Articles | Volume 11, issue 6
https://doi.org/10.5194/tc-11-2847-2017
© Author(s) 2017. 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-11-2847-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Snowmelt response to simulated warming across a large elevation gradient, southern Sierra Nevada, California
Keith N. Musselman
CORRESPONDING AUTHOR
National Center for Atmospheric Research, Boulder, CO, USA
now at: Institute of Arctic and Alpine Research, University of
Colorado, Boulder, CO, USA
Noah P. Molotch
Department of Geography, Institute of Arctic and Alpine Research,
University of Colorado, Boulder, CO, USA
Jet Propulsion Laboratory,
California Institute of Technology, Pasadena, CA, USA
Steven A. Margulis
Department of Civil and Environmental Engineering, University of
California, Los Angeles, CA, USA
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Manon von Kaenel and Steve Margulis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3389, https://doi.org/10.5194/egusphere-2024-3389, 2024
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Accurate snow water equivalent (SWE) estimates are crucial for water management in snowmelt-dependent regions, but bias and uncertainty in precipitation data make this challenging. Here, we leverage insights from a historical SWE data product to correct these biases and yield more accurate SWE estimates and streamflow predictions. Incorporating snow depth observations further boosts accuracy. This study demonstrates an effective method to downscale and bias-correct global mountain precipitation.
Haorui Sun, Yiwen Fang, Steven Margulis, Colleen Mortimer, Lawrence Mudryk, and Chris Derksen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3213, https://doi.org/10.5194/egusphere-2024-3213, 2024
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The European Space Agency's Snow Climate Change Initiative (Snow CCI) developed a high-quality snow cover extent and snow water equivalent (SWE) Climate Data Record. However, gaps exist in complex terrain due to challenges in using passive microwave sensing and in-situ measurements. This study presents a methodology to fill the mountain SWE gap using Snow CCI Snow Cover Fraction within a Bayesian SWE reanalysis framework, with potential applications in untested regions and with other sensors.
Yiwen Fang, Yufei Liu, Dongyue Li, Haorui Sun, and Steven A. Margulis
The Cryosphere, 17, 5175–5195, https://doi.org/10.5194/tc-17-5175-2023, https://doi.org/10.5194/tc-17-5175-2023, 2023
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Using newly developed snow reanalysis datasets as references, snow water storage is at high uncertainty among commonly used global products in the Andes and low-resolution products in the western United States, where snow is the key element of water resources. In addition to precipitation, elevation differences and model mechanism variances drive snow uncertainty. This work provides insights for research applying these products and generating future products in areas with limited in situ data.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Justin M. Pflug, Yiwen Fang, Steven A. Margulis, and Ben Livneh
Hydrol. Earth Syst. Sci., 27, 2747–2762, https://doi.org/10.5194/hess-27-2747-2023, https://doi.org/10.5194/hess-27-2747-2023, 2023
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Wolverine denning habitat inferred using a snow threshold differed for three different spatial representations of snow. These differences were based on the annual volume of snow and the elevation of the snow line. While denning habitat was most influenced by winter meteorological conditions, our results show that studies applying thresholds to environmental datasets should report uncertainties stemming from different spatial resolutions and uncertainties introduced by the thresholds themselves.
Oliver Wigmore and Noah P. Molotch
Earth Syst. Sci. Data, 15, 1733–1747, https://doi.org/10.5194/essd-15-1733-2023, https://doi.org/10.5194/essd-15-1733-2023, 2023
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We flew a custom-built drone fitted with visible, near-infrared and thermal cameras every week over a summer season at Niwot Ridge in Colorado's alpine tundra. We processed these images into seamless orthomosaics that record changes in snow cover, vegetation health and the movement of water over the land surface. These novel datasets provide a unique centimetre resolution snapshot of ecohydrologic processes, connectivity and spatial and temporal heterogeneity in the alpine zone.
Xiaoyu Ma, Dongyue Li, Yiwen Fang, Steven A. Margulis, and Dennis P. Lettenmaier
Hydrol. Earth Syst. Sci., 27, 21–38, https://doi.org/10.5194/hess-27-21-2023, https://doi.org/10.5194/hess-27-21-2023, 2023
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We explore satellite retrievals of snow water equivalent (SWE) along hypothetical ground tracks that would allow estimation of SWE over an entire watershed. The retrieval of SWE from satellites has proved elusive, but there are now technological options that do so along essentially one-dimensional tracks. We use machine learning (ML) algorithms as the basis for a track-to-area (TTA) transformation and show that at least one is robust enough to estimate domain-wide SWE with high accuracy.
Yufei Liu, Yiwen Fang, and Steven A. Margulis
The Cryosphere, 15, 5261–5280, https://doi.org/10.5194/tc-15-5261-2021, https://doi.org/10.5194/tc-15-5261-2021, 2021
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We examined the spatiotemporal distribution of stored water in the seasonal snowpack over High Mountain Asia, based on a new snow reanalysis dataset. The dataset was derived utilizing satellite-observed snow information, which spans across 18 water years, at a high spatial (~ 500 m) and temporal (daily) resolution. Snow mass and snow storage distribution over space and time are analyzed in this paper, which brings new insights into understanding the snowpack variability over this region.
Keith S. Jennings and Noah P. Molotch
Hydrol. Earth Syst. Sci., 23, 3765–3786, https://doi.org/10.5194/hess-23-3765-2019, https://doi.org/10.5194/hess-23-3765-2019, 2019
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There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix of the two. Here we show that method choice introduces marked uncertainty to simulated snowpack water storage (> 200 mm) and snow cover duration (> 1 month) in areas that receive significant winter and spring precipitation at air temperatures at and near freezing. This marked uncertainty has implications for water resources management as well as simulations of past and future hydroclimatic states.
Elisabeth Baldo and Steven A. Margulis
Hydrol. Earth Syst. Sci., 22, 3575–3587, https://doi.org/10.5194/hess-22-3575-2018, https://doi.org/10.5194/hess-22-3575-2018, 2018
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Montane snowpacks are extremely complex to represent and usually require assimilating remote sensing images at very fine spatial resolutions, which is computationally expensive. Adapting the grid size of the terrain to its complexity was shown to cut runtime and storage needs by half while preserving the accuracy of ~ 100 m snow estimates. This novel approach will facilitate the large-scale implementation of high-resolution remote sensing data assimilation over snow-dominated montane ranges.
Keith S. Jennings, Timothy G. F. Kittel, and Noah P. Molotch
The Cryosphere, 12, 1595–1614, https://doi.org/10.5194/tc-12-1595-2018, https://doi.org/10.5194/tc-12-1595-2018, 2018
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We show through observations and simulations that cold content, a key part of the snowpack energy budget, develops primarily through new snowfall. We also note that cold content damps snowmelt rate and timing at sub-seasonal timescales, while seasonal melt onset is controlled by the timing of peak cold content and total spring precipitation. This work has implications for how cold content is represented in snow models and improves our understanding of its effect on snowmelt processes.
Dominik Schneider, Noah P. Molotch, and Jeffrey S. Deems
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-167, https://doi.org/10.5194/tc-2017-167, 2017
Revised manuscript not accepted
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New data from the ongoing Airborne Snow Observatory (ASO) provides an unprecedented look at the spatial and temporal patterns of snow water content (SWE) over multiple years in California, USA. We found that relationships between SWE, snow covered area, and topography transfer between years at accuracy levels equivalent to those from models generated from ASO data collected on the day of interest. This research provides a first attempt at extending the value of ASO beyond the observations.
Felix C. Seidel, Karl Rittger, S. McKenzie Skiles, Noah P. Molotch, and Thomas H. Painter
The Cryosphere, 10, 1229–1244, https://doi.org/10.5194/tc-10-1229-2016, https://doi.org/10.5194/tc-10-1229-2016, 2016
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Quantifying the snow albedo effect is an important step to predict water availability as well as changes in climate and sea level. We use imaging spectroscopy to determine optical properties of mountain snow. We find an inverse relationship between snow albedo and grain size as well as between elevation and grain size. Under strong melt conditions, however, we show that the optical-equivalent snow grain size increases slower than expected at lower elevations and we explain possible reasons.
M. Navari, S. A. Margulis, S. M. Bateni, M. Tedesco, P. Alexander, and X. Fettweis
The Cryosphere, 10, 103–120, https://doi.org/10.5194/tc-10-103-2016, https://doi.org/10.5194/tc-10-103-2016, 2016
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An ensemble batch smoother was used to assess the feasibility of generating a reanalysis estimate of the Greenland ice sheet (GrIS) surface mass fluxes (SMF) via integrating measured ice surface temperatures with a regional climate model estimate. The results showed that assimilation of IST were able to overcome uncertainties in meteorological forcings that drive the GrIS surface processes. We showed that the proposed methodology is able to generate posterior reanalysis estimates of the SMF.
A. A. Harpold, J. A. Marshall, S. W. Lyon, T. B. Barnhart, B. A. Fisher, M. Donovan, K. M. Brubaker, C. J. Crosby, N. F. Glenn, C. L. Glennie, P. B. Kirchner, N. Lam, K. D. Mankoff, J. L. McCreight, N. P. Molotch, K. N. Musselman, J. Pelletier, T. Russo, H. Sangireddy, Y. Sjöberg, T. Swetnam, and N. West
Hydrol. Earth Syst. Sci., 19, 2881–2897, https://doi.org/10.5194/hess-19-2881-2015, https://doi.org/10.5194/hess-19-2881-2015, 2015
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This review's objective is to demonstrate the transformative potential of lidar by critically assessing both challenges and opportunities for transdisciplinary lidar applications in geomorphology, hydrology, and ecology. We find that using lidar to its full potential will require numerous advances, including more powerful open-source processing tools, new lidar acquisition technologies, and improved integration with physically based models and complementary observations.
Related subject area
Snow Hydrology
Exploring how Sentinel-1 wet-snow maps can inform fully distributed physically based snowpack models
Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy
Towards large-scale daily snow density mapping with spatiotemporally aware model and multi-source data
Drone-based ground-penetrating radar (GPR) application to snow hydrology
Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events
Two-dimensional liquid water flow through snow at the plot scale in continental snowpacks: simulations and field data comparisons
Fractional snow-covered area: scale-independent peak of winter parameterization
Seasonal components of freshwater runoff in Glacier Bay, Alaska: diverse spatial patterns and temporal change
Hydrologic flow path development varies by aspect during spring snowmelt in complex subalpine terrain
A continuum model for meltwater flow through compacting snow
Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment
Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada
Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments
A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation
Multilevel spatiotemporal validation of snow/ice mass balance and runoff modeling in glacierized catchments
Bulk meltwater flow and liquid water content of snowpacks mapped using the electrical self-potential (SP) method
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data
Inconsistency in precipitation measurements across the Alaska–Yukon border
Precipitation measurement intercomparison in the Qilian Mountains, north-eastern Tibetan Plateau
Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements
Topographic control of snowpack distribution in a small catchment in the central Spanish Pyrenees: intra- and inter-annual persistence
Modeling bulk density and snow water equivalent using daily snow depth observations
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements
Homogenisation of a gridded snow water equivalent climatology for Alpine terrain: methodology and applications
What drives basin scale spatial variability of snowpack properties in northern Colorado?
Micrometeorological processes driving snow ablation in an Alpine catchment
Understanding snow-transport processes shaping the mountain snow-cover
Freshwater flux to Sermilik Fjord, SE Greenland
Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas
The Cryosphere, 18, 5753–5767, https://doi.org/10.5194/tc-18-5753-2024, https://doi.org/10.5194/tc-18-5753-2024, 2024
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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 paves the way to further evaluation, calibration, and data assimilation using wet-snow maps.
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.
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.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
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Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Ryan W. Webb, Keith Jennings, Stefan Finsterle, and Steven R. Fassnacht
The Cryosphere, 15, 1423–1434, https://doi.org/10.5194/tc-15-1423-2021, https://doi.org/10.5194/tc-15-1423-2021, 2021
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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.
Ryan W. Webb, Steven R. Fassnacht, and Michael N. Gooseff
The Cryosphere, 12, 287–300, https://doi.org/10.5194/tc-12-287-2018, https://doi.org/10.5194/tc-12-287-2018, 2018
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We observed how snowmelt is transported on a hillslope through multiple measurements of snow and soil moisture across a small headwater catchment. We found that snowmelt flows through the snow with less infiltration on north-facing slopes and infiltrates the ground on south-facing slopes. This causes an increase in snow water equivalent at the base of the north-facing slope by as much as 170 %. We present a conceptualization of flow path development to improve future investigations.
Colin R. Meyer and Ian J. Hewitt
The Cryosphere, 11, 2799–2813, https://doi.org/10.5194/tc-11-2799-2017, https://doi.org/10.5194/tc-11-2799-2017, 2017
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We describe a new model for the evolution of snow temperature, density, and water content on the surface of glaciers and ice sheets. The model encompasses the surface hydrology of accumulation and ablation areas, allowing us to explore the transition from one to the other as thermal forcing varies. We predict year-round liquid water storage for intermediate values of the surface forcing. We also compare our model to data for the vertical percolation of meltwater in Greenland.
Emmy E. Stigter, Niko Wanders, Tuomo M. Saloranta, Joseph M. Shea, Marc F. P. Bierkens, and Walter W. Immerzeel
The Cryosphere, 11, 1647–1664, https://doi.org/10.5194/tc-11-1647-2017, https://doi.org/10.5194/tc-11-1647-2017, 2017
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
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This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Francesco Avanzi, Hiroyuki Hirashima, Satoru Yamaguchi, Takafumi Katsushima, and Carlo De Michele
The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, https://doi.org/10.5194/tc-10-2013-2016, 2016
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We investigate capillary barriers and preferential flow in layered snow during nine cold laboratory experiments. The dynamics of each sample were replicated solving Richards equation within the 1-D multi-layer physically based SNOWPACK model. Results show that both processes affect the speed of water infiltration in stratified snow and are marked by a high degree of spatial variability at cm scale and complex 3-D patterns.
Thomas Skaugen and Ingunn H. Weltzien
The Cryosphere, 10, 1947–1963, https://doi.org/10.5194/tc-10-1947-2016, https://doi.org/10.5194/tc-10-1947-2016, 2016
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In hydrological models it is important to properly simulate the spatial distribution of snow water equivalent (SWE) for the timing of spring melt floods and the accounting of energy fluxes. This paper describes a method for the spatial distribution of SWE which is parameterised from observed spatial variability of precipitation and has hence no calibration parameters. Results show improved simulation of SWE and the evolution of snow-free areas when compared with the standard method.
Florian Hanzer, Kay Helfricht, Thomas Marke, and Ulrich Strasser
The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, https://doi.org/10.5194/tc-10-1859-2016, 2016
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The hydroclimatological model AMUNDSEN is set up to simulate snow and ice accumulation, ablation, and runoff for a study region in the Ötztal Alps (Austria) in the period 1997–2013. A new validation concept is introduced and demonstrated by evaluating the model performance using several independent data sets, e.g. snow depth measurements, satellite-derived snow maps, lidar data, glacier mass balances, and runoff measurements.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
Z. Zheng, P. B. Kirchner, and R. C. Bales
The Cryosphere, 10, 257–269, https://doi.org/10.5194/tc-10-257-2016, https://doi.org/10.5194/tc-10-257-2016, 2016
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By analyzing high-resolution lidar products and using statistical methods, we quantified the snow depth dependency on elevation, slope and aspect of the terrain and also the surrounding vegetation in four catchment size sites in the southern Sierra Nevada during snow peak season. The relative importance of topographic and vegetation attributes varies with elevation and canopy, but all these attributes were found significant in affecting snow distribution in mountain basins.
L. Scaff, D. Yang, Y. Li, and E. Mekis
The Cryosphere, 9, 2417–2428, https://doi.org/10.5194/tc-9-2417-2015, https://doi.org/10.5194/tc-9-2417-2015, 2015
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The bias corrections show significant errors in the gauge precipitation measurements over the northern regions. Monthly precipitation is closely correlated between the stations across the Alaska--Yukon border, particularly for the warm months. Double mass curves indicate changes in the cumulative precipitation due to bias corrections over the study period. Overall the bias corrections lead to a smaller and inverted precipitation gradient across the border, especially for snowfall.
R. Chen, J. Liu, E. Kang, Y. Yang, C. Han, Z. Liu, Y. Song, W. Qing, and P. Zhu
The Cryosphere, 9, 1995–2008, https://doi.org/10.5194/tc-9-1995-2015, https://doi.org/10.5194/tc-9-1995-2015, 2015
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The catch ratio of Chinese standard precipitation gauge vs. wind speed relationship for different precipitation types was well quantified by cubic polynomials and exponential functions using 5-year field data in the high-mountain environment of the Tibetan Plateau. The daily precipitation measured by shielded gauges increases linearly with that of unshielded gauges. The pit gauge catches the most local precipitation in rainy season and could be used as a reference in most regions of China.
A. Hedrick, H.-P. Marshall, A. Winstral, K. Elder, S. Yueh, and D. Cline
The Cryosphere, 9, 13–23, https://doi.org/10.5194/tc-9-13-2015, https://doi.org/10.5194/tc-9-13-2015, 2015
J. Revuelto, J. I. López-Moreno, C. Azorin-Molina, and S. M. Vicente-Serrano
The Cryosphere, 8, 1989–2006, https://doi.org/10.5194/tc-8-1989-2014, https://doi.org/10.5194/tc-8-1989-2014, 2014
J. L. McCreight and E. E. Small
The Cryosphere, 8, 521–536, https://doi.org/10.5194/tc-8-521-2014, https://doi.org/10.5194/tc-8-521-2014, 2014
E. Kantzas, S. Quegan, M. Lomas, and E. Zakharova
The Cryosphere, 8, 487–502, https://doi.org/10.5194/tc-8-487-2014, https://doi.org/10.5194/tc-8-487-2014, 2014
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
G. A. Sexstone and S. R. Fassnacht
The Cryosphere, 8, 329–344, https://doi.org/10.5194/tc-8-329-2014, https://doi.org/10.5194/tc-8-329-2014, 2014
R. Mott, L. Egli, T. Grünewald, N. Dawes, C. Manes, M. Bavay, and M. Lehning
The Cryosphere, 5, 1083–1098, https://doi.org/10.5194/tc-5-1083-2011, https://doi.org/10.5194/tc-5-1083-2011, 2011
R. Mott, M. Schirmer, M. Bavay, T. Grünewald, and M. Lehning
The Cryosphere, 4, 545–559, https://doi.org/10.5194/tc-4-545-2010, https://doi.org/10.5194/tc-4-545-2010, 2010
S. H. Mernild, I. M. Howat, Y. Ahn, G. E. Liston, K. Steffen, B. H. Jakobsen, B. Hasholt, B. Fog, and D. van As
The Cryosphere, 4, 453–465, https://doi.org/10.5194/tc-4-453-2010, https://doi.org/10.5194/tc-4-453-2010, 2010
Cited articles
Bales, R. C., Molotch, N. P., Painter, T. H., Dettinger, M. D., Rice, R., and Dozier, J.: Mountain hydrology of the western United States, Water Resour. Res., 42, W08432, https://doi.org/10.1029/2005WR004387, 2006.
Barnett, T. P. and Pierce, D. W.: Sustainable water deliveries from the Colorado River in a changing climate, P. Natl. Acad. Sci., 106, 7334–7338, 2009.
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, 2005.
Barnhart, T. B., Molotch, N. P., Livneh, B., Harpold, A. A., Knowles, J. F., and Schneider, D.: Snowmelt rate dictates streamflow, Geophys. Res. Lett., 43, 8006–8016, 2016.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: numerical model, Cold Reg. Sci. Technol., 35, 123–145, 2002.
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, 2014.
Bavay, M., Lehning, M., Jonas, T., and Löwe, H.: Simulations of future snow cover and discharge in Alpine headwater catchments, Hydrol. Process., 23, 95–108, 2009.
Bavay, M., Grünewald, T., and Lehning, M.: Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland, Adv. Water Res., 55, 4–16, 2013.
Berghuijs, W., Woods, R., and Hrachowitz, M.: A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4, 583–586, 2014.
Brown, R. D. and Mote, P. W.: The response of northern hemisphere snow cover to a changing climate*, J. Climate, 22, 2124–2145, 2009.
Cayan, D. R., Maurer, E. P., Dettinger, M. D., Tyree, M., and Hayhoe, K.: Climate change scenarios for the California region, Climatic change, 87, 21–42, 2008.
Christensen, L., Tague, C. L., and Baron, J. S.:, Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem, Hydrol. Process., 22, 3576–3588, 2008.
Cooper, M. G., Nolin, A. W., and Safeeq, M.:Testing the recent snow drought as an analog for climate warming sensitivity of Cascades snowpacks, Environ. Res. Lett., 11, 084009, https://doi.org/10.1088/1748-9326/11/8/084009, 2016.
Dettinger, M.: Climate Change, Atmospheric Rivers, and Floods in California – A Multimodel Analysis of Storm Frequency and Magnitude Changes, J. Am. Water Resour. As., 47, 514–523, 2011.
Dettinger, M. D. and Cayan, D. R.: Large-scale atmospheric forcing of recent trends toward early snowmelt runoff in California, J. Climate, 8, 606–623, 1995.
Dettinger, M. D., Cayan, D. R., Meyer, M. K., and Jeton, A. E.: Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900–2099, Clim. Change, 62, 283–317, 2004.
Eiriksson, D., Whitson, M., Luce, C. H., Marshall, H. P., Bradford, J., Benner, S. G., Black, T., Hetrick, H., and McNamara, J. P.:An evaluation of the hydrologic relevance of lateral flow in snow at hillslope and catchment scales, Hydrol. Process., 27, 640–654, 2013.
Elder, K., Dozier, J., and Michaelsen, J.: Spatial and temporal variation of net snow accumulation in a small alpine watershed, Emerald Lake basin, Sierra Nevada, California, USA, Ann. Glaciol., 13, 56–63, 1988.
Etchevers, P., Martin, E., Brown, R., Fierz, C., Lejeune, Y., Bazile, E., Boone, A., Dai, Y.-J., Essery, R., and Fernandez, A.: Validation of the energy budget of an alpine snowpack simulated by several snow models (SnowMIP project), Ann. Glaciol., 38, 150–158, 2004.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Flerchinger, G., Xaio, W., Marks, D., Sauer, T., and Yu, Q.: Comparison of algorithms for incoming atmospheric long wave radiation, Water Resour. Res., 45, W03423, https://doi.org/10.1029/2008WR007394, 2009.
Fry, J. A., Xian, G., Jin, S., Dewitz, J. A., Homer, C. G., Limin, Y., Barnes, C. A., Herold, N. D., and Wickham, J. D.: Completion of the 2006 national land cover database for the conterminous United States, Photogr. Eng. Remote Sens., 77, 858–864, 2011.
Fyfe, J. C., Derksen, C., Mudryk, L., Flato, G. M., Santer, B. D., Swart, N. C., Molotch, N. P., Zhang, X., Wan, H., and Arora, V. K.: Large near-term projected snowpack loss over the western United States, Nature Commun., 8, 14996, https://doi.org/10.1038/ncomms14996, 2017.
Girotto, M., Margulis, S. A., and Durand, M.: Probabilistic SWE reanalysis as a generalization of deterministic SWE reconstruction techniques, Hydrol. Process., 28, 3875–3895, 2014a.
Girotto, M., Cortés, G., Margulis, S. A., and Durand, M.: Examining spatial and temporal variability in snow water equivalent using a 27 year reanalysis: Kern River watershed, Sierra Nevada, Water Resour. Res., 50, 6713–6734, 2014b.
Gleason, K. E., Nolin, A. W., and Roth, T. R.: Developing a representative snow-monitoring network in a forested mountain watershed, Hydrol. Earth Syst. Sci., 21, 1137–1147, https://doi.org/10.5194/hess-21-1137-2017, 2017.
Gleick, P. H.: The development and testing of a water balance model for climate impact assessment: modeling the Sacramento basin, Water Resour. Res., 23, 1049–1061, 1987.
Gleick, P. H. and Chalecki, E. L.: The impacts of climate changes for water resources of the Colorado and Sacramento-San Joaquin River basins, J. Am. Water Resour. As., 35, 1429–1441, 1999.
Godsey, S., Kirchner, J., and Tague, C.: Effects of changes in winter snowpacks on summer low flows: case studies in the Sierra Nevada, California, USA, Hydrol. Process., 28, 5048–5064, 2013.
Hamlet, A. F. and Lettenmaier, D. P.: Effects of 20th century warming and climate variability on flood risk in the western US, Water Resour. Res., 43, https://doi.org/10.1029/2006WR005099, 2007.
Howat, I. M. and Tulaczyk, S.: Climate sensitivity of spring snowpack in the Sierra Nevada, J. Geophys. Res.-Earth Surface, 110, https://doi.org/10.1029/2005JF000356, 2005.
Hunsaker, C. T., Whitaker, T. W., and Bales, R. C.: Snowmelt runoff and water yield along elevation and temperature gradients in California's Southern Sierra Nevada1, edited, Wiley Online Library, 2012.
Huntington, J. L. and Niswonger, R. G.: Role of surface water and groundwater interactions on projected summertime streamflow in snow dominated regions: An integrated modeling approach, Water Resour. Res., 48, https://doi.org/10.1029/2012WR012319, 2012.
Jepsen, S. M., Molotch, N. P., Williams, M. W., Rittger, K. E., and Sickman, J. O.: Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: Examples from two alpine watersheds, Water Resour. Res., 48, https://doi.org/10.1029/2011WR011006, 2012.
Klein Tank, A., Zwiers, F. W., and Zhang, X.: Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation, C. D. a. Monitoring, p. 56, World Meteorological Organization, 2009.
Knowles, N. and Cayan, D. R.: Potential effects of global warming on the Sacramento/San Joaquin watershed and the San Francisco estuary, Geophys. Res. Lett., 29, 38-31–38-34, 2002.
Knowles, N. and Cayan, D. R.: Elevational dependence of projected hydrologic changes in the San Francisco estuary and watershed, Clim. Change, 62, 319–336, 2004.
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.
Kobierska, F., Jonas, T., Magnusson, J., Zappa, M., Bavay, M., Bosshard,, T., Paul, F., and Bernasconi, S. M.: Climate change effects on snow melt and discharge of a partly glacierized watershed in Central Switzerland (SoilTrec Critical Zone Observatory), Appl. Geochem., 26, Supplement, S60–S62, 2011.
Kobierska, F., Jonas, T., Zappa, M., Bavay, M., Magnusson, J., and Bernasconi, S. M.: Future runoff from a partly glacierized watershed in Central Switzerland: a two-model approach, Adv. Water Res., 55, 204–214, 2013.
Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T. A., Stähli, M., and Zappa, M.: ALPINE3D: a detailed model of mountain surface processes and its application to snow hydrology, Hydrol. Process., 20, 2111–2128, 2006.
Letcher, T. W. and Minder, J. R.: Characterization of the Simulated Regional Snow Albedo Feedback Using a Regional Climate Model over Complex Terrain, J. Climate, 28, 7576–7595, 2015.
Lettenmaier, D. P. and Gan, T. Y.: Hydrologic sensitivities of the Sacramento San Joaquin River Basin, California, to global warming, Water Resour. Res., 26, 69–86, 1990.
Lettenmaier, D. P., Wood, A. W., Palmer, R. N., Wood, E. F., and Stakhiv, E. Z.: Water resources implications of global warming: A US regional perspective, Climatic Change, 43, 537–579, 1999.
Liston, G. E. and Elder, K.: A Meteorological Distribution System for High-Resolution Terrestrial Modeling (MicroMet), J. Hydrometeorol., 7, 217–234, 2006.
Liu, C., Ikeda, K., Rasmussen, R., Barlage, M., Newman, A. J., Prein, A. F., Chen, F., Chen, L., Clark, M., and Dai, A.: Continental-scale convection-permitting modeling of the current and future climate of North America, Clim. Dynam., 49, 71–95, https://doi.org/10.1007/s00382-016-3327-9, 2017.
López-Moreno, J. I., Fassnacht, S., Heath, J., Musselman, K., Revuelto, J., Latron, J., Morán-Tejeda, E., and Jonas, T.: Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent, Adv. Water Res., 55, 40–52, 2013.
López-Moreno, J. I., Mott, R., Faure, F., Lehning, M., Löwe, H., Hynek, B., Michlmayer, G., Prokop, A., and Schöner, W.: Different sensitivities of snowpacks to warming in Mediterranean climate mountain areas, Environ. Res. Lett., 49, 155–160, 2017.
Luce, C. H. and Holden, Z. A.: Declining annual streamflow distributions in the Pacific Northwest United States, 1948–2006, Geophys. Res. Lett., 36, https://doi.org/10.1029/2009GL039407, 2009.
Lundquist, J. D. and Loheide, S. P.: How evaporative water losses vary between wet and dry water years as a function of elevation in the Sierra Nevada, California, and critical factors for modeling, Water Resour. Res., 47, https://doi.org/10.1029/2010WR010050, 2011.
Magnusson, J., Farinotti, D., Jonas, T., and Bavay, M.: Quantitative evaluation of different hydrological modelling approaches in a partly glacierized Swiss watershed, Hydrol. Process., 25, 2071–2084, 2011.
Margulis, S. A., Cortés, G., Girotto, M., and Durand, M.: A Landsat-Era Sierra Nevada Snow Reanalysis (1985–2015), J. Hydrometeorol., 17, 1203–1221, 2016.
Marks, D. and Dozier, J.: Climate and energy exchange at the snow surface in the alpine region of the Sierra Nevada: 2. Snow cover energy balance, Water Resour. Res., 28, 3043–3054, 1992.
Marks, D., Dozier, J., and Davis, R. E.: Climate and energy exchange at the snow surface in the Alpine Region of the Sierra Nevada: 1. Meteorological measurements and monitoring, Water Resour. Res., 28, 3029–3042, 1992.
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.
McCabe, G. J. and Clark, M. P.: Trends and variability in snowmelt runoff in the western United States, J. Hydrometeorol., 6, 476–482, 2005.
Michlmayr, G., Lehning, M., Koboltschnig, G., Holzmann, H., Zappa, M., Mott, R., and Schöner, W.: Application of the Alpine 3D model for glacier mass balance and glacier runoff studies at Goldbergkees, Austria, Hydrol. Process., 22, 3941–3949, 2008.
Minder, J. R.: The Sensitivity of Mountain Snowpack Accumulation to Climate Warming, J. Climate, 23, 2634–2650, 2010.
Molotch, N., Colee, M., Bales, R., and Dozier, J.: Estimating the spatial distribution of snow water equivalent in an alpine basin using binary regression tree models: the impact of digital elevation data and independent variable selection, Hydrol. Process., 19, 1459–1479, 2005.
Molotch, N. P. and Meromy, L.: Physiographic and climatic controls on snow cover persistence in the Sierra Nevada Mountains, Hydrol. Process., 28, 4573–4586, 2014.
Molotch, N. P., Blanken, P. D., Williams, M. W., Turnipseed, A. A., Monson, R. K., and Margulis, S. A.: Estimating sublimation of intercepted and sub-canopy snow using eddy covariance systems, Hydrol. Process., 21, 1567–1575, 2007.
Mote, P. W., Hamlet, A. F., Clark, M. P., and Lettenmaier, D.: Declining mountain snowpack in western North America, B. Am. Meteorol. Soc., 86, 39–49, 2005.
Mott, R., Faure, F., Lehning, M., Löwe, H., Hynek, B., Michlmayer, G., Prokop, A., and Schöner, W.: Simulation of seasonal snow-cover distribution for glacierized sites on Sonnblick, Austria, with the Alpine3D model, Ann. Glaciol., 49, 155–160, 2008.
Musselman, K. N., Molotch, N. P., Margulis, S. A., Lehning, M., and Gustafsson, D.: Improved snowmelt simulations with a canopy model forced with photo-derived direct beam canopy transmissivity, Water Resour. Res., 48, https://doi.org/10.1029/2012WR012285, 2012a.
Musselman, K. N., Molotch, N. P., Margulis, S. A., Kirchner, P., and Bales, R. C.: Influence of canopy structure and direct beam solar irradiance on snowmelt rates in a mixed conifer forest, Agr. Forest Meteorol., 161C, 46–56, 2012b.
Musselman, K. N., Pomeroy, J. W., Essery, R. L., and Leroux, N.: Impact of windflow calculations on simulations of alpine snow accumulation, redistribution and ablation, Hydrol. Process., 29, 3983–3999, 2015.
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K., and Rasmussen, R.: Slower snowmelt in a warmer world, Nature Clim. Change, 7, 214–219, 2017.
Nolin, A. W. and Daly, C.: Mapping “at risk” snow in the Pacific Northwest, J. Hydrometeorol., 7, 1164–1171, 2006.
National Park Service: Sequoia and Kings Canyon Weather. National Park Service, U.S. Department of the Interior, 5 January 2017, available at: https://www.nps.gov/seki/planyourvisit/weather.htm, last access: 7 July 2017.
Penna, D., Tromp-van Meerveld, H. J., Gobbi, A., Borga, M., and Dalla Fontana, G.: The influence of soil moisture on threshold runoff generation processes in an alpine headwater catchment, Hydrol. Earth Syst. Sci., 15, 689–702, https://doi.org/10.5194/hess-15-689-2011, 2011.
Pepin, N. and Lundquist, J.: Temperature trends at high elevations: patterns across the globe, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL034026, 2008.
Perrot, D., Molotch, N. P., Williams, M. W., Jepsen, S. M., and Sickman, J. O.: Relationships between stream nitrate concentration and spatially distributed snowmelt in high elevation catchments of the western US, Water Resour. Res., 50, 8694–8713, 2014.
Prein, A. F., Rasmussen, R. M., Ikeda, K., Liu, C., Clark, M. P., and Holland, G. J.: The future intensification of hourly precipitation extremes, Nature Clim. Change, 7, 48–52, https://doi.org/10.1038/nclimate3168, 2016.
Rasouli, K., Pomeroy, J. W., and Marks, D. G.: Snowpack sensitivity to perturbed climate in a cool mid latitude mountain catchment, Hydrol. Process., 29, 3925–3940, 2015.
Rice, R., Bales, R. C., Painter, T. H., and Dozier, J.: Snow water equivalent along elevation gradients in the Merced and Tuolumne River basins of the Sierra Nevada, Water Resour. Res., 47, https://doi.org/10.1029/2010WR009278, 2011.
Rutter, N., Essery, R., Pomeroy, J., et al.: Evaluation of forest snow processes models (SnowMIP2), J. Geophys. Res.-Atmos., 114, https://doi.org/10.1029/2008JD011063, 2009.
Schlögl, S., Marty, C., Bavay, M., and Lehning, M.: Sensitivity of Alpine3D modeled snow cover to modifications in DEM resolution, station coverage and meteorological input quantities, Environ. Model. Softw., 83, 387–396, 2016.
Seager, R., Ting, M., Li, C., Naik, N., Cook, B., Nakamura, J., and Liu, H.: Projections of declining surface-water availability for the southwestern United States, Nature Clim. Change, 3, 482–486, 2013.
Sexstone, G. A., Clow, D. W., Stannard, D. I., and Fassnacht, S. R.: Comparison of methods for quantifying surface sublimation over seasonally snow covered terrain, Hydrol. Process., 30, 3373–3389, 2016.
Sickman, J. O., Leydecker, A., Chang, C. C., Kendall, C., Melack, J. M., Lucero, D. M., and Schimel, J.: Mechanisms underlying export of N from high-elevation catchments during seasonal transitions, Biogeochemistry, 64, 1–24, 2003.
Sproles, E. A., Roth, T. R., and Nolin, A. W.: Future snow? A spatial-probabilistic assessment of the extraordinarily low snowpacks of 2014 and 2015 in the Oregon Cascades, The Cryosphere, 11, 331–341, https://doi.org/10.5194/tc-11-331-2017, 2017.
Stewart, I. T., Cayan, D. R., and Dettinger, M. D.: Changes in snowmelt runoff timing in western North America under abusiness as usual climate change scenario, Climatic Change, 62, 217–232, 2004.
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.: Climate Change 2013. The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change-Abstract for decision-makers, Groupe d'experts intergouvernemental sur l'evolution du climat/Intergovernmental Panel on Climate Change-IPCC, C/O World Meteorological Organization, 7bis Avenue de la Paix, CP 2300 CH-1211 Geneva 2 (Switzerland), 2013.
Sturm, M., Goldstein, M. A., and Parr, C.: Water and life from snow: A trillion dollar science question, Water Resour. Res., 53, 3534–3544, https://doi.org/10.1002/2017WR020840, 2017.
Sun, F., Hall, A., Schwartz, M., Walton, D. B., and Berg, N.: Twenty-First-Century Snowfall and Snowpack Changes over the Southern California Mountains, J. Climate, 29, 91–110, 2016.
Tague, C. and Peng, H.: The sensitivity of forest water use to the timing of precipitation and snowmelt recharge in the California Sierra: Implications for a warming climate, J. Geophys. Res.-Biogeosc., 118, 875–887, 2013.
Tague, C., Grant, G., Farrell, M., Choate, J., and Jefferson, A.: Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades, Climatic Change, 86, 189–210, 2008.
Tonnessen, K. A.: The Emerald Lake watershed study: introduction and site description, Water Resour. Res., 27, 1537–1539, 1991.
Trenberth, K. E.: Changes in precipitation with climate change, Clim. Res., 47, 123–138, 2011.
Trujillo, E. and Molotch, N. P.: Snowpack regimes of the Western United States, Water Resour. Res., 50, 5611–5623, 2014.
Trujillo, E. and Lehning, M.: Theoretical analysis of errors when estimating snow distribution through point measurements, The Cryosphere, 9, 1249–1264, https://doi.org/10.5194/tc-9-1249-2015, 2015.
Trujillo, E., Molotch, N. P., Goulden, M. L., Kelly, A. E., and Bales, R. C.: Elevation-dependent influence of snow accumulation on forest greening, Nature Geosci., 5, 705–709, 2012.
Vano, J. A., Udall, B., Cayan, D. R., Overpeck, J. T., Brekke, L. D., Das, T., Hartmann, H. C., Hidalgo, H. G., Hoerling, M., and McCabe, G. J.: Understanding uncertainties in future Colorado River streamflow, B. Am. Meteorol. Soc., 95, 59–78, 2014.
van Oldenborgh, G. J., Collins, M., Arblaster, J., Christensen, J. H., Marotzke, J., Power, S. B., Rummukainen, M., and Zhou, T. (Eds.): Annex I: Atlas of global and regional climate projections supplementary material RCP8.5. Climate Change 2013: The Physical Science Basis, edited by: Stocker, T. F. et al., Cambridge University Press, AISM-1-AISM-159, available at: www.climatechange2013.org/images/report/WG1AR5_AISM8.5_FINAL.pdf, 2013.
West, A. J. and Knoerr, K. R.: Water losses in the Sierra Nevada, J. Am. Water Works Assoc., 51, 481–488, 1959.
Williams, M. W. and Melack, J. M.: Solute chemistry of snowmelt and runoff in an alpine basin, Sierra Nevada, Water Resour. Res., 27, 1575–1588, 1991.
Winchell, T. S., Barnard, D. M., Monson, R. K., Burns, S. P., and Molotch, N. P.: Earlier snowmelt reduces atmospheric carbon uptake in midlatitude subalpine forests, Geophys. Res. Lett., 43, 8160–8168, 2016.
Short summary
We present a study of how melt rates in the California Sierra Nevada respond to a range of warming projected for this century. Snowfall and melt were simulated for historical and modified (warmer) snow seasons. Winter melt occurs more frequently and more intensely, causing an increase in extreme winter melt. In a warmer climate, less snow persists into the spring, causing spring melt to be substantially lower. The results offer insight into how snow water resources may respond to climate change.
We present a study of how melt rates in the California Sierra Nevada respond to a range of...