Articles | Volume 7, issue 3
https://doi.org/10.5194/tc-7-961-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-7-961-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Jun 2013
Research article |
| 20 Jun 2013
Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)
Centre d'Applications et de Recherches en Télédétection (CARTEL), Université de Sherbrooke, 2500 Boulder Université, J1K2R1 Sherbrooke, QC, Canada
A. Royer
Centre d'Applications et de Recherches en Télédétection (CARTEL), Université de Sherbrooke, 2500 Boulder Université, J1K2R1 Sherbrooke, QC, Canada
B. Montpetit
Centre d'Applications et de Recherches en Télédétection (CARTEL), Université de Sherbrooke, 2500 Boulder Université, J1K2R1 Sherbrooke, QC, Canada
P. A. Bartlett
Climate Processes Section, Environment Canada, 4905 Dufferin street, M3H 5T4 Toronto, ON, Canada
A. Langlois
Centre d'Applications et de Recherches en Télédétection (CARTEL), Université de Sherbrooke, 2500 Boulder Université, J1K2R1 Sherbrooke, QC, Canada
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Short summary
Short summary
A multisensor C-Band SAR near-daily time series in an Arctic environment was developed to create a high-resolution freeze/thaw algorithm with an accuracy of 96 %. The FT detection was highly correlated to near-surface state as measured by soil temperature. Small but significant FT date differences were identified for different Arctic ecotypes, showing the spatial variability of freeze/thaw process in Arctic environment.
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This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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We propose a new method to determine the ground surface temperature under the snowpack in the Arctic area from satellite observations. The obtained ground temperatures time series were evaluated over 21 reference sites in Northern Alaska and compared with ground temperatures obtained with global models. The method is excessively promising for monitoring ground temperature below the snowpack and studying the spatiotemporal variability thanks to 15 years of observations over the whole Arctic area.
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We present an analysis of soil CO2 emissions in boreal and tundra regions during the non-growing season. We show that when the soil is completely frozen, soil temperature is the main control on CO2 emissions. When the soil is around the freezing point, with a mix of liquid water and ice, the liquid water content is the main control on CO2 emissions. This study highlights that the vegetation–snow–soil interactions must be considered to understand soil CO2 emissions during the non-growing season.
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
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A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
Short summary
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This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
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Preprint archived
Short summary
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
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Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
Short summary
Short summary
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The Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, https://doi.org/10.5194/tc-15-5079-2021, 2021
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Short summary
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Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
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Short summary
Short summary
Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, https://doi.org/10.5194/essd-10-2055-2018, 2018
Short summary
Short summary
This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
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.
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
Short summary
Short summary
To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
Short summary
Short summary
Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Peter Toose, Alexandre Roy, Frederick Solheim, Chris Derksen, Tom Watts, Alain Royer, and Anne Walker
Geosci. Instrum. Method. Data Syst., 6, 39–51, https://doi.org/10.5194/gi-6-39-2017, https://doi.org/10.5194/gi-6-39-2017, 2017
Short summary
Short summary
Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers used for monitoring essential climate variables. A 385-channel hyperspectral L-band radiometer system was designed with the means to quantify the strength and type of RFI. The compact design makes it ideal for mounting on both surface and airborne platforms to be used for calibrating and validating measurement from spaceborne sensors.
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C. Papasodoro, E. Berthier, A. Royer, C. Zdanowicz, and A. Langlois
The Cryosphere, 9, 1535–1550, https://doi.org/10.5194/tc-9-1535-2015, https://doi.org/10.5194/tc-9-1535-2015, 2015
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Located at the far south (~62.5° N) of the Canadian Arctic, Grinnell and Terra Nivea Ice Caps are good climate proxies in this scarce data region. Multiple data sets (in situ, airborne and spaceborne) reveal changes in area, elevation and mass over the past 62 years. Ice wastage sharply accelerated during the last decade for both ice caps, as illustrated by the strongly negative mass balance of Terra Nivea over 2007-2014 (-1.77 ± 0.36 m a-1 w.e.). Possible climatic drivers are also discussed.
G. Picard, A. Royer, L. Arnaud, and M. Fily
The Cryosphere, 8, 1105–1119, https://doi.org/10.5194/tc-8-1105-2014, https://doi.org/10.5194/tc-8-1105-2014, 2014
G. Picard, L. Brucker, A. Roy, F. Dupont, M. Fily, A. Royer, and C. Harlow
Geosci. Model Dev., 6, 1061–1078, https://doi.org/10.5194/gmd-6-1061-2013, https://doi.org/10.5194/gmd-6-1061-2013, 2013
Related subject area
Seasonal Snow
Benchmarking of snow water equivalent (SWE) products based on outcomes of the SnowPEx+ Intercomparison Project
Snow depth sensitivity to mean temperature, precipitation, and elevation in the Austrian and Swiss Alps
Use of multiple reference data sources to cross-validate gridded snow water equivalent products over North America
Characterization of non-Gaussianity in the snow distributions of various landscapes
A simple snow temperature index model exposes discrepancies between reanalysis snow water equivalent products
Which global reanalysis dataset has better representativeness in snow cover on the Tibetan Plateau?
Spatial and temporal changes in autumn Eurasian snow cover and its relationship with the Arctic Oscillation
Historical snowfall measurements in the Central and Southern Apennine Mountains: climatology, variability and trend
From snow accumulation to snow depth distributions by quantifying meteoric ice fractions in the Weddell Sea
Snow depth in high-resolution regional climate model simulations over southern Germany – suitable for extremes and impact-related research?
Snow water equivalent retrieval over Idaho – Part 2: Using L-band UAVSAR repeat-pass interferometry
Variability and drivers of winter near-surface temperatures over boreal and tundra landscapes
Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera
Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018
Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets
Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas
Change in the potential snowfall phenology: past, present, and future in the Chinese Tianshan mountainous region, Central Asia
The benefits of homogenising snow depth series – Impacts on decadal trends and extremes for Switzerland
Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain
Impact of measured and simulated tundra snowpack properties on heat transfer
Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods
Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network
Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014
Past changes in natural and managed snow reliability of French Alps ski resorts from 1961 to 2019
Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest of eastern Canada
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset
Recent changes in pan-Arctic sea ice, lake ice, and snow-on/off timing
Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements
Observed snow depth trends in the European Alps: 1971 to 2019
Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
Quantification of the radiative impact of light-absorbing particles during two contrasted snow seasons at Col du Lautaret (2058 m a.s.l., French Alps)
Local-scale variability of snow density on Arctic sea ice
Snow depth estimation and historical data reconstruction over China based on a random forest machine learning approach
Evaluation of long-term Northern Hemisphere snow water equivalent products
Towards a webcam-based snow cover monitoring network: methodology and evaluation
Simulated single-layer forest canopies delay Northern Hemisphere snowmelt
Spatiotemporal variability and decadal trends of snowmelt processes on Antarctic sea ice observed by satellite scatterometers
Converting snow depth to snow water equivalent using climatological variables
Avalanches and micrometeorology driving mass and energy balance of the lowest perennial ice field of the Alps: a case study
The optical characteristics and sources of chromophoric dissolved organic matter (CDOM) in seasonal snow of northwestern China
Brief Communication: Early season snowpack loss and implications for oversnow vehicle recreation travel planning
Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps
Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system
Canadian snow and sea ice: historical trends and projections
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models
Black carbon and mineral dust in snow cover on the Tibetan Plateau
Snow farming: conserving snow over the summer season
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites
Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012
Measuring snow water equivalent from common-offset GPR records through migration velocity analysis
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner
The Cryosphere, 19, 201–218, https://doi.org/10.5194/tc-19-201-2025, https://doi.org/10.5194/tc-19-201-2025, 2025
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We evaluate and rank 23 different datasets on their ability to accurately estimate historical snow amounts. The evaluation uses new a set of surface snow measurements with improved spatial coverage, enabling evaluation across both mountainous and nonmountainous regions. Performance measures vary tremendously across the products: while most perform reasonably in nonmountainous regions, accurate representation of snow amounts in mountainous regions and of historical trends is much more variable.
Matthew Switanek, Gernot Resch, Andreas Gobiet, Daniel Günther, Christoph Marty, and Wolfgang Schöner
The Cryosphere, 18, 6005–6026, https://doi.org/10.5194/tc-18-6005-2024, https://doi.org/10.5194/tc-18-6005-2024, 2024
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Snow depth plays an important role in water resources, mountain tourism, and hazard management across the European Alps. Our study uses station-based historical observations to quantify how changes in temperature and precipitation affect average seasonal snow depth. We find that the relationship between these variables has been surprisingly robust over the last 120 years. This allows us to more accurately estimate how future climate will affect seasonal snow depth in different elevation zones.
Colleen Mortimer, Lawrence Mudryk, Eunsang Cho, Chris Derksen, Mike Brady, and Carrie Vuyovich
The Cryosphere, 18, 5619–5639, https://doi.org/10.5194/tc-18-5619-2024, https://doi.org/10.5194/tc-18-5619-2024, 2024
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Ground measurements of snow water equivalent (SWE) are vital for understanding the accuracy of large-scale estimates from satellites and climate models. We compare two types of measurements – snow courses and airborne gamma SWE estimates – and analyze how measurement type impacts the accuracy assessment of gridded SWE products. We use this analysis to produce a combined reference SWE dataset for North America, applicable for future gridded SWE product evaluations and other applications.
Noriaki Ohara, Andrew D. Parsekian, Benjamin M. Jones, Rodrigo C. Rangel, Kenneth M. Hinkel, and Rui A. P. Perdigão
The Cryosphere, 18, 5139–5152, https://doi.org/10.5194/tc-18-5139-2024, https://doi.org/10.5194/tc-18-5139-2024, 2024
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Snow distribution characterization is essential for accurate snow water estimation for water resource prediction from existing in situ observations and remote-sensing data at a finite spatial resolution. Four different observed snow distribution datasets were analyzed for Gaussianity. We found that non-Gaussianity of snow distribution is a signature of the wind redistribution effect. Generally, seasonal snowpack can be approximated well by a Gaussian distribution for a fully snow-covered area.
Aleksandra Elias Chereque, Paul J. Kushner, Lawrence Mudryk, Chris Derksen, and Colleen Mortimer
The Cryosphere, 18, 4955–4969, https://doi.org/10.5194/tc-18-4955-2024, https://doi.org/10.5194/tc-18-4955-2024, 2024
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We look at three commonly used snow depth datasets that are produced through a combination of snow modelling and historical measurements (reanalysis). When compared with each other, these datasets have differences that arise for various reasons. We show that a simple snow model can be used to examine these inconsistencies and highlight issues. This method indicates that one of the complex datasets should be excluded from further studies.
Shirui Yan, Yang Chen, Yaliang Hou, Kexin Liu, Xuejing Li, Yuxuan Xing, Dongyou Wu, Jiecan Cui, Yue Zhou, Wei Pu, and Xin Wang
The Cryosphere, 18, 4089–4109, https://doi.org/10.5194/tc-18-4089-2024, https://doi.org/10.5194/tc-18-4089-2024, 2024
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The snow cover over the Tibetan Plateau (TP) plays a role in climate and hydrological systems, yet there are uncertainties in snow cover fraction (SCF) estimations within reanalysis datasets. This study utilized the Snow Property Inversion from Remote Sensing (SPIReS) SCF data to assess the accuracy of eight widely used reanalysis SCF datasets over the TP. Factors contributing to uncertainties were analyzed, and a combined averaging method was employed to provide optimized SCF simulations.
Gareth J. Marshall
EGUsphere, https://doi.org/10.5194/egusphere-2024-1892, https://doi.org/10.5194/egusphere-2024-1892, 2024
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Eurasian autumn snow cover (SC) can influence Northern Hemisphere weather in the following winter by affecting the Arctic Oscillation (AO) mode of atmospheric variability. We find that the relationship between the rate of October snow advance and the AO is predominantly of opposite sign between east and west Eurasia. Periods when the SC advance is strongly related to the AO, and thus might be used for weather prediction, occur when the sign of the relationship is reversed in one of the regions.
Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon
EGUsphere, https://doi.org/10.5194/egusphere-2024-1056, https://doi.org/10.5194/egusphere-2024-1056, 2024
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This study offers a “journey through time” to discover historical information about snow precipitation in the Italian Apennines. In this area, in the second half of past century, a gradual decline in snow persistence on the ground as well as in the frequency of occurrence of snowfall events has been observed, especially in sites located above 1000 m a.s.l.. The old data rescued in this study strongly enhances our knowledge about past snowfall variability and climate in the Mediterranean area.
Stefanie Arndt, Nina Maaß, Leonard Rossmann, and Marcel Nicolaus
The Cryosphere, 18, 2001–2015, https://doi.org/10.5194/tc-18-2001-2024, https://doi.org/10.5194/tc-18-2001-2024, 2024
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Antarctic sea ice maintains year-round snow cover, crucial for its energy and mass budgets. Despite its significance, snow depth remains poorly understood. Over the last decades, Snow Buoys have been deployed extensively on the sea ice to measure snow accumulation but not actual depth due to snow transformation into meteoric ice. Therefore, in this study we utilize sea ice and snow models to estimate meteoric ice fractions in order to calculate actual snow depth in the Weddell Sea.
Benjamin Poschlod and Anne Sophie Daloz
The Cryosphere, 18, 1959–1981, https://doi.org/10.5194/tc-18-1959-2024, https://doi.org/10.5194/tc-18-1959-2024, 2024
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Information about snow depth is important within climate research but also many other sectors, such as tourism, mobility, civil engineering, and ecology. Climate models often feature a spatial resolution which is too coarse to investigate snow depth. Here, we analyse high-resolution simulations and identify added value compared to a coarser-resolution state-of-the-art product. Also, daily snow depth extremes are well reproduced by two models.
Zachary Hoppinen, Shadi Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, and Carrie Vuyovich
The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
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We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.
Vilna Tyystjärvi, Pekka Niittynen, Julia Kemppinen, Miska Luoto, Tuuli Rissanen, and Juha Aalto
The Cryosphere, 18, 403–423, https://doi.org/10.5194/tc-18-403-2024, https://doi.org/10.5194/tc-18-403-2024, 2024
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At high latitudes, winter ground surface temperatures are strongly controlled by seasonal snow cover and its spatial variation. Here, we measured surface temperatures and snow cover duration in 441 study sites in tundra and boreal regions. Our results show large variations in how much surface temperatures in winter vary depending on the landscape and its impact on snow cover. These results emphasise the importance of understanding microclimates and their drivers under changing winter conditions.
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.
Kerttu Kouki, Kari Luojus, and Aku Riihelä
The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, https://doi.org/10.5194/tc-17-5007-2023, 2023
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We evaluated snow cover properties in state-of-the-art reanalyses (ERA5 and ERA5-Land) with satellite-based datasets. Both ERA5 and ERA5-Land overestimate snow mass, whereas albedo estimates are more consistent between the datasets. Snow cover extent (SCE) is accurately described in ERA5-Land, while ERA5 shows larger SCE than the satellite-based datasets. The trends in snow mass, SCE, and albedo are mostly negative in 1982–2018, and the negative trends become more apparent when spring advances.
Diego Monteiro and Samuel Morin
The Cryosphere, 17, 3617–3660, https://doi.org/10.5194/tc-17-3617-2023, https://doi.org/10.5194/tc-17-3617-2023, 2023
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Beyond directly using in situ observations, often sparsely available in mountain regions, climate model simulations and so-called reanalyses are increasingly used for climate change impact studies. Here we evaluate such datasets in the European Alps from 1950 to 2020, with a focus on snow cover information and its main drivers: air temperature and precipitation. In terms of variability and trends, we identify several limitations and provide recommendations for future use of these datasets.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
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Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Xuemei Li, Xinyu Liu, Kaixin Zhao, Xu Zhang, and Lanhai Li
The Cryosphere, 17, 2437–2453, https://doi.org/10.5194/tc-17-2437-2023, https://doi.org/10.5194/tc-17-2437-2023, 2023
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Quantifying change in the potential snowfall phenology (PSP) is an important area of research for understanding regional climate change past, present, and future. However, few studies have focused on the PSP and its change in alpine mountainous regions. We proposed three innovative indicators to characterize the PSP and its spatial–temporal variation. Our study provides a novel approach to understanding PSP in alpine mountainous regions and can be easily extended to other snow-dominated regions.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
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Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Zachary S. Miller, Erich H. Peitzsch, Eric A. Sproles, Karl W. Birkeland, and Ross T. Palomaki
The Cryosphere, 16, 4907–4930, https://doi.org/10.5194/tc-16-4907-2022, https://doi.org/10.5194/tc-16-4907-2022, 2022
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Snow depth varies across steep, complex mountain landscapes due to interactions between dynamic natural processes. Our study of a winter time series of high-resolution snow depth maps found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability at a couloir study site in the Bridger Range of Montana, USA. The results of this research have the potential to reduce uncertainty associated with snowpack and snow water resource analysis.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
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Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, https://doi.org/10.5194/tc-16-1281-2022, 2022
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The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
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We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Lucas Berard-Chenu, Hugues François, Emmanuelle George, and Samuel Morin
The Cryosphere, 16, 863–881, https://doi.org/10.5194/tc-16-863-2022, https://doi.org/10.5194/tc-16-863-2022, 2022
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This study investigates the past snow reliability (1961–2019) of 16 ski resorts in the French Alps using state-of-the-art snowpack modelling. We used snowmaking investment figures to infer the evolution of snowmaking coverage at the individual ski resort level. Snowmaking improved snow reliability for the core of the winter season for the highest-elevation ski resorts. However it did not counterbalance the decreasing trend in snow cover reliability for lower-elevation ski resorts and in spring.
Achut Parajuli, Daniel F. Nadeau, François Anctil, and Marco Alves
The Cryosphere, 15, 5371–5386, https://doi.org/10.5194/tc-15-5371-2021, https://doi.org/10.5194/tc-15-5371-2021, 2021
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Cold content is the energy required to attain an isothermal (0 °C) state and resulting in the snow surface melt. This study focuses on determining the multi-layer cold content (30 min time steps) relying on field measurements, snow temperature profile, and empirical formulation in four distinct forest sites of Montmorency Forest, eastern Canada. We present novel research where the effect of forest structure, local topography, and meteorological conditions on cold content variability is explored.
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.
Alicia A. Dauginis and Laura C. Brown
The Cryosphere, 15, 4781–4805, https://doi.org/10.5194/tc-15-4781-2021, https://doi.org/10.5194/tc-15-4781-2021, 2021
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This work examines changes in the timing (on/off dates) of Arctic snow, lake ice, and sea ice to investigate how they have responded to recent climate change and determine if they are responding similarly. We looked at pan-Arctic trends since 1997 and regional trends since 2004 using (mainly) satellite data. Strong regional variability was shown in the snow and ice trends, which highlights the need for a detailed understanding of the regional response to ongoing changes in the Arctic climate.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
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We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
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The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791, https://doi.org/10.5194/tc-15-771-2021, https://doi.org/10.5194/tc-15-771-2021, 2021
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High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Joshua King, Stephen Howell, Mike Brady, Peter Toose, Chris Derksen, Christian Haas, and Justin Beckers
The Cryosphere, 14, 4323–4339, https://doi.org/10.5194/tc-14-4323-2020, https://doi.org/10.5194/tc-14-4323-2020, 2020
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Physical measurements of snow on sea ice are sparse, making it difficulty to evaluate satellite estimates or model representations. Here, we introduce new measurements of snow properties on sea ice to better understand variability at distances less than 200 m. Our work shows that similarities in the snow structure are found at longer distances on younger ice than older ice.
Jianwei Yang, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu
The Cryosphere, 14, 1763–1778, https://doi.org/10.5194/tc-14-1763-2020, https://doi.org/10.5194/tc-14-1763-2020, 2020
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There are many challenges for accurate snow depth estimation using passive microwave data. Machine learning (ML) techniques are deemed to be powerful tools for establishing nonlinear relations between independent variables and a given target variable. In this study, we investigate the potential capability of the random forest (RF) model on snow depth estimation at temporal and spatial scales. The result indicates that the fitted RF algorithms perform better on temporal than spatial scales.
Colleen Mortimer, Lawrence Mudryk, Chris Derksen, Kari Luojus, Ross Brown, Richard Kelly, and Marco Tedesco
The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, https://doi.org/10.5194/tc-14-1579-2020, 2020
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Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Céline Portenier, Fabia Hüsler, Stefan Härer, and Stefan Wunderle
The Cryosphere, 14, 1409–1423, https://doi.org/10.5194/tc-14-1409-2020, https://doi.org/10.5194/tc-14-1409-2020, 2020
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We present a method to derive snow cover maps from freely available webcam images in the Swiss Alps. With marginal manual user input, we can transform a webcam image into a georeferenced map and therewith perform snow cover analyses with a high spatiotemporal resolution over a large area. Our evaluation has shown that webcams could not only serve as a reference for improved validation of satellite-based approaches, but also complement satellite-based snow cover retrieval.
Markus Todt, Nick Rutter, Christopher G. Fletcher, and Leanne M. Wake
The Cryosphere, 13, 3077–3091, https://doi.org/10.5194/tc-13-3077-2019, https://doi.org/10.5194/tc-13-3077-2019, 2019
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Vegetation is often represented by a single layer in global land models. Studies have found deficient simulation of thermal radiation beneath forest canopies when represented by single-layer vegetation. This study corrects thermal radiation in forests for a global land model using single-layer vegetation in order to assess the effect of deficient thermal radiation on snow cover and snowmelt. Results indicate that single-layer vegetation causes snow in forests to be too cold and melt too late.
Stefanie Arndt and Christian Haas
The Cryosphere, 13, 1943–1958, https://doi.org/10.5194/tc-13-1943-2019, https://doi.org/10.5194/tc-13-1943-2019, 2019
David F. Hill, Elizabeth A. Burakowski, Ryan L. Crumley, Julia Keon, J. Michelle Hu, Anthony A. Arendt, Katreen Wikstrom Jones, and Gabriel J. Wolken
The Cryosphere, 13, 1767–1784, https://doi.org/10.5194/tc-13-1767-2019, https://doi.org/10.5194/tc-13-1767-2019, 2019
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We present a new statistical model for converting snow depths to water equivalent. The only variables required are snow depth, day of year, and location. We use the location to look up climatological parameters such as mean winter precipitation and mean temperature difference (difference between hottest month and coldest month). The model is simple by design so that it can be applied to depth measurements anywhere, anytime. The model is shown to perform better than other widely used approaches.
Rebecca Mott, Andreas Wolf, Maximilian Kehl, Harald Kunstmann, Michael Warscher, and Thomas Grünewald
The Cryosphere, 13, 1247–1265, https://doi.org/10.5194/tc-13-1247-2019, https://doi.org/10.5194/tc-13-1247-2019, 2019
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The mass balance of very small glaciers is often governed by anomalous snow accumulation, winter precipitation being multiplied by snow redistribution processes, or by suppressed snow ablation driven by micrometeorological effects lowering net radiation and turbulent heat exchange. In this study we discuss the relative contribution of snow accumulation (avalanches) versus micrometeorology (katabatic flow) on the mass balance of the lowest perennial ice field of the Alps, the Ice Chapel.
Yue Zhou, Hui Wen, Jun Liu, Wei Pu, Qingcai Chen, and Xin Wang
The Cryosphere, 13, 157–175, https://doi.org/10.5194/tc-13-157-2019, https://doi.org/10.5194/tc-13-157-2019, 2019
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We first investigated the optical characteristics and potential sources of chromophoric dissolved organic matter (CDOM) in seasonal snow over northwestern China. The abundance of CDOM showed regional variation. At some sites strongly influenced by local soil, the absorption of CDOM cannot be neglected compared to black carbon. We found two humic-like and one protein-like fluorophores in snow. The major sources of snow CDOM were soil, biomass burning, and anthropogenic pollution.
Benjamin J. Hatchett and Hilary G. Eisen
The Cryosphere, 13, 21–28, https://doi.org/10.5194/tc-13-21-2019, https://doi.org/10.5194/tc-13-21-2019, 2019
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We examine the timing of early season snowpack relevant to oversnow vehicle (OSV) recreation over the past 3 decades in the Lake Tahoe region (USA). Data from two independent data sources suggest that the timing of achieving sufficient snowpack has shifted later by 2 weeks. Increasing rainfall and more dry days play a role in the later onset. Adaptation strategies are provided for winter travel management planning to address negative impacts of loss of early season snowpack for OSV usage.
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
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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.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Lawrence R. Mudryk, Chris Derksen, Stephen Howell, Fred Laliberté, Chad Thackeray, Reinel Sospedra-Alfonso, Vincent Vionnet, Paul J. Kushner, and Ross Brown
The Cryosphere, 12, 1157–1176, https://doi.org/10.5194/tc-12-1157-2018, https://doi.org/10.5194/tc-12-1157-2018, 2018
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This paper presents changes in both snow and sea ice that have occurred over Canada during the recent past and shows climate model estimates for future changes expected to occur by the year 2050. The historical changes of snow and sea ice are generally coherent and consistent with the regional history of temperature and precipitation changes. It is expected that snow and sea ice will continue to decrease in the future, declining by an additional 15–30 % from present day values by the year 2050.
Andrew M. Snauffer, William W. Hsieh, Alex J. Cannon, and Markus A. Schnorbus
The Cryosphere, 12, 891–905, https://doi.org/10.5194/tc-12-891-2018, https://doi.org/10.5194/tc-12-891-2018, 2018
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Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.
Yulan Zhang, Shichang Kang, Michael Sprenger, Zhiyuan Cong, Tanguang Gao, Chaoliu Li, Shu Tao, Xiaofei Li, Xinyue Zhong, Min Xu, Wenjun Meng, Bigyan Neupane, Xiang Qin, and Mika Sillanpää
The Cryosphere, 12, 413–431, https://doi.org/10.5194/tc-12-413-2018, https://doi.org/10.5194/tc-12-413-2018, 2018
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Light-absorbing impurities deposited on snow can reduce surface albedo and contribute to the near-worldwide melting of snowpack and ice. This study focused on the black carbon and mineral dust in snow cover on the Tibetan Plateau. We discussed their concentrations, distributions, possible sources, and albedo reduction and radiative forcing. Findings indicated that the impacts of black carbon and mineral dust need to be properly accounted for in future regional climate projections.
Thomas Grünewald, Fabian Wolfsperger, and Michael Lehning
The Cryosphere, 12, 385–400, https://doi.org/10.5194/tc-12-385-2018, https://doi.org/10.5194/tc-12-385-2018, 2018
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Snow farming is the conservation of snow during summer. Large snow piles are covered with a sawdust insulation layer, reducing melt and guaranteeing a specific amount of available snow in autumn, independent of the weather conditions. Snow volume changes in two heaps were monitored, showing that about a third of the snow was lost. Model simulations confirmed the large effect of the insulation on energy balance and melt. The model can now be used as a tool to examine future snow-farming projects.
Kristoffer Aalstad, Sebastian Westermann, Thomas Vikhamar Schuler, Julia Boike, and Laurent Bertino
The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, https://doi.org/10.5194/tc-12-247-2018, 2018
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We demonstrate how snow cover data from satellites can be used to constrain estimates of snow distributions at sites in the Arctic. In this effort, we make use of data assimilation to combine the information contained in the snow cover data with a simple snow model. By comparing our snow distribution estimates to independent observations, we find that this method performs favorably. Being modular, this method could be applied to other areas as a component of a larger reanalysis system.
Xinyue Zhong, Tingjun Zhang, Shichang Kang, Kang Wang, Lei Zheng, Yuantao Hu, and Huijuan Wang
The Cryosphere, 12, 227–245, https://doi.org/10.5194/tc-12-227-2018, https://doi.org/10.5194/tc-12-227-2018, 2018
James St. Clair and W. Steven Holbrook
The Cryosphere, 11, 2997–3009, https://doi.org/10.5194/tc-11-2997-2017, https://doi.org/10.5194/tc-11-2997-2017, 2017
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We investigate the performance of a semiautomated algorithm for measuring snow water equivalent (SWE) from common-offset ground-penetrating radar (GPR) data. GPR-derived SWE estimates are similar to manual measurements, indicating that the method is reliable. Our results will hopefully make GPR a more attractive tool for monitoring SWE in mountain watersheds.
Cited articles
Adams, E. and Sato, A.: Model for effective thermal conductivity of a dry snow cover composed of uniform ice spheres, Ann. Glaciol., 18, 300–304, 1993.
Andreadis, K. M., Liang, D., Tsang, L., Lettenmaier, D. P., and Josberger, E. G.: Characterization of errors in a coupled snow hydrology microwave emission model, J. Hydrometeorol., 9, 149–164, 2008.
Aoki, T., Kuchiki, K., Niwano, M., Kodama, Y., Hosaka, M., and Tanaka, T.: Physically based snow albedo model for calculating broadband albedos and the solar heating profile in snowpack for general circulation models, J. Geophys. Res., 116, D11114, https://doi.org/10.1029/2010JD015507, 2011.
Armstrong, R. and Brun, E.: Snow and climate: physical processes, surface energy exchange and modeling, Cambridge University Press, Cambridge, 2008.
Arnaud, L., Picard, G., Champollion, N., Domine, F., Gallet, J. C., Lefebvre, E., Fily, M., and Barnola, J. M.: Measurement of vertical profiles of snow specific surface area with a 1 cm resolution using infrared reflectance: instrument description and validation, J. Glaciol., 57, 17–29, 2011.
Baggaley, D. G. and Hanesiak, J. M.: An empirical blowing snow forecast technique for the Canadian arctic and the Prairie provinces, Weather Forecast., 20, 51–62, 2005.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning, Part I: Numerical model, Cold region Science and Technology, 35, 123–145, 2002.
Bartlett, P. A., MacKay, M. D., and Verseghy, D. L.: Modified snow algorithms in the Canadian land surface scheme: model runs and sensitivity analysis at three boreal forest stands, Atmos. Ocean, 44, 207–222, 2006.
Belair, S., Brown, R., Mailhot, J., Bilodeau, B., and Crevier, L.: Operational implementation of the ISBA land surface scheme in the Canadian regional weather forecast model. Part II: Cold season results, J. Hydrometeorol., 4, 371–386, 2003.
Bougamont, M., Bamber, J. L., and Greuell, W.: A surface mass balance model for the Greenland ice sheet, 110, 2003–2012, 2005.
Brown, R., Bartlett, P., MacKay, M., and Verseghy, D.: Evaluation of snow cover in CLASS for SnowMIP, Atmos. Ocean, 44, 223–238, 2006.
Brucker, L., Picard, G., Arnaud, L., Barnola, J.-M., Schneebeli, M., Brunjail, H., Lefebvre, E., and Fily, M.: Modelling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements, J. Glaciol., 57, 171–182, 2011.
Brun, E.: Investigation on wet-snow metamorphism in respect of liquid-water content, Ann. Glaciol., 13, 22–26, 1989.
Brun, E., David, P., Suduland, M., and Brunot, G.: A numerical model simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 14–22, 1992.
Cabanes, A., Legagneux, L., and Domine, F.: Rate of evolution of the specific surface area of surface snow layers, Environ. Sci. Technol., 37, 661–666, 2003.
Caya, D. and Laprise, R.: A semi-implicit semi-Lagrangian regional climate model: the Canadian RCM, Mon. Weather Rev., 127, 341–362, 1999.
Chen, S. and Baker, I.: Evolution of individual snowflakes during metamorphism, J. Geophys. Res., 115, D21114, https://doi.org/10.1029/2010JD014132, 2010.
Colbeck, S.: Theory of metamorphism of dry snow, J. Geophys. Res., 88, 5475–5482, 1983.
Derksen, C., Toose, P., Lemmetyinen, J., Pulliainen, J., Langlois, A., Rutter, N., and Fuller, M.: Evaluation of passive microwave brightness temperature simulations and snow water equivalent retrievals through a winter season, Remote Sens. Environ., 117, 236–248, 2012.
Domine, F., Cabanes, A., Taillandier, A., and Legagneux, L.: Specific surface area of snow samples determined by CH4 adsorption at 77 K and estimated by optical microscopy and scanning electron microscopy, Environ. Sci. Technol., 35, 771–780, 2001.
Domine, F., Lauzier, T., Cabanes, A., Legagneux, L., Kuhs, W., Techmer, K., and Heinrichs, T.: Snow metamorphism as revealed by scanning electron microscopy, Microsc. Res. Techniq., 62, 33–48, 2003.
Domine, F., Taillandier, A.-S., and Simpson, W. R.: A parameterization of the specific surface area of seasonal snow for field use and for models of snowpack evolution, J. Geophys. Res., 112, F02031, https://doi.org/10.1029/2006JF000512, 2007.
Domine, F., Albert, M., Huthwelker, T., Jacobi, H.-W., Kokhanovsky, A. A., Lehning, M., Picard, G., and Simpson, W. R.: Snow physics as relevant to snow photochemistry, Atmos. Chem. Phys., 8, 171–208, https://doi.org/10.5194/acp-8-171-2008, 2008.
Domine, F., Taillandier, A.-S., Cabanes, A., Douglas, T. A., and Sturm, M.: Three examples where the specific surface area of snow increased over time, The Cryosphere, 3, 31–39, https://doi.org/10.5194/tc-3-31-2009, 2009.
Durand, M. and Liu, D.: The need for prior information in characterizing snow water equivalent from microwave brightness temperatures, Remote Sens. Environ., 126, 248–257, 2012.
Durand, M., Kim, E. C., and Margulis, S.: Quantifying uncertainty in modeling snow microwave radiance for a mountain snowpack at the point-scale, including stratigraphic effects, IEEE T. Geosci. Remote, 46, 1753–1767, 2008.
Durand, M., Kim, E., and Margulis, S.: Radiance assimilation shows promise for snowpack characterization, Geophys. Res. Lett., 36, L02503, https://doi.org/10.1029/2008GL035214, 2009.
Ettema, J., van den Broeke, M. R., van Meijgaard, E., van de Berg, W., Bamber, J. L., Box, J. E., and Bales, R. C.: Higher surface mass balance of the Greenland ice sheet revealed by high-resolution climate modeling, Geophys. Res. Lett., 36, L12501, https://doi.org/10.1029/2009GL038110, 2009.
Flanner, M. and Zender, C.: Linking snowpack microphysics and albedo evolution, J. Geophys. Res., 111, D12208, https://doi.org/10.1029/2005JD006834, 2006.
Flanner, M., Zender, C., Randerson, J., and Rasch, P.: Present-day climate forcing and response from black carbon in snow, J. Geophys. Res., 112, D11202, https://doi.org/10.1029/2006JD008003, 2007.
Flin, F. and Brzoska, J.: The temperature-gradient metamorphism of snow: vapour diffusion model and application to tomographic images, Ann. Glaciol., 49, 17–21, 2008.
Flin, F., Brzoska, J., Lesaffre, B., Coléou, C., and Pieritz, R.: Three-dimensional geometric measurements of snow microstructural evolution under isothermal conditions, Ann. Glaciol., 38, 39–44, 2004.
Franz, K., Butcher, P., and Ajami, N.: Addressing snow model uncertainty for hydrologic prediction, Adv. Water Resour., 33, 820–832, 2010.
Gallet, J.-C., Domine, F., Zender, C. S., and Picard, G.: Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm, The Cryosphere, 3, 167–182, https://doi.org/10.5194/tc-3-167-2009, 2009.
Gardner, A. and Sharp, M.: A review of snow and ice albedo and the development of a new physically based broadband albedo parameterization, J. Geophys. Res., 115, F01009, https://doi.org/10.1029/2009JF001444, 2010.
Gouttevin, I., Menegoz, M., Domine, F., Krinner, G., Koven, C., Ciais, P., Tarnocai, C., and Boike, J.: How the insulating properties of snow affect soil carbon distribution in the continental pan-arctic area, J. Geophys. Res., 117, G02020, https://doi.org/10.1029/2011JG001916, 2012.
Grody, N.: Relationship between snow parameters and microwave satellite measurements: theory compared with Advanced Microwave Sounding Unit observations from 23 to 150 GHz, J. Geophys. Res., 113, D22108, https://doi.org/10.1029/2007JD009685, 2008.
Hedstrom, N. and Pomeroy, J.: Measurements and modelling of snow interception in the boreal forest, Hydrol. Process., 12, 1611–1625, 1998.
Huang, C., Margulis, S., Durand, M., and Musselman, K.: Assessment of Snow Grain-Size Model and Stratigraphy Representation Impacts on Snow Radiance Assimilation: Forward Modeling Evaluation, IEEE T. Geosci. Remote, 50, 4551–4564, 2012.
Jacobi, H.-W., Domine, F., Simpson, W. R., Douglas, T. A., and Sturm, M.: Simulation of the specific surface area of snow using a one-dimensional physical snowpack model: implementation and evaluation for subarctic snow in Alaska, The Cryosphere, 4, 35–51, https://doi.org/10.5194/tc-4-35-2010, 2010.
Jin, Z., Charlock, T. P., Yang, P., Xie, Y., and Miller, W.: Snow optical properties for different particle shapes with application to snow grain size retrieval and MODIS/CERES radiance comparison over Antarctica, Remote Sens. Environ., 112, 3563–3581, 2008.
Kaempfer, T. and Schneebeli, M.: Observation of isothermal metamorphism of new snow and interpretation as a sintering process, J. Geophys. Res., 112, D24101, https://doi.org/10.1029/2007JD009047, 2007.
Kokhanovsky, A. A. and Zege, E. P.: Scattering optics of snow, Appl. Optics, 43, 1589–1602, 2004.
Kondo, J. and Yamazaki, T.: A prediction model for snowmelt, snow surface temperature and freezing depth using a heat balance method, J. Appl. Meteorol., 29, 375–384, 1990.
Kontu, A. and Pulliainen, J.: Simulation of spaceborne microwave radiometer measurements of snow cover using in situ data and brightness temperature modeling, IEEE T. Geosci. Remote, 48, 1031–1044, 2010.
Langlois, A., Brucker, L., Kohn, J., Royer, A., Derksen, C., Cliche, P., Picard, G., Willemet, J. M., and Fily, M.: Simulation of snow water equivalent (SWE) using thermodynamic snow models in Québec, Canada, J. Hydrometeorol., 10, 1447–1463, 2009.
Langlois, A., Royer, A., Derksen, C., Montpetit, B., Dupont, F., and Goïta, K.: Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals, Water Ressour. Res., 48, W12524, https://doi.org/10.1029/2012WR012133, 2012.
Langlois, A., Bergeron, J., Brown, R., Royer, A., Harvey, R., Roy, A., Wang, L., and Thériault, N.: Evaluation of CLASS 2.7 and 3.5 simulations of snow cover from the Canadian Climate model (CRCM4) over Québec, Canada, J. Hydrometeorol., submitted (AMSJHM-S-13-00073), 2013.
Leathers, D. J., Palecki, M. A., Robinson, D. A., and Dewey, K. F.: Climatology of the daily temperature range annual cycle in the United States, Clim. Res., 9, 197–211, 1998.
Legagneux, L., Lauzier, T., Domine, F., Kuhs, W., Heinrichs, T., and Techmer, K.: Rate of decay of specific surface area of snow during isothermal experiments and morphological changes studied by scanning electron microscopy, Can. J. Phys., 81, 459–468, 2003.
Li, L. and Pomeroy, J.: Estimates of threshold wind speeds for snow transport using meteorological data, J. Appl. Meteorol., 36, 205–213, 1997.
Liston, G. and Hiemstra, C.: The changing cryosphere: Pan-Arctic snow trends (1979–2009), J. Climate, 24, 5691–5712, 2011.
Lyapustin, A., Tedesco, M., Wang, Y., Aoki, T., Horif, M., and Kokhanovsky, A. A.: Retrieval of snow grain size over Greenland from MODIS, Remote Sens. Environ., 113, 1976–1987, 2009.
Marbouty, D.: An experimental study of temperature gradient metamorphism, J. Glaciol., 26, 303–312, 1980.
Mesinger, F., DiMego, G., Kalnay, E., Mitchell, K., Shafran, P., Ebisuzaki, W., Jovic, D., Woollen, J., Rogers, E., and Berbery, E.: North American regional reanalysis, B. Am. Meteorol. Soc., 87, 343–360, 2006.
Montpetit, B., Royer, A., Langlois, A., Cliche, P., Roy, A., Champollion, N., Picard, G., Domine, F., and Obbard, R.: New shortwave infrared albedo measurements for snow specific surface area retrieval, J. Glaciol., 58, 941, https://doi.org/10.1016/j.coldregions.2010.01.004, 2012.
Montpetit, B., Royer, A., Roy, A., Langlois, L., and Derksen, D.: Snow microwave emission modeling of ice lenses within a snowpack using the microwave emission model for layered snowpacks, IEEE T. Geosci. Remote, available online, https://doi.org/10.1109/TGRS.2013.2250509, 2013.
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, 2012.
Morin, S., Domine, F., Dufour, A., Lejeune, Y., Lesaffre, B., Willemet, J., Carmagnola, C., and Jacobi, H.: Measurements and modeling of the vertical profile of specific surface area of an alpine snowpack, Adv. Water Resour., 55, 111–120, https://doi.org/10.1016/j.advwatres.2012.01.010, 2013.
Music, B. and Caya, D.: Evaluation of the hydrological cycle over the Mississippi River basin as simulated by the Canadian Regional Climate Model (CRCM), J. Hydrometeorol., 8, 969–988, 2007.
Niwano, M., Aoki, T., Kuchiki, K., Hosaka, M., and Kodama, Y.: Snow metamorphism and albedo process (SMAP) model for climate studies: Model validation using meteorological and snow impurity data measured at Sapporo, Japan, J. Geophys. Res., 117, F03008, https://doi.org/10.1029/2011JF002239, 2012.
Pardé, M., Goïta, K., and Royer, A.: Inversion of a passive microwave snow emission model for water equivalent estimation using airborne and satellite data, Remote Sens. Environ., 111, 346–356, 2007.
Picard, G., Brucker, L., Roy, A., Dupont, F., Fily, M., and Royer, A.: Simulation of the microwave emission of multi-layered snowpacks using the dense media radiative transfer theory: the DMRT-ML model, Geosci. Model Dev. Discuss., 5, 3647–3694, https://doi.org/10.5194/gmdd-5-3647-2012, 2012.
Pietroniro, A., Leconte, R., Toth, B., Peters, D. L., Kouwen, N., Conley, F. M., and Prowse, T.: Modelling climate change impacts in the Peace and Athabasca catchment and delta III – integrated model assessment, Hydrol. Process., 20, 4231–4235, 2006.
Pinzer, B. and Schneebeli, M.: Snow metamorphism under alternating temperature gradients: morphology and recrystallization in surface snow, Geophys. Res. Lett., 36, L23503, https://doi.org/10.1029/2009GL039618, 2009.
Reichle, R.: Data assimilation methods in the Earth sciences, Adv. Water Resour., 31, 1411–1418, 2008.
Roy, V., Goïta, K., Royer, A., Walker, A., and Goodison, B.: Snow water equivalent retrieval in a Canadian boreal environment from microwave measurements using the HUT snow emission model, IEEE T. Geosci. Remote, 42, 1850–1859, 2004.
Roy, A., Picard, G., Royer, A., Montpetit, B., Dupont, F., Langlois, A., Derksen, C., and Champollion, N.: Brightness temperature simulations of the Canadian seasonal snowpack driven by measurements of the snow specific surface area, IEEE T. Geosci. Remote, available online, https://doi.org/10.1109/TGRS.2012.2235842, 2013.
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., 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., 114, D06111, https://doi.org/10.1029/2008JD011063, 2009.
Scinocca, J. F., McFarlane, N. A., Lazare, M., Li, J., and Plummer, D.: Technical Note: The CCCma third generation AGCM and its extension into the middle atmosphere, Atmos. Chem. Phys., 8, 7055–7074, https://doi.org/10.5194/acp-8-7055-2008, 2008.
Sommerfeld, R. and LaChapelle, E.: The classification of snow metamorphism, J. Glaciol., 9, 3–17, 1970.
Sturm, M., Holmgren, J., König, M., and Morris, K.: The thermal conductivity of seasonal snow, J. Glaciol., 43, 26–41, 1997.
Sun, S., Jin, J., and Xue, Y.: A simple snow-atmosphere-soil transfer model, J. Geophys. Res., 104, 19587–19597, 1999.
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., Douglas, T. A., and Severin, K.: Evolution of the snow area index of the subarctic snowpack in central Alaska over a whole season, consequences for the air to snow transfer of pollutants, Environ. Sci. Technol., 40, 7521–7527, 2006.
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., and Douglas, T. A.: Rate of decrease of the specific surface area of dry snow: Isothermal and temperature gradient conditions, J. Geophys. Res., 112, F03003, https://doi.org/10.1029/2006JF000514, 2007.
Teutschbein, C. and Seibert, J.: Regional climate models for hydrological impact studies at the catchment scale: a review of recent modeling strategies, Geography Compass, 4, 834–860, 2010.
Toure, A., Goïta, K., Royer, A., Kim, E., Durand, M., Margulis, S., and Lu, H.: A Case study of using a multilayered thermodynamical snow model for radiance assimilation, IEEE T. Geosci. Remote, 9, 2828–2837, 2011.
Turcotte, R., Fortin, L.-G., Fortin, V., Fortin, J.-P., and Villeneuve, J.-P.: Operational analysis of the spatial distribution and the temporal evolution of the snowpack water equivalent in southern Québec, Canada, Nord. Hydrol., 38, 211–234, 2007.
Vachon, F., Goïta, K., De Sève, D., and Royer, A.: Inversion of a snow emision model calibrated with in situ data for snow water equivalent monitoring, IEEE T. Geosci. Remote, 48, 59–71, 2010.
Verseghy, D.: CLASS-A Canadian land surface scheme for GCMs, I. Soil model, Int. J. Climateol., 11, 111–133, 1991.
Verseghy, D.: CLASS – The Canadian Land Surface Scheme (Version 3.4): Technical Documentation (Version 1.1), 2009.
Verseghy, D., McFarlane, N., and Lazare, M.: CLASS-A Canadian land surface scheme for GCMs, II. Vegetation model and coupled runs, Int. J. Climateol., 13, 347–370, 1993.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Wiscombe, W. and Warren, S.: A model for the spectral albedo of snow, I: Pure snow, J. Atmos. Sci., 37, 2712–2733, 1980.
