches with high spatial resolution. Thermal energy increase due to friction was mainly depending on the elevation drop of the avalanche. Warming due to entrainment was very specific to the individual avalanche and depends on the temperature of the snow along the path and the erosion depth. The warmest temperatures were located in the deposits of the dense core.
A. Gallice, B. Schaefli, M. Lehning, M. B. Parlange, and H. Huwald
Hydrol. Earth Syst. Sci., 19, 3727–3753, https://doi.org/10.5194/hess-19-3727-2015, https://doi.org/10.5194/hess-19-3727-2015, 2015
Short summary
Short summary
This study presents a new model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country. Contrary to the other approaches developed to date, which are usually based on standard regression techniques, our model makes use of the understanding that we have about the physics controlling stream temperature. On top of its accuracy being comparable to that of the other models, it can be used to gain some knowledge about the stream temperature dynamics
F. Domine, M. Barrere, D. Sarrazin, S. Morin, and L. Arnaud
The Cryosphere, 9, 1265–1276, https://doi.org/10.5194/tc-9-1265-2015, https://doi.org/10.5194/tc-9-1265-2015, 2015
Short summary
Short summary
The thermal conductivity of Arctic snow strongly impacts ground temperature, nutrient recycling and vegetation growth. We have monitored the thermal conductivity of snow in low-Arctic shrub tundra for two consecutive winters using heated needle probes. We observe very different thermal conductivity evolutions in both winters studied, with more extensive melting in the second winter. Results illustrate the effect of vegetation on snow properties and the need to include it in snow physics models.
E. Trujillo and M. Lehning
The Cryosphere, 9, 1249–1264, https://doi.org/10.5194/tc-9-1249-2015, https://doi.org/10.5194/tc-9-1249-2015, 2015
Short summary
Short summary
In this article, we present a methodology for the objective evaluation of the error in capturing mean snow depths from point measurements. We demonstrate, using LIDAR snow depths, how the model can be used for assisting the design of survey strategies such that the error is minimized or an estimation threshold is achieved. Furthermore, the model can be extended to other spatially distributed snow variables (e.g., SWE) whose statistical properties are comparable to those of snow depth.
J. Schwaab, M. Bavay, E. Davin, F. Hagedorn, F. Hüsler, M. Lehning, M. Schneebeli, E. Thürig, and P. Bebi
Biogeosciences, 12, 467–487, https://doi.org/10.5194/bg-12-467-2015, https://doi.org/10.5194/bg-12-467-2015, 2015
T. Grünewald, Y. Bühler, and M. Lehning
The Cryosphere, 8, 2381–2394, https://doi.org/10.5194/tc-8-2381-2014, https://doi.org/10.5194/tc-8-2381-2014, 2014
Short summary
Short summary
Elevation dependencies of snow depth are analysed based on snow depth maps obtained from airborne remote sensing. Elevation gradients are characterised by a specific shape: an increase of snow depth with elevation is followed by a distinct peak at a certain level and a decrease in the highest elevations. We attribute this shape to an increase of precipitation with altitude, which is modified by topographical-induced redistribution processes of the snow on the ground (wind, gravitation).
N. Wever, T. Jonas, C. Fierz, and M. Lehning
Hydrol. Earth Syst. Sci., 18, 4657–4669, https://doi.org/10.5194/hess-18-4657-2014, https://doi.org/10.5194/hess-18-4657-2014, 2014
Short summary
Short summary
We simulated a severe rain-on-snow event in the Swiss Alps in October 2011 with a detailed multi-layer snow cover model. We found a strong modulating effect of the incoming rainfall signal by the snow cover. Initially, water from both rainfall and snow melt was absorbed by the snowpack. But once the snowpack released the stored water, simulated outflow rates exceeded rainfall and snow melt rates. The simulations suggest that structural snowpack changes enhanced the outflow during this event.
J.-C. Gallet, F. Domine, J. Savarino, M. Dumont, and E. Brun
The Cryosphere, 8, 1205–1215, https://doi.org/10.5194/tc-8-1205-2014, https://doi.org/10.5194/tc-8-1205-2014, 2014
J.-C. Gallet, F. Domine, and M. Dumont
The Cryosphere, 8, 1139–1148, https://doi.org/10.5194/tc-8-1139-2014, https://doi.org/10.5194/tc-8-1139-2014, 2014
C. M. Carmagnola, S. Morin, M. Lafaysse, F. Domine, B. Lesaffre, Y. Lejeune, G. Picard, and L. Arnaud
The Cryosphere, 8, 417–437, https://doi.org/10.5194/tc-8-417-2014, https://doi.org/10.5194/tc-8-417-2014, 2014
N. Wever, C. Fierz, C. Mitterer, H. Hirashima, and M. Lehning
The Cryosphere, 8, 257–274, https://doi.org/10.5194/tc-8-257-2014, https://doi.org/10.5194/tc-8-257-2014, 2014
F. Domine, S. Morin, E. Brun, M. Lafaysse, and C. M. Carmagnola
The Cryosphere, 7, 1915–1929, https://doi.org/10.5194/tc-7-1915-2013, https://doi.org/10.5194/tc-7-1915-2013, 2013
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, https://doi.org/10.5194/hess-17-3005-2013, 2013
C. M. Carmagnola, F. Domine, M. Dumont, P. Wright, B. Strellis, M. Bergin, J. Dibb, G. Picard, Q. Libois, L. Arnaud, and S. Morin
The Cryosphere, 7, 1139–1160, https://doi.org/10.5194/tc-7-1139-2013, https://doi.org/10.5194/tc-7-1139-2013, 2013
C. D. Groot Zwaaftink, A. Cagnati, A. Crepaz, C. Fierz, G. Macelloni, M. Valt, and M. Lehning
The Cryosphere, 7, 333–347, https://doi.org/10.5194/tc-7-333-2013, https://doi.org/10.5194/tc-7-333-2013, 2013
Related subject area
Discipline: Snow | Subject: Snow Hydrology
Exploring how Sentinel-1 wet-snow maps can inform fully distributed physically based snowpack models
Towards large-scale daily snow density mapping with spatiotemporally aware model and multi-source data
Drone-based ground-penetrating radar (GPR) application to snow hydrology
Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events
Two-dimensional liquid water flow through snow at the plot scale in continental snowpacks: simulations and field data comparisons
Fractional snow-covered area: scale-independent peak of winter parameterization
Seasonal components of freshwater runoff in Glacier Bay, Alaska: diverse spatial patterns and temporal change
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
The Cryosphere, 18, 5753–5767, https://doi.org/10.5194/tc-18-5753-2024, https://doi.org/10.5194/tc-18-5753-2024, 2024
Short summary
Short summary
We use novel wet-snow maps from Sentinel-1 to evaluate simulations of a snow-hydrological model over Switzerland. These data are complementary to available in situ snow depth observations as they capture a broad diversity of topographic conditions. Wet-snow maps allow us to detect a delayed melt onset in the model, which we resolve thanks to an improved parametrization. This paves the way to further evaluation, calibration, and data assimilation using wet-snow maps.
Huadong Wang, Xueliang Zhang, Pengfeng Xiao, Tao Che, Zhaojun Zheng, Liyun Dai, and Wenbo Luan
The Cryosphere, 17, 33–50, https://doi.org/10.5194/tc-17-33-2023, https://doi.org/10.5194/tc-17-33-2023, 2023
Short summary
Short summary
The geographically and temporally weighted neural network (GTWNN) model is constructed for estimating large-scale daily snow density by integrating satellite, ground, and reanalysis data, which addresses the importance of spatiotemporal heterogeneity and a nonlinear relationship between snow density and impact variables, as well as allows us to understand the spatiotemporal pattern and heterogeneity of snow density in different snow periods and snow cover regions in China from 2013 to 2020.
Eole Valence, Michel Baraer, Eric Rosa, Florent Barbecot, and Chloe Monty
The Cryosphere, 16, 3843–3860, https://doi.org/10.5194/tc-16-3843-2022, https://doi.org/10.5194/tc-16-3843-2022, 2022
Short summary
Short summary
The internal properties of the snow cover shape the annual hygrogram of northern and alpine regions. This study develops a multi-method approach to measure the evolution of snowpack internal properties. The snowpack hydrological property evolution was evaluated with drone-based ground-penetrating radar (GPR) measurements. In addition, the combination of GPR observations and time domain reflectometry measurements is shown to be able to be adapted to monitor the snowpack moisture over winter.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
Short summary
Short summary
Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Ryan W. Webb, Keith Jennings, Stefan Finsterle, and Steven R. Fassnacht
The Cryosphere, 15, 1423–1434, https://doi.org/10.5194/tc-15-1423-2021, https://doi.org/10.5194/tc-15-1423-2021, 2021
Short summary
Short summary
We simulate the flow of liquid water through snow and compare results to field experiments. This process is important because it controls how much and how quickly water will reach our streams and rivers in snowy regions. We found that water can flow large distances downslope through the snow even after the snow has stopped melting. Improved modeling of snowmelt processes will allow us to more accurately estimate available water resources, especially under changing climate conditions.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
Short summary
Short summary
The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Ryan L. Crumley, David F. Hill, Jordan P. Beamer, and Elizabeth R. Holzenthal
The Cryosphere, 13, 1597–1619, https://doi.org/10.5194/tc-13-1597-2019, https://doi.org/10.5194/tc-13-1597-2019, 2019
Short summary
Short summary
In this study we investigate the historical (1980–2015) and projection scenario (2070–2099) components of freshwater runoff to Glacier Bay, Alaska, using a modeling approach. We find that many of the historically snow-dominated watersheds in Glacier Bay National Park and Preserve may transition towards rainfall-dominated hydrographs in a projection scenario under RCP 8.5 conditions. The changes in timing and volume of freshwater entering Glacier Bay will affect bay ecology and hydrochemistry.
Cited articles
Avanzi, F., Hirashima, H., Yamaguchi, S., Katsushima, T., and De Michele, C.: Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments, The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, 2016.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002.
Beaudry, P. and Golding, D.: Snowmelt during rain-on-snow in coastal British Columbia, in: Proceedings of the Western Snow Conference, 19–21 April 1983, Vancouver, Canada, Washinton, USA, 1983, 55–66, 1983.
Berg, N., Osterhuber, R., and Bergman, J.: Rain-induced outflow from deep snowpacks in the central Sierra Nevada, California, Hydrolog. Sci. J., 36, 611–629, https://doi.org/10.1080/02626669109492547, 1991.
Berris, S. N. and Harr, R. D.: Comparative snow accumulation and melt during rainfall in forested and clear-cut plots in the Western Cascades of Oregon, Water Resour. Res., 23, 135–142, https://doi.org/10.1029/WR023i001p00135, 1987.
Bouchard, B., Nadeau, D. F., and Domine, F.: Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest, Hydrol. Process., 36, e14681, https://doi.org/10.1002/hyp.14681, 2022.
Bouchard, B., Nadeau, D. F., Domine, F., Anctil, F., Jonas, T., and Tremblay, É.: How does a warm and low-snow winter impact the snow cover dynamics in a humid and discontinuous boreal forest? An observational study in eastern Canada, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2023-191, in review, 2023a.
Bouchard, B., Nadeau, D. F., Dominé, F., Wever, N., Michel, A., Lehning, M., and Isabelle, P.-E.: Dataset from “Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy”, Zenodo [data set], https://doi.org/10.5281/zenodo.10357451, 2023b.
Bouchard, B., Nadeau, D., Domine, F., Wever, N., Michel, A., Lehning, M., and Isabelle, P.-E.: Source code from the Intercepted Snow Densification development from “Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy”, Zenodo [code], https://doi.org/10.5281/zenodo.11656366, 2024.
Brandt, T. W., Haleakala, K., Hatchett, B. J., and Pan, M.: A Review of the Hydrologic Response Mechanisms During Mountain Rain-on-Snow, Front. Earth Sci., 10, 1–9, https://doi.org/10.3389/feart.2022.791760, 2022.
Bründl, M., Schneebeli, M., and Flühler, H.: Routing of canopy drip in the snowpack below a spruce crown, Hydrol. Process., 13, 49–58, https://doi.org/10.1002/(SICI)1099-1085(199901)13:1<49::AID-HYP700>3.0.CO;2-L, 1999.
Colbeck, S. C.: An overview of seasonal snow metamorphism, Rev. Geophys., 20, 45–61, https://doi.org/10.1029/RG020i001p00045, 1982.
Conger, S. M. and McClung, D. M.: Comparison of density cutters for snow profile observations, J. Glaciol., 55, 163–169, https://doi.org/10.3189/002214309788609038, 2009.
Domine, F., Taillandier, A.-S., Cabanes, A., Douglas, T. A., and Sturm, M.: Three examples where the specific surface area of snow increased over time, The Cryosphere, 3, 31–39, https://doi.org/10.5194/tc-3-31-2009, 2009.
Domine, F., Picard, G., Morin, S., Barrere, M., Madore, J.-B. T., and Langlois, A.: Major Issues in Simulating Some Arctic Snowpack Properties Using Current Detailed Snow Physics Models: Consequences for the Thermal Regime and Water Budget of Permafrost, J. Adv. Model. Earth Sy., 11, 34–44, https://doi.org/10.1029/2018MS001445, 2019.
Eiriksson, D., Whitson, M., Luce, C. H., Marshall, H. P., Bradford, J., Benner, S. G., Black, T., Hetrick, H., and McNamara, J. P.: An evaluation of the hydrologic relevance of lateral flow in snow at hillslope and catchment scales, Hydrol. Process., 27, 640–654, https://doi.org/10.1002/hyp.9666, 2013.
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung, D. M., Nishimura, K., Satyawali, P. K., and Sokratov, S. A.: The International Classification for Seasonal Snow on the Ground (IC-SSG), IHP-VII Technical Documents in Hydrology, UNESCO-IHP, Paris, France83, 2009.
Floyd, W. and Weiler, M.: Measuring snow accumulation and ablation dynamics during rain-on-snow events: innovative measurement techniques, Hydrol. Process., 22, 4805–4812, https://doi.org/10.1002/hyp.7142, 2008.
Friesen, J., Lundquist, J., and Van Stan, J. T.: Evolution of forest precipitation water storage measurement methods, Hydrol. Process., 29, 2504–2520, https://doi.org/10.1002/hyp.10376, 2015.
Garvelmann, J., Pohl, S., and Weiler, M.: Spatio-temporal controls of snowmelt and runoff generation during rain-on-snow events in a mid-latitude mountain catchment, Hydrol. Process., 29, 3649–3664, https://doi.org/10.1002/hyp.10460, 2015.
Gouttevin, I., Lehning, M., Jonas, T., Gustafsson, D., and Mölder, M.: A two-layer canopy model with thermal inertia for an improved snowpack energy balance below needleleaf forest (model SNOWPACK, version 3.2.1, revision 741), Geosci. Model Dev., 8, 2379–2398, https://doi.org/10.5194/gmd-8-2379-2015, 2015.
Grenfell, T. C. and Warren, S. G.: Representation of a nonspherical ice particle by a collection of independent spheres for scattering and absorption of radiation, J. Geophys. Res., 104, 31697–31709, https://doi.org/10.1029/1999JD900496, 1999.
Guillemette, F., Plamondon, A. P., Preìvost, M., and Leìvesque, D.: Rainfall generated stormflow response to clearcutting a boreal forest: peak flow comparison with 50 world-wide basin studies, J. Hydrol., 302, 137–153, https://doi.org/10.1016/j.jhydrol.2004.06.043, 2005.
Hadiwijaya, B., Pepin, S., Isabelle, P.-E., and Nadeau, D. F.: The Dynamics of Transpiration to Evapotranspiration Ratio under Wet and Dry Canopy Conditions in a Humid Boreal Forest, Forests-Sui., 11, 1–25, https://doi.org/10.3390/f11020237, 2020.
Haleakala, K., Brandt, W. T., Hatchett, B. J., Li, D., Lettenmaier, D. P., and Gebremichael, M.: Watershed memory amplified the Oroville rain-on-snow flood of February 2017, P. Natl. Acad. Sci. USA, 2, 1–15, https://doi.org/10.1093/pnasnexus/pgac295, 2023.
Hedstrom, N. R. and Pomeroy, J. W.: Measurements and modelling of snow interception in the boreal forest, Hydrol. Process., 12, 1611–1625, https://doi.org/10.1002/(SICI)1099-1085(199808/09)12:10/11<1611::AID-HYP684>3.0.CO;2-4, 1998.
Hirashima, H., Avanzi, F., and Wever, N.: Wet-Snow Metamorphism Drives the Transition From Preferential to Matrix Flow in Snow, Geophys. Res. Lett., 46, 14548–14557, https://doi.org/10.1029/2019GL084152, 2019.
Höller, P.: The influence of the forest on night-time snow surface temperature, Ann. Glaciol., 32, 217–222, https://doi.org/10.3189/172756401781819256, 2001.
Hotovy, O., Nedelcev, O., and Jenicek, M.: Changes in rain-on-snow events in mountain catchments in the rain–snow transition zone, Hydrol. Sci. J., 68, 572–584, https://doi.org/10.1080/02626667.2023.2177544, 2023.
IPCC: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA, edited by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., https://doi.org/10.1017/9781009325844, 2023.
Isabelle, P.-E., Nadeau, D. F., Asselin, M.-H., Harvey, R., Musselman, K. N., Rousseau, A. N., and Anctil, F.: Solar radiation transmittance of a boreal balsam fir canopy: Spatiotemporal variability and impacts on growing season hydrology, Agric. For. Meteorol., 263, 1–14, https://doi.org/10.1016/j.agrformet.2018.07.022, 2018.
Isabelle, P.-E., Nadeau, D. F., Anctil, F., Rousseau, A. N., Jutras, S., and Music, B.: Impacts of high precipitation on the energy and water budgets of a humid boreal forest, Agric. For. Meteorol., 280, 107813, https://doi.org/10.1016/j.agrformet.2019.107813, 2020.
Jafari, M., Gouttevin, I., Couttet, M., Wever, N., Michel, A., Sharma, V., Rossmann, L., Maass, N., Nicolaus, M., and Lehning, M.: The Impact of Diffusive Water Vapor Transport on Snow Profiles in Deep and Shallow Snow Covers and on Sea Ice, Front. Earth Sci., 8, 1–25, https://doi.org/10.3389/feart.2020.00249, 2020.
Jennings, K. S., Kittel, T. G. F., and Molotch, N. P.: Observations and simulations of the seasonal evolution of snowpack cold content and its relation to snowmelt and the snowpack energy budget, The Cryosphere, 12, 1595–1614, https://doi.org/10.5194/tc-12-1595-2018, 2018.
Jonas, T., Webster, C., Mazzotti, G., and Malle, J.: HPEval: A canopy shortwave radiation transmission model using high-resolution hemispherical images, Agric. For. Meteorol., 284, 107903, https://doi.org/10.1016/j.agrformet.2020.107903, 2020.
Juras, R., Würzer, S., Pavlásek, J., Vitvar, T., and Jonas, T.: Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions, Hydrol. Earth Syst. Sci., 21, 4973–4987, https://doi.org/10.5194/hess-21-4973-2017, 2017.
Kapil, J. C., Prasher, C., Datt, P., and Satyawali, P. K.: Growth of melt-freeze clusters and formation of impeding layers to water flow in snow irradiated by a sun simulator under controlled laboratory conditions, Ann. Glaciol., 51, 19–26, https://doi.org/10.3189/172756410791386599, 2010.
Katsushima, T., Yamaguchi, S., Kumakura, T., and Sato, A.: Experimental analysis of preferential flow in dry snowpack, Cold Reg. Sci. Technol., 85, 206–216, https://doi.org/10.1016/j.coldregions.2012.09.012, 2013.
Kattelmann, R.: Snowmelt lysimeters in the evaluation of snowmelt models, Ann. Glaciol., 31, 406–410, https://doi.org/10.3189/172756400781820048, 2000.
Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J. r., and Mauser, W.: Retrieval of Snow Water Equivalent, Liquid Water Content, and Snow Height of Dry and Wet Snow by Combining GPS Signal Attenuation and Time Delay, Water Resour. Res., 55, 4465–4487, https://doi.org/10.1029/2018WR024431, 2019.
Kontu, A., Lemmetyinen, J., Vehviläinen, J., Leppänen, L., and Pulliainen, J.: Coupling SNOWPACK-modeled grain size parameters with the HUT snow emission model, Remote Sens. Environ., 194, 33–47, https://doi.org/10.1016/j.rse.2016.12.021, 2017.
Krinner, G., Derksen, C., Essery, R., Flanner, M., Hagemann, S., Clark, M., Hall, A., Rott, H., Brutel-Vuilmet, C., Kim, H., Ménard, C. B., Mudryk, L., Thackeray, C., Wang, L., Arduini, G., Balsamo, G., Bartlett, P., Boike, J., Boone, A., Chéruy, F., Colin, J., Cuntz, M., Dai, Y., Decharme, B., Derry, J., Ducharne, A., Dutra, E., Fang, X., Fierz, C., Ghattas, J., Gusev, Y., Haverd, V., Kontu, A., Lafaysse, M., Law, R., Lawrence, D., Li, W., Marke, T., Marks, D., Ménégoz, M., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Raleigh, M. S., Schaedler, G., Semenov, V., Smirnova, T. G., Stacke, T., Strasser, U., Svenson, S., Turkov, D., Wang, T., Wever, N., Yuan, H., Zhou, W., and Zhu, D.: ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks, Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, 2018.
Lehning, M., Fierz, C., and Lundy, C.: An objective snow profile comparison method and its application to SNOWPACK, Cold Reg. Sci. Technol., 33, 253–261, https://doi.org/10.1016/S0165-232X(01)00044-1, 2001.
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning: Part III: Meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, https://doi.org/10.1016/S0165-232X(02)00072-1, 2002a.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002b.
Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T. A., Stähli, M., and Zappa, M.: ALPINE3D: a detailed model of mountain surface processes and its application to snow hydrology, Hydrol. Process., 20, 2111–2128, https://doi.org/10.1002/hyp.6204, 2006.
Lumbrazo, C., Bennett, A., Nijssen, B., and Lundquist, J.: Evaluating Multiple Canopy-Snow Unloading Parameterizations in SUMMA With Time-Lapse Photography Characterized by Citizen Scientists, Water Resour. Res., 58, e2021WR030852, https://doi.org/10.1029/2021WR030852, 2022.
Lundquist, J. D., Dickerson-Lange, S., Gutmann, E., Jonas, T., Lumbrazo, C., and Reynolds, D.: Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities, Hydrol. Process., 35, e14274, https://doi.org/10.1002/hyp.14274, 2021.
MacDonald, J.: Unloading of intercepted snow in conifer forests, M.S. thesis, Department of Geography & Planning University of Saskatchewan Saskatoon, University of Saskatchewan, Saskatoon, Saskatchewan, 94 pp., 2010.
Malle, J., Rutter, N., Mazzotti, G., and Jonas, T.: Shading by trees and fractional snow cover control the subcanopy radiation budget, J. Geophys. Res.-Atmos., 124, 3195–3207, https://doi.org/10.1029/2018JD029908, 2019.
Marks, D., Kimball, J., Tingey, D., and Link, T.: The sensitivity of snowmelt processes to climate conditions and forest cover during rain-on-snow: a case study of the 1996 Pacific Northwest flood, Hydrol. Process., 12, 1569–1587, https://doi.org/10.1002/(SICI)1099-1085(199808/09)12:10/11<1569::AID-HYP682>3.0.CO;2-L, 1998.
Mazzotti, G., Essery, R., Webster, C., Malle, J., and Jonas, T.: Process-level evaluation of a hyper-resolution forest snow model using distributed multisensor observations, Water Resour. Res., 56, e2020WR027572, https://doi.org/10.1029/2020WR027572, 2020.
Mazzotti, G., Nousu, J.-P., Vionnet, V., Jonas, T., Nheili, R., and Lafaysse, M.: Exploring the potential of forest snow modelling at the tree and snowpack layer scale, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2781, 2023.
McCabe, G. J., Clark, M. P., and Hay, L. E.: Rain-on-snow events in the western United States, B. Am. Meteorol. Soc., 88, 319–328, https://doi.org/10.1175/BAMS-88-3-319, 2007.
Molotch, N. P., Barnard, D. M., Burns, S. P., and Painter, T. H.: Measuring spatiotemporal variation in snow optical grain size under a subalpine forest canopy using contact spectroscopy, Water Resour. Res., 52, 7513–7522, https://doi.org/10.1002/2016WR018954, 2016.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Musselman, K. N., Molotch, N. P., and Brooks, P. D.: Effects of vegetation on snow accumulation and ablation in a mid-latitude sub-alpine forest, Hydrol. Process., 22, 2767–2776, https://doi.org/10.1002/hyp.7050, 2008.
Musselman, K. N., Lehner, F., Ikeda, K., Clark, M. P., Prein, A. F., Liu, C., Barlage, M., and Rasmussen, R.: Projected increases and shifts in rain-on-snow flood risk over western North America, Nat. Clim. Change, 8, 808–812, https://doi.org/10.1038/s41558-018-0236-4, 2018.
Parajuli, A., Nadeau, D. F., Anctil, F., Parent, A.-C., Bouchard, B., Girard, M., and Jutras, S.: Exploring the spatiotemporal variability of the snow water equivalent in a small boreal forest catchment through observation and modelling, Hydrol. Process., 34, 2628–2644, https://doi.org/10.1002/hyp.13756, 2020.
Pierre, A., Jutras, S., Smith, C., Kochendorfer, J., Fortin, V., and Anctil, F.: Evaluation of catch efficiency transfer functions for unshielded and single-alter-shielded solid precipitation measurements, J. Atmos. Ocean. Tech., 36, 865–881, https://doi.org/10.1175/JTECH-D-18-0112.1, 2019.
Pomeroy, J. W., Parviainen, J., Hedstrom, N., and Gray, D. M.: Coupled modelling of forest snow interception and sublimation, Hydrol. Process., 12, 2317–2337, https://doi.org/10.1002/(SICI)1099-1085(199812)12:15<2317::AID-HYP799>3.0.CO;2-X, 1998.
Pomeroy, J. W., Gray, D. M., Hedstrom, N. R., and Janowicz, J. R.: Prediction of seasonal snow accumulation in cold climate forests, Hydrol. Process., 16, 3543–3558, https://doi.org/10.1002/hyp.1228, 2002.
Quéno, L., Fierz, C., van Herwijnen, A., Longridge, D., and Wever, N.: Deep ice layer formation in an alpine snowpack: monitoring and modeling, The Cryosphere, 14, 3449–3464, https://doi.org/10.5194/tc-14-3449-2020, 2020.
Raleigh, M. S., Gutmann, E. D., Van Stan, J. T., Burns, S. P., Blanken, P. D., and Small, E. E.: Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring, Water Resour. Res., 58, e2021WR030972, https://doi.org/10.1029/2021WR030972, 2022.
Rasmus, S., Grönholm, T., Lehning, M., Rasmus, K., and Kulmala, M.: Validation of the SNOWPACK model in five different snow zones in Finland, Boreal Environ. Res., 12, 467–488, 2007.
Rodell, M., Houser, P. R., Berg, A. A., and Famiglietti, J. S.: Evaluation of 10 Methods for Initializing a Land Surface Model, J. Hydrometeorol., 6, 146–155, https://doi.org/10.1175/JHM414.1, 2005.
Rössler, O., Froidevaux, P., Börst, U., Rickli, R., Martius, O., and Weingartner, R.: Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?, Hydrol. Earth Syst. Sci., 18, 2265–2285, https://doi.org/10.5194/hess-18-2265-2014, 2014.
Rutter, N., Essery, R., Pomeroy, J., Altimir, N., Andreadis, K., Baker, I., Barr, A., Bartlett, P., Boone, A., Deng, H., Douville, H., Dutra, E., Elder, K., Ellis, C., Feng, X., Gelfan, A., Goodbody, A., Gusev, Y., Gustafsson, D., Hellström, R., Hirabayashi, Y., Hirota, T., Jonas, T., Koren, V., Kuragina, A., Lettenmaier, D., Li, W.-P., Luce, C., Martin, E., Nasonova, O., Pumpanen, J., Pyles, R. D., Samuelsson, P., Sandells, M., Schädler, G., Shmakin, A., Smirnova, T. G., Stähli, M., Stöckli, R., Strasser, U., Su, H., Suzuki, K., Takata, K., Tanaka, K., Thompson, E., Vesala, T., Viterbo, P., Wiltshire, A., Xia, K., Xue, Y., and Yamazaki, T.: Evaluation of forest snow processes models (SnowMIP2), J. Geophys. Res.-Atmos., 114, 1–18, https://doi.org/10.1029/2008JD011063, 2009.
Schmidt, R. A. and Gluns, D. R.: Snowfall interception on branches of three conifer species, Can. J. Forest Res., 21, 1262–1269, https://doi.org/10.1139/x91-176, 1991.
Schneebeli, M.: Development and stability of preferential flow paths in a layered snowpack, in: Proceedings of IAHS Publications-Series and Reports-Intern Assoc Hydrological Sciences, Boulder, USA, 1995, 89–96, July 1995.
Singh, P., Spitzbart, G., Hübl, H., and Weinmeister, H. W.: Hydrological response of snowpack under rain-on-snow events: a field study, J. Hydrol., 202, 1–20, https://doi.org/10.1016/S0022-1694(97)00004-8, 1997.
Storck, P., Lettenmaier, D. P., and Bolton, S. M.: Measurement of snow interception and canopy effects on snow accumulation and melt in a mountainous maritime climate, Oregon, United States, Water Resour. Res., 38, 5-1–5-16, https://doi.org/10.1029/2002WR001281, 2002.
Teich, M., Giunta, A. D., Hagenmuller, P., Bebi, P., Schneebeli, M., and Jenkins, M. J.: Effects of bark beetle attacks on forest snowpack and avalanche formation - Implications for protection forest management, Forest Ecol. Manag., 438, 186–203, https://doi.org/10.1016/j.foreco.2019.01.052, 2019.
Todt, M., Rutter, N., Fletcher, C. G., Wake, L. M., Bartlett, P. A., Jonas, T., Kropp, H., Loranty, M. M., and Webster, C.: Simulation of Longwave Enhancement in Boreal and Montane Forests, J. Geophys. Res.-Atmos., 123, 731–713, https://doi.org/10.1029/2018JD028719, 2018.
Trubilowicz, J. W. and Moore, R. D.: Quantifying the role of the snowpack in generating water available for run-off during rain-on-snow events from snow pillow records, Hydrol. Process., 31, 4136–4150, https://doi.org/10.1002/hyp.11310, 2017.
van Gardingen, P. R., Jackson, G. E., Hernandez-Daumas, S., Russell, G., and Sharp, L.: Leaf area index estimates obtained for clumped canopies using hemispherical photography, Agric. For. Meteorol., 94, 243–257, https://doi.org/10.1016/S0168-1923(99)00018-0, 1999.
Varhola, A., Coops, N. C., Weiler, M., and Moore, R. D.: Forest canopy effects on snow accumulation and ablation: An integrative review of empirical results, J. Hydrol., 392, 219–233, https://doi.org/10.1016/j.jhydrol.2010.08.009, 2010.
Vincent, L., Lejeune, Y., Lafaysse, M., Boone, A., Le Gac, E., Coulaud, C., Freche, G., and Sicart, J.-E.: Interception of snowfall by the trees is the main challenge for snowpack simulations under forests, in: Proceedings of the International Snow Science Workshop, 7–12 October 2018, Innsbruck, Austria, 2018, 705–710, 2018.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Waldner, P. A., Schneebeli, M., Schultze-Zimmermann, U., and Flühler, H.: Effect of snow structure on water flow and solute transport, Hydrol. Process., 18, 1271–1290, https://doi.org/10.1002/hyp.1401, 2004.
Wayand, N. E., Lundquist, J. D., and Clark, M. P.: Modeling the influence of hypsometry, vegetation, and storm energy on snowmelt contributions to basins during rain-on-snow floods, Water Resour. Res., 51, 8551–8569, https://doi.org/10.1002/2014WR016576, 2015.
Webb, R. W., Fassnacht, S. R., Gooseff, M. N., and Webb, S. W.: The Presence of Hydraulic Barriers in Layered Snowpacks: TOUGH2 Simulations and Estimated Diversion Lengths, Transport. Porous Med., 123, 457–476, https://doi.org/10.1007/s11242-018-1079-1, 2018a.
Webb, R. W., Williams, M. W., and Erickson, T. A.: The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters, Water Resour. Res., 54, 1146, https://doi.org/10.1002/2017WR020866, 2018b.
Wever, N., Fierz, C., Mitterer, C., Hirashima, H., and Lehning, M.: Solving Richards Equation for snow improves snowpack meltwater runoff estimations in detailed multi-layer snowpack model, The Cryosphere, 8, 257–274, https://doi.org/10.5194/tc-8-257-2014, 2014.
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M.: Verification of the multi-layer SNOWPACK model with different water transport schemes, The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, 2015.
Wever, N., Würzer, S., Fierz, C., and Lehning, M.: Simulating ice layer formation under the presence of preferential flow in layered snowpacks, The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, 2016.
Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053–4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.
Würzer, S., Jonas, T., Wever, N., and Lehning, M.: Influence of Initial Snowpack Properties on Runoff Formation during Rain-on-Snow Events, J. Hydrometeorol., 17, 1801–1815, https://doi.org/10.1175/JHM-D-15-0181.1, 2016.
Würzer, S., Wever, N., Juras, R., Lehning, M., and Jonas, T.: Modelling liquid water transport in snow under rain-on-snow conditions – considering preferential flow, Hydrol. Earth Syst. Sci., 21, 1741–1756, https://doi.org/10.5194/hess-21-1741-2017, 2017.
Zaqout, T., Andradóttir, H. Ó., and Sörensen, J.: Trends in soil frost formation in a warming maritime climate and the impacts on urban flood risk, J. Hydrol., 617, 128978, https://doi.org/10.1016/j.jhydrol.2022.128978, 2023.
Short summary
Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow (ROS) events lead to the formation of melt–freeze layers and that preferential flow is an important water transport mechanism in the sub-canopy snowpack. Simulations with SNOWPACK generally show good agreement with observations, except for the reproduction of melt–freeze layers. This was improved by simulating intercepted snow microstructure evolution, which also modulates ROS-induced runoff.
Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow...