Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2545-2020
© 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-24-2545-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 May 2020
Research article |
| 15 May 2020
| 15 May 2020
Snow processes in mountain forests: interception modeling for coarse-scale applications
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
David Moeser
USGS New Mexico Water Science Center, Albuquerque, NM, USA
Michaela Teich
Austrian Federal Research Centre for Forests, Natural Hazards and Landscape (BFW), Innsbruck, Austria
Department of Wildland Resources, Utah State University, Logan, UT, USA
Laure Vincent
Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France
Yves Lejeune
Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France
Jean-Emmanuel Sicart
Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Institut des Géosciences de l’Environnement (IGE) – UMR 5001, 38000 Grenoble, France
Jean-Matthieu Monnet
Université Grenoble Alpes, INRAE, LESSEM, 38402 St-Martin-d'Hères, France
Related authors
Louis Le Toumelin, Isabelle Gouttevin, Clovis Galiez, and Nora Helbig
Nonlin. Processes Geophys., 31, 75–97, https://doi.org/10.5194/npg-31-75-2024, https://doi.org/10.5194/npg-31-75-2024, 2024
Short summary
Short summary
Forecasting wind fields over mountains is of high importance for several applications and particularly for understanding how wind erodes and disperses snow. Forecasters rely on operational wind forecasts over mountains, which are currently only available on kilometric scales. These forecasts can also be affected by errors of diverse origins. Here we introduce a new strategy based on artificial intelligence to correct large-scale wind forecasts in mountains and increase their spatial resolution.
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
Short summary
Short summary
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.
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.
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
Louis Le Toumelin, Isabelle Gouttevin, Clovis Galiez, and Nora Helbig
Nonlin. Processes Geophys., 31, 75–97, https://doi.org/10.5194/npg-31-75-2024, https://doi.org/10.5194/npg-31-75-2024, 2024
Short summary
Short summary
Forecasting wind fields over mountains is of high importance for several applications and particularly for understanding how wind erodes and disperses snow. Forecasters rely on operational wind forecasts over mountains, which are currently only available on kilometric scales. These forecasts can also be affected by errors of diverse origins. Here we introduce a new strategy based on artificial intelligence to correct large-scale wind forecasts in mountains and increase their spatial resolution.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
Short summary
Short summary
Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Mathieu Le Breton, Éric Larose, Laurent Baillet, Yves Lejeune, and Alec van Herwijnen
The Cryosphere, 17, 3137–3156, https://doi.org/10.5194/tc-17-3137-2023, https://doi.org/10.5194/tc-17-3137-2023, 2023
Short summary
Short summary
We monitor the amount of snow on the ground using passive radiofrequency identification (RFID) tags. These small and inexpensive tags are wirelessly read by a stationary reader placed above the snowpack. Variations in the radiofrequency phase delay accurately reflect variations in snow amount, known as snow water equivalent. Additionally, each tag is equipped with a sensor that monitors the snow temperature.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
Short summary
Short summary
We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Christopher J. L. D'Amboise, Michael Neuhauser, Michaela Teich, Andreas Huber, Andreas Kofler, Frank Perzl, Reinhard Fromm, Karl Kleemayr, and Jan-Thomas Fischer
Geosci. Model Dev., 15, 2423–2439, https://doi.org/10.5194/gmd-15-2423-2022, https://doi.org/10.5194/gmd-15-2423-2022, 2022
Short summary
Short summary
The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
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
Short summary
Short summary
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.
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.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
E. Tusa, J. M. Monnet, J. B. Barré, M. Dalla Mura, and J. Chanussot
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 487–494, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-487-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-487-2020, 2020
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
Short summary
Short summary
This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Yves Lejeune, Marie Dumont, Jean-Michel Panel, Matthieu Lafaysse, Philippe Lapalus, Erwan Le Gac, Bernard Lesaffre, and Samuel Morin
Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, https://doi.org/10.5194/essd-11-71-2019, 2019
Short summary
Short summary
This paper introduces and provides access to a daily (1960–2017) and an hourly (1993–2017) dataset of snow and meteorological data measured at the Col de Porte site, 1325 m a.s.l, Charteuse, France. The daily dataset can be used to quantify the effect of climate change at this site, with a reduction of the mean snow depth of 39 cm from 1960–1990 to 1990–2017. The daily and hourly datasets are useful and appropriate for driving and evaluating a snowpack model over such a long period.
Thomas Condom, Marie Dumont, Lise Mourre, Jean Emmanuel Sicart, Antoine Rabatel, Alessandra Viani, and Alvaro Soruco
Geosci. Instrum. Method. Data Syst., 7, 169–178, https://doi.org/10.5194/gi-7-169-2018, https://doi.org/10.5194/gi-7-169-2018, 2018
Short summary
Short summary
This study presents a new instrument called a low-cost albedometer (LCA) composed of two illuminance sensors. The ratio between reflected vs. incident illuminances is called the albedo index and can be compared with actual albedo values. We demonstrate that our system performs well and thus provides relevant opportunities to document spatiotemporal changes in the surface albedo from direct observations at the scale of an entire catchment at a low cost.
Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, https://doi.org/10.5194/tc-12-1249-2018, 2018
Short summary
Short summary
This article addresses local changes of seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps, for the period 1960–2100. We use an ensemble of adjusted RCM outputs consistent with IPCC AR5 GCM outputs (RCPs 2.6, 4.5 and 8.5) and the snowpack model Crocus. Beyond scenario-based approach, global temperature levels on the order of 1.5 °C and 2 °C above preindustrial levels correspond to 25 and 32% reduction of mean snow depth.
Francois Tuzet, Marie Dumont, Matthieu Lafaysse, Ghislain Picard, Laurent Arnaud, Didier Voisin, Yves Lejeune, Luc Charrois, Pierre Nabat, and Samuel Morin
The Cryosphere, 11, 2633–2653, https://doi.org/10.5194/tc-11-2633-2017, https://doi.org/10.5194/tc-11-2633-2017, 2017
Short summary
Short summary
Light-absorbing impurities deposited on snow, such as soot or dust, strongly modify its evolution. We implemented impurity deposition and evolution in a detailed snowpack model, thereby expanding the reach of such models into addressing the subtle interplays between snow physics and impurities' optical properties. Model results were evaluated based on innovative field observations at an Alpine site. This allows future investigations in the fields of climate, hydrology and avalanche prediction.
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
Short summary
Short summary
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.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
Short summary
Short summary
Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Maxime Litt, Jean-Emmanuel Sicart, Delphine Six, Patrick Wagnon, and Warren D. Helgason
The Cryosphere, 11, 971–987, https://doi.org/10.5194/tc-11-971-2017, https://doi.org/10.5194/tc-11-971-2017, 2017
Short summary
Short summary
Climate variations might change the frequency of typical weather conditions. We present a weather pattern classification as an useful tool for identifying changing glacier wind regimes. We show the intensity of turbulent heat exchanges between ice and air changes with these regimes, as well as the importance of discrepancies between bulk-aerodynamic and eddy-covariance fluxes. The results suggest these discrepancies influence melt estimates from surface energy balance calculations.
J.-M. Monnet, C. Ginzler, and J.-C. Clivaz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 727–731, https://doi.org/10.5194/isprs-archives-XLI-B8-727-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-727-2016, 2016
L. Mourre, T. Condom, C. Junquas, T. Lebel, J. E. Sicart, R. Figueroa, and A. Cochachin
Hydrol. Earth Syst. Sci., 20, 125–141, https://doi.org/10.5194/hess-20-125-2016, https://doi.org/10.5194/hess-20-125-2016, 2016
Short summary
Short summary
Three different types of gridded precipitation products are compared in a high glaciated tropical mountain environment (Cordillera Blanca, Peru): ground-based interpolation, a satellite-derived product (TRMM3B42), and outputs from the WRF regional climate model. While none of the products meets the challenge of representing both accumulated quantities and frequency of occurrence at the short timescale, we concluded that new methods should be used to merge those various precipitation products.
M. Litt, J.-E. Sicart, and W. Helgason
Atmos. Meas. Tech., 8, 3229–3250, https://doi.org/10.5194/amt-8-3229-2015, https://doi.org/10.5194/amt-8-3229-2015, 2015
Short summary
Short summary
We deal with surface turbulent flux calculations on a tropical glacier and analyse the related errors. We use data from two eddy-covariance systems and wind speed and temperature profiles collected during a 2-month measurement campaign undertaken within the atmospheric surface layer of the glacier. We show the largest error sources are related to roughness length uncertainties and to nonstationarity of the flow induced by the interaction of outer-layer eddies with the surface-layer flow.
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
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
A. Rabatel, B. Francou, A. Soruco, J. Gomez, B. Cáceres, J. L. Ceballos, R. Basantes, M. Vuille, J.-E. Sicart, C. Huggel, M. Scheel, Y. Lejeune, Y. Arnaud, M. Collet, T. Condom, G. Consoli, V. Favier, V. Jomelli, R. Galarraga, P. Ginot, L. Maisincho, J. Mendoza, M. Ménégoz, E. Ramirez, P. Ribstein, W. Suarez, M. Villacis, and P. Wagnon
The Cryosphere, 7, 81–102, https://doi.org/10.5194/tc-7-81-2013, https://doi.org/10.5194/tc-7-81-2013, 2013
Related subject area
Subject: Snow and Ice | Techniques and Approaches: Modelling approaches
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
Satellite-derived products of solar and longwave irradiances used for snowpack modelling in mountainous terrain
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
Estimating degree-day factors from MODIS for snowmelt runoff modeling
Effect of meteorological forcing and snow model complexity on hydrological simulations in the Sieber catchment (Harz Mountains, Germany)
Model simulations of the modulating effect of the snow cover in a rain-on-snow event
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Louis Quéno, Fatima Karbou, Vincent Vionnet, and Ingrid Dombrowski-Etchevers
Hydrol. Earth Syst. Sci., 24, 2083–2104, https://doi.org/10.5194/hess-24-2083-2020, https://doi.org/10.5194/hess-24-2083-2020, 2020
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Z. H. He, J. Parajka, F. Q. Tian, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 4773–4789, https://doi.org/10.5194/hess-18-4773-2014, https://doi.org/10.5194/hess-18-4773-2014, 2014
Short summary
Short summary
In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Snow density is estimated as the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. DDFS values are estimated as the ratio between changes in the snow water equivalent and difference between the daily temperature and a threshold value for days with snowmelt.
K. Förster, G. Meon, T. Marke, and U. Strasser
Hydrol. Earth Syst. Sci., 18, 4703–4720, https://doi.org/10.5194/hess-18-4703-2014, https://doi.org/10.5194/hess-18-4703-2014, 2014
Short summary
Short summary
Four snow models of different complexity (temperature-index vs. energy balance models) are compared using observed and dynamically downscaled atmospheric analysis data as input. Biases in simulated precipitation lead to lower model performance. However, simulated meteorological conditions are proven to be a valuable meteorological data source as they provide model input in regions with limited availability of observations and allow the application of energy balance approaches.
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.
Cited articles
Andreadis, K. M., Storck, P., and Lettenmaier, D. P.: Modeling snow
accumulation and ablation processes in forested environments, Water Resour.
Res., 45, W05429, https://doi.org/10.1029/2008WR007042, 2009. a
Aston, A. R.: Rainfall interception by eight small trees, J. Hydrol., 42,
383–396, 1993. a
Bartlett, P. A. and Verseghy, D. L.: Modified treatment of intercepted snow
improves the simulated forest albedo in the Canadian Land Surface Scheme,
Hydrol. Process., 29, 3208–3226, https://doi.org/10.1002/hyp.10431,
2015. a, b
Bründl, M., Bartelt, P., Schneebeli, M., and Flühler, H.: Measuring branch
deflection of spruce branches caused by intercepted snow load, Hydrol.
Process., 13, 2357–2369, 1999. a
Danish Geodata Agency:
https://download.kortforsyningen.dk/content/dhmpunktsky, last
access: 22 November 2019. a
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T., and Hanasaki, N.:
GSWP-2: Multimodel analysis and implications for our perception of the land
surface, B. Am. Meteorol. Soc., 87, 1381–1398, 2006. a
Essery, R.: Large-scale simulations of snow albedo masking by forests, Geophys.
Res. Lett., 40, 5521–5525, https://doi.org/10.1002/grl.51008, 2013. a
Essery, R. L., Pomeroy, J. W., Parviainen, J., and Storck, P.: Sublimation of
snow from coniferous forests in a climate model, J. Climate, 16, 1855–1864,
2003. a
Essery, R. L., Bunting, P., Hardy, J., Link, T., Marks, D., Melloh, R.,
Pomeroy, J., Rowlands, A., and Rutter, N.: Scaling and parametrization of
clear-sky solar radiation over complex topography, J. Hydrometeorol., 9,
228–241, 2008. a
Eysn, L., Hollaus, M., Lindberg, E., Berger, F., Monnet, J.-M., Dalponte, M.,
Kobal, M., Pellegrini, M., Lingua, E., Mongus, D., and Pfeifer, N.: A
Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous
Forest Data from the Alpine Space, Forests, 6, 1721–1747, 2015. a
Federal Office of Topography Swisstopo:
https://www.swisstopo.admin.ch/en/knowledge-facts/geoinformation/lidar-data.html,
last access: 22 November 2019. a
Helbig, N. and Löwe, H.: Parameterization of the spatially averaged sky view
factor in complex topography, J. Geophys. Res., 119, 4616–4625,
https://doi.org/10.1002/2013JD020892, 2014. a
Hellström, R. A.: Forest cover algorithms for estimating meteorological
forcing in a numerical snow model, Hydrol. Process., 14, 3239–3256, 2000. a
Kaartinen, H., Hyyppä, J., Yu, X., Vastaranta, M., Hyyppä, H., Kukko, A., Holopainen, M., Heipke, C., Hirschmugl, M., Morsdorf, F., Næsset, E., Pitkänen, J., Popescu, S., Solberg, S., Wolf, B. M., and Wu, J.-C.: An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning, Remote Sens., 4, 950–974,
https://doi.org/10.3390/rs4040950, 2012. a
Knowles, N., Dettinger, M. D., and Cayan, D. R.: Trends in snowfall versus
rainfall in the western United States, J. Climate, 19, 4545–4559, 2006. a
Krinner, G., Derksen, C., Essery, R., Flanner, M., Hagemann, S., Clark, M., Hall, A., Rott, H., Brutel-Vuilmet, C., Kim, H., Ménard, C. B., Mudryk, L., Thackeray, C., Wang, L., Arduini, G., Balsamo, G., Bartlett, P., Boike, J., Boone, A., Chéruy, F., Colin, J., Cuntz, M., Dai, Y., Decharme, B., Derry, J., Ducharne, A., Dutra, E., Fang, X., Fierz, C., Ghattas, J., Gusev, Y., Haverd, V., Kontu, A., Lafaysse, M., Law, R., Lawrence, D., Li, W., Marke, T., Marks, D., Ménégoz, M., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Raleigh, M. S., Schaedler, G., Semenov, V., Smirnova, T. G., Stacke, T., Strasser, U., Svenson, S., Turkov, D., Wang, T., Wever, N., Yuan, H., Zhou, W., and Zhu, D.: ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks, Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, 2018. a
Latvian Geospatial Information Agency:
https://www.lgia.gov.lv/lv/Digit%C4%81lais%20virsmas%20modelis,
last access: 22 November 2019. a
Lejeune, Y., Dumont, M., Panel, J.-M., Lafaysse, M., Lapalus, P., Le Gac, E., Lesaffre, B., and Morin, S.: 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m of altitude), Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, 2019. a
Lundberg, A., Nakai, Y., Thunehed, H., and Halldin, S.: Snow accumulation in
forests from ground and remote-sensing data, Hydrol. Process., 18,
1941–1955, https://doi.org/10.1002/hyp.1459, 2004. a, b
Mahat, V. and Tarboton, D. G.: Canopy radiation transmission for an energy
balance snowmelt model, Water Resour. Res., 48, 1–16,
https://doi.org/10.1029/2011WR010438, 2012. a
Mahat, V. and Tarboton, D. G.: Representation of canopy snow interception,
unloading and melt in a parsimonious snowmelt model, Hydrol. Process., 28,
6320–6336, https://doi.org/10.1002/hyp.10116, 2014. a
Moeser, D., Mazotti, G., Helbig, N., and Jonas, T.: Representing spatial
variability of forest snow: Implementation of a new interception model, Water
Resour. Res., 52, 5041–5059, https://doi.org/10.1002/2015WR017961, 2016. a, b, c, d
Morin, S., Lejeune, Y., Lesaffre, B., Panel, J.-M., Poncet, D., David, P., and Sudul, M.: An 18-yr long (1993–2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) for driving and evaluating snowpack models, Earth Syst. Sci. Data, 4, 13–21, https://doi.org/10.5194/essd-4-13-2012, 2012. a
Morsdorf, F., Kötz, B., Meier, E., Itten, K. I., and Allgöwer, B.:
Estimation of LAI and fractional cover from small footprint airborne laser
scanning data based on gap fraction, Remote Sens. Environ., 104, 50–61,
2006. a
PRISM Climate Group: 30-Year Normals, Oregon State University, available at:
http://www.prism.oregonstate.edu/normals/ (created: 7 November 2012;
last access: 28 June 2019), 2012. a
Roesch, A. and Roeckner, E.: Assessment of snow cover and surface albedo in
the ECHAM5 general circulation model, J. Clim., 19, 3828–3843, 2006. a
Rousseeuw, P., Croux, C., Todorov, V., Ruckstuhl, A., Salibian-Barrera, M.,
Verbeke, T., Koller, M., and Maechler, M.: robustbase: Basic Robust
Statistics, available at: http://CRAN.R-project.org/package=robustbase (last access: 12 May 2020), r
package version 0.92-5, 2015. a
Rutter, N., Essery, R., Pomeroy, J., Altimir, N., Andreadis, K., Baker, I.,
Barr, A., Bartlett, P., Boone, A., Deng, H., Douville, H., Dutra, E., Elder, K., Ellis, C., Feng, X., Gelfan, A., Goodbody, A., Gusev, Y., Gustafsson, D., Hellström, R., Hirabayashi, Y., Hirota, T., Jonas, T., Koren, V., Kuragina, A., Lettenmaier, D., Li, W.-P., Luce, C., Martin, E., Nasonova, O., Pumpanen, J., Pyles, R. D., Samuelsson, P., Sandells, M., Schädler, G., Shmakin, A., Smirnova, T. G., Stähli, M., Stöckli, R., Strasser, U., Su, H., Suzuki, K., Takata, K., Tanaka, K., Thompson, E., Vesala, T., Viterbo, P., Wiltshire, A., Xia, K., Xue, Y., and Yamazaki, T.: Evaluation of forest
snow processes models (SnowMIP2), J. Geophys. Res.-Atmos., 114, D061111,
https://doi.org/10.1029/2008JD011063, 2009. a, b, c
Sicart, J. E., Essery, R. L. H., Pomeroy, J. W., Hardy, J., Link, T., and
Marks, D.: A sensitivity study of daytime net radiation during snowmelt to
forest canopy and atmospheric conditions, J. Hydrometeorol., 5, 774–784,
2004. a
Siegel, R. and Howell, J. R.: Thermal Radiation Heat Transfer, Hemisphere
Publishing Corp., 1978. a
Storck, P. and Lettenmaier, D. P.: Measurement of snow interception and canopy
effects on snow accumulation and m elt in a mountainous maritime climate,
Oregon, United States, Water Resour. Res., 38, 11, https://doi.org/10.1029/2002WR001281,
2002. a, b, c
Suzuki, K. and Nakai, Y.: Canopy snow influence on water and energy balances
in a coniferous forest plantation in Northern Japan, J. Hydrol., 352,
126–138, 2008. a
Teich, M. and Tarboton, D. G.: TW Daniels Experimental Forest (TWDEF) Lidar,
HydroShare, https://doi.org/10.4211/hs.36f3314971a547bc8bc72dc60d6bd03c, 2016.
a
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, For.
Ecol. Manage., 438, 186–203, https://doi.org/10.1016/j.foreco.2019.01.052, 2019. a
Varhola, A., Coops, N., Weiler, M., and Moore, R. D.: Forest canopy effects on
snow accumulation and ablation: An integrative review of empirical results,
J. Hydrol., 392, 219–233, 2010. a
Vincent, L., Lejeune, Y., M, L., Boone, A., Gac, E. L., Coulaud, C., Freche,
G., and Sicart, J. E.: Interception of snowfall by the trees is the main
challenge for snowpack simulations under forests, in: Proceedings of the
International Snow Science Workshop (ISSW), Innsbruck, Austria, pp. 705–710,
available at: http://arc.lib.montana.edu/snow-science/objects/ISSW2018_O08.4.pdf (last access: 12 May 2020),
2018. a, b, c
Webster, C. and Jonas, T.: Influence of canopy shading and snow coverage on
effective albedo in a snow-dominated evergreen needleleaf forest, Remote
Sens. Environ., 214, 48–58, 2018. a
Yakir, B.: Nonparametric Tests: Kolmogorov-Smirnov and Peacock, chap. 6, pp.
103–124, John Wiley & Sons, Ltd, https://doi.org/10.1002/9781118720608.ch6, 2013. a
Short summary
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.
Snow retained in the forest canopy (snow interception) drives spatial variability of the...
