Articles | Volume 28, issue 12
https://doi.org/10.5194/hess-28-2745-2024
© 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/hess-28-2745-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Jun 2024
Research article |
| 27 Jun 2024
| 27 Jun 2024
How does a warm and low-snow winter impact the snow cover dynamics in a humid and discontinuous boreal forest? Insights from observations and modeling in eastern Canada
Benjamin Bouchard
CORRESPONDING AUTHOR
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
CentrEau – 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 – 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
François Anctil
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
CentrEau – Water Research Centre, Université Laval, Québec, G1V 0A6, Canada
Tobias Jonas
WSL Institute for Snow and Avalanche Research (SLF), 7260 Davos Dorf, Switzerland
Étienne Tremblay
Department of Civil and Water Engineering, Université Laval, Québec, G1V 0A6, Canada
Related authors
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.
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, Nander Wever, Adrien Michel, Michael Lehning, and Pierre-Erik Isabelle
The Cryosphere, 18, 2783–2807, https://doi.org/10.5194/tc-18-2783-2024, https://doi.org/10.5194/tc-18-2783-2024, 2024
Short summary
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.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
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 past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
EGUsphere, https://doi.org/10.5194/egusphere-2024-2546, https://doi.org/10.5194/egusphere-2024-2546, 2024
Short summary
Short summary
How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
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.
Giulia Mazzotti, Jari-Pekka Nousu, Vincent Vionnet, Tobias Jonas, Rafife Nheili, and Matthieu Lafaysse
The Cryosphere, 18, 4607–4632, https://doi.org/10.5194/tc-18-4607-2024, https://doi.org/10.5194/tc-18-4607-2024, 2024
Short summary
Short summary
As many boreal and alpine forests have seasonal snow, models are needed to predict forest snow under future environmental conditions. We have created a new forest snow model by combining existing, very detailed model components for the canopy and the snowpack. We applied it to forests in Switzerland and Finland and showed how complex forest cover leads to a snowpack layering that is very variable in space and time because different processes prevail at different locations in the forest.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-374, https://doi.org/10.5194/essd-2024-374, 2024
Preprint under review for ESSD
Short summary
Short summary
In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land-surface, and hydrological models, with potential applications in similar high-alpine catchments.
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.
Kh Rahat Usman, Rodolfo Alvarado Montero, Tadros Ghobrial, François Anctil, and Arnejan van Loenen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-116, https://doi.org/10.5194/gmd-2024-116, 2024
Preprint under review for GMD
Short summary
Short summary
Rivers in cold climate regions such as Canada undergo freeze up during winters which makes the estimation forecasting of under-ice discharge very challenging and uncertain since there is no reliable method other than direct measurements. The current study explored the potential of deploying a coupled modelling framework for the estimation and forecasting of this parameter. The framework showed promising potential in addressing the challenge of estimating and forecasting the under-ice discharge.
Johanna Teresa Malle, Giulia Mazzotti, Dirk Nikolaus Karger, and Tobias Jonas
Earth Syst. Dynam., 15, 1073–1115, https://doi.org/10.5194/esd-15-1073-2024, https://doi.org/10.5194/esd-15-1073-2024, 2024
Short summary
Short summary
Land surface processes are crucial for the exchange of carbon, nitrogen, and energy in the Earth system. Using meteorological and land use data, we found that higher resolution improved not only the model representation of snow cover but also plant productivity and that water returned to the atmosphere. Only by combining high-resolution models with high-quality input data can we accurately represent complex spatially heterogeneous processes and improve our understanding of the Earth system.
Louis Quéno, Rebecca Mott, Paul Morin, Bertrand Cluzet, Giulia Mazzotti, and Tobias Jonas
The Cryosphere, 18, 3533–3557, https://doi.org/10.5194/tc-18-3533-2024, https://doi.org/10.5194/tc-18-3533-2024, 2024
Short summary
Short summary
Snow redistribution by wind and avalanches strongly influences snow hydrology in mountains. This study presents a novel modelling approach to best represent these processes in an operational context. The evaluation of the simulations against airborne snow depth measurements showed remarkable improvement in the snow distribution in mountains of the eastern Swiss Alps, with a representation of snow accumulation and erosion areas, suggesting promising benefits for operational snow melt forecasts.
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.
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, Nander Wever, Adrien Michel, Michael Lehning, and Pierre-Erik Isabelle
The Cryosphere, 18, 2783–2807, https://doi.org/10.5194/tc-18-2783-2024, https://doi.org/10.5194/tc-18-2783-2024, 2024
Short summary
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.
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
Preprint 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.
Florian Zellweger, Eric Sulmoni, Johanna T. Malle, Andri Baltensweiler, Tobias Jonas, Niklaus E. Zimmermann, Christian Ginzler, Dirk Nikolaus Karger, Pieter De Frenne, David Frey, and Clare Webster
Biogeosciences, 21, 605–623, https://doi.org/10.5194/bg-21-605-2024, https://doi.org/10.5194/bg-21-605-2024, 2024
Short summary
Short summary
The microclimatic conditions experienced by organisms living close to the ground are not well represented in currently used climate datasets derived from weather stations. Therefore, we measured and mapped ground microclimate temperatures at 10 m spatial resolution across Switzerland using a novel radiation model. Our results reveal a high variability in microclimates across different habitats and will help to better understand climate and land use impacts on biodiversity and ecosystems.
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.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci., 27, 2375–2395, https://doi.org/10.5194/hess-27-2375-2023, https://doi.org/10.5194/hess-27-2375-2023, 2023
Short summary
Short summary
A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm that the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. The proposed approach supports the participation of end-users in interpreting the impact of climate change on water resources.
Giulia Mazzotti, Clare Webster, Louis Quéno, Bertrand Cluzet, and Tobias Jonas
Hydrol. Earth Syst. Sci., 27, 2099–2121, https://doi.org/10.5194/hess-27-2099-2023, https://doi.org/10.5194/hess-27-2099-2023, 2023
Short summary
Short summary
This study analyses snow cover evolution in mountainous forested terrain based on 2 m resolution simulations from a process-based model. We show that snow accumulation patterns are controlled by canopy structure, but topographic shading modulates the timing of melt onset, and variability in weather can cause snow accumulation and melt patterns to vary between years. These findings advance our ability to predict how snow regimes will react to rising temperatures and forest disturbances.
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.
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.
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.
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022, https://doi.org/10.5194/hess-26-1001-2022, 2022
Short summary
Short summary
The performance of the non-dominated sorting genetic algorithm II (NSGA-II) is compared with a conventional post-processing method of affine kernel dressing. NSGA-II showed its superiority in improving the forecast skill and communicating trade-offs with end-users. It allows the enhancement of the forecast quality since it allows for setting multiple specific objectives from scratch. This flexibility should be considered as a reason to implement hydrologic ensemble prediction systems (H-EPSs).
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
Short summary
Short summary
Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos
Hydrol. Earth Syst. Sci., 26, 197–220, https://doi.org/10.5194/hess-26-197-2022, https://doi.org/10.5194/hess-26-197-2022, 2022
Short summary
Short summary
We investigated how a precipitation post-processor interacts with other tools for uncertainty quantification in a hydrometeorological forecasting chain. Four systems were implemented to generate 7 d ensemble streamflow forecasts, which vary from partial to total uncertainty estimation. Overall analysis showed that post-processing and initial condition estimation ensure the most skill improvements, in some cases even better than a system that considers all sources of uncertainty.
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.
Simon Ricard, Philippe Lucas-Picher, and François Anctil
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-451, https://doi.org/10.5194/hess-2021-451, 2021
Revised manuscript not accepted
Short summary
Short summary
We propose a simplified hydroclimatic modelling workflow for producing hydrologic scenarios without resorting to meteorological observations. This innovative approach preserves trends and physical consistency between simulated climate variables, allows the implementation of modelling cascades despite observation scarcity, and supports the participation of end-users in producing and interpreting climate change impacts on water resources.
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.
Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil
Hydrol. Earth Syst. Sci., 25, 4611–4629, https://doi.org/10.5194/hess-25-4611-2021, https://doi.org/10.5194/hess-25-4611-2021, 2021
Short summary
Short summary
The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.
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.
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.
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.
Marius G. Floriancic, Wouter R. Berghuijs, Tobias Jonas, James W. Kirchner, and Peter Molnar
Hydrol. Earth Syst. Sci., 24, 5423–5438, https://doi.org/10.5194/hess-24-5423-2020, https://doi.org/10.5194/hess-24-5423-2020, 2020
Short summary
Short summary
Low river flows affect societies and ecosystems. Here we study how precipitation and potential evapotranspiration shape low flows across a network of 380 Swiss catchments. Low flows in these rivers typically result from below-average precipitation and above-average potential evapotranspiration. Extreme low flows result from long periods of the combined effects of both drivers.
Antoine Thiboult, Gregory Seiller, Carine Poncelet, and François Anctil
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-6, https://doi.org/10.5194/hess-2020-6, 2020
Preprint withdrawn
Short summary
Short summary
HOOPLA, the HydrOlOgical Prediction LAboratory, is a toolbox that converts precipitation into river runoff. It relies on numerical models to compute snow accumulation and melting, water loss to the atmosphere, and the main on-land water cycle processes. HOOPLA includes several techniques to handle forecast uncertainty. In particular, it adopts a probabilistic approach to describe the model structure, the initial condition, and the meteorological uncertainties.
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.
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.
Roman Juras, Sebastian Würzer, Jirka Pavlásek, Tomáš Vitvar, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 4973–4987, https://doi.org/10.5194/hess-21-4973-2017, https://doi.org/10.5194/hess-21-4973-2017, 2017
Short summary
Short summary
This research investigates the rainwater dynamics in the snowpack under artificial rain-on-snow events. Deuterium-enriched water was sprayed on the isolated snowpack and rainwater was further identified in the runoff. We found that runoff from cold snowpack was created faster than from the ripe snowpack. Runoff from the cold snowpack also contained more rainwater compared to the ripe snowpack. These results are valuable for further snowpack runoff forecasting.
Étienne Gaborit, Vincent Fortin, Xiaoyong Xu, Frank Seglenieks, Bryan Tolson, Lauren M. Fry, Tim Hunter, François Anctil, and Andrew D. Gronewold
Hydrol. Earth Syst. Sci., 21, 4825–4839, https://doi.org/10.5194/hess-21-4825-2017, https://doi.org/10.5194/hess-21-4825-2017, 2017
Short summary
Short summary
The work presents an original methodology for optimizing streamflow simulations with the distributed hydrological model GEM-Hydro.
While minimizing the computational time required for automatic calibration, the approach allows us to end up with a spatially coherent and transferable parameter set. The GEM-Hydro model is useful because it allows simulation of all physical components of the hydrological cycle in every part of a domain.
It proves to be competitive with other distributed models.
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.
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.
Nena Griessinger, Franziska Mohr, and Tobias Jonas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-295, https://doi.org/10.5194/tc-2016-295, 2017
Revised manuscript not accepted
Short summary
Short summary
We demonstrate the potential of ground penetrating radar for efficient and accurate measurements of snow depth and snow water equivalent when liquid water is present in the snowpack. We were able to derive snow ablation rates with high accuracy from repeated measurements.
We present the design of our light-weight setup consisting of a common-mid-point assembly on a plastic sled, which is mobile even in complex heterogeneous terrain like our investigated field sites in the eastern Swiss Alps.
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.
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.
Nena Griessinger, Jan Seibert, Jan Magnusson, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 3895–3905, https://doi.org/10.5194/hess-20-3895-2016, https://doi.org/10.5194/hess-20-3895-2016, 2016
Short summary
Short summary
In Alpine catchments, snowmelt is a major contribution to runoff. In this study, we address the question of whether the performance of a hydrological model can be enhanced by integrating data from an external snow monitoring system. To this end, a hydrological model was driven with snowmelt input from snow models of different complexities. Best performance was obtained with a snow model, which utilized data assimilation, in particular for catchments at higher elevations and for snow-rich years.
Antoine Thiboult, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 20, 1809–1825, https://doi.org/10.5194/hess-20-1809-2016, https://doi.org/10.5194/hess-20-1809-2016, 2016
Short summary
Short summary
Issuing a good hydrological forecast is challenging because of the numerous sources of uncertainty that lay in the description of the hydrometeorological processes. Several modeling techniques are investigated in this paper to assess how they contribute to the forecast quality. It is shown that the best modeling approach uses several dissimilar techniques that each tackle one source of uncertainty.
Michal Jenicek, Jan Seibert, Massimiliano Zappa, Maria Staudinger, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 859–874, https://doi.org/10.5194/hess-20-859-2016, https://doi.org/10.5194/hess-20-859-2016, 2016
Short summary
Short summary
We quantified how long snowmelt affects runoff, and we estimated the sensitivity of catchments to changes in snowpack. This is relevant as the increase of air temperature might cause decreased snow storage. We used time series from 14 catchments in Switzerland. On average, a decrease of maximum snow storage by 10 % caused a decrease of minimum discharge in July by 2 to 9 %. The results showed a higher sensitivity of summer low flow to snow in alpine catchments compared to pre-alpine catchments.
F. Kobierska, T. Jonas, J. W. Kirchner, and S. M. Bernasconi
Hydrol. Earth Syst. Sci., 19, 3681–3693, https://doi.org/10.5194/hess-19-3681-2015, https://doi.org/10.5194/hess-19-3681-2015, 2015
I. Gouttevin, M. Lehning, T. Jonas, D. Gustafsson, and M. Mölder
Geosci. Model Dev., 8, 2379–2398, https://doi.org/10.5194/gmd-8-2379-2015, https://doi.org/10.5194/gmd-8-2379-2015, 2015
Short summary
Short summary
We improve the canopy module of a very detailed snow model, SNOWPACK, with a view of a more consistent representation of the sub-canopy energy balance with regard to the snowpack.
We show that adding a formulation of (i) the canopy heat capacity and (ii) a lowermost canopy layer (alike trunk + solar shaded leaves) yields significant improvement in the representation of sub-canopy incoming long-wave radiations, especially at nighttime. This energy is an important contributor to snowmelt.
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.
N. Helbig, A. van Herwijnen, J. Magnusson, and T. Jonas
Hydrol. Earth Syst. Sci., 19, 1339–1351, https://doi.org/10.5194/hess-19-1339-2015, https://doi.org/10.5194/hess-19-1339-2015, 2015
Y. Bühler, M. Marty, L. Egli, J. Veitinger, T. Jonas, P. Thee, and C. Ginzler
The Cryosphere, 9, 229–243, https://doi.org/10.5194/tc-9-229-2015, https://doi.org/10.5194/tc-9-229-2015, 2015
Short summary
Short summary
We are able to map snow depth over large areas ( > 100km2) using airborne digital photogrammetry. Digital photogrammetry is more economical than airborne Laser Scanning but slightly less accurate. Comparisons to independent snow depth measurements reveal an accuracy of about 30cm. Spatial continuous mapping of snow depth is a major step forward compared to point measurements usually applied today. Limitations are steep slopes (> 50°) and areas covered by trees and scrubs.
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
G. Seiller and F. Anctil
Hydrol. Earth Syst. Sci., 18, 2033–2047, https://doi.org/10.5194/hess-18-2033-2014, https://doi.org/10.5194/hess-18-2033-2014, 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
F. Hüsler, T. Jonas, M. Riffler, J. P. Musial, and S. Wunderle
The Cryosphere, 8, 73–90, https://doi.org/10.5194/tc-8-73-2014, https://doi.org/10.5194/tc-8-73-2014, 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
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
Related subject area
Subject: Snow and Ice | Techniques and Approaches: Instruments and observation techniques
Climatology of snow depth and water equivalent measurements in the Italian Alps (1967–2020)
Contribution of rock glacier discharge to late summer and fall streamflow in the Uinta Mountains, Utah, USA
Monitoring snowpack outflow volumes and their isotopic composition to better understand streamflow generation during rain-on-snow events
Recent evolution and associated hydrological dynamics of a vanishing tropical Andean glacier: Glaciar de Conejeras, Colombia
Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions
The importance of snowmelt spatiotemporal variability for isotope-based hydrograph separation in a high-elevation catchment
Dye tracing to determine flow properties of hydrocarbon-polluted Rabots glaciär, Kebnekaise, Sweden
Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland
Spatial distribution of stable water isotopes in alpine snow cover
From observation to the quantification of snow processes with a time-lapse camera network
Estimation of soil redistribution rates due to snow cover related processes in a mountainous area (Valle d'Aosta, NW Italy)
Roberto Ranzi, Paolo Colosio, and Giorgio Galeati
Hydrol. Earth Syst. Sci., 28, 2555–2578, https://doi.org/10.5194/hess-28-2555-2024, https://doi.org/10.5194/hess-28-2555-2024, 2024
Short summary
Short summary
We studied temporal trends and variability of snow depth and snow water equivalent (SWE) in six regions of the Italian Alps. We applied different statistical analyses to a dataset of homogeneous and continuous measurements of snow depth and SWE, temporally spanning from 1967 to 2020, and discussed the results with meteo-climatic data. Our results quantify the decrease of SWE in the study area, confirming the impacts of climate modifications on the cryosphere in the Alps.
Jeffrey S. Munroe and Alexander L. Handwerger
Hydrol. Earth Syst. Sci., 27, 543–557, https://doi.org/10.5194/hess-27-543-2023, https://doi.org/10.5194/hess-27-543-2023, 2023
Short summary
Short summary
Rock glaciers are mixtures of ice and rock debris that are common landforms in high-mountain environments. We evaluated the role of rock glaciers as a component of mountain hydrology by collecting water samples during the summer and fall of 2021. Our results indicate that the water draining from rock glaciers late in the melt season is likely derived from old buried ice; they further demonstrate that this water collectively makes up about a quarter of streamflow during the month of September.
Andrea Rücker, Stefan Boss, James W. Kirchner, and Jana von Freyberg
Hydrol. Earth Syst. Sci., 23, 2983–3005, https://doi.org/10.5194/hess-23-2983-2019, https://doi.org/10.5194/hess-23-2983-2019, 2019
Short summary
Short summary
To better understand how rain-on-snow (ROS) events affect snowpack outflow volumes and streamflow generation, we measured snowpack outflow volumes and isotopic composition during 10 ROS events with automated snowmelt lysimeters at three locations in a pre-Alpine catchment. We quantified the spatio-temporal variability of snowpack outflow and its relative contribution to streamflow, and identified rainfall characteristics and initial snow depth as major controls on snow hydrological processes.
Enrique Morán-Tejeda, Jorge Luis Ceballos, Katherine Peña, Jorge Lorenzo-Lacruz, and Juan Ignacio López-Moreno
Hydrol. Earth Syst. Sci., 22, 5445–5461, https://doi.org/10.5194/hess-22-5445-2018, https://doi.org/10.5194/hess-22-5445-2018, 2018
Short summary
Short summary
We studied the recent evolution of a small glacier in the Colombian Andes that is close to extinction, focusing on the water release from the glacier. For this we used hydro-climatological data collected at the the glacier surroundings at an hourly resolution. Our results indicate that water from glacier melt increased as a consequence of accelerated glacier retreat, but up to a certain point (mid-2016) it started to decrease, with glacier melt becoming decreasingly important.
Roman Juras, Sebastian Würzer, Jirka Pavlásek, Tomáš Vitvar, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 4973–4987, https://doi.org/10.5194/hess-21-4973-2017, https://doi.org/10.5194/hess-21-4973-2017, 2017
Short summary
Short summary
This research investigates the rainwater dynamics in the snowpack under artificial rain-on-snow events. Deuterium-enriched water was sprayed on the isolated snowpack and rainwater was further identified in the runoff. We found that runoff from cold snowpack was created faster than from the ripe snowpack. Runoff from the cold snowpack also contained more rainwater compared to the ripe snowpack. These results are valuable for further snowpack runoff forecasting.
Jan Schmieder, Florian Hanzer, Thomas Marke, Jakob Garvelmann, Michael Warscher, Harald Kunstmann, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 20, 5015–5033, https://doi.org/10.5194/hess-20-5015-2016, https://doi.org/10.5194/hess-20-5015-2016, 2016
Short summary
Short summary
We present novel research on the spatiotemporal variability of snowmelt isotopic content in a high-elevation catchment with complex terrain
to improve the isotope-based hydrograph separation method. A modelling approach was used to weight the plot-scale snowmelt isotopic content
with melt rates for the north- and south-facing slope. The investigations showed that it is important to sample at least north- and south-facing slopes,
because of distinct isotopic differences between both slopes.
C. C. Clason, C. Coch, J. Jarsjö, K. Brugger, P. Jansson, and G. Rosqvist
Hydrol. Earth Syst. Sci., 19, 2701–2715, https://doi.org/10.5194/hess-19-2701-2015, https://doi.org/10.5194/hess-19-2701-2015, 2015
K. Meusburger, G. Leitinger, L. Mabit, M. H. Mueller, A. Walter, and C. Alewell
Hydrol. Earth Syst. Sci., 18, 3763–3775, https://doi.org/10.5194/hess-18-3763-2014, https://doi.org/10.5194/hess-18-3763-2014, 2014
N. Dietermann and M. Weiler
Hydrol. Earth Syst. Sci., 17, 2657–2668, https://doi.org/10.5194/hess-17-2657-2013, https://doi.org/10.5194/hess-17-2657-2013, 2013
J. Garvelmann, S. Pohl, and M. Weiler
Hydrol. Earth Syst. Sci., 17, 1415–1429, https://doi.org/10.5194/hess-17-1415-2013, https://doi.org/10.5194/hess-17-1415-2013, 2013
E. Ceaglio, K. Meusburger, M. Freppaz, E. Zanini, and C. Alewell
Hydrol. Earth Syst. Sci., 16, 517–528, https://doi.org/10.5194/hess-16-517-2012, https://doi.org/10.5194/hess-16-517-2012, 2012
Cited articles
Albert, M. and Hardy, J.: Snowpack stratigraphy evolution at forested and open sites, in: Proceedings of the 50th Annual Eastern Snow Conference, Quebec City, Canada, 1993, 205–212, 8–10 June, 1993.
Albert, M. R. and Perron, F. E.: Ice layer and surface crust permeability in a seasonal snow pack, Hydrol. Process., 14, 3207–3214, https://doi.org/10.1002/1099-1085(20001230)14:18<3207::AID-HYP196>3.0.CO;2-C, 2000.
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005.
Barnhart, T. B., Molotch, N. P., Livneh, B., Harpold, A. A., Knowles, J. F., and Schneider, D.: Snowmelt rate dictates streamflow, Geophys. Res. Lett., 43, 8006–8016, https://doi.org/10.1002/2016GL069690, 2016.
Berghuijs, W., Woods, R., and Hrachowitz, M.: A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4, 583–586, https://doi.org/10.1038/nclimate2246, 2014.
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, 1–14, https://doi.org/10.1002/hyp.14681, 2022.
Bouchard, B., Nadeau, D. F., Domine, F., Anctil, F., and Jonas, T.: Dataset from “How does a warm and low-snow winter impact the snow cover dynamics in a humid and discontinuous boreal forest? Insights from observations and modeling in eastern Canada”, Zenodo [data set], https://doi.org/10.5281/zenodo.8213204, 2023.
Bouchard, B., Nadeau, D. F., Domine, F., Wever, N., Michel, A., Lehning, M., and Isabelle, P.-E.: Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy, The Cryosphere, 18, 2783–2807, https://doi.org/10.5194/tc-18-2783-2024, 2024.
Brundl, M., Schneebeli, M., and Fluhler, 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.
Calonne, N., Geindreau, C., Flin, F., Morin, S., Lesaffre, B., Rolland du Roscoat, S., and Charrier, P.: 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy, The Cryosphere, 6, 939–951, https://doi.org/10.5194/tc-6-939-2012, 2012.
Choquette, Y., Ducharme, P., and Rogoza, J.: CS725, an accurate sensor for the snow water equivalent and soil moisture measurements, in: Proceedings of the International Snow Science Workshop, Grenoble, France, 2013, 931–936, 7–11 Octobre 2013.
Climate Data for a Resilient Canada: https://climatedata.ca/ (last access: 19 November 2023), 2023.
Cohen, J., Ye, H., and Jones, J.: Trends and variability in rain-on-snow events, Geophys. Res. Lett., 42, 7115–7122, https://doi.org/10.1002/2015GL065320, 2015.
Colbeck, S. C.: Theory of metamorphism of dry snow, J. Geophys. Res.-Oceans, 88, 5475–5482, https://doi.org/10.1029/jc088ic09p05475, 1983.
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.
Conway, J. P., Pomeroy, J. W., Helgason, W. D., and Kinar, N. J.: Challenges in Modeling Turbulent Heat Fluxes to Snowpacks in Forest Clearings, J. Hydrometeorol., 19, 1599–1616, https://doi.org/10.1175/JHM-D-18-0050.1, 2018.
Crawford, R. M. M. and Braendle, R.: Oxygen deprivation stress in a changing environment, J. Exp. Bot, 47, 145–159, https://doi.org/10.1093/jxb/47.2.145, 1996.
D'Orangeville, L., Duchesne, L., Houle, D., Kneeshaw, D., Coteí, B., and Pederson, N.: Northeastern North America as a potential refugium for boreal forests in a warming climate, Science, 352, 1452–1455, https://doi.org/10.1126/science.aaf4951, 2016.
Demand, D., Selker, J. S., and Weiler, M.: Influences of macropores on infiltration into seasonally frozen soil, Vadose Zone J., 18, 1–14, https://doi.org/10.2136/vzj2018.08.0147, 2019.
Dharmadasa, V., Kinnard, C., and Baraër, M.: Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar, The Cryosphere, 17, 1225–1246, https://doi.org/10.5194/tc-17-1225-2023, 2023.
Domine, F., Taillandier, A., Houdier, S., Parrenin, F., Simpson, W. R., and Douglas, T. A.: Interactions between snow metamorphism and climate: Physical and chemical aspects, in: Physics and Chemistry of Ice, edited by: Kuhs, W. F., Royal Society of Chemistry, Cambridge, UK, 27–46, https://doi.org/10.1039/9781847557773, 2007.
Domine, F., Morin, S., Brun, E., Lafaysse, M., and Carmagnola, C. M.: Seasonal evolution of snow permeability under equi-temperature and temperature-gradient conditions, The Cryosphere, 7, 1915–1929, https://doi.org/10.5194/tc-7-1915-2013, 2013.
Domine, F., Barrere, M., Sarrazin, D., Morin, S., and Arnaud, L.: Automatic monitoring of the effective thermal conductivity of snow in a low-Arctic shrub tundra, The Cryosphere, 9, 1265–1276, https://doi.org/10.5194/tc-9-1265-2015, 2015.
Domine, F., Belke-Brea, M., Barrere, M., Sarrazin, D., Poirier, M., and Arnaud, L.: Soil moisture, wind speed and depth hoar formation in the Arctic snowpack, J. Glaciol., 64, 990–1002, https://doi.org/10.1017/jog.2018.89, 2018.
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.
Ellis, C. R., Pomeroy, J. W., Essery, R. L. H., and Link, T. E.: Effects of needleleaf forest cover on radiation and snowmelt dynamics in the Canadian Rocky Mountains, Can. J. Forest Res., 41, 608–620, https://doi.org/10.1139/X10-227, 2011.
Ellis, C. R., Pomeroy, J. W., and Link, T. E.: Modeling increases in snowmelt yield and desynchronization resulting from forest gap-thinning treatments in a northern mountain headwater basin, Water Resour. Res., 49, 936–949, https://doi.org/10.1002/wrcr.20089, 2013.
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.
Fourteau, K., Domine, F., and Hagenmuller, P.: Impact of water vapor diffusion and latent heat on the effective thermal conductivity of snow, The Cryosphere, 15, 2739–2755, https://doi.org/10.5194/tc-15-2739-2021, 2021.
Fourteau, K., Hagenmuller, P., Roulle, J., and Domine, F.: On the use of heated needle probes for measuring snow thermal conductivity, J. Glaciol., 68, 705–719, https://doi.org/10.1017/jog.2021.127, 2022.
Furey, P. R., Kampf, S. K., Lanini, J. S., and Dozier, A. Q.: A stochastic conceptual modeling approach for examining the effects of climate change on streamflows in mountain basins, J. Hydrometeorol., 13, 837–855, https://doi.org/10.1175/JHM-D-11-037.1, 2012.
Gallet, J.-C., Domine, F., Zender, C. S., and Picard, G.: Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm, The Cryosphere, 3, 167–182, https://doi.org/10.5194/tc-3-167-2009, 2009.
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.
Guay, C., Minville, M., and Braun, M.: A global portrait of hydrological changes at the 2050 horizon for the province of Québec, Can. Water Resour. J., 40, 285–302, https://doi.org/10.1080/07011784.2015.1043583, 2015.
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.
Hamlet, A. F., Mote, P. W., Clark, M. P., and Lettenmaier, D. P.: Effects of temperature and precipitation variability on snowpack trends in the Western United States, J. Climate, 18, 4545–4561, https://doi.org/10.1175/JCLI3538.1, 2005.
Hansen, B. B., Aanes, R., Herfindal, I., Kohler, J., and Sæther, B.-E.: Climate, icing, and wild arctic reindeer: past relationships and future prospects, Ecology, 92, 1917–1923, https://doi.org/10.1890/11-0095.1, 2011.
Hardy, J. P., Melloh, R., Robinson, P., and Jordan, R.: Incorporating effects of forest litter in a snow process model, Hydrol. Process., 14, 3227–3237, https://doi.org/10.1002/1099-1085(20001230)14:18<3227::AID-HYP198>3.0.CO;2-4, 2000.
Hardy, J. P., Groffman, P. M., Fitzhugh, R. D., Henry, K. S., Welman, A. T., Demers, J. D., Fahey, T. J., Driscoll, C. T., Tierney, G. L., and Nolan, S.: Snow depth manipulation and its influence on soil frost and water dynamics in a northern hardwood forest, Biogeochemistry, 56, 151–174, https://doi.org/10.1023/A:1013036803050, 2001.
Hotovy, O., Nedelcev, O., and Jenicek, M.: Changes in rain-on-snow events in mountain catchments in the rain–snow transition zone, Hydrolog. Sci. J., 68, 572–584, https://doi.org/10.1080/02626667.2023.2177544, 2023.
Il Jeong, D. and Sushama, L.: Rain-on-snow events over North America based on two Canadian regional climate models, Clim. Dynam., 50, 303–316, https://doi.org/10.1007/s00382-017-3609-x, 2018.
IPCC: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the 6th Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, UK, 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, Agr. 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, Agr. For. Meteorol., 280, https://doi.org/10.1016/j.agrformet.2019.107813, 2020.
Jennings, K. S., and Molotch, N. P.: Snowfall fraction, cold content, and energy balance changes drive differential response to simulated warming in an alpine and subalpine snowpack, Front. Earth Sci., 8, 1–16, https://doi.org/10.3389/feart.2020.00186, 2020.
Johnsen, K., Boonstra, R., Boutin, S., Devineau, O., Krebs, C. J., and Andreassen, H. P.: Surviving winter: Food, but not habitat structure, prevents crashes in cyclic vole populations, Ecol. Evol., 7, 115–124, https://doi.org/10.1002/ece3.2635, 2017.
Jonas, T., Webster, C., Mazzotti, G., and Malle, J.: HPEval: A canopy shortwave radiation transmission model using high-resolution hemispherical images, Agr. For. Meteorol., 284, 107903, https://doi.org/10.1016/j.agrformet.2020.107903, 2020.
Kattelmann, R.: Snowmelt lysimeters in the evaluation of snowmelt models, Ann. Glaciol., 31, 406–410, https://doi.org/10.3189/172756400781820048, 2000.
Kunkel, K. E., Robinson, D. A., Champion, S., Yin, X., Estilow, T., and Frankson, R. M.: Trends and extremes in Northern Hemisphere snow characteristics, Curr. Clim. Change Rep., 2, 65–73, https://doi.org/10.1007/s40641-016-0036-8, 2016.
Lackner, G., Domine, F., Nadeau, D. F., Parent, A.-C., Anctil, F., Lafaysse, M., and Dumont, M.: On the energy budget of a low-Arctic snowpack, The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022, 2022.
Laternser, M. and Schneebeli, M.: Long-term snow climate trends of the Swiss Alps (1931–99), Int. J. Climatol., 23, 733–750, https://doi.org/10.1002/joc.912, 2003.
Lawler, R. R. and Link, T. E.: Quantification of incoming all-wave radiation in discontinuous forest canopies with application to snowmelt prediction, Hydrol. Process., 25, 3322–3331, https://doi.org/10.1002/hyp.8150, 2011.
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, 2002.
Loìpez-Moreno, J. I., Pomeroy, J. W., Revuelto, J., and Vicente-Serrano, S. M.: Response of snow processes to climate change: spatial variability in a small basin in the Spanish Pyrenees, Hydrol. Process., 27, 2637–2650, https://doi.org/10.1002/hyp.9408, 2013.
Luce, C. H. and Holden, Z. A.: Declining annual streamflow distributions in the Pacific Northwest United States, 1948–2006, Geophys. Res. Lett., 36, L16401, https://doi.org/10.1029/2009GL039407, 2009.
Lundquist, J. D. and Flint, A. L.: Onset of snowmelt and streamflow in 2004 in the Western United States: How shading may affect spring streamflow timing in a warmer world, J. Hydrometeorol., 7, 1199–1217, https://doi.org/10.1175/JHM539.1, 2006.
Lundquist, J. D., Dickerson-Lange, S. E., Lutz, J. A., and Cristea, N. C.: Lower forest density enhances snow retention in regions with warmer winters: A global framework developed from plot-scale observations and modeling, Water Resour. Res., 49, 6356–6370, https://doi.org/10.1002/wrcr.20504, 2013.
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.
Manninen, T. and Stenberg, P.: Simulation of the effect of snow covered forest floor on the total forest albedo, Agr. For. Meteorol., 149, 303–319, https://doi.org/10.1016/j.agrformet.2008.08.016, 2009.
Mazzotti, G., Currier, W. R., Deems, J. S., Pflug, J. M., Lundquist, J. D., and Jonas, T.: Revisiting snow cover variability and canopy structure within forest stands: Insights from airborne LiDAR data, Water Resour. Res., 55, 6198–6216, https://doi.org/10.1029/2019WR024898, 2019.
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, 1–25, 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, 2023a.
Mazzotti, G., Webster, C., Quéno, L., Cluzet, B., and Jonas, T.: Canopy structure, topography, and weather are equally important drivers of small-scale snow cover dynamics in sub-alpine forests, Hydrol. Earth Syst. Sci., 27, 2099–2121, https://doi.org/10.5194/hess-27-2099-2023, 2023b.
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.
Mellander, P.-E., Laudon, H., and Bishop, K.: Modelling variability of snow depths and soil temperatures in Scots pine stands, Agr. For. Meteorol., 133, 109–118, https://doi.org/10.1016/j.agrformet.2005.08.008, 2005.
Melloh, R. A., Hardy, J. P., Davis, R. E., and Robinson, P. B.: Spectral albedo/reflectance of littered forest snow during the melt season, Hydrol. Process., 15, 3409–3422, https://doi.org/10.1002/hyp.1043, 2001.
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.
Morin, S., Domine, F., Arnaud, L., and Picard, G.: In-situ monitoring of the time evolution of the effective thermal conductivity of snow, Cold Reg. Sci. Technol., 64, 73–80, https://doi.org/10.1016/j.coldregions.2010.02.008, 2010.
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K., and Rasmussen, R.: Slower snowmelt in a warmer world, Nat. Clim. Change, 7, 214–219, https://doi.org/10.1038/nclimate3225, 2017.
Ouranos and MELCCFP: Guide de l'atlas hydroclimatique du Québec méridional, Quebec City, Can, https://cehq.gouv.qc.ca/atlas-hydroclimatique/guide-atlas-hydroclimatique-2022.pdf (last access: 1 May 2023), 2022.
Pall, P., Tallaksen, L. M., and Stordal, F.: A Climatology of Rain-on-Snow Events for Norway, J. Climate, 32, 6995–7016, https://doi.org/10.1175/JCLI-D-18-0529.1, 2019.
Paquotte, A. and Baraer, M.: Hydrological behaviour of an ice-layered snowpack in a non-mountainous environment, Hydrol. Process., 36, 1–15, https://doi.org/10.1002/hyp.14433, 2022.
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.
Patel, K. F., Tarariw, C., MacRae, J. D., Ohno, T., Nelson, S. J., and Fernandez, I. J.: Soil carbon and nitrogen responses to snow removal and concrete frost in a northern coniferous forest, Can. J. Soil Sci., 98, 436–447, https://doi.org/10.1139/cjss-2017-0132, 2018.
Pepin, N., Bradley, R. S., Diaz, H., Baraër, M., Caceres, E., Forsythe, N., Fowler, H., Greenwood, G., Hashmi, M., and Liu, X.: Elevation-dependent warming in mountain regions of the world, Nat. Clim. Change, 5, 424–430, https://doi.org/10.1038/nclimate2563, 2015.
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.
Poirier, M., Gauthier, G., and Domine, F.: What guides lemmings movements through the snowpack?, J. Mammal., 100, 1416–1426, https://doi.org/10.1093/jmammal/gyz129, 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., Marks, D., Link, T., Ellis, C., Hardy, J., Rowlands, A., and Granger, R.: The impact of coniferous forest temperature on incoming longwave radiation to melting snow, Hydrol. Process., 23, 2513–2525, https://doi.org/10.1002/hyp.7325, 2009.
Price, D. T., R.I., A., Brown, K. J., Flannigan, M. D., Fleming, R. A., Hogg, E. H., Girardin, M. P., Lakusta, T., Johnston, M., McKenney, D. W., Pedlar, J. H., Stratton, T., Sturrock, R. N., Thompson, I. D., Trofymow, J. A., and Venier, L. A.: Anticipating the consequences of climate change for Canada's boreal forest ecosystems, Environ. Rev., 21, 322–365, https://doi.org/10.1139/er-2013-0042, 2013.
Proulx, S. and Stein, J.: Classification of meteorological conditions to assess the potential for concrete frost formation in boreal forest floors, Can. J. Forest Res., 27, 953–958, https://doi.org/10.1139/x96-217, 1997.
Scheffer, M., Hirota, M., Holmgren, M., Van Nes, E. H., and Chapin, F. S.: Thresholds for boreal biome transitions, P. Natl. Acad. Sci. USA, 109, 21384–21389, https://doi.org/10.1073/pnas.1219844110, 2012.
Schilling, O. S., Parajuli, A., Müller, T. U., Tremblay, Y., Brennwald, M. S., Nadeau, D. F., Jutras, S., Kipfer, R., and Therrien, R.: Quantifying groundwater recharge dynamics and unsaturated zone processes in snow-dominated catchments via on-site dissolved gas analysis, Water Resour. Res., 57, 1–24, https://doi.org/10.1029/2020WR028479, 2021.
Schmelzer, I., Lewis, K. P., Jacobs, J. D., and McCarthy, S. C.: Boreal caribou survival in a warming climate, Labrador, Canada 1996–2014, Glob. Ecol. Conser., 23, e010308, https://doi.org/10.1016/j.gecco.2020.e01038, 2020.
Shanley, J. B. and Chalmers, A.: The effect of frozen soil on snowmelt runoff at Sleepers River, Vermont, Hydrol. Process., 13, 1843–1857, https://doi.org/10.1002/(SICI)1099-1085(199909)13:12/13<1843::AID-HYP879>3.0.CO;2-G, 1999.
Sicart, J. E., Pomeroy, J. W., Essery, R. L. H., and Bewley, D.: Incoming longwave radiation to melting snow: observations, sensitivity and estimation in Northern environments, Hydrol. Process., 20, 3697–3708, https://doi.org/10.1002/hyp.6383, 2006.
Slater, A. G., Lawrence, D. M., and Koven, C. D.: Process-level model evaluation: a snow and heat transfer metric, The Cryosphere, 11, 989–996, https://doi.org/10.5194/tc-11-989-2017, 2017.
Stadler, D., Wunderli, H., Auckenthaler, A., Fluhler, H., and Brundl, M.: Measurement of frost-induced snowmelt runoff in a forest soil, Hydrol. Process., 10, 1293–1304, https://doi.org/10.1002/(SICI)1099-1085(199610)10:10<1293::AID-HYP461>3.0.CO;2-I, 1996.
Sun, N., Wigmosta, M., Zhou, T., Lundquist, J., Dickerson-Lange, S., and Cristea, N.: Evaluating the functionality and streamflow impacts of explicitly modelling forest-snow interactions and canopy gaps in a distributed hydrologic model, Hydrol. Process., 32, 2128–2140, https://doi.org/10.1002/hyp.13150, 2018.
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., and Douglas, T. A.: Rate of decrease of the specific surface area of dry snow: Isothermal and temperature gradient conditions, J. Geophys. Res. Earth Surf., 112, 1–13, https://doi.org/10.1029/2006JF000514, 2007.
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.
Thackeray, C. W. and Fletcher, C. G.: Snow albedo feedback: Current knowledge, importance, outstanding issues and future directions, Prog. Phys. Geog., 40, 392–408, https://doi.org/10.1177/0309133315620999, 2015.
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.
Van Loon, A. F., Ploum, S. W., Parajka, J., Fleig, A. K., Garnier, E., Laaha, G., and Van Lanen, H. A. J.: Hydrological drought types in cold climates: quantitative analysis of causing factors and qualitative survey of impacts, Hydrol. Earth Syst. Sci., 19, 1993–2016, https://doi.org/10.5194/hess-19-1993-2015, 2015.
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.
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, 2018.
Westermann, S., Boike, J., Langer, M., Schuler, T. V., and Etzelmüller, B.: Modeling the impact of wintertime rain events on the thermal regime of permafrost, The Cryosphere, 5, 945–959, https://doi.org/10.5194/tc-5-945-2011, 2011.
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.
WSL: SNOWPACK, License: GNU LHPLv3, Institute for Snow and Avalanche Research SLF, Davos, Switzerland, WSL [code], https://gitlabext.wsl.ch/snow-models/snowpack (last access: 9 March 2024), 2024.
Yang, K., Peng, C., Peñuelas, J., Kardol, P., Li, Z., Zhang, L., Ni, X., Yue, K., Tan, B., Yin, R., and Xu, Z.: Immediate and carry-over effects of increased soil frost on soil respiration and microbial activity in a spruce forest, Soil Biol. Biochem., 135, 51–59, https://doi.org/10.1016/j.soilbio.2019.04.012, 2019.
Zhang, T.: Influence of the seasonal snow cover on the ground thermal regime: An overview, Rev. Geophys., 43, 1–23, https://doi.org/10.1029/2004RG000157, 2005.
Zheng, B., Ciais, P., Chevallier, F., Yang, H., Canadell, J. G., Chen, Y., van der Velde, I. R., Aben, I., Chuvieco, E., Davis, S. J., Deeter, M., Hong, C., Kong, Y., Li, H., Li, H., Lin, X., He, K., and Zhang, Q.: Record-high CO2 emissions from boreal fires in 2021, Science, 379, 912–917, https://doi.org/10.1126/science.ade0805, 2023.
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.
Observations and simulations from an exceptionally low-snow and warm winter, which may become...
