Articles | Volume 24, issue 4
https://doi.org/10.5194/hess-24-2083-2020
© Author(s) 2020. 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-24-2083-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Satellite-derived products of solar and longwave irradiances used for snowpack modelling in mountainous terrain
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, 38000 Grenoble, France
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Invited contribution by Louis Quéno, recipient of the EGU Cryospheric Sciences Outstanding Student Poster and PICO Award 2017.
Fatima Karbou
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, 38000 Grenoble, France
Vincent Vionnet
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, 38000 Grenoble, France
Environmental Numerical Research Prediction, Environment and Climate Change Canada, Dorval, QC, Canada
Ingrid Dombrowski-Etchevers
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Related authors
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
Revised manuscript under review for ESSD
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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
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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.
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
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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.
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
EGUsphere, https://doi.org/10.5194/egusphere-2024-209, https://doi.org/10.5194/egusphere-2024-209, 2024
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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 opens the way to further evaluation, calibration and data assimilation using wet snow maps.
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
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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.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
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
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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.
Louis Quéno, Vincent Vionnet, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Marie Dumont, and Fatima Karbou
The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, https://doi.org/10.5194/tc-10-1571-2016, 2016
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Simulations are carried out in the Pyrenees with the snowpack model Crocus, driven by meteorological forecasts from the model AROME at kilometer resolution. The evaluation is done with ground-based measurements, satellite data and reference simulations. Studying daily snow depth variations allows to separate different physical processes affecting the snowpack. We show the benefits of AROME kilometric resolution and dynamical behavior in terms of snowpack spatial variability in a mountain range.
Julien Meloche, Nicolas R. Leroux, Benoit Montpetit, Vincent Vionnet, and Chris Derksen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3169, https://doi.org/10.5194/egusphere-2024-3169, 2024
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Measuring the snow mass from radar measurements is possible with information on the snow and a radar model to link the measurements to snow. A key variable in a retrieval is the number of snow layers, with more layer yielding richer information but at increased computational cost. Here, we show the capabilities of a new method to simplify a complex snowpack, while preserving the scattering behavior of the snowpack and conserving the mass.
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
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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
Revised manuscript 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.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
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.
Manon Gaillard, Vincent Vionnet, Matthieu Lafaysse, Marie Dumont, and Paul Ginoux
EGUsphere, https://doi.org/10.5194/egusphere-2024-1795, https://doi.org/10.5194/egusphere-2024-1795, 2024
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This study presents an efficient method to improve large-scale snow albedo simulations by considering the spatial variability of light-absorbing particles (LAPs) like black carbon and dust. A global climatology of LAP deposition was created and used to optimize a parameter in the Crocus snow model. Testing at ten global sites improved albedo predictions by 10 % on average and over 25 % in the Arctic. This method can also enhance other snow models' predictions without complex simulations.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamps-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
The Cryosphere, 18, 3081–3116, https://doi.org/10.5194/tc-18-3081-2024, https://doi.org/10.5194/tc-18-3081-2024, 2024
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations with snow transport against snow depths from Pléiades stereo imagery and snow melt-out dates from Sentinel-2 and Landsat-8 satellites. Additionally, we disentangle error contributions between blowing snow, precipitation heterogeneity, and unresolved subgrid variability. Snow transport enhances the snow simulations at high elevations, while precipitation biases are the main error source in other areas.
Marin Kneib, Amaury Dehecq, Fanny Brun, Fatima Karbou, Laurane Charrier, Silvan Leinss, Patrick Wagnon, and Fabien Maussion
The Cryosphere, 18, 2809–2830, https://doi.org/10.5194/tc-18-2809-2024, https://doi.org/10.5194/tc-18-2809-2024, 2024
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Avalanches are important for the mass balance of mountain glaciers, but few data exist on where and when they occur and which glaciers they affect the most. We developed an approach to map avalanches over large glaciated areas and long periods of time using satellite radar data. The application of this method to various regions in the Alps and High Mountain Asia reveals the variability of avalanches on these glaciers and provides key data to better represent these processes in glacier models.
Alireza Amani, Marie-Amélie Boucher, Alexandre R. Cabral, Vincent Vionnet, and Étienne Gaborit
EGUsphere, https://doi.org/10.5194/egusphere-2024-1277, https://doi.org/10.5194/egusphere-2024-1277, 2024
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Accurately estimating groundwater recharge using numerical models is particularly difficult in cold regions with snow and soil freezing. This study evaluated a physics-based model against high-resolution field measurements. Our findings highlight a need for a better representation of soil freezing processes, offering a roadmap for future model development. This leads to more accurate models to aid water resources management decisions in cold climates.
Georgina Jean Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamund Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
EGUsphere, https://doi.org/10.5194/egusphere-2024-1237, https://doi.org/10.5194/egusphere-2024-1237, 2024
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Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of SVS2-Crocus and evaluated using density and SSA measurements at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and SSA were identified. Top performing ensemble members featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift and increase viscosity in basal layers.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
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Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
EGUsphere, https://doi.org/10.5194/egusphere-2024-209, https://doi.org/10.5194/egusphere-2024-209, 2024
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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 opens the way to further evaluation, calibration and data assimilation using wet snow maps.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
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
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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.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
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Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Vincent Vionnet, Colleen Mortimer, Mike Brady, Louise Arnal, and Ross Brown
Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, https://doi.org/10.5194/essd-13-4603-2021, 2021
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Water equivalent of snow cover (SWE) is a key variable for water management, hydrological forecasting and climate monitoring. A new Canadian SWE dataset (CanSWE) is presented in this paper. It compiles data collected by multiple agencies and companies at more than 2500 different locations across Canada over the period 1928–2020. Snow depth and derived bulk snow density are also included when available.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
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Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
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
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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.
Guoqiang Tang, Martyn P. Clark, Andrew J. Newman, Andrew W. Wood, Simon Michael Papalexiou, Vincent Vionnet, and Paul H. Whitfield
Earth Syst. Sci. Data, 12, 2381–2409, https://doi.org/10.5194/essd-12-2381-2020, https://doi.org/10.5194/essd-12-2381-2020, 2020
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Station observations are critical for hydrological and meteorological studies, but they often contain missing values and have short measurement periods. This study developed a serially complete dataset for North America (SCDNA) from 1979 to 2018 for 27 276 precipitation and temperature stations. SCDNA is built on multiple data sources and infilling/reconstruction strategies to achieve high-quality estimates which can be used for a variety of applications.
Vincent Vionnet, Vincent Fortin, Etienne Gaborit, Guy Roy, Maria Abrahamowicz, Nicolas Gasset, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2141–2165, https://doi.org/10.5194/hess-24-2141-2020, https://doi.org/10.5194/hess-24-2141-2020, 2020
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The 2013 Alberta flood in Canada was typical of late-spring floods in mountain basins combining intense precipitation with rapid melting of late-lying snowpack. Hydrological simulations of this event are mainly influenced by (i) the spatial resolution of the atmospheric forcing due to the best estimate of precipitation at the kilometer scale and changes in turbulent fluxes contributing to snowmelt and (ii) uncertainties in initial snow conditions at high elevations. Soil texture has less impact.
Tony Le Bastard, Olivier Caumont, Nicolas Gaussiat, and Fatima Karbou
Atmos. Meas. Tech., 12, 5669–5684, https://doi.org/10.5194/amt-12-5669-2019, https://doi.org/10.5194/amt-12-5669-2019, 2019
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The estimation of surface rainfall from radars becomes less effective at long ranges or in mountainous regions where the radar beam is far from the ground. The method proposed in this paper investigates how vertical profiles simulated from high-resolution model can be used to predict the evolution of the precipitation below the radar beam. Our results show that this novel method leads to better results than the current operational methods that either use climatological or idealised profiles.
Satoru Yamaguchi, Masaaki Ishizaka, Hiroki Motoyoshi, Sent Nakai, Vincent Vionnet, Teruo Aoki, Katsuya Yamashita, Akihiro Hashimoto, and Akihiro Hachikubo
The Cryosphere, 13, 2713–2732, https://doi.org/10.5194/tc-13-2713-2019, https://doi.org/10.5194/tc-13-2713-2019, 2019
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The specific surface area (SSA) of solid precipitation particles (PPs) includes detailed information of PP. This work is based on field measurement of SSA of PPs in Nagaoka, the city with the heaviest snowfall in Japan. The values of SSA strongly depend on wind speed (WS) and wet-bulb temperature (Tw) on the ground. An equation to empirically estimate the SSA of fresh PPs with WS and Tw was established and the equation successfully reproduced the fluctuation of SSA in Nagaoka.
Gilbert Guyomarc'h, Hervé Bellot, Vincent Vionnet, Florence Naaim-Bouvet, Yannick Déliot, Firmin Fontaine, Philippe Puglièse, Kouichi Nishimura, Yves Durand, and Mohamed Naaim
Earth Syst. Sci. Data, 11, 57–69, https://doi.org/10.5194/essd-11-57-2019, https://doi.org/10.5194/essd-11-57-2019, 2019
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The paper introduces a meteorological and blowing snow data set from Col du Lac Blanc (2720 m a.s.l., French Alps) allowing physical parameterizations and numerical models of blowing snow to be developed and evaluated. In situ winter season data consist of wind, snow depth, air temperature measurements and a database of blowing snow occurrence (2000–2016) complemented by measurements of blowing snow fluxes (2010–2016). Atmospheric data from a meteorological reanalysis and a DEM are also provided.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Marion Réveillet, Delphine Six, Christian Vincent, Antoine Rabatel, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Vincent Vionnet, and Maxime Litt
The Cryosphere, 12, 1367–1386, https://doi.org/10.5194/tc-12-1367-2018, https://doi.org/10.5194/tc-12-1367-2018, 2018
Lawrence R. Mudryk, Chris Derksen, Stephen Howell, Fred Laliberté, Chad Thackeray, Reinel Sospedra-Alfonso, Vincent Vionnet, Paul J. Kushner, and Ross Brown
The Cryosphere, 12, 1157–1176, https://doi.org/10.5194/tc-12-1157-2018, https://doi.org/10.5194/tc-12-1157-2018, 2018
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This paper presents changes in both snow and sea ice that have occurred over Canada during the recent past and shows climate model estimates for future changes expected to occur by the year 2050. The historical changes of snow and sea ice are generally coherent and consistent with the regional history of temperature and precipitation changes. It is expected that snow and sea ice will continue to decrease in the future, declining by an additional 15–30 % from present day values by the year 2050.
Jesús Revuelto, Grégoire Lecourt, Matthieu Lafaysse, Isabella Zin, Luc Charrois, Vincent Vionnet, Marie Dumont, Antoine Rabatel, Delphine Six, Thomas Condom, Samuel Morin, Alessandra Viani, and Pascal Sirguey
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-184, https://doi.org/10.5194/tc-2017-184, 2017
Revised manuscript not accepted
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We evaluated distributed and semi-distributed modeling approaches to simulating the spatial and temporal evolution of snow and ice over an extended mountain catchment, using the Crocus snowpack model. The distributed approach simulated the snowpack dynamics on a 250-m grid, enabling inclusion of terrain shadowing effects. The semi-distributed approach simulated the snowpack dynamics for discrete topographic classes characterized by elevation range, aspect, and slope.
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
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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.
Matthieu Lafaysse, Bertrand Cluzet, Marie Dumont, Yves Lejeune, Vincent Vionnet, and Samuel Morin
The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, https://doi.org/10.5194/tc-11-1173-2017, 2017
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Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC by implementing new representations of different physical processes in a coupled multilayer ground/snowpack model. This system is a promising tool to integrate snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.
Louis Quéno, Vincent Vionnet, Ingrid Dombrowski-Etchevers, Matthieu Lafaysse, Marie Dumont, and Fatima Karbou
The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, https://doi.org/10.5194/tc-10-1571-2016, 2016
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Simulations are carried out in the Pyrenees with the snowpack model Crocus, driven by meteorological forecasts from the model AROME at kilometer resolution. The evaluation is done with ground-based measurements, satellite data and reference simulations. Studying daily snow depth variations allows to separate different physical processes affecting the snowpack. We show the benefits of AROME kilometric resolution and dynamical behavior in terms of snowpack spatial variability in a mountain range.
V. Vionnet, E. Martin, V. Masson, G. Guyomarc'h, F. Naaim-Bouvet, A. Prokop, Y. Durand, and C. Lac
The Cryosphere, 8, 395–415, https://doi.org/10.5194/tc-8-395-2014, https://doi.org/10.5194/tc-8-395-2014, 2014
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
Related subject area
Subject: Snow and Ice | Techniques and Approaches: Modelling approaches
Inferring sediment-discharge event types in an Alpine catchment from sub-daily time series
Debris cover effects on energy and mass balance of Batura Glacier in the Karakoram over the past 20 years
Evaluation of high resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA
The application and modification of WRF-Hydro/Glacier to a cold-based Antarctic glacier
Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation
Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance
Spatial distribution and controls of snowmelt runoff in a sublimation-dominated environment in the semiarid Andes of Chile
Snow data assimilation for seasonal streamflow supply prediction in mountainous basins
Canopy structure, topography, and weather are equally important drivers of small-scale snow cover dynamics in sub-alpine forests
Climate sensitivity of the summer runoff of two glacierised Himalayan catchments with contrasting climate
A snow and glacier hydrological model for large catchments – case study for the Naryn River, central Asia
Precipitation biases and snow physics limitations drive the uncertainties in macroscale modeled snow water equivalent
Development and parameter estimation of snowmelt models using spatial snow-cover observations from MODIS
Recent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configuration
Future projections of High Atlas snowpack and runoff under climate change
Trends and variability in snowmelt in China under climate change
Assimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow Observations
Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area
The evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchments
Learning about precipitation lapse rates from snow course data improves water balance modeling
Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model
Application of machine learning techniques for regional bias correction of snow water equivalent estimates in Ontario, Canada
Sensitivity of snow models to the accuracy of meteorological forcings in mountain environments
Snow processes in mountain forests: interception modeling for coarse-scale applications
Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes
The role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)
Hyper-resolution ensemble-based snow reanalysis in mountain regions using clustering
The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
Assessment of SWAT spatial and temporal transferability for a high-altitude glacierized catchment
Modeling experiments on seasonal lake ice mass and energy balance in the Qinghai–Tibet Plateau: a case study
A simple model for local-scale sensible and latent heat advection contributions to snowmelt
Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada
A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model
Technical note: Representing glacier geometry changes in a semi-distributed hydrological model
Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach
Scenario approach for the seasonal forecast of Kharif flows from the Upper Indus Basin
The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments
Modelling hydrologic impacts of light absorbing aerosol deposition on snow at the catchment scale
Liquid water infiltration into a layered snowpack: evaluation of a 3-D water transport model with laboratory experiments
Assessing glacier melt contribution to streamflow at Universidad Glacier, central Andes of Chile
Modelling liquid water transport in snow under rain-on-snow conditions – considering preferential flow
Developing a representative snow-monitoring network in a forested mountain watershed
Subgrid parameterization of snow distribution at a Mediterranean site using terrestrial photography
Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments
Stable oxygen isotope variability in two contrasting glacier river catchments in Greenland
Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover
A conceptual, distributed snow redistribution model
Diagnostic calibration of a hydrological model in a mountain area by hydrograph partitioning
Meltwater run-off from Haig Glacier, Canadian Rocky Mountains, 2002–2013
Modeling the snow surface temperature with a one-layer energy balance snowmelt model
Amalie Skålevåg, Oliver Korup, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 4771–4796, https://doi.org/10.5194/hess-28-4771-2024, https://doi.org/10.5194/hess-28-4771-2024, 2024
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We present a cluster-based approach for inferring sediment discharge event types from suspended sediment concentration and streamflow. Applying it to a glacierised catchment, we find event magnitude and shape complexity to be the key characteristics separating event types, while hysteresis is less important. The four event types are attributed to compound rainfall–melt extremes, high snowmelt and glacier melt, freeze–thaw-modulated snow-melt and precipitation, and late-season glacier melt.
Yu Zhu, Shiyin Liu, Ben W. Brock, Lide Tian, Ying Yi, Fuming Xie, Donghui Shangguan, and Yiyuan Shen
Hydrol. Earth Syst. Sci., 28, 2023–2045, https://doi.org/10.5194/hess-28-2023-2024, https://doi.org/10.5194/hess-28-2023-2024, 2024
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This modeling-based study focused on Batura Glacier from 2000 to 2020, revealing that debris alters its energy budget, affecting mass balance. We propose that the presence of debris on the glacier surface effectively reduces the amount of latent heat available for ablation, which creates a favorable condition for Batura Glacier's relatively low negative mass balance. Batura Glacier shows a trend toward a less negative mass balance due to reduced ablation.
Laura Sourp, Simon Gascoin, Lionel Jarlan, Vanessa Pedinotti, Kat J. Bormann, and Mohamed Wassim Baba
EGUsphere, https://doi.org/10.5194/egusphere-2024-791, https://doi.org/10.5194/egusphere-2024-791, 2024
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An accurate knowledge of the spatial distribution of the snow mass across the landscape is important for water management in mountain catchments. We present a new tool to estimate the snow water resources without ground measurements. We evaluate the output of this tool using accurate airborne measurements in the Sierra Nevada and find that it provides realistic estimates of the snow mass and snow depth at the catchment scale.
Tamara Pletzer, Jonathan P. Conway, Nicolas J. Cullen, Trude Eidhammer, and Marwan Katurji
Hydrol. Earth Syst. Sci., 28, 459–478, https://doi.org/10.5194/hess-28-459-2024, https://doi.org/10.5194/hess-28-459-2024, 2024
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We applied a glacier and hydrology model in the McMurdo Dry Valleys (MDV) to model the start and duration of melt over a summer in this extreme polar desert. To do so, we found it necessary to prevent the drainage of melt into ice and optimize the albedo scheme. We show that simulating albedo (for the first time in the MDV) is critical to modelling the feedbacks of albedo, snowfall and melt in the region. This paper is a first step towards more complex spatial modelling of melt and streamflow.
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023, https://doi.org/10.5194/hess-27-4637-2023, 2023
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Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.
Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Étienne Leblois, and Marie Dumont
Hydrol. Earth Syst. Sci., 27, 4257–4277, https://doi.org/10.5194/hess-27-4257-2023, https://doi.org/10.5194/hess-27-4257-2023, 2023
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Ski resorts are a key socio-economic asset of several mountain areas. Grooming and snowmaking are routinely used to manage the snow cover on ski pistes, but despite vivid debate, little is known about their impact on water resources downstream. This study quantifies, for the pilot ski resort La Plagne in the French Alps, the impact of grooming and snowmaking on downstream river flow. Hydrological impacts are mostly apparent at the seasonal scale and rather neutral on the annual scale.
Álvaro Ayala, Simone Schauwecker, and Shelley MacDonell
Hydrol. Earth Syst. Sci., 27, 3463–3484, https://doi.org/10.5194/hess-27-3463-2023, https://doi.org/10.5194/hess-27-3463-2023, 2023
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As the climate of the semiarid Andes is very dry, much of the seasonal snowpack is lost to the atmosphere through sublimation. We propose that snowmelt runoff originates from specific areas that we define as snowmelt hotspots. We estimate that snowmelt hotspots produce half of the snowmelt runoff in a small study catchment but represent about a quarter of the total area. Snowmelt hotspots may be important for groundwater recharge, rock glaciers, and mountain peatlands.
Sammy Metref, Emmanuel Cosme, Matthieu Le Lay, and Joël Gailhard
Hydrol. Earth Syst. Sci., 27, 2283–2299, https://doi.org/10.5194/hess-27-2283-2023, https://doi.org/10.5194/hess-27-2283-2023, 2023
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Predicting the seasonal streamflow supply of water in a mountainous basin is critical to anticipating the operation of hydroelectric dams and avoiding hydrology-related hazard. This quantity partly depends on the snowpack accumulated during winter. The study addresses this prediction problem using information from streamflow data and both direct and indirect snow measurements. In this study, the prediction is improved by integrating the data information into a basin-scale hydrological model.
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
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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.
Sourav Laha, Argha Banerjee, Ajit Singh, Parmanand Sharma, and Meloth Thamban
Hydrol. Earth Syst. Sci., 27, 627–645, https://doi.org/10.5194/hess-27-627-2023, https://doi.org/10.5194/hess-27-627-2023, 2023
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A model study of two Himalayan catchments reveals that the summer runoff from the glacierized parts of the catchments responds strongly to temperature forcing and is insensitive to precipitation forcing. The runoff from the non-glacierized parts has the exact opposite behaviour. The interannual variability and decadal changes of runoff under a warming climate is determined by the response of glaciers to temperature forcing and that of off-glacier areas to precipitation perturbations.
Sarah Shannon, Anthony Payne, Jim Freer, Gemma Coxon, Martina Kauzlaric, David Kriegel, and Stephan Harrison
Hydrol. Earth Syst. Sci., 27, 453–480, https://doi.org/10.5194/hess-27-453-2023, https://doi.org/10.5194/hess-27-453-2023, 2023
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Climate change poses a potential threat to water supply in glaciated river catchments. In this study, we added a snowmelt and glacier melt model to the Dynamic fluxEs and ConnectIvity for Predictions of HydRology model (DECIPHeR). The model is applied to the Naryn River catchment in central Asia and is found to reproduce past change discharge and the spatial extent of seasonal snow cover well.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, Rhae Sung Kim, and Jennifer M. Jacobs
Hydrol. Earth Syst. Sci., 26, 5721–5735, https://doi.org/10.5194/hess-26-5721-2022, https://doi.org/10.5194/hess-26-5721-2022, 2022
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While land surface models are a common approach for estimating macroscale snow water equivalent (SWE), the SWE accuracy is often limited by uncertainties in model physics and forcing inputs. In this study, we found large underestimations of modeled SWE compared to observations. Precipitation forcings and melting physics limitations dominantly contribute to the SWE underestimations. Results provide insights into prioritizing strategies to improve the SWE simulations for hydrologic applications.
Dhiraj Raj Gyawali and András Bárdossy
Hydrol. Earth Syst. Sci., 26, 3055–3077, https://doi.org/10.5194/hess-26-3055-2022, https://doi.org/10.5194/hess-26-3055-2022, 2022
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In this study, different extensions of the degree-day model were calibrated on snow-cover distribution against freely available satellite snow-cover images. The calibrated models simulated the distribution very well in Baden-Württemberg (Germany) and Switzerland. In addition to reliable identification of snow cover, the melt outputs from the calibrated models were able to improve the flow simulations in different catchments in the study region.
Dhiraj Pradhananga and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 2605–2616, https://doi.org/10.5194/hess-26-2605-2022, https://doi.org/10.5194/hess-26-2605-2022, 2022
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This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation glaciers. Peyto and Athabasca glacier basins in the Canadian Rockies have undergone continuous glacier loss over the last 3 to 5 decades, leading to an increase in ice exposure and changes to the elevation and slope of the glacier surfaces. Streamflow from these glaciers continues to increase more due to climate warming than glacier recession.
Alexandre Tuel, Nabil El Moçayd, Moulay Driss Hasnaoui, and Elfatih A. B. Eltahir
Hydrol. Earth Syst. Sci., 26, 571–588, https://doi.org/10.5194/hess-26-571-2022, https://doi.org/10.5194/hess-26-571-2022, 2022
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Snowmelt in the High Atlas is critical for irrigation in Morocco but is threatened by climate change. We assess future trends in High Atlas snowpack by modelling it under historical and future climate scenarios and estimate their impact on runoff. We find that the combined warming and drying will result in a roughly 80 % decline in snowpack, a 5 %–30 % decrease in runoff efficiency and 50 %–60 % decline in runoff under a business-as-usual scenario.
Yong Yang, Rensheng Chen, Guohua Liu, Zhangwen Liu, and Xiqiang Wang
Hydrol. Earth Syst. Sci., 26, 305–329, https://doi.org/10.5194/hess-26-305-2022, https://doi.org/10.5194/hess-26-305-2022, 2022
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A comprehensive assessment of snowmelt is missing for China. Trends and variability in snowmelt in China under climate change are investigated using historical precipitation and temperature data (1951–2017) and projection scenarios (2006–2099). The snowmelt and snowmelt runoff ratio show significant spatial and temporal variability in China. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on the water supply.
Ryan L. Crumley, David F. Hill, Katreen Wikstrom Jones, Gabriel J. Wolken, Anthony A. Arendt, Christina M. Aragon, Christopher Cosgrove, and Community Snow Observations Participants
Hydrol. Earth Syst. Sci., 25, 4651–4680, https://doi.org/10.5194/hess-25-4651-2021, https://doi.org/10.5194/hess-25-4651-2021, 2021
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In this study, we use a new snow data set collected by participants in the Community Snow Observations project in coastal Alaska to improve snow depth and snow water equivalence simulations from a snow process model. We validate our simulations with multiple datasets, taking advantage of snow telemetry (SNOTEL), snow depth and snow water equivalence, and remote sensing measurements. Our results demonstrate that assimilating citizen science snow depth measurements can improve model performance.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, https://doi.org/10.5194/hess-25-4455-2021, 2021
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Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Michael Weber, Franziska Koch, Matthias Bernhardt, and Karsten Schulz
Hydrol. Earth Syst. Sci., 25, 2869–2894, https://doi.org/10.5194/hess-25-2869-2021, https://doi.org/10.5194/hess-25-2869-2021, 2021
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We compared a suite of globally available meteorological and DEM data with in situ data for physically based snow hydrological modelling in a small high-alpine catchment. Although global meteorological data were less suited to describe the snowpack properly, transferred station data from a similar location in the vicinity and substituting single variables with global products performed well. In addition, using 30 m global DEM products as model input was useful in such complex terrain.
Francesco Avanzi, Giulia Ercolani, Simone Gabellani, Edoardo Cremonese, Paolo Pogliotti, Gianluca Filippa, Umberto Morra di Cella, Sara Ratto, Hervè Stevenin, Marco Cauduro, and Stefano Juglair
Hydrol. Earth Syst. Sci., 25, 2109–2131, https://doi.org/10.5194/hess-25-2109-2021, https://doi.org/10.5194/hess-25-2109-2021, 2021
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Precipitation tends to increase with elevation, but the magnitude and distribution of this enhancement remain poorly understood. By leveraging over 11 000 spatially distributed, manual measurements of snow depth (snow courses) upstream of two reservoirs in the western European Alps, we show that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improved modeling accuracy and, ultimately, our understanding of the water budget.
Michael Winkler, Harald Schellander, and Stefanie Gruber
Hydrol. Earth Syst. Sci., 25, 1165–1187, https://doi.org/10.5194/hess-25-1165-2021, https://doi.org/10.5194/hess-25-1165-2021, 2021
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A new method to calculate the mass of snow is provided. It is quite simple but gives surprisingly good results. The new approach only requires regular snow depth observations to simulate respective water mass that is stored in the snow. It is called
ΔSNOW model, its code is freely available, and it can be applied in various climates. The method is especially interesting for studies on extremes (e.g., snow loads or flooding) and climate (e.g., precipitation trends).
Fraser King, Andre R. Erler, Steven K. Frey, and Christopher G. Fletcher
Hydrol. Earth Syst. Sci., 24, 4887–4902, https://doi.org/10.5194/hess-24-4887-2020, https://doi.org/10.5194/hess-24-4887-2020, 2020
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Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.
Silvia Terzago, Valentina Andreoli, Gabriele Arduini, Gianpaolo Balsamo, Lorenzo Campo, Claudio Cassardo, Edoardo Cremonese, Daniele Dolia, Simone Gabellani, Jost von Hardenberg, Umberto Morra di Cella, Elisa Palazzi, Gaia Piazzi, Paolo Pogliotti, and Antonello Provenzale
Hydrol. Earth Syst. Sci., 24, 4061–4090, https://doi.org/10.5194/hess-24-4061-2020, https://doi.org/10.5194/hess-24-4061-2020, 2020
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In mountain areas high-quality meteorological data to drive snow models are rarely available, so coarse-resolution data from spatial interpolation of the available in situ measurements or reanalyses are typically employed. We perform 12 experiments using six snow models with different degrees of complexity to show the impact of the accuracy of the forcing on snow depth and snow water equivalent simulations at the Alpine site of Torgnon, discussing the results in relation to the model complexity.
Nora Helbig, David Moeser, Michaela Teich, Laure Vincent, Yves Lejeune, Jean-Emmanuel Sicart, and Jean-Matthieu Monnet
Hydrol. Earth Syst. Sci., 24, 2545–2560, https://doi.org/10.5194/hess-24-2545-2020, https://doi.org/10.5194/hess-24-2545-2020, 2020
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Snow retained in the forest canopy (snow interception) drives spatial variability of the subcanopy snow accumulation. As such, accurately describing snow interception in models is of importance for various applications such as hydrological, weather, and climate predictions. We developed descriptions for the spatial mean and variability of snow interception. An independent evaluation demonstrated that the novel models can be applied in coarse land surface model grid cells.
Emma L. Robinson and Douglas B. Clark
Hydrol. Earth Syst. Sci., 24, 1763–1779, https://doi.org/10.5194/hess-24-1763-2020, https://doi.org/10.5194/hess-24-1763-2020, 2020
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This study used a water balance approach based on GRACE total water storage to infer the amount of cold-season precipitation in four Arctic river basins. This was used to evaluate four gridded meteorological data sets, which were used as inputs to a land surface model. We found that the cold-season precipitation in these data sets needed to be increased by up to 55 %. Using these higher precipitation inputs improved the model representation of Arctic hydrology, particularly lying snow.
Abbas Fayad and Simon Gascoin
Hydrol. Earth Syst. Sci., 24, 1527–1542, https://doi.org/10.5194/hess-24-1527-2020, https://doi.org/10.5194/hess-24-1527-2020, 2020
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Seasonal snowpack is an essential water resource in Mediterranean mountains. Here, we look at the role of water percolation in simulating snow mass (SWE), for the first time, in Mount Lebanon. We use SnowModel, a distributed snow model, forced by station data. The main sources of uncertainty were attributed to rain–snow partitioning, transient winter snowmelt, and the subpixel snow cover. Yet, we show that a process-based model is suitable to simulate wet snowpack in Mediterranean mountains.
Joel Fiddes, Kristoffer Aalstad, and Sebastian Westermann
Hydrol. Earth Syst. Sci., 23, 4717–4736, https://doi.org/10.5194/hess-23-4717-2019, https://doi.org/10.5194/hess-23-4717-2019, 2019
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In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.
Keith S. Jennings and Noah P. Molotch
Hydrol. Earth Syst. Sci., 23, 3765–3786, https://doi.org/10.5194/hess-23-3765-2019, https://doi.org/10.5194/hess-23-3765-2019, 2019
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There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix of the two. Here we show that method choice introduces marked uncertainty to simulated snowpack water storage (> 200 mm) and snow cover duration (> 1 month) in areas that receive significant winter and spring precipitation at air temperatures at and near freezing. This marked uncertainty has implications for water resources management as well as simulations of past and future hydroclimatic states.
Maria Andrianaki, Juna Shrestha, Florian Kobierska, Nikolaos P. Nikolaidis, and Stefano M. Bernasconi
Hydrol. Earth Syst. Sci., 23, 3219–3232, https://doi.org/10.5194/hess-23-3219-2019, https://doi.org/10.5194/hess-23-3219-2019, 2019
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We tested the performance of the SWAT hydrological model after being transferred from a small Alpine watershed to a greater area. We found that the performance of the model for the greater catchment was satisfactory and the climate change simulations gave insights into the impact of climate change on our site. Assessment tests are important in identifying the strengths and weaknesses of the models when they are applied under extreme conditions different to the ones that were calibrated.
Wenfeng Huang, Bin Cheng, Jinrong Zhang, Zheng Zhang, Timo Vihma, Zhijun Li, and Fujun Niu
Hydrol. Earth Syst. Sci., 23, 2173–2186, https://doi.org/10.5194/hess-23-2173-2019, https://doi.org/10.5194/hess-23-2173-2019, 2019
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Up to now, little has been known on ice thermodynamics and lake–atmosphere interaction over the Tibetan Plateau during ice-covered seasons due to a lack of field data. Here, model experiments on ice thermodynamics were conducted in a shallow lake using HIGHTSI. Water–ice heat flux was a major source of uncertainty for lake ice thickness. Heat and mass budgets were estimated within the vertical air–ice–water system. Strong ice sublimation occurred and was responsible for water loss during winter.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
Hydrol. Earth Syst. Sci., 23, 1–17, https://doi.org/10.5194/hess-23-1-2019, https://doi.org/10.5194/hess-23-1-2019, 2019
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As snow cover becomes patchy during snowmelt, energy is advected from warm snow-free surfaces to cold snow-covered surfaces. This paper proposes a simple sensible and latent heat advection model for snowmelt situations that can be coupled to one-dimensional energy balance snowmelt models. The model demonstrates that sensible and latent heat advection fluxes can compensate for one another, especially in early melt periods.
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, https://doi.org/10.5194/hess-22-5711-2018, 2018
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A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
Michael L. Follum, Jeffrey D. Niemann, Julie T. Parno, and Charles W. Downer
Hydrol. Earth Syst. Sci., 22, 2669–2688, https://doi.org/10.5194/hess-22-2669-2018, https://doi.org/10.5194/hess-22-2669-2018, 2018
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Spatial patterns of snow and frozen ground within watersheds can impact the volume and timing of runoff. Commonly used snow and frozen ground simulation methods were modified to better account for the effects of topography and land cover on the spatial patterns of snow and frozen ground. When tested using a watershed in Vermont the modifications resulted in more accurate temporal and spatial simulation of both snow and frozen ground.
Jan Seibert, Marc J. P. Vis, Irene Kohn, Markus Weiler, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 2211–2224, https://doi.org/10.5194/hess-22-2211-2018, https://doi.org/10.5194/hess-22-2211-2018, 2018
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In many glacio-hydrological models glacier areas are assumed to be constant over time, which is a crucial limitation. Here we describe a novel approach to translate mass balances as simulated by the (glacio)hydrological model into glacier area changes. We combined the Δh approach of Huss et al. (2010) with the bucket-type model HBV and introduced a lookup table approach, which also allows periods with advancing glaciers to be represented, which is not possible with the original Huss method.
Florian Hanzer, Kristian Förster, Johanna Nemec, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 22, 1593–1614, https://doi.org/10.5194/hess-22-1593-2018, https://doi.org/10.5194/hess-22-1593-2018, 2018
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Climate change effects on snow, glaciers, and hydrology are investigated for the Ötztal Alps region (Austria) using a hydroclimatological model driven by climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios. The results show declining snow amounts and strongly retreating glaciers with moderate effects on catchment runoff until the mid-21st century, whereas annual runoff volumes decrease strongly towards the end of the century.
Muhammad Fraz Ismail and Wolfgang Bogacki
Hydrol. Earth Syst. Sci., 22, 1391–1409, https://doi.org/10.5194/hess-22-1391-2018, https://doi.org/10.5194/hess-22-1391-2018, 2018
Marit Van Tiel, Adriaan J. Teuling, Niko Wanders, Marc J. P. Vis, Kerstin Stahl, and Anne F. Van Loon
Hydrol. Earth Syst. Sci., 22, 463–485, https://doi.org/10.5194/hess-22-463-2018, https://doi.org/10.5194/hess-22-463-2018, 2018
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Glaciers are important hydrological reservoirs. Short-term variability in glacier melt and also glacier retreat can cause droughts in streamflow. In this study, we analyse the effect of glacier changes and different drought threshold approaches on future projections of streamflow droughts in glacierised catchments. We show that these different methodological options result in different drought projections and that these options can be used to study different aspects of streamflow droughts.
Felix N. Matt, John F. Burkhart, and Joni-Pekka Pietikäinen
Hydrol. Earth Syst. Sci., 22, 179–201, https://doi.org/10.5194/hess-22-179-2018, https://doi.org/10.5194/hess-22-179-2018, 2018
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Certain particles that have the ability to absorb sunlight deposit onto mountain snow via atmospheric transport mechanisms and then lower the snow's ability to reflect sunlight, which increases snowmelt. Herein we present a model aiming to simulate this effect and model the impacts on the streamflow of a southern Norwegian river. We find a significant difference in streamflow between simulations with and without the effect of light absorbing particles applied, in particular during spring melt.
Hiroyuki Hirashima, Francesco Avanzi, and Satoru Yamaguchi
Hydrol. Earth Syst. Sci., 21, 5503–5515, https://doi.org/10.5194/hess-21-5503-2017, https://doi.org/10.5194/hess-21-5503-2017, 2017
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We reproduced the formation of capillary barriers and the development of preferential flow through snow using a multi-dimensional water transport model, which was then validated using laboratory experiments of liquid water infiltration into layered, initially dry snow. Simulation results showed that the model reconstructs some relevant features of capillary barriers and the timing of liquid water arrival at the snow base.
Claudio Bravo, Thomas Loriaux, Andrés Rivera, and Ben W. Brock
Hydrol. Earth Syst. Sci., 21, 3249–3266, https://doi.org/10.5194/hess-21-3249-2017, https://doi.org/10.5194/hess-21-3249-2017, 2017
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We present an analysis of meteorological conditions and melt for Universidad Glacier in central Chile. This glacier is characterized by high melt rates over the ablation season, representing a mean contribution of between 10 and 13 % of the total runoff observed in the upper Tinguiririca Basin during the November 2009 to March 2010 period. Few studies have quantified the glacier melt contribution to river runoff in Chile, and this work represents a new precedent for the Andes.
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
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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.
Kelly E. Gleason, Anne W. Nolin, and Travis R. Roth
Hydrol. Earth Syst. Sci., 21, 1137–1147, https://doi.org/10.5194/hess-21-1137-2017, https://doi.org/10.5194/hess-21-1137-2017, 2017
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We present a coupled modeling approach used to objectively identify representative snow-monitoring locations in a forested watershed in the western Oregon Cascades mountain range. The resultant Forest Elevational Snow Transect (ForEST) represents combinations of forested and open land cover types at low, mid-, and high elevations.
Rafael Pimentel, Javier Herrero, and María José Polo
Hydrol. Earth Syst. Sci., 21, 805–820, https://doi.org/10.5194/hess-21-805-2017, https://doi.org/10.5194/hess-21-805-2017, 2017
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This study analyses the subgrid variability of the snow distribution in a Mediterranean region and formulates a parametric approach that includes these scale effects in the physical modelling of snow by means of accumulation–depletion curves associated with snow evolution patterns, by means of terrestrial photography. The results confirm that the use of these on a cell scale provides a solid foundation for the extension of point snow models to larger areas.
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
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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.
Jacob C. Yde, Niels T. Knudsen, Jørgen P. Steffensen, Jonathan L. Carrivick, Bent Hasholt, Thomas Ingeman-Nielsen, Christian Kronborg, Nicolaj K. Larsen, Sebastian H. Mernild, Hans Oerter, David H. Roberts, and Andrew J. Russell
Hydrol. Earth Syst. Sci., 20, 1197–1210, https://doi.org/10.5194/hess-20-1197-2016, https://doi.org/10.5194/hess-20-1197-2016, 2016
E. Cornwell, N. P. Molotch, and J. McPhee
Hydrol. Earth Syst. Sci., 20, 411–430, https://doi.org/10.5194/hess-20-411-2016, https://doi.org/10.5194/hess-20-411-2016, 2016
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We present a high-resolution snow water equivalent estimation for the 2001–2014 period over the extratropical Andes Cordillera of Argentina and Chile, the first of its type. The effect of elevation on accumulation is confirmed, although this is less marked in the northern portion of the domain. The 3000–4000 m a.s.l. elevation band contributes the bulk of snowmelt, but the 4000–5000 m a.s.l. band is a significant source and deserves further monitoring and research.
S. Frey and H. Holzmann
Hydrol. Earth Syst. Sci., 19, 4517–4530, https://doi.org/10.5194/hess-19-4517-2015, https://doi.org/10.5194/hess-19-4517-2015, 2015
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Temperature index melt models often lead to snow accumulation in high mountainous elevations. We developed a simple conceptual snow redistribution model working on a commonly used grid cell size of 1x1km. That model is integrated in the hydrological rainfall runoff model COSERO. Applying the model to the catchment of Oetztaler Ache, Austria, could prevent the accumulation of snow in the upper altitudes and lead to an improved model efficiency regarding discharge and snow coverage (MODIS).
Z. H. He, F. Q. Tian, H. V. Gupta, H. C. Hu, and H. P. Hu
Hydrol. Earth Syst. Sci., 19, 1807–1826, https://doi.org/10.5194/hess-19-1807-2015, https://doi.org/10.5194/hess-19-1807-2015, 2015
S. J. Marshall
Hydrol. Earth Syst. Sci., 18, 5181–5200, https://doi.org/10.5194/hess-18-5181-2014, https://doi.org/10.5194/hess-18-5181-2014, 2014
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This paper presents a new 12-year glacier meteorological, mass balance, and run-off record from the Canadian Rocky Mountains. This provides insight into the glaciohydrological regime of the Rockies. For the period 2002-2013, about 60% of glacier meltwater run-off originated from seasonal snow and 40% was derived from glacier ice and firn. Ice and firn run-off is concentrated in the months of August and September, at which time it contributes significantly to regional-scale water resources.
J. You, D. G. Tarboton, and C. H. Luce
Hydrol. Earth Syst. Sci., 18, 5061–5076, https://doi.org/10.5194/hess-18-5061-2014, https://doi.org/10.5194/hess-18-5061-2014, 2014
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This paper evaluates three improvements to an energy balance snowmelt model aimed to represent snow surface temperature while retaining the parsimony of a single layer. Surface heat flow is modeled using a forcing term related to the vertical temperature difference and a restore term related to the temporal gradient of surface temperature. Adjustments for melt water refreezing and thermal conductivity when the snow is shallow are introduced. The model performs well at the three test sites.
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Short summary
In mountainous terrain, the snowpack is strongly affected by incoming shortwave and longwave radiation. Satellite-derived products of incoming radiation were assessed in the French Alps and the Pyrenees and compared to meteorological forecasts, reanalyses and in situ measurements. We showed their good quality in mountains. The different radiation datasets were used as radiative forcing for snowpack simulations with the detailed model Crocus. Their impact on the snowpack evolution was explored.
In mountainous terrain, the snowpack is strongly affected by incoming shortwave and longwave...