Articles | Volume 22, issue 11
Hydrol. Earth Syst. Sci., 22, 5711–5734, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
05 Nov 2018
Research article | 05 Nov 2018
Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada
Fanny Larue et al.
No articles found.
Sammy Metref, Emmanuel Cosme, Matthieu Le Lay, and Joël Gailhard
Predicting the seasonal streamflow supply of water in a mountainous basin is critical to anticipate the operation of hydroelectric damns and avoid hydrology-related hazard. This quantity partly depends on the snowpack accumulated during winter. The study addresses this prediction problem using information from streamflow data and both direct and indirect snow measurements. In this study, the prediction is improved by integrating the data information into a basin scale hydrological model.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Andreas Schmitt, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere, 16, 2163–2181,Short summary
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,Short summary
To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Alain Royer, Alexandre Roy, Sylvain Jutras, and Alexandre Langlois
The Cryosphere, 15, 5079–5098,Short summary
Dense spatially distributed networks of autonomous instruments for continuously measuring the amount of snow on the ground are needed for operational water resource and flood management and the monitoring of northern climate change. Four new-generation non-invasive sensors are compared. A review of their advantages, drawbacks and accuracy is discussed. This performance analysis is intended to help researchers and decision-makers choose the one system that is best suited to their needs.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614,Short summary
In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Alex Mavrovic, Renato Pardo Lara, Aaron Berg, François Demontoux, Alain Royer, and Alexandre Roy
Hydrol. Earth Syst. Sci., 25, 1117–1131,Short summary
This paper presents a new probe that measures soil microwave permittivity in the frequency range of satellite L-band sensors. The probe capacities will allow for validation and calibration of the models used to estimate landscape physical properties from raw microwave satellite datasets. Our results show important discrepancies between model estimates and instrument measurements that will need to be addressed.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
Biogeosciences, 18, 739–753,Short summary
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.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059,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.
Ann-Sophie Tissier, Jean-Michel Brankart, Charles-Emmanuel Testut, Giovanni Ruggiero, Emmanuel Cosme, and Pierre Brasseur
Ocean Sci., 15, 443–457,Short summary
To better exploit the observational information available for all scales in data assimilation systems, we investigate a new method to introduce scale separation in the algorithm. It consists in carrying out the analysis with spectral localisation for the large scales and spatial localisation for the residual scales. The performance is then checked explicitly and separately for all scales. Results show that accuracy can be improved for the large scales while preserving reliability at all scales.
Florent Garnier, Pierre Brasseur, Jean-Michel Brankart, Yeray Santana-Falcon, and Emmanuel Cosme
Ocean Sci. Discuss.,
Publication in OS not foreseen
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067,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.
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208,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,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,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.
Luc Charrois, Emmanuel Cosme, Marie Dumont, Matthieu Lafaysse, Samuel Morin, Quentin Libois, and Ghislain Picard
The Cryosphere, 10, 1021–1038,Short summary
This study investigates the assimilation of optical reflectances, snowdepth data and both combined into a multilayer snowpack model. Data assimilation is performed with an ensemble-based method, the Sequential Importance Resampling Particle filter. Experiments assimilating only synthetic data are conducted at one point in the French Alps, the Col du Lautaret, over five hydrological years. Results of the assimilation experiments show improvements of the snowpack bulk variables estimates.
Alexandre Roy, Alain Royer, Olivier St-Jean-Rondeau, Benoit Montpetit, Ghislain Picard, Alex Mavrovic, Nicolas Marchand, and Alexandre Langlois
The Cryosphere, 10, 623–638,
C. Papasodoro, E. Berthier, A. Royer, C. Zdanowicz, and A. Langlois
The Cryosphere, 9, 1535–1550,Short summary
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. A. Ruggiero, Y. Ourmières, E. Cosme, J. Blum, D. Auroux, and J. Verron
Nonlin. Processes Geophys., 22, 233–248,
S. Metref, E. Cosme, C. Snyder, and P. Brasseur
Nonlin. Processes Geophys., 21, 869–885,
G. Picard, A. Royer, L. Arnaud, and M. Fily
The Cryosphere, 8, 1105–1119,
G. Picard, L. Brucker, A. Roy, F. Dupont, M. Fily, A. Royer, and C. Harlow
Geosci. Model Dev., 6, 1061–1078,
A. Roy, A. Royer, B. Montpetit, P. A. Bartlett, and A. Langlois
The Cryosphere, 7, 961–975,
Related subject area
Subject: Snow and Ice | Techniques and Approaches: Modelling approachesRecent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configurationFuture projections of High Atlas snowpack and runoff under climate changeTrends and variability in snowmelt in China under climate changeAssimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow ObservationsSnowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered areaDevelopment and parameter estimation of snowmelt models using spatial snow-cover observations from MODISThe evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchmentsLearning about precipitation lapse rates from snow course data improves water balance modelingSnow water equivalents exclusively from snow depths and their temporal changes: the Δsnow modelApplication of machine learning techniques for regional bias correction of snow water equivalent estimates in Ontario, CanadaSensitivity of snow models to the accuracy of meteorological forcings in mountain environmentsSnow processes in mountain forests: interception modeling for coarse-scale applicationsSatellite-derived products of solar and longwave irradiances used for snowpack modelling in mountainous terrainUsing Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudesThe role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)Hyper-resolution ensemble-based snow reanalysis in mountain regions using clusteringThe sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradientAssessment of SWAT spatial and temporal transferability for a high-altitude glacierized catchmentModeling experiments on seasonal lake ice mass and energy balance in the Qinghai–Tibet Plateau: a case studyA simple model for local-scale sensible and latent heat advection contributions to snowmeltA simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed modelTechnical note: Representing glacier geometry changes in a semi-distributed hydrological modelProjected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approachScenario approach for the seasonal forecast of Kharif flows from the Upper Indus BasinThe role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchmentsModelling hydrologic impacts of light absorbing aerosol deposition on snow at the catchment scaleLiquid water infiltration into a layered snowpack: evaluation of a 3-D water transport model with laboratory experimentsAssessing glacier melt contribution to streamflow at Universidad Glacier, central Andes of ChileModelling liquid water transport in snow under rain-on-snow conditions – considering preferential flowDeveloping a representative snow-monitoring network in a forested mountain watershedSubgrid parameterization of snow distribution at a Mediterranean site using terrestrial photographyAssessing the benefit of snow data assimilation for runoff modeling in Alpine catchmentsStable oxygen isotope variability in two contrasting glacier river catchments in GreenlandSpatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow coverA conceptual, distributed snow redistribution modelDiagnostic calibration of a hydrological model in a mountain area by hydrograph partitioningMeltwater run-off from Haig Glacier, Canadian Rocky Mountains, 2002–2013Modeling the snow surface temperature with a one-layer energy balance snowmelt modelEstimating degree-day factors from MODIS for snowmelt runoff modelingEffect of meteorological forcing and snow model complexity on hydrological simulations in the Sieber catchment (Harz Mountains, Germany)Model simulations of the modulating effect of the snow cover in a rain-on-snow eventModelling runoff from a Himalayan debris-covered glacierLarge-scale analysis of changing frequencies of rain-on-snow events with flood-generation potentialChallenges in modelling river flow and ice regime on the Ningxia–Inner Mongolia reach of the Yellow River, ChinaCorrecting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing dataLarge scale snow water equivalent status monitoring: comparison of different snow water products in the upper Colorado BasinPrecipitation and snow cover in the Himalaya: from reanalysis to regional climate simulationsComparison of climate change signals in CMIP3 and CMIP5 multi-model ensembles and implications for Central Asian glaciersStatistical modelling of the snow depth distribution in open alpine terrainClimate change impacts on maritime mountain snowpack in the Oregon Cascades
Dhiraj Pradhananga and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 2605–2616,Short summary
This study considers the combined impacts of climate and glacier changes due to recession on the hydrology and water balance of two high-elevation glaciers. Peyto and Athabasca glacier basins in the Canadian Rockies have undergone continuous glacier loss over the last 3 to 5 decades, leading to an increase in ice exposure and changes to the elevation and slope of the glacier surfaces. Streamflow from these glaciers continues to increase more due to climate warming than glacier recession.
Alexandre Tuel, Nabil El Moçayd, Moulay Driss Hasnaoui, and Elfatih A. B. Eltahir
Hydrol. Earth Syst. Sci., 26, 571–588,Short summary
Snowmelt in the High Atlas is critical for irrigation in Morocco but is threatened by climate change. We assess future trends in High Atlas snowpack by modelling it under historical and future climate scenarios and estimate their impact on runoff. We find that the combined warming and drying will result in a roughly 80 % decline in snowpack, a 5 %–30 % decrease in runoff efficiency and 50 %–60 % decline in runoff under a business-as-usual scenario.
Yong Yang, Rensheng Chen, Guohua Liu, Zhangwen Liu, and Xiqiang Wang
Hydrol. Earth Syst. Sci., 26, 305–329,Short summary
A comprehensive assessment of snowmelt is missing for China. Trends and variability in snowmelt in China under climate change are investigated using historical precipitation and temperature data (1951–2017) and projection scenarios (2006–2099). The snowmelt and snowmelt runoff ratio show significant spatial and temporal variability in China. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on the water supply.
Ryan L. Crumley, David F. Hill, Katreen Wikstrom Jones, Gabriel J. Wolken, Anthony A. Arendt, Christina M. Aragon, Christopher Cosgrove, and Community Snow Observations Participants
Hydrol. Earth Syst. Sci., 25, 4651–4680,Short summary
In this study, we use a new snow data set collected by participants in the Community Snow Observations project in coastal Alaska to improve snow depth and snow water equivalence simulations from a snow process model. We validate our simulations with multiple datasets, taking advantage of snow telemetry (SNOTEL), snow depth and snow water equivalence, and remote sensing measurements. Our results demonstrate that assimilating citizen science snow depth measurements can improve model performance.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471,Short summary
Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Dhiraj Raj Gyawali and András Bárdossy
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
In this study, different extensions of the degree-day model were calibrated on snow-cover distribution against freely available satellite snow cover images. The calibrated models simulated the distribution very well in Baden-Wuerttemberg (Germany) and Switzerland. In addition to reliable identification of snow cover, the melt outputs from the calibrated models were able to improve the flow simulations in different catchments in the study region.
Michael Weber, Franziska Koch, Matthias Bernhardt, and Karsten Schulz
Hydrol. Earth Syst. Sci., 25, 2869–2894,Short summary
We compared a suite of globally available meteorological and DEM data with in situ data for physically based snow hydrological modelling in a small high-alpine catchment. Although global meteorological data were less suited to describe the snowpack properly, transferred station data from a similar location in the vicinity and substituting single variables with global products performed well. In addition, using 30 m global DEM products as model input was useful in such complex terrain.
Francesco Avanzi, Giulia Ercolani, Simone Gabellani, Edoardo Cremonese, Paolo Pogliotti, Gianluca Filippa, Umberto Morra di Cella, Sara Ratto, Hervè Stevenin, Marco Cauduro, and Stefano Juglair
Hydrol. Earth Syst. Sci., 25, 2109–2131,Short summary
Precipitation tends to increase with elevation, but the magnitude and distribution of this enhancement remain poorly understood. By leveraging over 11 000 spatially distributed, manual measurements of snow depth (snow courses) upstream of two reservoirs in the western European Alps, we show that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improved modeling accuracy and, ultimately, our understanding of the water budget.
Michael Winkler, Harald Schellander, and Stefanie Gruber
Hydrol. Earth Syst. Sci., 25, 1165–1187,Short summary
A new method to calculate the mass of snow is provided. It is quite simple but gives surprisingly good results. The new approach only requires regular snow depth observations to simulate respective water mass that is stored in the snow. It is called
ΔSNOW model, its code is freely available, and it can be applied in various climates. The method is especially interesting for studies on extremes (e.g., snow loads or flooding) and climate (e.g., precipitation trends).
Fraser King, Andre R. Erler, Steven K. Frey, and Christopher G. Fletcher
Hydrol. Earth Syst. Sci., 24, 4887–4902,Short summary
Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.
Silvia Terzago, Valentina Andreoli, Gabriele Arduini, Gianpaolo Balsamo, Lorenzo Campo, Claudio Cassardo, Edoardo Cremonese, Daniele Dolia, Simone Gabellani, Jost von Hardenberg, Umberto Morra di Cella, Elisa Palazzi, Gaia Piazzi, Paolo Pogliotti, and Antonello Provenzale
Hydrol. Earth Syst. Sci., 24, 4061–4090,Short summary
In mountain areas high-quality meteorological data to drive snow models are rarely available, so coarse-resolution data from spatial interpolation of the available in situ measurements or reanalyses are typically employed. We perform 12 experiments using six snow models with different degrees of complexity to show the impact of the accuracy of the forcing on snow depth and snow water equivalent simulations at the Alpine site of Torgnon, discussing the results in relation to the model complexity.
Nora Helbig, David Moeser, Michaela Teich, Laure Vincent, Yves Lejeune, Jean-Emmanuel Sicart, and Jean-Matthieu Monnet
Hydrol. Earth Syst. Sci., 24, 2545–2560,Short summary
Snow retained in the forest canopy (snow interception) drives spatial variability of the subcanopy snow accumulation. As such, accurately describing snow interception in models is of importance for various applications such as hydrological, weather, and climate predictions. We developed descriptions for the spatial mean and variability of snow interception. An independent evaluation demonstrated that the novel models can be applied in coarse land surface model grid cells.
Louis Quéno, Fatima Karbou, Vincent Vionnet, and Ingrid Dombrowski-Etchevers
Hydrol. Earth Syst. Sci., 24, 2083–2104,Short summary
In mountainous terrain, the snowpack is strongly affected by incoming shortwave and longwave radiation. Satellite-derived products of incoming radiation were assessed in the French Alps and the Pyrenees and compared to meteorological forecasts, reanalyses and in situ measurements. We showed their good quality in mountains. The different radiation datasets were used as radiative forcing for snowpack simulations with the detailed model Crocus. Their impact on the snowpack evolution was explored.
Emma L. Robinson and Douglas B. Clark
Hydrol. Earth Syst. Sci., 24, 1763–1779,Short summary
This study used a water balance approach based on GRACE total water storage to infer the amount of cold-season precipitation in four Arctic river basins. This was used to evaluate four gridded meteorological data sets, which were used as inputs to a land surface model. We found that the cold-season precipitation in these data sets needed to be increased by up to 55 %. Using these higher precipitation inputs improved the model representation of Arctic hydrology, particularly lying snow.
Abbas Fayad and Simon Gascoin
Hydrol. Earth Syst. Sci., 24, 1527–1542,Short summary
Seasonal snowpack is an essential water resource in Mediterranean mountains. Here, we look at the role of water percolation in simulating snow mass (SWE), for the first time, in Mount Lebanon. We use SnowModel, a distributed snow model, forced by station data. The main sources of uncertainty were attributed to rain–snow partitioning, transient winter snowmelt, and the subpixel snow cover. Yet, we show that a process-based model is suitable to simulate wet snowpack in Mediterranean mountains.
Joel Fiddes, Kristoffer Aalstad, and Sebastian Westermann
Hydrol. Earth Syst. Sci., 23, 4717–4736,Short summary
In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.
Keith S. Jennings and Noah P. Molotch
Hydrol. Earth Syst. Sci., 23, 3765–3786,Short summary
There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix of the two. Here we show that method choice introduces marked uncertainty to simulated snowpack water storage (> 200 mm) and snow cover duration (> 1 month) in areas that receive significant winter and spring precipitation at air temperatures at and near freezing. This marked uncertainty has implications for water resources management as well as simulations of past and future hydroclimatic states.
Maria Andrianaki, Juna Shrestha, Florian Kobierska, Nikolaos P. Nikolaidis, and Stefano M. Bernasconi
Hydrol. Earth Syst. Sci., 23, 3219–3232,Short summary
We tested the performance of the SWAT hydrological model after being transferred from a small Alpine watershed to a greater area. We found that the performance of the model for the greater catchment was satisfactory and the climate change simulations gave insights into the impact of climate change on our site. Assessment tests are important in identifying the strengths and weaknesses of the models when they are applied under extreme conditions different to the ones that were calibrated.
Wenfeng Huang, Bin Cheng, Jinrong Zhang, Zheng Zhang, Timo Vihma, Zhijun Li, and Fujun Niu
Hydrol. Earth Syst. Sci., 23, 2173–2186,Short summary
Up to now, little has been known on ice thermodynamics and lake–atmosphere interaction over the Tibetan Plateau during ice-covered seasons due to a lack of field data. Here, model experiments on ice thermodynamics were conducted in a shallow lake using HIGHTSI. Water–ice heat flux was a major source of uncertainty for lake ice thickness. Heat and mass budgets were estimated within the vertical air–ice–water system. Strong ice sublimation occurred and was responsible for water loss during winter.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
Hydrol. Earth Syst. Sci., 23, 1–17,Short summary
As snow cover becomes patchy during snowmelt, energy is advected from warm snow-free surfaces to cold snow-covered surfaces. This paper proposes a simple sensible and latent heat advection model for snowmelt situations that can be coupled to one-dimensional energy balance snowmelt models. The model demonstrates that sensible and latent heat advection fluxes can compensate for one another, especially in early melt periods.
Michael L. Follum, Jeffrey D. Niemann, Julie T. Parno, and Charles W. Downer
Hydrol. Earth Syst. Sci., 22, 2669–2688,Short summary
Spatial patterns of snow and frozen ground within watersheds can impact the volume and timing of runoff. Commonly used snow and frozen ground simulation methods were modified to better account for the effects of topography and land cover on the spatial patterns of snow and frozen ground. When tested using a watershed in Vermont the modifications resulted in more accurate temporal and spatial simulation of both snow and frozen ground.
Jan Seibert, Marc J. P. Vis, Irene Kohn, Markus Weiler, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 2211–2224,Short summary
In many glacio-hydrological models glacier areas are assumed to be constant over time, which is a crucial limitation. Here we describe a novel approach to translate mass balances as simulated by the (glacio)hydrological model into glacier area changes. We combined the Δh approach of Huss et al. (2010) with the bucket-type model HBV and introduced a lookup table approach, which also allows periods with advancing glaciers to be represented, which is not possible with the original Huss method.
Florian Hanzer, Kristian Förster, Johanna Nemec, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 22, 1593–1614,Short summary
Climate change effects on snow, glaciers, and hydrology are investigated for the Ötztal Alps region (Austria) using a hydroclimatological model driven by climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios. The results show declining snow amounts and strongly retreating glaciers with moderate effects on catchment runoff until the mid-21st century, whereas annual runoff volumes decrease strongly towards the end of the century.
Muhammad Fraz Ismail and Wolfgang Bogacki
Hydrol. Earth Syst. Sci., 22, 1391–1409,
Marit Van Tiel, Adriaan J. Teuling, Niko Wanders, Marc J. P. Vis, Kerstin Stahl, and Anne F. Van Loon
Hydrol. Earth Syst. Sci., 22, 463–485,Short summary
Glaciers are important hydrological reservoirs. Short-term variability in glacier melt and also glacier retreat can cause droughts in streamflow. In this study, we analyse the effect of glacier changes and different drought threshold approaches on future projections of streamflow droughts in glacierised catchments. We show that these different methodological options result in different drought projections and that these options can be used to study different aspects of streamflow droughts.
Felix N. Matt, John F. Burkhart, and Joni-Pekka Pietikäinen
Hydrol. Earth Syst. Sci., 22, 179–201,Short summary
Certain particles that have the ability to absorb sunlight deposit onto mountain snow via atmospheric transport mechanisms and then lower the snow's ability to reflect sunlight, which increases snowmelt. Herein we present a model aiming to simulate this effect and model the impacts on the streamflow of a southern Norwegian river. We find a significant difference in streamflow between simulations with and without the effect of light absorbing particles applied, in particular during spring melt.
Hiroyuki Hirashima, Francesco Avanzi, and Satoru Yamaguchi
Hydrol. Earth Syst. Sci., 21, 5503–5515,Short summary
We reproduced the formation of capillary barriers and the development of preferential flow through snow using a multi-dimensional water transport model, which was then validated using laboratory experiments of liquid water infiltration into layered, initially dry snow. Simulation results showed that the model reconstructs some relevant features of capillary barriers and the timing of liquid water arrival at the snow base.
Claudio Bravo, Thomas Loriaux, Andrés Rivera, and Ben W. Brock
Hydrol. Earth Syst. Sci., 21, 3249–3266,Short summary
We present an analysis of meteorological conditions and melt for Universidad Glacier in central Chile. This glacier is characterized by high melt rates over the ablation season, representing a mean contribution of between 10 and 13 % of the total runoff observed in the upper Tinguiririca Basin during the November 2009 to March 2010 period. Few studies have quantified the glacier melt contribution to river runoff in Chile, and this work represents a new precedent for the Andes.
Sebastian Würzer, Nander Wever, Roman Juras, Michael Lehning, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 1741–1756,Short summary
We discuss a dual-domain water transport model in a physics-based snowpack model to account for preferential flow (PF) in addition to matrix flow. So far no operationally used snow model has explicitly accounted for PF. The new approach is compared to existing water transport models and validated against in situ data from sprinkling and natural rain-on-snow (ROS) events. Our work demonstrates the benefit of considering PF in modelling hourly snowpack runoff, especially during ROS conditions.
Kelly E. Gleason, Anne W. Nolin, and Travis R. Roth
Hydrol. Earth Syst. Sci., 21, 1137–1147,Short summary
We present a coupled modeling approach used to objectively identify representative snow-monitoring locations in a forested watershed in the western Oregon Cascades mountain range. The resultant Forest Elevational Snow Transect (ForEST) represents combinations of forested and open land cover types at low, mid-, and high elevations.
Rafael Pimentel, Javier Herrero, and María José Polo
Hydrol. Earth Syst. Sci., 21, 805–820,Short summary
This study analyses the subgrid variability of the snow distribution in a Mediterranean region and formulates a parametric approach that includes these scale effects in the physical modelling of snow by means of accumulation–depletion curves associated with snow evolution patterns, by means of terrestrial photography. The results confirm that the use of these on a cell scale provides a solid foundation for the extension of point snow models to larger areas.
Nena Griessinger, Jan Seibert, Jan Magnusson, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 3895–3905,Short summary
In Alpine catchments, snowmelt is a major contribution to runoff. In this study, we address the question of whether the performance of a hydrological model can be enhanced by integrating data from an external snow monitoring system. To this end, a hydrological model was driven with snowmelt input from snow models of different complexities. Best performance was obtained with a snow model, which utilized data assimilation, in particular for catchments at higher elevations and for snow-rich years.
Jacob C. Yde, Niels T. Knudsen, Jørgen P. Steffensen, Jonathan L. Carrivick, Bent Hasholt, Thomas Ingeman-Nielsen, Christian Kronborg, Nicolaj K. Larsen, Sebastian H. Mernild, Hans Oerter, David H. Roberts, and Andrew J. Russell
Hydrol. Earth Syst. Sci., 20, 1197–1210,
E. Cornwell, N. P. Molotch, and J. McPhee
Hydrol. Earth Syst. Sci., 20, 411–430,Short summary
We present a high-resolution snow water equivalent estimation for the 2001–2014 period over the extratropical Andes Cordillera of Argentina and Chile, the first of its type. The effect of elevation on accumulation is confirmed, although this is less marked in the northern portion of the domain. The 3000–4000 m a.s.l. elevation band contributes the bulk of snowmelt, but the 4000–5000 m a.s.l. band is a significant source and deserves further monitoring and research.
S. Frey and H. Holzmann
Hydrol. Earth Syst. Sci., 19, 4517–4530,Short summary
Temperature index melt models often lead to snow accumulation in high mountainous elevations. We developed a simple conceptual snow redistribution model working on a commonly used grid cell size of 1x1km. That model is integrated in the hydrological rainfall runoff model COSERO. Applying the model to the catchment of Oetztaler Ache, Austria, could prevent the accumulation of snow in the upper altitudes and lead to an improved model efficiency regarding discharge and snow coverage (MODIS).
Z. H. He, F. Q. Tian, H. V. Gupta, H. C. Hu, and H. P. Hu
Hydrol. Earth Syst. Sci., 19, 1807–1826,
S. J. Marshall
Hydrol. Earth Syst. Sci., 18, 5181–5200,Short summary
This paper presents a new 12-year glacier meteorological, mass balance, and run-off record from the Canadian Rocky Mountains. This provides insight into the glaciohydrological regime of the Rockies. For the period 2002-2013, about 60% of glacier meltwater run-off originated from seasonal snow and 40% was derived from glacier ice and firn. Ice and firn run-off is concentrated in the months of August and September, at which time it contributes significantly to regional-scale water resources.
J. You, D. G. Tarboton, and C. H. Luce
Hydrol. Earth Syst. Sci., 18, 5061–5076,Short summary
This paper evaluates three improvements to an energy balance snowmelt model aimed to represent snow surface temperature while retaining the parsimony of a single layer. Surface heat flow is modeled using a forcing term related to the vertical temperature difference and a restore term related to the temporal gradient of surface temperature. Adjustments for melt water refreezing and thermal conductivity when the snow is shallow are introduced. The model performs well at the three test sites.
Z. H. He, J. Parajka, F. Q. Tian, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 4773–4789,Short summary
In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Snow density is estimated as the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. DDFS values are estimated as the ratio between changes in the snow water equivalent and difference between the daily temperature and a threshold value for days with snowmelt.
K. Förster, G. Meon, T. Marke, and U. Strasser
Hydrol. Earth Syst. Sci., 18, 4703–4720,Short summary
Four snow models of different complexity (temperature-index vs. energy balance models) are compared using observed and dynamically downscaled atmospheric analysis data as input. Biases in simulated precipitation lead to lower model performance. However, simulated meteorological conditions are proven to be a valuable meteorological data source as they provide model input in regions with limited availability of observations and allow the application of energy balance approaches.
N. Wever, T. Jonas, C. Fierz, and M. Lehning
Hydrol. Earth Syst. Sci., 18, 4657–4669,Short summary
We simulated a severe rain-on-snow event in the Swiss Alps in October 2011 with a detailed multi-layer snow cover model. We found a strong modulating effect of the incoming rainfall signal by the snow cover. Initially, water from both rainfall and snow melt was absorbed by the snowpack. But once the snowpack released the stored water, simulated outflow rates exceeded rainfall and snow melt rates. The simulations suggest that structural snowpack changes enhanced the outflow during this event.
K. Fujita and A. Sakai
Hydrol. Earth Syst. Sci., 18, 2679–2694,
D. Freudiger, I. Kohn, K. Stahl, and M. Weiler
Hydrol. Earth Syst. Sci., 18, 2695–2709,
C. Fu, I. Popescu, C. Wang, A. E. Mynett, and F. Zhang
Hydrol. Earth Syst. Sci., 18, 1225–1237,
M. Shrestha, L. Wang, T. Koike, H. Tsutsui, Y. Xue, and Y. Hirabayashi
Hydrol. Earth Syst. Sci., 18, 747–761,
G. A. Artan, J. P. Verdin, and R. Lietzow
Hydrol. Earth Syst. Sci., 17, 5127–5139,
M. Ménégoz, H. Gallée, and H. W. Jacobi
Hydrol. Earth Syst. Sci., 17, 3921–3936,
A. F. Lutz, W. W. Immerzeel, A. Gobiet, F. Pellicciotti, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 17, 3661–3677,
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021,
E. A. Sproles, A. W. Nolin, K. Rittger, and T. H. Painter
Hydrol. Earth Syst. Sci., 17, 2581–2597,
Andreadis, K. M. and Lettenmaier, D. P.: Implications of representing snowpack stratigraphy for the assimilation of passive microwave satellite observations, J. Hydrometeorology, 13, 1493–1506, https://doi.org/10.1175/JHM-D-11-056.1, 2012.
Arakawa, A.: Adjustment mechanisms in atmospheric motions, J. Meteor. Soc. Japan, Special issue of collected papers, 75, 155–179, 1997.
Arulampalam, M. S., Maskell, S., Gordon, N., and Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE T. Signal Proces., 50, 174–188, 2002.
Brankart, J.-M., E. Cosme, C.-E. Testut, P. Brasseur, and J. Verron: Efficient Adaptive Error Parameterizations for Square Root or Ensemble Kalman Filters: Application to the Control of Ocean Mesoscale Signals, Mon. Weather Rev., 138, 932–950, 2010.
Brown, R. and Tapsoba, D.: Improved mapping of snow water equivalent over Quebec, 64th Eastern Snow Conference, St. John's, Newfoundland, Canada, 2007.
Brown, R. D., Brasnett, B., and Robinson, D.: Gridded North American monthly snow depth and snow water equivalent for GCM evaluation, Atmos. Ocean, 41, 1–14, https://doi.org/10.3137/ao.410101, 2003.
Brown, R., Tapsoba, D., and Derksen, C.: Evaluation of snow water equivalent datasets over the Saint-Maurice river basin region of southern Québec, Hydrol. Process., 32, 2748–2764, https://doi.org/10.1002/hyp.13221, 2018.
Brucker, L., Royer, A., Picard, G., Langlois, A., and Fily, M.: Hourly simulations of the microwave brightness temperature of seasonal snow in Quebec, Canada, using a coupled snow evolution-emission model, Remote Sens. Environ., 115, 1966–1977, 2011.
Brun, E., Martin, E., Simon, V., Gendre, C., and Coleou, C.: An energy and mass model of snow cover suitable for operational avalanche forecasting, J. Glaciol., 35, 333–342, 1989.
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, 1992.
Carmagnola, C. M., Morin, S., Lafaysse, M., Domine, F., Lesaffre, B., Lejeune, Y., Picard, G., and Arnaud, L.: Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model, The Cryosphere, 8, 417–437, https://doi.org/10.5194/tc-8-417-2014, 2014.
Cavalieri, D. J., Gloersen, P., and Campbell, W. J.: Determination of sea ice parameters with the Nimbus 7 SMMR, J. Geophys. Res., 89, 5355–5369, 1984.
Chang, A. T. C., Foster, J. L., and Hall, D. K.: Nimbus-7 derived global snow cover parameters, Ann. Glaciol., 9, 39–44, 1987.
Chang, A. T. C., Foster, J. L., and Hall, D. K.: Effects of forest on the snow parameters derived from microwave measurements during the BOREAS winter field campaign, Hydrol. Process., 10, 1565–1574, 1996.
Charrois, L., Cosme, E., Dumont, M., Lafaysse, M., Morin, S., Libois, Q., and Picard, G.: On the assimilation of optical reflectances and snow depth observations into a detailed snowpack model, The Cryosphere, 10, 1021–1038, https://doi.org/10.5194/tc-10-1021-2016, 2016.
Choquette, Y., Lavigne, P., Nadeau, M., Ducharme, P., Martin, J. P., Houdayer, A., and Rogoza, J.: GMON, a new sensor for snow water equivalent via gamma monitoring, Proceedings Whistler 2008 International Snow Science Workshop, 21–27 September 2008, Whistler, B. C., 2008.
Côté, J., Gravel, S., Méthot, A., Patoine, A., Roch, M., and Staniforth, A.: The operational CMC-MRB Global Environmental Multiscale model: Part I – Design considerations and formulation, Mon. Weather Rev., 126, 1373–1395, 1998.
DeChant, C. and Moradkhani, H.: Radiance data assimilation for operational snow and streamflow forecasting, Adv. Water Res., 34, 351–364, 2011.
Decharme, B., Boone, A., Delire, C., and Noilhan, J.: Local evaluation of the Interaction between Soil Bio- sphere Atmosphere soil multilayer diffusion scheme using four pedotransfer functions, J. Geophys. Res., 116, D20, https://doi.org/10.1029/2011JD016002, 2011.
Dee, D. P.: On-line Estimation of Error Covariance Parameters for Atmospheric Data Assimilation, Mon. Weather Rev., 123, 1128–1145, 1995.
De Lannoy, G. J. M., Reichle, R., Houser, P., Arsenault, K., Verhoest, N., and Pauwels, V.: Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model, J. Hydrometeorol., 11, 352–369, https://doi.org/10.1175/2009JHM1192.1, 2010.
De Lannoy, G. J. M., Reichle, R. H., Arsenault, K. R., Houser, P. R., Kumar, S., Verhoest, N. E. C., and Pauwels, V. R. N.: Multiscale assimilation of AMSR-E snow water equivalent and MODIS snow cover fraction observations in northern Colorado, Water Resour. Res., 48, W01522, https://doi.org/10.1029/2011WR010588, 2012.
De Sève, D., Bernier, M., Fortin, J. P., and Walker, A. E.: Preliminary analysis of the snow microwave radiometry using SSM/I passive microwave data: The case of the La Grande River watershed (Québec), Ann. Glaciol., 25, 353–361, 1997.
De Sève, D., Bernier, M., Fortin, J. P., and Walker, A.: Spatio-temporal analysis of microwave radiometry of snow cover with SSM/I data in a taïga area, Eastern Snow Conference, Fredericton, Canada, 200–205, 1999.
De Sève, D., Evora, N. D., and Tapsoba, D.: Comparison of three algorithms for estimating Snow Water Equivalent (SWE) over the La Grande River watershed using SSM/I data in the context of Hydro-Québec's hydraulic power management, Int. Geosci. Remote Se., IGARSS 23–28 July 2007, https://doi.org/10.1109/IGARSS.2007.4423791, 2007.
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.
Derksen, C., Lemmetyinen, J., Toose, P., Silis, A., Pulliainen, J., and Sturm, M.: Physical properties of Arctic versus subarctic snow: Implications for high latitude passive microwave snow water equivalent retrievals, J. Geophys. Res.-Atmos., 119, 7254–7270, 2014.
Dobson, M. C., Ulaby, F. T., Hallikainen, M. T., and El-Rayes, M. A.: Microwave dielectric behavior of wet soil-part II: dielectric miximg models, IEEE T. Geosci. Remote, 1, 35–46, 1985.
Dolant, C., Langlois, A., Montpetit, B., Brucker, L., Roy, A., and Royer, A.: Development of a rain-on-snow detection algorithm using passive microwave radiometry, Hydrol. Process., 30, 3184–3196, https://doi.org/10.1002/hyp.10828, 2016.
Ducharme, P.: Estimation de l'équivalent en eau du couvert nival (Plan de projet étape 3), Technical report, Plate-forme Production, Hydro-Québec publication, Varennes, QC, Canada, 2003.
Durand, M. and Margulis, S.: Feasibility test of multi-frequency radiometric data assimilation to estimate snow water equivalent, J. Hydrometeorol., 7, 443–457, 2006.
Durand, M. and Margulis, S. A.: Correcting first-order errors in snow water equivalent estimates using a multifrequency, multiscale radiometric data assimilation scheme, J. Geophys. Res., 112, D13121, https://doi.org/10.1029/2006JD008067, 2007.
Durand, M., Kim, E. J., and Margulis, S. A.: Radiance assimilation shows promise for snowpack characterization, Geophys. Res. Lett., 36, L02503, https://doi.org/10.1029/2008GL035214, 2009.
Durand, M., Kim, E., Margulis, S., and Molotch, N.: A first-order characterization of errors from neglecting stratigraphy in forward and inverse passive microwave modeling of snow, IEEE Geosci. Remote Se., 8, 730–734, 2011.
Dutra, E., Kotlarski, S., Viterbo, P., Balsamo, G., Miranda, P. M. A., Schär, C., Bissolli, P., and Jonas, T.: Snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing in a land surface model, J. Geophys. Res., 116, D21109, https://doi.org/10.1029/2011JD016061, 2011.
Foster, J., Sun, C., Walker, J., Kelly, R., Chang, A., Dong, J., and Powell, H.: Quantifying the uncertainty in passive microwave snow water equivalent observations, Remote Sens. Environ., 94, 187–203, 2005.
Franklin, S. E.: Terrain analysis from digital patterns in geomorphometry and Landsat MSS spectral response, Photogramm. Eng. Rem. S., 53, 59–65, 1987.
Gordon, N. J., Salmond, D. J., and Smith, A. F.: Novel approach to nonlinear/non-Gaussian Bayesian state estimation, IEEE Proc.-F, 140, 107–113, 1993.
Grant, J. P., Saleh, K., Wigneron, J.-P., Guglielmetti, M., Kerr, Y. H., Schwank, M., Skou, N., and Van de Griend, A.: Calibrationof the L-MEB model over a coniferous and a deciduous forest, IEEE Trans. Geosci. Remote Sens., 46, 808–818, https://doi.org/10.1109/TGRS.2007.914801, 2008.
Grant, A., Van de Griend, A., Schwank, M., and Wigneron, J.-P.: Observations and modeling of a pine forest floor at L-band, IEEE T. Geosci. Remote, 47, 2024–2034, https://doi.org/10.1109/TGRS.2008.2010252, 2009.
Hallikainen, M.: Retrieval of Snow Water Equivalent from Nimbus-7 SMMR Data: Effect of Land-Cover Categories and Weather Conditions, IEEE J. Oceanic Eng., OE-9, 372–376, https://doi.org/10.1109/JOE.1984.1145656, 1984.
Imaoka, K., Kachi, M., Kasahara, M., Nakagawa, K., and Oki, T.: Instrument performance and calibration of AMSR-E and AMSR2, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, ISPRS, Kyoto, Japan, 2010.
Jordan, R. E.: A one-dimensional temperature model for a snow cover: Technical documentation for SNTHERM.89, Special Rep. 91-16, U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH, 49 pp., 1991.
Kelly, R., Chang, A. T. C., Tsang, L., and Foster, J.: A prototypeAMSR-E global snowarea and snow depth algorithm, IEEE Trans. Geosci. Rem. Sens, 41, 23, 2003.
Kelly, R., Chang, A. T. C., Tsang, L., and Foster, J.: A prototype AMSR-E global snow area and snow depth algorithm, IEEE T. Gesoci. Remote, 41, 230–242, 2010.
Klehmet, K., Geyer, B., and Rockel, B.: A regional climate model hindcast for Siberia: analysis of snow water equivalent, The Cryosphere, 7, 1017–1034, https://doi.org/10.5194/tc-7-1017-2013, 2013.
Koenig, L. S. and Forster, R. R.: Evaluation of passive microwave snow water equivalent algorithms in the depth-hoar dominated snowpack of the Kuparuk River Watershed, Alaska, USA, Remote Sens. Environ., 93, 511–527, 2004.
Kwon, Y., Yang, Z.-L., Zhao, L., Hoar, T. J., Toure, A. M., and Rodell, M.: Estimating snow water storage in North America using CLM4, DART, and snow radiance data assimilation, J. Hydrometeorol., 17, 2853–2874, 2016.
Kwon, Y., Yang, Z.-L., Hoar, T. J., and Toure, A. M.: Improving the Radiance Assimilation Performance in Estimating Snow Water Storage across Snow and Land-Cover Types in North America, J. Hydrometeorol., 18, 651–668, 2017.
Lafaysse, M., Cluzet, B., Dumont, M., Lejeune, Y., Vionnet, V., and Morin, S.: A multiphysical ensemble system of numerical snow modelling, The Cryosphere, 11, 1173–1198, https://doi.org/10.5194/tc-11-1173-2017, 2017.
Langlois, A., Royer, A., Derksen, C., Montpetit, B., Dupont, F., and Goïta, K.: Coupling of the snow thermodynamic model SNOWPACK with the Microwave Emission Model for Layered Snowpacks (MEMLS) for subarctic and arctic Snow Water Equivalent retrievals, Water Resour. Res., 48, W12524, https://doi.org/10.1029/2012WR012133, 2012.
Langlois, A. et al.: Detection of rain-on-snow (ROS) events and ice layer formation using passive microwave radiometry: a context for Peary caribou habitat in the Canadian Arctic, Remote Sens. Environ., 189, 84–95, https://doi.org/10.1109/TGRS.1982.4307521, 2017.
Larue, F., Royer, A., De Sève, D., Langlois, A., Roy, A., and Brucker, L.: Validation of GlobSnow-2 snow water equivalent over Eastern Canada, Remote Sens. Environ., 194, 264–277, https://doi.org/10.1016/j.rse.2017.03.027, 2017.
Larue, F., Royer, A., De Sève, D., Roy, A., Picard, G., Vionnet, V., and Cosme, E.: Simulation and assimilation of passive microwave data using a snowpack model coupled to a calibrated radiative transfer model over northeastern Canada, Water Resour. Res., 54, 4823–4848, https://doi.org/10.1029/2017WR022132, 2018.
Lehning, M., Bartelt, P., Brown, R. L., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning; Part III: meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, 2002.
Leppänen, L., Kontu, A., Vehviläinen, J., Lemmetyinen, J., and Pulliainen, J.: Comparison of traditional and optical grain size field measurements with SNOWPACK simulations in a taiga environment, J. Glaciol., 61, 151–162, 2015.
Liebe, H.: MPM – an atmospheric millimeter-wave propagation model, Int. J. Infrared Milli., 10, 631–650, 1989.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Smolander, T., and Derksen, C.: The GlobSnow Snow Water Equivalent Product, 22 July 2014, SnowPEX ISSPI-1, College Park, Maryland, USA, 2014.
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013.
Mätzler, C.: Applications of the interaction of microwaveswith the natural snow cover, Remote Sens. Rev., 2, 259–387, https://doi.org/10.1080/02757258709532086, 1987.
Mätzler, C.: Passive microwave signatures of landscapes in winter, Meteorol. Atmos. Phys., 54, 241–260, 1994.
Mätzler, C., Schanda, E., and Good, W.: Towards the definition of optimum sensor specifications for microwave remote sensing of snow, IEEE T. Geosci. Remote, GE-20, 57–66, 1982.
Meissner, T. and Wentz, F.: Intercalibration of AMSR-E and WINDSAT brightness temperature measurements over land scenes, presented at the 11th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad 2010), 1–4 March 2010, Washington, DC, USA, 2010.
Mo, T., Choudhury, B. J., Schmugge, T. J., Wang, J. R., and Jackson, T. J.: A model for microwave emission from vegetation-covered fields, J. Geophys. Res., 87, 11 229–11 237, 1982.
Molotch, N. P. and Bales, R. C.: Scaling snow observations from the point to the grid element: Implications for observation network design, Water Resour. Res., 41, W11421, https://doi.org/10.1029/2005WR004229, 2005.
Montpetit, B., Royer, A., Roy, A., Langlois, A., 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, 51, 4705–4717, https://doi.org/10.1109/TGRS.2013.2250509, 2013.
Montpetit, B., Royer, A., Roy, A., and Langlois, A.: In-situ passive microwave parameterization of sub-arctic frozen organic soils, Remote Sens. Environ., 205, 112–118, 2018.
Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J. L., Glassy, J., Tian, Y., Wang, Y., Song, X., Zhang, Y., Smith, G. R., Lotsch, A., Friedl, M., Morisette, J. T., Votava, P., Nemani, R. R., and Running, S. W.: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data, Remote Sens. Environ., 83, 214–231, 2002.
Miyoshi, T.: The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter, Mon. Weather Rev., 139, 1519–1535, 2011.
Pampaloni, P. and Paloscia, S.: Microwave emission and plant water content: A comparison between field measurements and theory, IEEE T. Geosci. Remote, GE-24, 900–905, https://doi.org/10.1109/TGRS.1986.289705, 1986.
Pellarin, T., Kerr, Y. H., and Wigneron, J. P.: Global simulation of brightness temperatures at 6.6 and 10.7 GHz over land based on SMMR data set analysis, IEEE T. Geosci. Remote, 44, 2492–2505, 2006.
Picard, G., Brucker, L., Roy, A., Dupont, F., Fily, M., Royer, A., and Harlow, C.: Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model, Geosci. Model Dev., 6, 1061–1078, https://doi.org/10.5194/gmd-6-1061-2013, 2013.
Pietroniro, A. and Leconte, R.: A review of Canadian Remote Sensing and Hydrology 1999–2003, Hydrol. Process., 19, 285–301, 2005.
Pulliainen, J. T., Grandel, J., and Hallikainen, M. T.: HUT snow emission model and its applicability to snow water equivalent retrieval, IEEE T. Geosci. Remote, 37, 1378—1390, 1999.
Quéno, L., Vionnet, V., Dombrowski-Etchevers, I., Lafaysse, M., Dumont, M., and Karbou, F.: Snowpack modelling in the Pyrenees driven by kilometric-resolution meteorological forecasts, The Cryosphere, 10, 1571–1589, https://doi.org/10.5194/tc-10-1571-2016, 2016.
Raleigh, M. S., Lundquist, J. D., and Clark, M. P.: Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework, Hydrol. Earth Syst. Sci., 19, 3153–3179, https://doi.org/10.5194/hess-19-3153-2015, 2015.
Rott, H., Yueh, S. H., Cline, D. W., Duguay, C., Essery, R., Haas, C., Hélière, F., Kern, M. G., Malnes, E., Nagler, T., Pulliainen, J., Rebhan, H., and Thompson, A.: Cold regions hydrology high-resolution observatory for Snow and Cold Land Processes, Proc. IEEE,, 98, 752–765, https://doi.org/10.1109/JPROC.2009.2038947, 2010.
Roy, A., Royer, A., and Turcotte, R.: Analyse de l'identification de la fonte de neige printanière avec QuickSCAT dans le Sud du Québec, Canada, Can. J. Remote Sens., 36, 89–98, 2010.
Roy, A., Royer, A., Wigneron, J.-P., Langlois, A., Bergeron, J., and Cliche, P.: A simple parameterization for a boreal forest radiative transfer model at microwave frequencies, Remote Sens. Environ., 124, 371–383, 2012.
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., 51, 4692–4704, 2013.
Roy, A., Royer, A., and Hall, R.: Relationship between forest microwave transmissivity and structural parameters for Canadian boreal forest, IEEE Geosci. Remote S., 11, 1802–1806, 2014.
Roy, A., Royer, A., St-Jean-Rondeau, O., Montpetit, B., Picard, G., Mavrovic, A., Marchand, N., and Langlois, A.: Microwave snow emission modeling uncertainties in boreal and subarctic environments, The Cryosphere, 10, 623–638, https://doi.org/10.5194/tc-10-623-2016, 2016.
Royer, A., Roy, A., Montpetit, B., Saint-Jean-Rondeau, O., Picard, G., Brucker, L., and Langlois, A.: Comparison of commonly-used microwave radiative transfer models for snow remote sensing, Remote Sens. Environ., 190, 247–259, 2017.
Sandells, M., Essery, R., Rutter, N., Wake, L., Leppänen, L., and Lemmetyinen, J.: Microstructure representation of snow in coupled snowpack and microwave emission models, The Cryosphere, 11, 229–246, https://doi.org/10.5194/tc-11-229-2017, 2017.
Sun, C., Walker, J. P., and Houser, P. R.: A methodology for snow data assimilation in a land surface model, J. Geophys. Res., 109, D08108, https://doi.org/10.1029/2003JD003765, 2004.
Takala, M., Luojus, K., Pulliainen, J., Derksen, C., Lemmetyinen, J., Kärnä, J.-P., Koskinen, J., and Bojkov, B.: Estimating northern hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements, Remote Sens. Environ., 115, 3517–3529, 2011.
Tapsoba, D., Fortin, V., Anctil, F., Haché, M.: Apport de la technique du krigeage avec dérive externe pour une cartographie raisonnée de l'équivalent en eau de la neige: application aux bassins de la rivière Gatineau, Can. J. Civ. Eng., 32, 289–297, 2005.
Tapsoba, D., Fortin, V., Anctil, F., and Haché, M.: Apport de la technique du krigeage avec dérive externe pour une cartographie raisonnée de l'équivalent en eau de la neige: Application aux bassins de la rivière Gatineau, Can. J. Civil Eng., 32, 289–297, 2009.
Tedesco, M. and Narvekar, P. S.: Assessment of the NASA AMSR-E SWE product, IEEE J. Sel. Top. Appl., 3, 141–159, 2010.
Tedesco, M., Kelly, R., Foster, J. L., and Chang, A. T. C.: AMSR-E/Aqua Daily L3 Global Snow Water Equivalent EASE-Grids, Version 2, NASA National Snow and Ice data center Distributed Active Archive Center, Boulder, Colorado, USA, https://doi.org/10.5067/AMSR-E/AE_DYSNO.002, 2004.
Touré, A., Goïta, K., Royer, A., Kim, E., Durand, M., Margulis, S. A., and Huizhong, Lu: A Case Study of Using a Multi-Layered Thermo-Dynamical Snow Model for Radiance Assimilation, IEEE T. Geosci. Remote, 49, 2828–2837, 2011.
Tsang, L. and Kong, J. A.: Scattering of Electromagnetic Waves, vol. 3, Advanced Topics, Wiley Intersci., Hoboken, N. J., 2001.
Tsang, L., Ding, K. H., and Wen, B.: Dense Media Radiative Transfer Theory for Dense Discrete Random Media with Particles of Multiple Sizes and Permitivities, Pr. Electromagn. Res., 6, 181–230, 1992.
Turcotte, R., Fortier-Filion, T.-C., Fortin, V., Roy, A., and Royer, A.: Simulation hydrologiques des derniers jours de la crue du printemps: le problème de la neige manquante, Hydrolog. Sci. J., 55, 872–882, 2010.
Vachon, F.: Estimation de l'équivalent en eau de la neige en milieu subarctique du Québec par télédétection micro-ondes passives, Mémoire de thèse, Université de Sherbrooke, Sherbrooke, Canada, Mai 2009.
Van Leeuwen, P. J.: Particle filtering in geophysical systems, Mon. Weather Rev., 137, 4089–4114, https://doi.org/10.1175/2009MWR2835.1, 2009.
Van Leeuwen, P. J.: Particle filters for the geosciences, Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012, in: Advanced Data Assimilation for Geosciences, 291–318, https://doi.org/10.1093/acprof:oso/9780198723844.003.0013, 2014.
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.
Wang, N., Liu, C., Ferraro, R., Wolff, D., Zipser, E., and Kummerow, C.: TRMM 2A12 land precipitation product-status and future plans, J. Met. Soc. of Japan, 87, 237–253, 2009.
Wegmüller, U. and Mätzler, C.: Rough bare soil reflectivity model, IEEE T. Geosci. Remote, 37, 1391–1395, 1999.
Xu, X., Li, J., and Tolsonv, B. A.: Progress in integrating remote sensing data and hydrologic modeling, Prog. Phys. Geog., 38, https://doi.org/10.1177/0309133314536583, 2014.
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.
A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by...