Articles | Volume 16, issue 9
https://doi.org/10.5194/tc-16-3469-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-3469-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events
Swiss Federal Institute for Forest, Snow and Landscape Research, 8903
Birmensdorf, Switzerland
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos,
Switzerland
Adam Winstral
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos,
Switzerland
deceased, March 2021
Tobias Jonas
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos,
Switzerland
Paolo Burlando
Institute of Environmental Engineering, ETH Zurich, 8093 Zurich,
Switzerland
Nadav Peleg
Institute of Environmental Engineering, ETH Zurich, 8093 Zurich,
Switzerland
Institute of Earth Surface Dynamics, University of Lausanne, 1015
Lausanne, Switzerland
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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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Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
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.
Martina Botter, Matthias Zeeman, Paolo Burlando, and Simone Fatichi
Biogeosciences, 18, 1917–1939, https://doi.org/10.5194/bg-18-1917-2021, https://doi.org/10.5194/bg-18-1917-2021, 2021
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
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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.
Marius G. Floriancic, Wouter R. Berghuijs, Tobias Jonas, James W. Kirchner, and Peter Molnar
Hydrol. Earth Syst. Sci., 24, 5423–5438, https://doi.org/10.5194/hess-24-5423-2020, https://doi.org/10.5194/hess-24-5423-2020, 2020
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Low river flows affect societies and ecosystems. Here we study how precipitation and potential evapotranspiration shape low flows across a network of 380 Swiss catchments. Low flows in these rivers typically result from below-average precipitation and above-average potential evapotranspiration. Extreme low flows result from long periods of the combined effects of both drivers.
Giulia Battista, Peter Molnar, and Paolo Burlando
Earth Surf. Dynam., 8, 619–635, https://doi.org/10.5194/esurf-8-619-2020, https://doi.org/10.5194/esurf-8-619-2020, 2020
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Suspended sediment load in rivers is highly uncertain because of spatial and temporal variability. By means of a hydrology and suspended sediment transport model, we investigated the effect of spatial variability in precipitation and surface erodibility on catchment sediment fluxes in a mesoscale river basin.
We found that sediment load depends on the spatial variability in erosion drivers, as this affects erosion rates and the location and connectivity to the channel of the erosion areas.
Naika Meili, Gabriele Manoli, Paolo Burlando, Elie Bou-Zeid, Winston T. L. Chow, Andrew M. Coutts, Edoardo Daly, Kerry A. Nice, Matthias Roth, Nigel J. Tapper, Erik Velasco, Enrique R. Vivoni, and Simone Fatichi
Geosci. Model Dev., 13, 335–362, https://doi.org/10.5194/gmd-13-335-2020, https://doi.org/10.5194/gmd-13-335-2020, 2020
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We developed a novel urban ecohydrological model (UT&C v1.0) that is able to account for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements in three cities in different climates (Singapore, Melbourne, Phoenix) and can be used to assess urban climate mitigation strategies that aim at increasing or changing urban green cover.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
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Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Michael Schirmer and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 143–157, https://doi.org/10.5194/hess-24-143-2020, https://doi.org/10.5194/hess-24-143-2020, 2020
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The spatial distribution of snow water equivalent (SWE) and melt are important for hydrological applications in alpine terrain. We measured the spatial distribution of melt using a drone in very high resolution and could relate melt to topographic characteristics. Interestingly, melt and SWE were not related spatially, which influences the speed of areal melt out. We could explain this by melt varying over larger distances than SWE.
Martina Botter, Paolo Burlando, and Simone Fatichi
Hydrol. Earth Syst. Sci., 23, 1885–1904, https://doi.org/10.5194/hess-23-1885-2019, https://doi.org/10.5194/hess-23-1885-2019, 2019
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The study focuses on the solute export from rivers with the purpose of discerning the impacts of anthropic activities and catchment characteristics on water quality. The results revealed a more detectable impact of the anthropic activities than of the catchment characteristics. The solute export follows different dynamics depending on catchment characteristics and mainly on solute-specific properties. The export modality is consistent across different catchments only for a minority of solutes.
Sahani Pathiraja, Daniela Anghileri, Paolo Burlando, Ashish Sharma, Lucy Marshall, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 22, 2903–2919, https://doi.org/10.5194/hess-22-2903-2018, https://doi.org/10.5194/hess-22-2903-2018, 2018
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Hydrologic modeling methodologies must be developed that are capable of predicting runoff in catchments with changing land cover conditions. This article investigates the efficacy of a recently developed approach that allows for runoff prediction in catchments with unknown land cover changes, through experimentation in a deforested catchment in Vietnam. The importance of key elements of the method in ensuring its success, such as the chosen hydrologic model, is investigated.
Roman Juras, Sebastian Würzer, Jirka Pavlásek, Tomáš Vitvar, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 4973–4987, https://doi.org/10.5194/hess-21-4973-2017, https://doi.org/10.5194/hess-21-4973-2017, 2017
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This research investigates the rainwater dynamics in the snowpack under artificial rain-on-snow events. Deuterium-enriched water was sprayed on the isolated snowpack and rainwater was further identified in the runoff. We found that runoff from cold snowpack was created faster than from the ripe snowpack. Runoff from the cold snowpack also contained more rainwater compared to the ripe snowpack. These results are valuable for further snowpack runoff forecasting.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
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.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
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We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
Nena Griessinger, Franziska Mohr, and Tobias Jonas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-295, https://doi.org/10.5194/tc-2016-295, 2017
Revised manuscript not accepted
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We demonstrate the potential of ground penetrating radar for efficient and accurate measurements of snow depth and snow water equivalent when liquid water is present in the snowpack. We were able to derive snow ablation rates with high accuracy from repeated measurements.
We present the design of our light-weight setup consisting of a common-mid-point assembly on a plastic sled, which is mobile even in complex heterogeneous terrain like our investigated field sites in the eastern Swiss Alps.
Phillip Harder, Michael Schirmer, John Pomeroy, and Warren Helgason
The Cryosphere, 10, 2559–2571, https://doi.org/10.5194/tc-10-2559-2016, https://doi.org/10.5194/tc-10-2559-2016, 2016
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This paper assesses the accuracy of high-resolution snow depth maps generated from unmanned aerial vehicle imagery. Snow depth maps are generated from differencing snow-covered and snow-free digital surface models produced from structure from motion techniques. On average, the estimated snow depth error was 10 cm. This technique is therefore useful for observing snow accumulation and melt in deep snow but is restricted to observing peak snow accumulation in shallow snow.
Nena Griessinger, Jan Seibert, Jan Magnusson, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 3895–3905, https://doi.org/10.5194/hess-20-3895-2016, https://doi.org/10.5194/hess-20-3895-2016, 2016
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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.
Michal Jenicek, Jan Seibert, Massimiliano Zappa, Maria Staudinger, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 859–874, https://doi.org/10.5194/hess-20-859-2016, https://doi.org/10.5194/hess-20-859-2016, 2016
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We quantified how long snowmelt affects runoff, and we estimated the sensitivity of catchments to changes in snowpack. This is relevant as the increase of air temperature might cause decreased snow storage. We used time series from 14 catchments in Switzerland. On average, a decrease of maximum snow storage by 10 % caused a decrease of minimum discharge in July by 2 to 9 %. The results showed a higher sensitivity of summer low flow to snow in alpine catchments compared to pre-alpine catchments.
F. Kobierska, T. Jonas, J. W. Kirchner, and S. M. Bernasconi
Hydrol. Earth Syst. Sci., 19, 3681–3693, https://doi.org/10.5194/hess-19-3681-2015, https://doi.org/10.5194/hess-19-3681-2015, 2015
I. Gouttevin, M. Lehning, T. Jonas, D. Gustafsson, and M. Mölder
Geosci. Model Dev., 8, 2379–2398, https://doi.org/10.5194/gmd-8-2379-2015, https://doi.org/10.5194/gmd-8-2379-2015, 2015
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We improve the canopy module of a very detailed snow model, SNOWPACK, with a view of a more consistent representation of the sub-canopy energy balance with regard to the snowpack.
We show that adding a formulation of (i) the canopy heat capacity and (ii) a lowermost canopy layer (alike trunk + solar shaded leaves) yields significant improvement in the representation of sub-canopy incoming long-wave radiations, especially at nighttime. This energy is an important contributor to snowmelt.
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
M. Schirmer and B. Jamieson
The Cryosphere, 9, 587–601, https://doi.org/10.5194/tc-9-587-2015, https://doi.org/10.5194/tc-9-587-2015, 2015
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Numerical Weather Prediction (NWP) models are rarely verified for mountainous regions during the winter season, although avalanche forecasters and other decision makers frequently rely on NWP models. We verified two NWP models (GEM-LAM and GEM15) and a precipitation analysis system (CaPA) at approximately 100 stations in the mountains of western Canada and northwestern USA. Ultrasonic snow depth sensors and snow pillows were used to observe daily precipitation amounts.
N. Helbig, A. van Herwijnen, J. Magnusson, and T. Jonas
Hydrol. Earth Syst. Sci., 19, 1339–1351, https://doi.org/10.5194/hess-19-1339-2015, https://doi.org/10.5194/hess-19-1339-2015, 2015
Y. Bühler, M. Marty, L. Egli, J. Veitinger, T. Jonas, P. Thee, and C. Ginzler
The Cryosphere, 9, 229–243, https://doi.org/10.5194/tc-9-229-2015, https://doi.org/10.5194/tc-9-229-2015, 2015
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We are able to map snow depth over large areas ( > 100km2) using airborne digital photogrammetry. Digital photogrammetry is more economical than airborne Laser Scanning but slightly less accurate. Comparisons to independent snow depth measurements reveal an accuracy of about 30cm. Spatial continuous mapping of snow depth is a major step forward compared to point measurements usually applied today. Limitations are steep slopes (> 50°) and areas covered by trees and scrubs.
N. Peleg, E. Shamir, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 19, 567–581, https://doi.org/10.5194/hess-19-567-2015, https://doi.org/10.5194/hess-19-567-2015, 2015
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
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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.
M. Schirmer and B. Jamieson
The Cryosphere, 8, 387–394, https://doi.org/10.5194/tc-8-387-2014, https://doi.org/10.5194/tc-8-387-2014, 2014
F. Hüsler, T. Jonas, M. Riffler, J. P. Musial, and S. Wunderle
The Cryosphere, 8, 73–90, https://doi.org/10.5194/tc-8-73-2014, https://doi.org/10.5194/tc-8-73-2014, 2014
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, https://doi.org/10.5194/hess-17-3005-2013, 2013
N. Peleg, M. Ben-Asher, and E. Morin
Hydrol. Earth Syst. Sci., 17, 2195–2208, https://doi.org/10.5194/hess-17-2195-2013, https://doi.org/10.5194/hess-17-2195-2013, 2013
Related subject area
Discipline: Snow | Subject: Snow Hydrology
Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy
Using Sentinel-1 wet snow maps to inform fully-distributed physically-based snowpack models
Towards large-scale daily snow density mapping with spatiotemporally aware model and multi-source data
Drone-based ground-penetrating radar (GPR) application to snow hydrology
Two-dimensional liquid water flow through snow at the plot scale in continental snowpacks: simulations and field data comparisons
Fractional snow-covered area: scale-independent peak of winter parameterization
Seasonal components of freshwater runoff in Glacier Bay, Alaska: diverse spatial patterns and temporal change
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, Nander Wever, Adrien Michel, Michael Lehning, and Pierre-Erik Isabelle
The Cryosphere, 18, 2783–2807, https://doi.org/10.5194/tc-18-2783-2024, https://doi.org/10.5194/tc-18-2783-2024, 2024
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Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow (ROS) events lead to the formation of melt–freeze layers and that preferential flow is an important water transport mechanism in the sub-canopy snowpack. Simulations with SNOWPACK generally show good agreement with observations, except for the reproduction of melt–freeze layers. This was improved by simulating intercepted snow microstructure evolution, which also modulates ROS-induced runoff.
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.
Huadong Wang, Xueliang Zhang, Pengfeng Xiao, Tao Che, Zhaojun Zheng, Liyun Dai, and Wenbo Luan
The Cryosphere, 17, 33–50, https://doi.org/10.5194/tc-17-33-2023, https://doi.org/10.5194/tc-17-33-2023, 2023
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The geographically and temporally weighted neural network (GTWNN) model is constructed for estimating large-scale daily snow density by integrating satellite, ground, and reanalysis data, which addresses the importance of spatiotemporal heterogeneity and a nonlinear relationship between snow density and impact variables, as well as allows us to understand the spatiotemporal pattern and heterogeneity of snow density in different snow periods and snow cover regions in China from 2013 to 2020.
Eole Valence, Michel Baraer, Eric Rosa, Florent Barbecot, and Chloe Monty
The Cryosphere, 16, 3843–3860, https://doi.org/10.5194/tc-16-3843-2022, https://doi.org/10.5194/tc-16-3843-2022, 2022
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The internal properties of the snow cover shape the annual hygrogram of northern and alpine regions. This study develops a multi-method approach to measure the evolution of snowpack internal properties. The snowpack hydrological property evolution was evaluated with drone-based ground-penetrating radar (GPR) measurements. In addition, the combination of GPR observations and time domain reflectometry measurements is shown to be able to be adapted to monitor the snowpack moisture over winter.
Ryan W. Webb, Keith Jennings, Stefan Finsterle, and Steven R. Fassnacht
The Cryosphere, 15, 1423–1434, https://doi.org/10.5194/tc-15-1423-2021, https://doi.org/10.5194/tc-15-1423-2021, 2021
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We simulate the flow of liquid water through snow and compare results to field experiments. This process is important because it controls how much and how quickly water will reach our streams and rivers in snowy regions. We found that water can flow large distances downslope through the snow even after the snow has stopped melting. Improved modeling of snowmelt processes will allow us to more accurately estimate available water resources, especially under changing climate conditions.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Ryan L. Crumley, David F. Hill, Jordan P. Beamer, and Elizabeth R. Holzenthal
The Cryosphere, 13, 1597–1619, https://doi.org/10.5194/tc-13-1597-2019, https://doi.org/10.5194/tc-13-1597-2019, 2019
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In this study we investigate the historical (1980–2015) and projection scenario (2070–2099) components of freshwater runoff to Glacier Bay, Alaska, using a modeling approach. We find that many of the historically snow-dominated watersheds in Glacier Bay National Park and Preserve may transition towards rainfall-dominated hydrographs in a projection scenario under RCP 8.5 conditions. The changes in timing and volume of freshwater entering Glacier Bay will affect bay ecology and hydrochemistry.
Cited articles
Addor, N., Rössler, O., Köplin, N., Huss, M., Weingartner, R., and
Seibert, J.: Robust changes and sources of uncertainty in the projected
hydrological regimes of Swiss catchments, Water Resour. Res., 50,
7541–7562, https://doi.org/10.1002/2014WR015549, 2014.
Anandhi, A., Frei, A., Pierson, D. C., Schneiderman, E. M., Zion, M. S.,
Lounsbury, D., and Matonse, A. H.: Examination of change factor
methodologies for climate change impact assessment, Water Resour.
Res., 47, W03501, https://doi.org/10.1029/2010WR009104, 2011.
Beniston, M. and Stoffel, M.: Rain-on-snow events, floods and climate
change in the Alps: Events may increase with warming up to 4 C and decrease
thereafter, Sci. Total Environ., 571, 228–236,
https://doi.org/10.1016/j.scitotenv.2016.07.146, 2016.
CH2018 Project Team: CH2018 – Climate Scenarios for Switzerland, National
Centre for Climate Services, https://doi.org/10.18751/Climate/Scenarios/CH2018/1.0,
2018.
Chegwidden, O. S., Rupp, D. E., and Nijssen, B.: Climate change alters flood
magnitudes and mechanisms in climatically-diverse headwaters across the
northwestern United States, Environ. Res. Lett., 15, 094048,
https://doi.org/10.1088/1748-9326/ab986f, 2020.
Clark, M. P., Wilby, R. L., Gutmann, E. D., Vano, J. A., Gangopadhyay, S.,
Wood, A. W., Fowler, H. J., Prudhomme, Ch., Arnold, J. R., and Brekke, L. D.:
Characterizing uncertainty of the hydrologic impacts of climate change,
Current Climate Change Reports, 2, 55–64,
https://doi.org/10.1007/s40641-016-0034-x, 2016.
Deser, C., Knutti, R., Solomon, S., and Phillips, A. S.: Communication of the
role of natural variability in future North American climate, Nat. Clim.
Change, 2, 775, https://doi.org/10.1038/nclimate1562, 2012a.
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate
change projections: the role of internal variability, Clim. Dynam.,
38, 527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012b.
Egli, L., Jonas, T., and Meister, R.: Comparison of different automatic methods
for estimating snow water equivalent, Cold Reg. Sci. Technol.,
57, 107–115, https://doi.org/10.1016/j.coldregions.2009.02.008, 2009.
Essery, R., Morin, S., Lejeune, Y., and Ménard, C. B.: A comparison of
1701 snow models using observations from an alpine site, Adv. Water
Resour., 55, 131–148, https://doi.org/10.1016/j.advwatres.2012.07.013, 2013.
Fatichi, S., Rimkus, S., Burlando, P., and Bordoy, R.: Does internal climate
variability overwhelm climate change signals in streamflow? The upper Po and
Rhone basin case studies, Sci. Total Environ., 493, 1171–1182,
https://doi.org/10.1016/j.scitotenv.2013.12.014, 2014.
Fatichi, S., Ivanov, V. Y., Paschalis, A., Peleg, N., Molnar, P., Rimkus, S.,
Kim, J., Burlando, P., and Caporali, E.: Uncertainty partition challenges the
predictability of vital details of climate change, Earth's Future, 4,
240–251, https://doi.org/10.1002/2015EF000336, 2016.
Ghil, M.: Natural climate variability, Encyclopedia of Global Environmental
Change, 1, 544–549, 2002.
Griessinger, N., Schirmer, M., Helbig, N., Winstral, A., Michel, A., and
Jonas, T.: Implications of observation-enhanced energy-balance snowmelt
simulations for runoff modeling of Alpine catchments, Adv. Water
Resour., 133, 103410, https://doi.org/10.1016/j.advwatres.2019.103410,
2019.
Grünewald, T. and Lehning, M.: Are flat-field snow depth measurements
representative? A comparison of selected index sites with areal snow depth
measurements at the small catchment scale, Hydrol. Process., 29, 1717–1728,
https://doi.org/10.1002/hyp.10295, 2015.
Hawkins, E. and Sutton, R.: The potential to narrow uncertainty in regional
climate predictions, B. Am. Meteorol. Soc., 90,
1095–1108, https://doi.org/10.1007/s00382-010-0810-6, 2009.
Hawkins, E. and Sutton, R.: The potential to narrow uncertainty in
projections of regional precipitation change, Clim. Dynam., 37,
407–418, https://doi.org/10.1175/2009BAMS2607.1, 2011.
Helbig, N., van Herwijnen, A., Magnusson, J., and Jonas, T.: Fractional snow-covered area parameterization over complex topography, Hydrol. Earth Syst. Sci., 19, 1339–1351, https://doi.org/10.5194/hess-19-1339-2015, 2015.
Helbig, N., Schirmer, M., Magnusson, J., Mäder, F., van Herwijnen, A., Quéno, L., Bühler, Y., Deems, J. S., and Gascoin, S.: A seasonal algorithm of the snow-covered area fraction for mountainous terrain, The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, 2021.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution
climate change projections for European impact research, Reg. Environ. Change,
14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014.
Lafaysse, M., Hingray, B., Mezghani, A., Gailhard, J., and Terray, L.:
Internal variability and model uncertainty components in future
hydrometeorological projections: The Alpine Durance basin, Water Resour.
Res., 50, 3317–3341, https://doi.org/10.1002/2013WR014897, 2014.
Lehner, F., Deser, C., Maher, N., Marotzke, J., Fischer, E. M., Brunner, L., Knutti, R., and Hawkins, E.: Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6, Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, 2020.
Magnusson, J., Gustafsson, D., Hüsler, F., and Jonas, T.: Assimilation
of point SWE data into a distributed snow cover model comparing two
contrasting methods, Water Resour. Res., 50, 7816–7835,
https://doi.org/10.1002/2014WR015302, 2014.
Magnusson, J., Wever, N., Essery, R., Helbig, N., Winstral, A., and Jonas,
T.: Evaluating snow models with varying process representations for
hydrological applications, Water Resour. Res., 51, 2707–2723,
https://doi.org/10.1002/2014WR016498, 2015.
Maher, N., Milinski, S., and Ludwig, R.: Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble, Earth Syst. Dynam., 12, 401–418, https://doi.org/10.5194/esd-12-401-2021, 2021.
Marty, C., Schlögl, S., Bavay, M., and Lehning, M.: How much can we save? Impact of different emission scenarios on future snow cover in the Alps, The Cryosphere, 11, 517–529, https://doi.org/10.5194/tc-11-517-2017, 2017.
MeteoSwiss:
https://www.meteoswiss.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/produkt/raeumliche-daten-niederschlag/doc/ProdDoc_RhiresD.pdf (last access: 27 August 2022), 2019.
Moraga, J. S., Peleg, N., Fatichi, S., Molnar, P., and Burlando, P.:
Revealing the impacts of climate change on mountainous catchments through
high-resolution modelling, J. Hydrol., 603, 126806,
https://doi.org/10.1016/j.jhydrol.2021.126806, 2021.
Morán-Tejeda, E., López-Moreno, J. I., Stoffel, M., and Beniston,
M.: Rain-on-snow events in Switzerland: recent observations and projections
for the 21st century, Clim. Res., 71, 111–125,
https://doi.org/10.3354/cr01435, 2016.
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K., and Rasmussen, R.:
Slower snowmelt in a warmer world, Nat. Clim. Change, 7, 214–219,
https://doi.org/10.1038/nclimate3225, 2017.
Musselman, K. N., Lehner, F., Ikeda, K., Clark, M. P., Prein, A. F., Liu C.,
Barlage, M., and Rasmussen, R.: Projected increases and shifts in
rain-on-snow flood risk over western North America, Nat. Clim. Change,
8, 808–812, https://doi.org/10.1038/s41558-018-0236-4, 2018.
Ohba, M. and Kawase, H.: Rain-on-Snow events in Japan as projected by a
large ensemble of regional climate simulations, Clim. Dynam., 55, 2785–2800,
https://doi.org/10.1007/s00382-020-05419-8, 2020.
Peleg, N., Fatichi, S., Paschalis, A., Molnar, P., and Burlando, P.: An
advanced stochastic weather generator for simulating 2-D high-resolution
climate variables, J. Adv. Model. Earth Sy., 9,
1595–1627, https://doi.org/10.1002/2016MS000854, 2017.
Peleg, N., Molnar, P., Burlando, P., and Fatichi, S.: Exploring stochastic
climate uncertainty in space and time using a gridded hourly weather
generator, J. Hydrol., 571, 627–641,
https://doi.org/10.1016/j.jhydrol.2019.02.010, 2019.
Peleg, N., Sinclair, S., Fatichi, S., and Burlando, P.: Downscaling climate
projections over large and data sparse regions: Methodological application
in the Zambezi River Basin, Int. J. Climatol., 40, 6242–6264, https://doi.org/10.1002/joc.6578, 2020.
Schirmer, M., Winstral, A., Jonas, T., Burlando, P., and Peleg, N.: Multiple
realizations of daily snow water equivalent, surface water input and liquid
precipitation projections for mid- and late-century, EnviDat [data set],
https://doi.org/10.16904/envidat.339, 2021.
Schwarb, M.: The Alpine precipitation climate: evaluation of a
high-resolution analysis scheme using comprehensive rain-gauge data,
Doctoral dissertation, ETH Zurich,
https://doi.org/10.3929/ethz-a-004121274, 2000.
Sezen, C., Šraj, M., Medved, A., and Bezak, N.: Investigation of Rain-On-Snow
Floods under Climate Change, Appl. Sci., 10, 1242,
https://doi.org/10.3390/app10041242, 2020.
Sikorska-Senoner, A. E. and Seibert, J.: Flood-type trend analysis for
alpine catchments Hydrolog. Sci. J., 65, 1281–1299,
https://doi.org/10.1080/02626667.2020.1749761, 2020.
Surfleet, C. G. and Tullos, D.: Variability in effect of climate
change on rain-on-snow peak flow events in a temperate climate, J.
Hydrol., 479, 24–34, https://doi.org/10.1016/j.jhydrol.2012.11.021, 2013.
Verfaillie, D., Lafaysse, M., Déqué, M., Eckert, N., Lejeune, Y., and Morin, S.: Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps, The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, 2018.
Willibald, F., Kotlarski, S., Grêt-Regamey, A., and Ludwig, R.: Anthropogenic climate change versus internal climate variability: impacts on snow cover in the Swiss Alps, The Cryosphere, 14, 2909–2924, https://doi.org/10.5194/tc-14-2909-2020, 2020.
Winstral, A., Jonas, T., and Helbig, N.: Statistical downscaling of gridded
wind speed data using local topography, J. Hydrometeorol., 18,
335–348, https://doi.org/10.1175/JHM-D-16-0054.1, 2017.
Winstral, A., Magnusson, J., Schirmer, M., and Jonas, T.: The bias-detecting
ensemble: A new and efficient technique for dynamically incorporating
observations into physics-based, multilayer snow models, Water Resour.
Res., 55, 613–631, https://doi.org/10.1029/2018WR024521, 2019.
Würzer, S., Jonas, T., Wever, N., and Lehning, M.: Influence of initial
snowpack properties on runoff formation during rain-on-snow events, J.
Hydrometeorol., 17, 1801–1815,
https://doi.org/10.1175/JHM-D-15-0181.1, 2016.
Yip, S., Ferro, C. A., Stephenson, D. B., and Hawkins, E.: A simple,
coherent framework for partitioning uncertainty in climate predictions,
J. Climate, 24, 4634–4643, 2011.
Short summary
Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Rain is highly variable in time at a given location so that there can be both wet and dry...