Articles | Volume 11, issue 1
https://doi.org/10.5194/tc-11-229-2017
© Author(s) 2017. 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-11-229-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Jan 2017
Research article |
| 27 Jan 2017
Microstructure representation of snow in coupled snowpack and microwave emission models
Melody Sandells
CORRESPONDING AUTHOR
CORES Science and Engineering Limited, Burnopfield, UK
Richard Essery
University of Edinburgh, Edinburgh, UK
Nick Rutter
Northumbria University, Newcastle-upon-Tyne, UK
Leanne Wake
Northumbria University, Newcastle-upon-Tyne, UK
Leena Leppänen
Finnish Meteorological Institute, Arctic Research Centre, Sodankylä, Finland
Juha Lemmetyinen
Finnish Meteorological Institute, Helsinki, Finland
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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
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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.
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
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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.
Ghislain Picard, Melody Sandells, and Henning Löwe
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The Snow Microwave Radiative Transfer (SMRT) is a novel model developed to calculate how microwaves are scattered and emitted by snow. The model is built from separate, interconnecting modules to make it easy to compare different aspects of the theory. SMRT is the first model to allow a choice of how to represent the microstructure of the snow, which is extremely important, and has been used to unite multiple previous studies. This model will ultimately be used to observe snow from space.
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Ice layers in snowpacks introduce uncertainty in satellite-derived estimates of snow water equivalent, have ecological impacts on plants and animals, and change the thermal and vapour transport properties of the snowpack. Here we present a new field method for measuring the density of ice layers. The method was used in the Arctic and mid-latitudes; the mean measured ice layer density was significantly higher than values typically used in the literature.
William Maslanka, Leena Leppänen, Anna Kontu, Mel Sandells, Juha Lemmetyinen, Martin Schneebeli, Martin Proksch, Margret Matzl, Henna-Reetta Hannula, and Robert Gurney
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The paper presents the initial findings of the Arctic Snow Microstructure Experiment in Sodankylä, Finland. The experiment observed the microwave emission of extracted snow slabs on absorbing and reflecting bases. Snow parameters were recorded to simulate the emission upon those bases using two different emission models. The smallest simulation errors were associated with the absorbing base at vertical polarization. The observations will be used for the development of snow emission modelling.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer Baltzer, Christophe Kinnard, and Alexandre Roy
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Snow water equivalent (SWE) is a valuable characteristic of snow cover. In this research, we improve the radiometer-based GlobSnow SWE retrieval methodology by implementing spatially and temporally varying snow densities into the retrieval procedure. In addition to improving the accuracy of SWE retrieval, varying snow densities were found to improve the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product.
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
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Saltmarsh in SE Greenland records sea-level changes over the past 300 years in sediments and microfossils. The pattern is rising sea level until ~1880 CE and small sea-level fall since. This disagrees with modelled sea-level, which over-predicts sea-level fall by at least 0.5 m. This is the same even when allowing more time for and reducing the overall amount of Greenland ice sheet melt. Fitting the model to the data leaves ~2.5 mm/yr of unexplained sea-level rise in SE Greenland since ~1880 CE.
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
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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.
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
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Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
The Cryosphere, 14, 2495–2514, https://doi.org/10.5194/tc-14-2495-2020, https://doi.org/10.5194/tc-14-2495-2020, 2020
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We analyze how well updated state-of-the-art climate models reproduce observed historical snow cover extent and snow mass and how they project that these quantities will change up to the year 2100. Overall the updated models better represent historical snow extent than previous models, and they simulate stronger historical trends in snow extent and snow mass. They project that spring snow extent will decrease by 8 % for each degree Celsius that the global surface air temperature increases.
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.
David M. W. Pritchard, Nathan Forsythe, Greg O'Donnell, Hayley J. Fowler, and Nick Rutter
The Cryosphere, 14, 1225–1244, https://doi.org/10.5194/tc-14-1225-2020, https://doi.org/10.5194/tc-14-1225-2020, 2020
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This study compares different snowpack model configurations applied in the western Himalaya. The results show how even sparse local observations can help to delineate climate input errors from model structure errors, which provides insights into model performance variation. The results also show how interactions between processes affect sensitivities to climate variability in different model configurations, with implications for model selection in climate change projections.
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.
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, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
Short summary
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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.
David Walters, Anthony J. Baran, Ian Boutle, Malcolm Brooks, Paul Earnshaw, John Edwards, Kalli Furtado, Peter Hill, Adrian Lock, James Manners, Cyril Morcrette, Jane Mulcahy, Claudio Sanchez, Chris Smith, Rachel Stratton, Warren Tennant, Lorenzo Tomassini, Kwinten Van Weverberg, Simon Vosper, Martin Willett, Jo Browse, Andrew Bushell, Kenneth Carslaw, Mohit Dalvi, Richard Essery, Nicola Gedney, Steven Hardiman, Ben Johnson, Colin Johnson, Andy Jones, Colin Jones, Graham Mann, Sean Milton, Heather Rumbold, Alistair Sellar, Masashi Ujiie, Michael Whitall, Keith Williams, and Mohamed Zerroukat
Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, https://doi.org/10.5194/gmd-12-1909-2019, 2019
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA7/GL7, which includes new aerosol and snow schemes and addresses the four critical errors identified in GA6. GA7/GL7 will underpin the UK's contributions to CMIP6, and hence their documentation is important.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Ghislain Picard, Melody Sandells, and Henning Löwe
Geosci. Model Dev., 11, 2763–2788, https://doi.org/10.5194/gmd-11-2763-2018, https://doi.org/10.5194/gmd-11-2763-2018, 2018
Short summary
Short summary
The Snow Microwave Radiative Transfer (SMRT) is a novel model developed to calculate how microwaves are scattered and emitted by snow. The model is built from separate, interconnecting modules to make it easy to compare different aspects of the theory. SMRT is the first model to allow a choice of how to represent the microstructure of the snow, which is extremely important, and has been used to unite multiple previous studies. This model will ultimately be used to observe snow from space.
Esteban Alonso-González, J. Ignacio López-Moreno, Simon Gascoin, Matilde García-Valdecasas Ojeda, Alba Sanmiguel-Vallelado, Francisco Navarro-Serrano, Jesús Revuelto, Antonio Ceballos, María Jesús Esteban-Parra, and Richard Essery
Earth Syst. Sci. Data, 10, 303–315, https://doi.org/10.5194/essd-10-303-2018, https://doi.org/10.5194/essd-10-303-2018, 2018
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We present a new daily gridded snow depth and snow water equivalent database over the Iberian Peninsula from 1980 to 2014 structured in common elevation bands. The data have proved their consistency with in situ observations and remote sensing data (MODIS). The presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management.
Tom Watts, Nick Rutter, Peter Toose, Chris Derksen, Melody Sandells, and John Woodward
The Cryosphere, 10, 2069–2074, https://doi.org/10.5194/tc-10-2069-2016, https://doi.org/10.5194/tc-10-2069-2016, 2016
Short summary
Short summary
Ice layers in snowpacks introduce uncertainty in satellite-derived estimates of snow water equivalent, have ecological impacts on plants and animals, and change the thermal and vapour transport properties of the snowpack. Here we present a new field method for measuring the density of ice layers. The method was used in the Arctic and mid-latitudes; the mean measured ice layer density was significantly higher than values typically used in the literature.
Juha Lemmetyinen, Anna Kontu, Jouni Pulliainen, Juho Vehviläinen, Kimmo Rautiainen, Andreas Wiesmann, Christian Mätzler, Charles Werner, Helmut Rott, Thomas Nagler, Martin Schneebeli, Martin Proksch, Dirk Schüttemeyer, Michael Kern, and Malcolm W. J. Davidson
Geosci. Instrum. Method. Data Syst., 5, 403–415, https://doi.org/10.5194/gi-5-403-2016, https://doi.org/10.5194/gi-5-403-2016, 2016
Silvan Leinss, Henning Löwe, Martin Proksch, Juha Lemmetyinen, Andreas Wiesmann, and Irena Hajnsek
The Cryosphere, 10, 1771–1797, https://doi.org/10.5194/tc-10-1771-2016, https://doi.org/10.5194/tc-10-1771-2016, 2016
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Four years of anisotropy measurements of seasonal snow are presented in the paper. The anisotropy was measured every 4 h with a ground-based polarimetric radar. An electromagnetic model has been developed to measured the anisotropy with radar instruments from ground and from space. The anisotropic permittivity was derived with Maxwell–Garnett-type mixing formulas which are shown to be equivalent to series expansions of the permittivity tensor based on spatial correlation function of snow.
Henna-Reetta Hannula, Juha Lemmetyinen, Anna Kontu, Chris Derksen, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 347–363, https://doi.org/10.5194/gi-5-347-2016, https://doi.org/10.5194/gi-5-347-2016, 2016
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The paper described an extensive in situ data set of bulk snow depth, snow water equivalent, and snow density collected as a support of SnowSAR-2 airborne campaign in northern Finland. The spatial and temporal variability of these snow properties was analyzed in different land cover types. The success of the chosen measurement protocol to provide an accurate reference for the simultaneous SAR data products was analyzed in the context of spatial scale, sample size, and uncertainty.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Leena Leppänen, Anna Kontu, Henna-Reetta Hannula, Heidi Sjöblom, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 163–179, https://doi.org/10.5194/gi-5-163-2016, https://doi.org/10.5194/gi-5-163-2016, 2016
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The manual snow survey program of Finnish Meteorological Institute consists of numerous observations of natural seasonal snowpack in Sodankylä, in northern Finland. Systematic snow measurements began in 1911 with snow depth and snow water equivalent. In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from snow pits. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack.
Jaakko Ikonen, Juho Vehviläinen, Kimmo Rautiainen, Tuomo Smolander, Juha Lemmetyinen, Simone Bircher, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, https://doi.org/10.5194/gi-5-95-2016, 2016
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A comprehensive, distributed network of in situ measurement stations gathering information on soil moisture has been set up in recent years at the Finnish Meteorological Institute's (FMI) Sodankylä Arctic research station. The network is used as a tool to evaluate the validity of satellite retrievals of soil properties. We present the soil moisture observation network and the results of comparisons of top layer soil moisture between 2012 and 2014 against ESA CCI product soil moisture retrievals.
William Maslanka, Leena Leppänen, Anna Kontu, Mel Sandells, Juha Lemmetyinen, Martin Schneebeli, Martin Proksch, Margret Matzl, Henna-Reetta Hannula, and Robert Gurney
Geosci. Instrum. Method. Data Syst., 5, 85–94, https://doi.org/10.5194/gi-5-85-2016, https://doi.org/10.5194/gi-5-85-2016, 2016
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The paper presents the initial findings of the Arctic Snow Microstructure Experiment in Sodankylä, Finland. The experiment observed the microwave emission of extracted snow slabs on absorbing and reflecting bases. Snow parameters were recorded to simulate the emission upon those bases using two different emission models. The smallest simulation errors were associated with the absorbing base at vertical polarization. The observations will be used for the development of snow emission modelling.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
Martin Proksch, Nick Rutter, Charles Fierz, and Martin Schneebeli
The Cryosphere, 10, 371–384, https://doi.org/10.5194/tc-10-371-2016, https://doi.org/10.5194/tc-10-371-2016, 2016
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Density is a fundamental property of porous media such as snow. During the MicroSnow Davos 2014 workshop, different approaches (box-, wedge- and cylinder-type density cutters, micro-computed tomography) to measure snow density were applied in a controlled laboratory environment and in the field. In general, results suggest that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably.
R. Essery
Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, https://doi.org/10.5194/gmd-8-3867-2015, 2015
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Models of snow on the ground need to represent processes of solar radiation absorption, heat conduction, liquid water movement and compaction in snow and transfers of heat from the atmosphere. There are many such models in use, but their wide range in complexity makes it hard to understand how differences in process representations determine differences in predictions. Processes in the factorial snow model can be switched on or off independently, allowing highly controlled numerical experiments.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
E. Collier, L. I. Nicholson, B. W. Brock, F. Maussion, R. Essery, and A. B. G. Bush
The Cryosphere, 8, 1429–1444, https://doi.org/10.5194/tc-8-1429-2014, https://doi.org/10.5194/tc-8-1429-2014, 2014
C. B. Ménard, R. Essery, and J. Pomeroy
Hydrol. Earth Syst. Sci., 18, 2375–2392, https://doi.org/10.5194/hess-18-2375-2014, https://doi.org/10.5194/hess-18-2375-2014, 2014
Related subject area
Seasonal Snow
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
Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models
Properties of black carbon and other insoluble light-absorbing particles in seasonal snow of northwestern China
In situ continuous visible and near-infrared spectroscopy of an alpine snowpack
Eurasian snow depth in long-term climate reanalyses
Determination of snowmaking efficiency on a ski slope from observations and modelling of snowmaking events and seasonal snow accumulation
Distributed snow and rock temperature modelling in steep rock walls using Alpine3D
How much can we save? Impact of different emission scenarios on future snow cover in the Alps
Future snow? A spatial-probabilistic assessment of the extraordinarily low snowpacks of 2014 and 2015 in the Oregon Cascades
Snow fracture in relation to slab avalanche release: critical state for the onset of crack propagation
Evaluation of single-band snow-patch mapping using high-resolution microwave remote sensing: an application in the maritime Antarctic
Relationships between snowfall density and solid hydrometeors, based on measured size and fall speed, for snowpack modeling applications
Simulating ice layer formation under the presence of preferential flow in layered snowpacks
Temporal evolution of crack propagation propensity in snow in relation to slab and weak layer properties
Frequency and distribution of winter melt events from passive microwave satellite data in the pan-Arctic, 1988–2013
Seasonal evolution of the effective thermal conductivity of the snow and the soil in high Arctic herb tundra at Bylot Island, Canada
Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China
Brief communication: Improved measurement of ice layer density in seasonal snowpacks
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.
Silvia Terzago, Jost von Hardenberg, Elisa Palazzi, and Antonello Provenzale
The Cryosphere, 11, 1625–1645, https://doi.org/10.5194/tc-11-1625-2017, https://doi.org/10.5194/tc-11-1625-2017, 2017
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The estimate of the current and future conditions of snow resources in mountain areas depends on the availability of reliable fine-resolution data sets and of climate models capable of properly representing snow processes and snow–climate interactions. This work considers the snow water equivalent data sets from remote sensing, reanalyses, regional and global climate models available for the Alps and explores their ability to provide a coherent view of the snowpack features and its changes.
Wei Pu, Xin Wang, Hailun Wei, Yue Zhou, Jinsen Shi, Zhiyuan Hu, Hongchun Jin, and Quanliang Chen
The Cryosphere, 11, 1213–1233, https://doi.org/10.5194/tc-11-1213-2017, https://doi.org/10.5194/tc-11-1213-2017, 2017
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We conducted a large field campaign to collect snow samples in Xinjiang. We measured insoluble light-absorbing particles with estimated black carbon concentrations of 10–150 ngg-1. We found a probable shift in emission sources with the progression of winter and dominated contributions of BC and OC to light absorption. A PMF model indicated an optimal three-factor/source solution that included industrial pollution, biomass burning, and soil dust.
Marie Dumont, Laurent Arnaud, Ghislain Picard, Quentin Libois, Yves Lejeune, Pierre Nabat, Didier Voisin, and Samuel Morin
The Cryosphere, 11, 1091–1110, https://doi.org/10.5194/tc-11-1091-2017, https://doi.org/10.5194/tc-11-1091-2017, 2017
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Snow spectral albedo in the visible/near-infrared range has been continuously measured during a winter season at Col de Porte alpine site (French Alps; 45.30° N, 5.77°E; 1325 m a.s.l.). This study highlights that the variations of spectral albedo can be successfully explained by variations of the following snow surface variables: snow-specific surface area, effective light-absorbing impurities content, presence of liquid water and slope.
Martin Wegmann, Yvan Orsolini, Emanuel Dutra, Olga Bulygina, Alexander Sterin, and Stefan Brönnimann
The Cryosphere, 11, 923–935, https://doi.org/10.5194/tc-11-923-2017, https://doi.org/10.5194/tc-11-923-2017, 2017
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We investigate long-term climate reanalyses datasets to infer their quality in reproducing snow depth values compared to in situ measured data from meteorological stations that go back to 1900. We found that the long-term reanalyses do a good job in reproducing snow depths but have some questionable snow states early in the 20th century. Thus, with care, climate reanalyses can be a valuable tool to investigate spatial snow evolution in global warming and climate change studies.
Pierre Spandre, Hugues François, Emmanuel Thibert, Samuel Morin, and Emmanuelle George-Marcelpoil
The Cryosphere, 11, 891–909, https://doi.org/10.5194/tc-11-891-2017, https://doi.org/10.5194/tc-11-891-2017, 2017
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The production of machine-made snow is generalized in ski resorts and represents the most common adaptation method to mitigate effects of climate variability and its projected changes. However, the actual snow mass that can be recovered from a given water mass used for snowmaking remains poorly known. All results were consistent with 60 % (±10 %) of the water mass found as snow within the edge of the ski slope, with most of the lost fraction of water being due to site-dependent characteristics.
Anna Haberkorn, Nander Wever, Martin Hoelzle, Marcia Phillips, Robert Kenner, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 585–607, https://doi.org/10.5194/tc-11-585-2017, https://doi.org/10.5194/tc-11-585-2017, 2017
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The effects of permafrost degradation on rock slope stability in the Alps affect people and infrastructure. Modelling the evolution of permafrost is therefore of great importance. However, the snow cover has generally not been taken into account in model studies of steep, rugged rock walls. Thus, we present a distributed model study on the influence of the snow cover on rock temperatures. The promising results are discussed against detailed rock temperature measurements and snow depth data.
Christoph Marty, Sebastian Schlögl, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 517–529, https://doi.org/10.5194/tc-11-517-2017, https://doi.org/10.5194/tc-11-517-2017, 2017
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We simulate the future snow cover in the Alps with the help of a snow model, which is fed by projected temperature and precipitation changes from a large set of climate models. The results demonstrate that snow below 1000 m is probably a rare guest at the end of the century. Moreover, even above 3000 m the simulations show a drastic decrease in snow depth. However, the results reveal that the projected snow cover reduction can be mitigated by 50 % if we manage to keep global warming below 2°.
Eric A. Sproles, Travis R. Roth, and Anne W. Nolin
The Cryosphere, 11, 331–341, https://doi.org/10.5194/tc-11-331-2017, https://doi.org/10.5194/tc-11-331-2017, 2017
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We present an innovative approach to quantify basin-wide snowpack using calculations of spatial exceedance probability. Our method quantifies how the extraordinarily low snowpacks of 2014 and 2015 in the Pacific Northwest of the United States compare to snowpacks in warmer conditions and the probability that similar snowpacks will occur. We present these extraordinarily low snowpacks as snow analogs to develop anticipatory capacity for natural resource management under warmer conditions.
Johan Gaume, Alec van Herwijnen, Guillaume Chambon, Nander Wever, and Jürg Schweizer
The Cryosphere, 11, 217–228, https://doi.org/10.5194/tc-11-217-2017, https://doi.org/10.5194/tc-11-217-2017, 2017
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Based on DEM simulations we developed a new model for the onset of crack propagation in snow slab avalanche release. The model reconciles past approaches by considering the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The model agrees with extensive field data and can reproduce crack propagation on low-angle terrain and the decrease in critical crack length with increasing slope angle observed in numerical experiments.
Carla Mora, Juan Javier Jiménez, Pedro Pina, João Catalão, and Gonçalo Vieira
The Cryosphere, 11, 139–155, https://doi.org/10.5194/tc-11-139-2017, https://doi.org/10.5194/tc-11-139-2017, 2017
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We evaluate the use of high-resolution microwave satellite images from TerraSAR-X for mapping snow-patch distribution in ice-free areas of the maritime Antarctic (King George Island). The imagery was acquired simultaneously to ground truthing of snow. Image classification resulted in very high accuracy when discriminating between snow, water and bare ground. The method provides a solution for characterizing the snowmelt patterns in the ice-free areas of the Antarctic Peninsula.
Masaaki Ishizaka, Hiroki Motoyoshi, Satoru Yamaguchi, Sento Nakai, Toru Shiina, and Ken-ichiro Muramoto
The Cryosphere, 10, 2831–2845, https://doi.org/10.5194/tc-10-2831-2016, https://doi.org/10.5194/tc-10-2831-2016, 2016
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We measured the snowfall densities with a CCD camera, simultaneously observing the predominant snowfall types determined by the measured size and the fall speed. With a CCD camera, we obtain the quantitative relationships between snowfall densities and presumed density derived from the size and mass components. This suggests the possibility of estimating snowfall densities from the measured size and the fall speed data, and using them as the initial densities for a snowpack in a numerical model.
Nander Wever, Sebastian Würzer, Charles Fierz, and Michael Lehning
The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, https://doi.org/10.5194/tc-10-2731-2016, 2016
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The study presents a dual domain approach to simulate liquid water flow in snow using the 1-D physics based snow cover model SNOWPACK. In this approach, the pore space is separated into a part for matrix flow and a part that represents preferential flow. Using this approach, water can percolate sub-freezing snow and form dense (ice) layers. A comparison with snow pits shows that some of the observed ice layers were reproduced by the model while others remain challenging to simulate.
Jürg Schweizer, Benjamin Reuter, Alec van Herwijnen, Bettina Richter, and Johan Gaume
The Cryosphere, 10, 2637–2653, https://doi.org/10.5194/tc-10-2637-2016, https://doi.org/10.5194/tc-10-2637-2016, 2016
Libo Wang, Peter Toose, Ross Brown, and Chris Derksen
The Cryosphere, 10, 2589–2602, https://doi.org/10.5194/tc-10-2589-2016, https://doi.org/10.5194/tc-10-2589-2016, 2016
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The conventional wisdom is that Arctic warming will result in an increase in the frequency of winter melt events. However, results in this study show little evidence of trends in winter melt frequency over 1988–2013 period. The frequency of winter melt events is strongly influenced by the selection of the start and end dates of winter period, and a fixed-window method for analyzing winter melt events is observed to generate false increasing trends from a shift in the timing of snow cover season.
Florent Domine, Mathieu Barrere, and Denis Sarrazin
The Cryosphere, 10, 2573–2588, https://doi.org/10.5194/tc-10-2573-2016, https://doi.org/10.5194/tc-10-2573-2016, 2016
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The thermal conductivity (TC) of the snow and top soil greatly impacts the permafrost energy budget. We report the first winter-long monitoring of snow and soil TC in the high Arctic.
The data and field observations show the formation of a highly insulating basal depth hoar layer overlaid by a more conductive wind slab. Detailed snow physics models developed for alpine snow cannot reproduce observations because they neglect the strong upward vertical water vapor flux prevailing in Arctic snow.
Xiaodong Huang, Jie Deng, Xiaofang Ma, Yunlong Wang, Qisheng Feng, Xiaohua Hao, and Tiangang Liang
The Cryosphere, 10, 2453–2463, https://doi.org/10.5194/tc-10-2453-2016, https://doi.org/10.5194/tc-10-2453-2016, 2016
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Integrated snow products were used to analyze the temporal and spatial variation of the snow cover in China during 2000–2014. The results indicated that the overall annual number of snow-covered days and average snow depth in China have increased in the past 14 years, but differences in the snow cover variation in China were significant. Overall, the snow cover increased significantly in south and northeast China, but decreased significantly in Xinjiang and the Tibetan Plateau.
Tom Watts, Nick Rutter, Peter Toose, Chris Derksen, Melody Sandells, and John Woodward
The Cryosphere, 10, 2069–2074, https://doi.org/10.5194/tc-10-2069-2016, https://doi.org/10.5194/tc-10-2069-2016, 2016
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Ice layers in snowpacks introduce uncertainty in satellite-derived estimates of snow water equivalent, have ecological impacts on plants and animals, and change the thermal and vapour transport properties of the snowpack. Here we present a new field method for measuring the density of ice layers. The method was used in the Arctic and mid-latitudes; the mean measured ice layer density was significantly higher than values typically used in the literature.
Cited articles
Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 29, 872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006.
Andreadis, K. M. and Lettenmaier, D. P.: Implications of Representing Snowpack Stratigraphy for the Assimilation of Passive Microwave Satellite Observations, J. Hydrometeorol., 13, 1493–1506, https://doi.org/10.1175/JHM-D-11-056.1, 2012.
Boyarskii, D. and Tikhonov, V.: The Influence of Stratigraphy On Microwave Radiation From Natural Snow Cover, J. Electromagnet. Wave., 14, 1265–1285, https://doi.org/10.1163/156939300X01201, 2000.
Brown, R., Derksen, C., and Wang, L.: A multi-data set analysis of variability and change in Arctic spring snow cover extent, 1967–2008, J. Geophys. Res., 115, D16111, https://doi.org/10.1029/2010JD013975, 2010.
Brown, R. D. and Robinson, D. A.: Northern Hemisphere spring snow cover variability and change over 1922–2010 including an assessment of uncertainty, The Cryosphere, 5, 219–229, https://doi.org/10.5194/tc-5-219-2011, 2011.
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, https://doi.org/10.1016/j.rse.2011.03.019, 2011.
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.
Chang, A. T. C., Gloersen, P., Schmugge, T., Wilheit, T. T., and Zwally, H. J.: Microwave emission from snow and glacier ice, J. Glaciol., 16, 23–39, 1976.
Chang, A. T. C., Foster, J. L., and Hall, D. K.: Nimbus-7 SMMR Derived Global Snow Cover Parameters, Ann. Glaciol., 9, 39–44, 1987.
Clifford, D.: Global estimates of snow water equivalent from passive microwave instruments: history, challenges and future developments, Int. J. Remote Sens., 31, 3707–3726, https://doi.org/10.1080/01431161.2010.483482, 2010.
Davenport, I., Sandells, M., and Gurney, R.: The effects of variation in snow properties on passive microwave snow mass estimation, Remote Sens. Environ., 118, 168–175, https://doi.org/10.1016/j.rse.2011.11.014, 2012.
Derksen, C. and Brown, R.: Spring snow cover extent reductions in the 2008–2012 period exceeding climate model projections, Geophys. Res. Lett., 39, L19504, https://doi.org/10.1029/2012GL053387, 2012.
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, https://doi.org/10.1016/j.rse.2011.09.021, 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, https://doi.org/10.1002/2013JD021264, 2014.
Du, J., Shi, J., and Wu, S.: A comparison of a second-order snow model with field observations, in: Geoscience and Remote Sensing Symposium, 2005, IGARSS '05, Proceedings, 2005 IEEE International, 4, p. 2649, 2005.
Durand, M., Kim, E., 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, https://doi.org/10.1109/TGRS.2008.916221, 2008.
Eom, H. J., Lee, K. K., and Fung, A. K.: Microwave emission from an irregular snow layer, Remote Sens. Environ. 13, 423–437, https://doi.org/10.1016/0034-4257(83)90011-1, 1983.
Essery, R.: A factorial snowpack model (FSM 1.0), Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, 2015.
Essery, R., Best, M., and Cox, P.: MOSES 2.2 Technical Documentation, Tech. rep., Hadley Centre, Met Office, UK, Hadley Centre technical note 30, 31 pp., 2001.
Essery, R., Morin, S., Lejeune, Y., and Ménard, C. B.: A comparison of 1701 snow models using observations from an alpine site, Adv. Water Res., 55, 131–148, 2013.
Essery, R., Kontu, A., Lemmetyinen, J., Dumont, M., and Ménard, C. B.: A 7-year dataset for driving and evaluating snow models at an Arctic site (Sodankylä, Finland), Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, 2016.
Flanner, M. G. and Zender, C. S.: Linking snowpack microphysics and albedo evolution, J. Geophys. Res., 111, D12208, https://doi.org/10.1029/2005JD006834, 2006.
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.
Hallikainen, M., Ulaby, F., and Van Deventer, T.: Extinction Behavior of Dry Snow in the 18-to 90- GHz Range, IEEE T. Geosci. Remote, GE-25, 737–745, https://doi.org/10.1109/TGRS.1987.289743, 1987.
Hancock, S., Baxter, R., Evans, J., and Huntley, B.: Evaluating global snow water equivalent products for testing land surface models, Remote Sens. Environ., 128, 107–117, 2013.
Jin, Y.-Q.: Simulation of a multi-layer model of dense scatterers for anomalous scattering signatures from SSM/I snow data, Int. J. Remote Sens., 18, 2531–2538, https://doi.org/10.1080/014311697217459, 1997.
Jordan, R.: A One-Dimensional Temperature Model for a Snow Cover: Technical Documentation for SNTHERM.89, Cold Regions Research and Engineering Laboratory (U.S.), Engineer Research and Development Center (U.S.), Special Report 91-16, 1991.
Kelly, R.: The AMSR-E Snow Depth Algorithm: Description and Initial Results, Journal of The Remote Sensing Society of Japan, 29, 307–317, https://doi.org/10.11440/rssj.29.307, 2009.
Kendra, J., Sarabandi, K., and Ulaby, F.: Radar measurements of snow: experiment and analysis, IEEE T. Geosci. Remote, 36, 864–879, https://doi.org/10.1109/36.673679, 1998.
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, https://doi.org/10.1109/TGRS.2009.2030499, 2010.
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 Resour. Res., 48, W12524, https://doi.org/10.1029/2012WR012133, 2012.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002.
Leinss, S., Löwe, H., Proksch, M., Lemmetyinen, J., Wiesmann, A., and Hajnsek, I.: Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series, The Cryosphere, 10, 1771–1797, https://doi.org/10.5194/tc-10-1771-2016, 2016.
Lemmetyinen, J., Derksen, C., Pulliainen, J., Strapp, W., Toose, P., Walker, A., Tauriainen, S., Pihlflyckt, J., Kärnä, J., and Hallikainen, M.: A Comparison of Airborne Microwave Brightness Temperatures and Snowpack Properties Across the Boreal Forests of Finland and Western Canada, IEEE T. Geosci. Remote, 47, 965–978, https://doi.org/10.1109/TGRS.2008.2006358, 2009.
Lemmetyinen, J., Pulliainen, J., Rees, A., Kontu, A., Qiu, Y., and Derksen, C.: Multiple-Layer Adaptation of HUT Snow Emission Model: Comparison With Experimental Data, IEEE T. Geosci. Remote, 48, 2781–2794, https://doi.org/10.1109/TGRS.2010.2041357, 2010.
Lemmetyinen, J., Derksen, C., Toose, P., Proksch, M., Pulliainen, J., Kontu, A., Rautiainen, K., Seppänen, J., and Hallikainen, M.: Simulating seasonally and spatially varying snow cover brightness temperature using HUT snow emission model and retrieval of a microwave effective grain size, Remote Sens. Environ. 156, 71–95, https://doi.org/10.1016/j.rse.2014.09.016, 2015.
Lemmetyinen, J., Kontu, A., Pulliainen, J., Vehviläinen, J., Rautiainen, K., Wiesmann, A., Mätzler, C., Werner, C., Rott, H., Nagler, T., Schneebeli, M., Proksch, M., Schüttemeyer, D., Kern, M., and Davidson, M. W. J.: Nordic Snow Radar Experiment, Geosci. Instrum. Method. Data Syst., 5, 403–415, https://doi.org/10.5194/gi-5-403-2016, 2016.
Leppänen, L., Kontu, A., Hannula, H.-R., Sjöblom, H., and Pulliainen, J.: Sodankylä manual snow survey program, Geosci. Instrum. Method. Data Syst., 5, 163–179, https://doi.org/10.5194/gi-5-163-2016, 2016.
Liang, D., Xu, X., Tsang, L., Andreadis, K., and Josberger, E.: The Effects of Layers in Dry Snow on Its Passive Microwave Emissions Using Dense Media Radiative Transfer Theory Based on the Quasicrystalline Approximation (QCA/DMRT), IEEE T. Geosci. Remote, 46, 3663–3671, https://doi.org/10.1109/TGRS.2008.922143, 2008.
Löwe, H. and Picard, G.: Microwave scattering coefficient of snow in MEMLS and DMRT-ML revisited: the relevance of sticky hard spheres and tomography-based estimates of stickiness, The Cryosphere, 9, 2101–2117, https://doi.org/10.5194/tc-9-2101-2015, 2015.
Löwe, H., Riche, F., and Schneebeli, M.: A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity, The Cryosphere, 7, 1473–1480, https://doi.org/10.5194/tc-7-1473-2013, 2013.
Mätzler, C.: Improved Born approximation for scattering of radiation in a granular medium, J. Appl. Phys., 83, 6111–6117, https://doi.org/10.1063/1.367496, 1998.
Mätzler, C.: Relation between grain-size and correlation length of snow, J. Glaciol., 48, 461–466, https://doi.org/10.3189/172756502781831287, 2002.
Mätzler, C. and Wiesmann, A.: Extension of the Microwave Emission Model of Layered Snowpacks to Coarse-Grained Snow, Remote Sens. Environ., 70, 317–325, https://doi.org/10.1016/S0034-4257(99)00047-4, 1999.
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, 941–952, https://doi.org/10.3189/2012JoG11J248, 2012.
Montpetit, B., Royer, A., Roy, A., Langlois, A., and Derksen, C.: 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.
Pan, J., Durand, M., Sandells, M., Lemmetyinen, J., Kim, E., Pulliainen, J., Kontu, A., and Derksen, C.: Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation, IEEE T. Geosci. Remote, 54, 2001–2019, https://doi.org/10.1109/TGRS.2015.2493505, 2015.
Picard, G., Brucker, L., Fily, M., Gallée, H., and Krinner, G.: Modeling time series of microwave brightness temperature in Antarctica, J. Glaciol., 55, 537–551, https://doi.org/10.3189/002214309788816678, 2009.
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.
Picard, G., Royer, A., Arnaud, L., and Fily, M.: Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica, The Cryosphere, 8, 1105–1119, https://doi.org/10.5194/tc-8-1105-2014, 2014.
Pulliainen, J., Grandell, J., and Hallikainen, M.: HUT snow emission model and its applicability to snow water equivalent retrieval, IEEE T. Geosci. Remote, 37, 1378–1390, https://doi.org/10.1109/36.763302, 1999.
Rosenfeld, S. and Grody, N.: Anomalous microwave spectra of snow cover observed from Special Sensor Microwave/Imager measurements, J. Geophys. Res., 105, 14913–14925, https://doi.org/10.1029/1999JD900486, 2000.
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, https://doi.org/10.1109/TGRS.2012.2235842, 2013.
Roy, V., Goita, K., Royer, R., 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, https://doi.org/10.1109/TGRS.2004.832245, 2004.
Rutter, N., Essery, R., Pomeroy, J., Altimir, N., Andreadis, K., Baker, I., Barr, A., Bartlett, P., Boone, A., Deng, H., Douville, H., Dutra, E., Elder, K., Ellis, C., Feng, X., Gelfan, A., Goodbody, A., Gusev, Y., Gustafsson, D., Hellström, R., Hirabayashi, Y., Hirota, T., Jonas, T., Koren, V., Kuragina, A., Lettenmaier, D., Li, W.-P., Luce, C., Martin, E., Nasonova, O., Pumpanen, J., Pyles, R. D., Samuelsson, P., Sandells, M., Schädler, G., Shmakin, A., Smirnova, T. G., Stähli, M., Stöckli, R., Strasser, U., Su, H., Suzuki, K., Takata, K., Tanaka, K., Thompson, E., Vesala, T., Viterbo, P., Wiltshire, A., Xia, K., Xue, Y., and Yamazaki, T.: Evaluation of forest snow processes models (SnowMIP2), J. Geophys. Res., 114, D06111, https://doi.org/10.1029/2008JD011063, 2009.
Rutter, N., Sandells, M., Derksen, C., Toose, P., Royer, A., Montpetit, B., Langlois, A., Lemmetyinen, J., and Pulliainen, J.: Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: Implications for emission modeling, J. Geophys. Res.-Earth, 119, 550–565, https://doi.org/10.1002/2013JF003017, 2014.
Sandells, M., Essery, R., Rutter, N., Wake, L., Leppänen, L., and Lemmetyinen, J.: The Cryosphere Sandells et al. 2017 Datafiles, figshare, https://doi.org/10.6084/m9.figshare.4552822.v1, retrieved: 17 January 2017.
Shih, S.-E., Ding, K.-H., Kong, J., Yang, Y., Davis, R., Hardy, J., and Jordan, R.: Modeling of millimeter wave backscatter of time-varying snow cover, J. Electromagnet. Wave., 11, 1289–1298, 1997.
Song, K. and Zhang, Y.: Snow-cover environmental monitoring and assessment in Northeast China using passive microwave emission models, Environ. Monit. Assess., 140, 223–229, https://doi.org/10.1007/s10661-007-9862-4, 2007.
Stogryn, A.: A Study of the Microwave Brightness Temperature of Snow from the Point of View of Strong Fluctuation Theory, IEEE T. Geosci. Remote, GE-24, 220–231, https://doi.org/10.1109/TGRS.1986.289641, 1986.
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, https://doi.org/10.1016/j.rse.2011.08.014, 2011.
Tedesco, M. and Kim, E.: Intercomparison of Electromagnetic Models for Passive Microwave Remote Sensing of Snow, IEEE T. Geosci. Remote, 44, 2654–2666, https://doi.org/10.1109/TGRS.2006.873182, 2006.
Tedesco, M., Kim, E. J., Cline, D., Graf, T., Koike, T., Armstrong, R., Brodzik, M. J., and Hardy, J.: Comparison of local scale measured and modelled brightness temperatures and snow parameters from the CLPX 2003 by means of a dense medium radiative transfer theory model, Hydrol. Process., 20, 657–672, https://doi.org/10.1002/hyp.6129, 2006.
Tsang, L., Chen, C.-T., Chang, A. T. C., Guo, J., and Ding, K.-H.: Dense media radiative transfer theory based on quasicrystalline approximation with applications to passive microwave remote sensing of snow, Radio Sci., 35, 731–749, https://doi.org/10.1029/1999RS002270, 2000.
Tsang, L., Pan, J., Liang, D., Li, Z., Cline, D., and Tan, Y.: Modeling Active Microwave Remote Sensing of Snow Using Dense Media Radiative Transfer (DMRT) Theory With Multiple-Scattering Effects, IEEE T. Geosci. Remote, 45, 990–1004, https://doi.org/10.1109/TGRS.2006.888854, 2007.
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.
Wiesmann, A. and Mätzler, C.: Microwave Emission Model of Layered Snowpacks, Remote Sens. Environ. 70, 307–316, https://doi.org/10.1016/S0034-4257(99)00046-2, 1999.
Wiesmann, A., Fierz, C., and Mätzler, C.: Simulation of microwave emission from physically modeled snowpacks, Ann. Glaciol., 31, 397–405, https://doi.org/10.3189/172756400781820453, 2000.
Xu, X., Tsang, L., and Yueh, S.: Electromagnetic Models of Co/Cross Polarization of Bicontinuous/DMRT in Radar Remote Sensing of Terrestrial Snow at X- and Ku-band for CoReH2O and SCLP Applications, IEEE J. Sel. Top. Appl., 5, 1024–1032, https://doi.org/10.1109/JSTARS.2012.2190719, 2012.
Zuanon, N.: IceCube, a portable and reliable instruments for snow specific surface area measurement in the field, in: Proceedings, International Snow Science Workshop Grenoble – Chamonix Mont-Blance – 2013, 1020–1023, 2013.
Short summary
This study looks at a wide range of options for simulating sensor signals for satellite monitoring of water stored as snow, though an ensemble of 1323 coupled snow evolution and microwave scattering models. The greatest improvements will be made with better computer simulations of how the snow microstructure changes, followed by how the microstructure scatters radiation at microwave frequencies. Snow compaction should also be considered in systems to monitor snow mass from space.
This study looks at a wide range of options for simulating sensor signals for satellite...
