Articles | Volume 17, issue 2
https://doi.org/10.5194/tc-17-889-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-889-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2023
Research article |
| 21 Feb 2023
Towards long-term records of rain-on-snow events across the Arctic from satellite data
b.geos GmbH, Industriestrasse 1, 2100 Korneuburg, Austria
Helena Bergstedt
b.geos GmbH, Industriestrasse 1, 2100 Korneuburg, Austria
Georg Pointner
b.geos GmbH, Industriestrasse 1, 2100 Korneuburg, Austria
Xaver Muri
b.geos GmbH, Industriestrasse 1, 2100 Korneuburg, Austria
Kimmo Rautiainen
Earth Observation Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Leena Leppänen
Earth Observation Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Arctic Centre, University of Lapland, Pohjoisranta 4, 96101 Rovaniemi, Finland
Kyle Joly
Gates of the Arctic National Park and Preserve, Arctic Inventory and Monitoring Program, National Park Service, 99709 Fairbanks, Alaska, USA
Aleksandr Sokolov
Arctic Research Station, Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences, Zelenaya Gorka Str. 21, Labytnangi, Yamal-Nenets Autonomous District, Russia
Pavel Orekhov
Arctic Research Station, Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences, Zelenaya Gorka Str. 21, Labytnangi, Yamal-Nenets Autonomous District, Russia
Dorothee Ehrich
Department of Arctic and Marine Biology, UiT, The Arctic University of Norway, 9037 Tromsø, Norway
Eeva Mariatta Soininen
Department of Arctic and Marine Biology, UiT, The Arctic University of Norway, 9037 Tromsø, Norway
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Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
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This study presents strong new indications that regions of anomalously low backscatter in C-band synthetic aperture radar (SAR) imagery of ice of Lake Neyto in northwestern Siberia are related to strong emissions of natural gas. Spatio-temporal dynamics and potential scattering and formation mechanisms are assessed. It is suggested that exploiting the spatial and temporal properties of Sentinel-1 SAR data may be beneficial for the identification of similar phenomena in other Arctic lakes.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Jaroslav Obu, Sebastian Westermann, Gonçalo Vieira, Andrey Abramov, Megan Ruby Balks, Annett Bartsch, Filip Hrbáček, Andreas Kääb, and Miguel Ramos
The Cryosphere, 14, 497–519, https://doi.org/10.5194/tc-14-497-2020, https://doi.org/10.5194/tc-14-497-2020, 2020
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Little is known about permafrost in the Antarctic outside of the few research stations. We used a simple equilibrium permafrost model to estimate permafrost temperatures in the whole Antarctic. The lowest permafrost temperature on Earth is −36 °C in the Queen Elizabeth Range in the Transantarctic Mountains. Temperatures are commonly between −23 and −18 °C in mountainous areas rising above the Antarctic Ice Sheet, between −14 and −8 °C in coastal areas, and up to 0 °C on the Antarctic Peninsula.
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Knowledge about permafrost extent is required with respect to climate change. We used borehole temperature records from across the Arctic for the assessment of surface status information (frozen or unfrozen) derived from space-borne microwave sensors for permafrost extent mapping. The comparison to mean annual ground temperature (MAGT) at the coldest sensor depth revealed that not only extent but also temperature can be obtained from C-band-derived surface state with a residual error of 2.22 °C.
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Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
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Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
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Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
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The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally. The relationship between active-layer thickness (ALT) and X-band SAR backscatter of TerraSAR-X has been investigated in order to explore the possibility of delineating ALT with continuous and larger spatial coverage.
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Hydrol. Earth Syst. Sci., 20, 1211–1223, https://doi.org/10.5194/hess-20-1211-2016, https://doi.org/10.5194/hess-20-1211-2016, 2016
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Gridded fields of daily max. and min. temperatures for the Austrian domain are used to calculate ET0 based on a re-calibrated Hargreaves method. Newly derived, station-based calibration parameters, with Penman–Monteith ET0 as a reference, show a distinct altitude and seasonal dependence. Theses features are used to interpolate the new calibration values in space and time onto the temperature grids. The ET0 is then calculated based on the entire gridded temperature data starting back in 1961.
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Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Georg Pointner, Annett Bartsch, Yury A. Dvornikov, and Alexei V. Kouraev
The Cryosphere, 15, 1907–1929, https://doi.org/10.5194/tc-15-1907-2021, https://doi.org/10.5194/tc-15-1907-2021, 2021
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This study presents strong new indications that regions of anomalously low backscatter in C-band synthetic aperture radar (SAR) imagery of ice of Lake Neyto in northwestern Siberia are related to strong emissions of natural gas. Spatio-temporal dynamics and potential scattering and formation mechanisms are assessed. It is suggested that exploiting the spatial and temporal properties of Sentinel-1 SAR data may be beneficial for the identification of similar phenomena in other Arctic lakes.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
Short summary
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Jaroslav Obu, Sebastian Westermann, Gonçalo Vieira, Andrey Abramov, Megan Ruby Balks, Annett Bartsch, Filip Hrbáček, Andreas Kääb, and Miguel Ramos
The Cryosphere, 14, 497–519, https://doi.org/10.5194/tc-14-497-2020, https://doi.org/10.5194/tc-14-497-2020, 2020
Short summary
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Little is known about permafrost in the Antarctic outside of the few research stations. We used a simple equilibrium permafrost model to estimate permafrost temperatures in the whole Antarctic. The lowest permafrost temperature on Earth is −36 °C in the Queen Elizabeth Range in the Transantarctic Mountains. Temperatures are commonly between −23 and −18 °C in mountainous areas rising above the Antarctic Ice Sheet, between −14 and −8 °C in coastal areas, and up to 0 °C on the Antarctic Peninsula.
Christine Kroisleitner, Annett Bartsch, and Helena Bergstedt
The Cryosphere, 12, 2349–2370, https://doi.org/10.5194/tc-12-2349-2018, https://doi.org/10.5194/tc-12-2349-2018, 2018
Short summary
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Knowledge about permafrost extent is required with respect to climate change. We used borehole temperature records from across the Arctic for the assessment of surface status information (frozen or unfrozen) derived from space-borne microwave sensors for permafrost extent mapping. The comparison to mean annual ground temperature (MAGT) at the coldest sensor depth revealed that not only extent but also temperature can be obtained from C-band-derived surface state with a residual error of 2.22 °C.
Sarah E. Chadburn, Gerhard Krinner, Philipp Porada, Annett Bartsch, Christian Beer, Luca Belelli Marchesini, Julia Boike, Altug Ekici, Bo Elberling, Thomas Friborg, Gustaf Hugelius, Margareta Johansson, Peter Kuhry, Lars Kutzbach, Moritz Langer, Magnus Lund, Frans-Jan W. Parmentier, Shushi Peng, Ko Van Huissteden, Tao Wang, Sebastian Westermann, Dan Zhu, and Eleanor J. Burke
Biogeosciences, 14, 5143–5169, https://doi.org/10.5194/bg-14-5143-2017, https://doi.org/10.5194/bg-14-5143-2017, 2017
Short summary
Short summary
Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
Sina Muster, Kurt Roth, Moritz Langer, Stephan Lange, Fabio Cresto Aleina, Annett Bartsch, Anne Morgenstern, Guido Grosse, Benjamin Jones, A. Britta K. Sannel, Ylva Sjöberg, Frank Günther, Christian Andresen, Alexandra Veremeeva, Prajna R. Lindgren, Frédéric Bouchard, Mark J. Lara, Daniel Fortier, Simon Charbonneau, Tarmo A. Virtanen, Gustaf Hugelius, Juri Palmtag, Matthias B. Siewert, William J. Riley, Charles D. Koven, and Julia Boike
Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
Short summary
Short summary
Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
Barbara Widhalm, Annett Bartsch, Marina Leibman, and Artem Khomutov
The Cryosphere, 11, 483–496, https://doi.org/10.5194/tc-11-483-2017, https://doi.org/10.5194/tc-11-483-2017, 2017
Short summary
Short summary
The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally. The relationship between active-layer thickness (ALT) and X-band SAR backscatter of TerraSAR-X has been investigated in order to explore the possibility of delineating ALT with continuous and larger spatial coverage.
Annett Bartsch, Barbara Widhalm, Peter Kuhry, Gustaf Hugelius, Juri Palmtag, and Matthias Benjamin Siewert
Biogeosciences, 13, 5453–5470, https://doi.org/10.5194/bg-13-5453-2016, https://doi.org/10.5194/bg-13-5453-2016, 2016
Short summary
Short summary
A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR) data from the ENVISAT satellite. It can be shown that measurements of C-band SAR under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. The approach provides the first spatially consistent account of soil organic carbon across the Arctic.
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
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
Short summary
Short summary
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.
Simone Bircher, Mie Andreasen, Johanna Vuollet, Juho Vehviläinen, Kimmo Rautiainen, François Jonard, Lutz Weihermüller, Elena Zakharova, Jean-Pierre Wigneron, and Yann H. Kerr
Geosci. Instrum. Method. Data Syst., 5, 109–125, https://doi.org/10.5194/gi-5-109-2016, https://doi.org/10.5194/gi-5-109-2016, 2016
Short summary
Short summary
At the Finnish Meteorological Institute in Sodankylä and the Danish Center for Hydrology, calibration functions for organic surface layers were derived for two in situ soil moisture sensors to be used in the validation of coarse-resolution soil moisture from satellites and land surface models. There was no clear difference in the data from a variety of humus types, strengthening confidence that these calibrations are applicable over a wide range of conditions as encountered in the large areas.
Klaus Haslinger and Annett Bartsch
Hydrol. Earth Syst. Sci., 20, 1211–1223, https://doi.org/10.5194/hess-20-1211-2016, https://doi.org/10.5194/hess-20-1211-2016, 2016
Short summary
Short summary
Gridded fields of daily max. and min. temperatures for the Austrian domain are used to calculate ET0 based on a re-calibrated Hargreaves method. Newly derived, station-based calibration parameters, with Penman–Monteith ET0 as a reference, show a distinct altitude and seasonal dependence. Theses features are used to interpolate the new calibration values in space and time onto the temperature grids. The ET0 is then calculated based on the entire gridded temperature data starting back in 1961.
I. Gouttevin, A. Bartsch, G. Krinner, and V. Naeimi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-11241-2013, https://doi.org/10.5194/hessd-10-11241-2013, 2013
Manuscript not accepted for further review
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Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
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We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
Vasana Dharmadasa, Christophe Kinnard, and Michel Baraër
The Cryosphere, 17, 1225–1246, https://doi.org/10.5194/tc-17-1225-2023, https://doi.org/10.5194/tc-17-1225-2023, 2023
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This study highlights the successful usage of UAV lidar to monitor small-scale snow depth distribution. Our results show that underlying topography and wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. This emphasizes the importance of including and better representing these processes in physically based models for accurate snowpack estimates.
Ruben Urraca and Nadine Gobron
The Cryosphere, 17, 1023–1052, https://doi.org/10.5194/tc-17-1023-2023, https://doi.org/10.5194/tc-17-1023-2023, 2023
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We evaluate the fitness of some of the longest satellite (NOAA CDR, 1966–2020) and reanalysis (ERA5, 1950–2020; ERA5-Land, 1950–2020) products currently available to monitor the Northern Hemisphere snow cover trends using 527 stations as the reference. We found different artificial trends and stepwise discontinuities in all the products that hinder the accurate monitoring of snow trends, at least without bias correction. The study also provides updates on the snow cover trends during 1950–2020.
Pinja Venäläinen, Kari Luojus, Colleen Mortimer, Juha Lemmetyinen, Jouni Pulliainen, Matias Takala, Mikko Moisander, and Lina Zschenderlein
The Cryosphere, 17, 719–736, https://doi.org/10.5194/tc-17-719-2023, https://doi.org/10.5194/tc-17-719-2023, 2023
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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.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
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We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Timbo Stillinger, Karl Rittger, Mark S. Raleigh, Alex Michell, Robert E. Davis, and Edward H. Bair
The Cryosphere, 17, 567–590, https://doi.org/10.5194/tc-17-567-2023, https://doi.org/10.5194/tc-17-567-2023, 2023
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Understanding global snow cover is critical for comprehending climate change and its impacts on the lives of billions of people. Satellites are the best way to monitor global snow cover, yet snow varies at a finer spatial resolution than most satellite images. We assessed subpixel snow mapping methods across a spectrum of conditions using airborne lidar. Spectral-unmixing methods outperformed older operational methods and are ready to to advance snow cover mapping at the global scale.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-224, https://doi.org/10.5194/tc-2022-224, 2022
Revised manuscript accepted for TC
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently monitor how much water is in mountain snowpack from satellites. In this research, we test the ability of an experimental remote sensing technique to monitor snow from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found the method worked better than expected in estimating important snowpack properties.
Ghislain Picard, Henning Löwe, and Christian Mätzler
The Cryosphere, 16, 3861–3866, https://doi.org/10.5194/tc-16-3861-2022, https://doi.org/10.5194/tc-16-3861-2022, 2022
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Microwave satellite observations used to monitor the cryosphere require radiative transfer models for their interpretation. These models represent how microwaves are scattered by snow and ice. However no existing theory is suitable for all types of snow and ice found on Earth. We adapted a recently published generic scattering theory to snow and show how it may improve the representation of snows with intermediate densities (~500 kg/m3) and/or with coarse grains at high microwave frequencies.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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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.
Elisabeth D. Hafner, Patrick Barton, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 16, 3517–3530, https://doi.org/10.5194/tc-16-3517-2022, https://doi.org/10.5194/tc-16-3517-2022, 2022
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Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
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, https://doi.org/10.5194/tc-16-2163-2022, https://doi.org/10.5194/tc-16-2163-2022, 2022
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Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
Jayson Eppler, Bernhard Rabus, and Peter Morse
The Cryosphere, 16, 1497–1521, https://doi.org/10.5194/tc-16-1497-2022, https://doi.org/10.5194/tc-16-1497-2022, 2022
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We introduce a new method for mapping changes in the snow water equivalent (SWE) of dry snow based on differences between time-repeated synthetic aperture radar (SAR) images. It correlates phase differences with variations in the topographic slope which allows the method to work without any "reference" targets within the imaged area and without having to numerically unwrap the spatial phase maps. This overcomes the key challenges faced in using SAR interferometry for SWE change mapping.
Sebastian Buchelt, Kirstine Skov, Kerstin Krøier Rasmussen, and Tobias Ullmann
The Cryosphere, 16, 625–646, https://doi.org/10.5194/tc-16-625-2022, https://doi.org/10.5194/tc-16-625-2022, 2022
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In this paper, we present a threshold and a derivative approach using Sentinel-1 synthetic aperture radar time series to capture the small-scale heterogeneity of snow cover (SC) and snowmelt. Thereby, we can identify start of runoff and end of SC as well as perennial snow and SC extent during melt with high spatiotemporal resolution. Hence, our approach could support monitoring of distribution patterns and hydrological cascading effects of SC from the catchment scale to pan-Arctic observations.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
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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.
Christopher Donahue, S. McKenzie Skiles, and Kevin Hammonds
The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, https://doi.org/10.5194/tc-16-43-2022, 2022
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The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Xiaodan Wu, Kathrin Naegeli, Valentina Premier, Carlo Marin, Dujuan Ma, Jingping Wang, and Stefan Wunderle
The Cryosphere, 15, 4261–4279, https://doi.org/10.5194/tc-15-4261-2021, https://doi.org/10.5194/tc-15-4261-2021, 2021
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We performed a comprehensive accuracy assessment of an Advanced Very High Resolution Radiometer global area coverage snow-cover extent time series dataset for the Hindu Kush Himalayan (HKH) region. The sensor-to-sensor consistency, the accuracy related to snow depth, elevations, land-cover types, slope, and aspects, and topographical variability were also explored. Our analysis shows an overall accuracy of 94 % in comparison with in situ station data, which is the same with MOD10A1 V006.
Pia Nielsen-Englyst, Jacob L. Høyer, Kristine S. Madsen, Rasmus T. Tonboe, Gorm Dybkjær, and Sotirios Skarpalezos
The Cryosphere, 15, 3035–3057, https://doi.org/10.5194/tc-15-3035-2021, https://doi.org/10.5194/tc-15-3035-2021, 2021
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The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic ice-covered areas is heavily under-sampled when it comes to in situ measurements. This paper presents a method for estimating daily mean 2 m air temperatures (T2m) in the Arctic from satellite observations of skin temperature, providing spatially detailed observations of the Arctic. The satellite-derived T2m product covers clear-sky snow and ice surfaces in the Arctic for the period 2000–2009.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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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.
Linlu Mei, Vladimir Rozanov, Christine Pohl, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2757–2780, https://doi.org/10.5194/tc-15-2757-2021, https://doi.org/10.5194/tc-15-2757-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 1 of two companion papers and shows the method description and sensitivity study. The paper investigates the major factors, including the assumptions of snow optical properties, snow particle distribution and atmospheric conditions (cloud and aerosol), impacting snow property retrievals from satellite observation.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Jennifer M. Jacobs, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, Elizabeth A. Burakowski, Christina Herrick, and Eunsang Cho
The Cryosphere, 15, 1485–1500, https://doi.org/10.5194/tc-15-1485-2021, https://doi.org/10.5194/tc-15-1485-2021, 2021
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This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to map shallow snowpack (< 20 cm) depth in open terrain and forests. The 1 m2 resolution snow depth map, generated by subtracting snow-off from snow-on lidar-derived digital terrain models, consistently had 0.5 to 1 cm precision in the field, with a considerable reduction in accuracy in the forest. Performance depends on the point cloud density and the ground surface variability and vegetation.
Elisabeth D. Hafner, Frank Techel, Silvan Leinss, and Yves Bühler
The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, https://doi.org/10.5194/tc-15-983-2021, 2021
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Satellites prove to be very valuable for documentation of large-scale avalanche periods. To test reliability and completeness, which has not been satisfactorily verified before, we attempt a full validation of avalanches mapped from two optical sensors and one radar sensor. Our results demonstrate the reliability of high-spatial-resolution optical data for avalanche mapping, the suitability of radar for mapping of larger avalanches and the unsuitability of medium-spatial-resolution optical data.
Xiongxin Xiao, Shunlin Liang, Tao He, Daiqiang Wu, Congyuan Pei, and Jianya Gong
The Cryosphere, 15, 835–861, https://doi.org/10.5194/tc-15-835-2021, https://doi.org/10.5194/tc-15-835-2021, 2021
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Daily time series and full space-covered sub-pixel snow cover area data are urgently needed for climate and reanalysis studies. Due to the fact that observations from optical satellite sensors are affected by clouds, this study attempts to capture dynamic characteristics of snow cover at a fine spatiotemporal resolution (daily; 6.25 km) accurately by using passive microwave data. We demonstrate the potential to use the passive microwave and the MODIS data to map the fractional snow cover area.
Marco Bongio, Ali Nadir Arslan, Cemal Melih Tanis, and Carlo De Michele
The Cryosphere, 15, 369–387, https://doi.org/10.5194/tc-15-369-2021, https://doi.org/10.5194/tc-15-369-2021, 2021
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The capability of time-lapse photography to retrieve snow depth time series was tested. We demonstrated that this method can be efficiently used in three different case studies: two in the Italian Alps and one in a forested region of Finland, with an accuracy comparable to the most common methods such as ultrasonic sensors or manual measurements. We hope that this simple method based only on a camera and a graduated stake can enable snow depth measurements in dangerous and inaccessible sites.
Lucie A. Eberhard, Pascal Sirguey, Aubrey Miller, Mauro Marty, Konrad Schindler, Andreas Stoffel, and Yves Bühler
The Cryosphere, 15, 69–94, https://doi.org/10.5194/tc-15-69-2021, https://doi.org/10.5194/tc-15-69-2021, 2021
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In spring 2018 in the alpine Dischma valley (Switzerland), we tested different industrial photogrammetric platforms for snow depth mapping. These platforms were high-resolution satellites, an airplane, unmanned aerial systems and a terrestrial system. Therefore, this study gives a general overview of the accuracy and precision of the different photogrammetric platforms available in space and on earth and their use for snow depth mapping.
Maxim Lamare, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud
The Cryosphere, 14, 3995–4020, https://doi.org/10.5194/tc-14-3995-2020, https://doi.org/10.5194/tc-14-3995-2020, 2020
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Terrain features found in mountainous regions introduce large errors into the calculation of the physical properties of snow using optical satellite images. We present a new model performing rapid calculations of solar radiation over snow-covered rugged terrain that we tested over a site in the French Alps. The results of the study show that all the interactions between sunlight and the terrain should be accounted for over snow-covered surfaces to correctly estimate snow properties from space.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 14, 3959–3978, https://doi.org/10.5194/tc-14-3959-2020, https://doi.org/10.5194/tc-14-3959-2020, 2020
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The angular reflection of solar radiation by snow surfaces is particularly anisotropic and highly variable. We measured the angular reflection from an aircraft using a digital camera in Antarctica in 2013/14 and studied its variability: the anisotropy increases with a lower Sun but decreases for rougher surfaces and larger snow grains. The applied methodology allows for a direct comparison with satellite observations, which generally underestimated the anisotropy measured within this study.
César Deschamps-Berger, Simon Gascoin, Etienne Berthier, Jeffrey Deems, Ethan Gutmann, Amaury Dehecq, David Shean, and Marie Dumont
The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, https://doi.org/10.5194/tc-14-2925-2020, 2020
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We evaluate a recent method to map snow depth based on satellite photogrammetry. We compare it with accurate airborne laser-scanning measurements in the Sierra Nevada, USA. We find that satellite data capture the relationship between snow depth and elevation at the catchment scale and also small-scale features like snow drifts and avalanche deposits. We conclude that satellite photogrammetry stands out as a convenient method to estimate the spatial distribution of snow depth in high mountains.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
The Cryosphere, 14, 1919–1935, https://doi.org/10.5194/tc-14-1919-2020, https://doi.org/10.5194/tc-14-1919-2020, 2020
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Unmanned-aerial-vehicle-based (UAV) structure-from-motion (SfM) techniques have the ability to map snow depths in open areas. Here UAV lidar and SfM are compared to map sub-canopy snowpacks. Snow depth accuracy was assessed with data from sites in western Canada collected in 2019. It is demonstrated that UAV lidar can measure the sub-canopy snow depth at a high accuracy, while UAV-SfM cannot. UAV lidar promises to quantify snow–vegetation interactions at unprecedented accuracy and resolution.
Carlo Marin, Giacomo Bertoldi, Valentina Premier, Mattia Callegari, Christian Brida, Kerstin Hürkamp, Jochen Tschiersch, Marc Zebisch, and Claudia Notarnicola
The Cryosphere, 14, 935–956, https://doi.org/10.5194/tc-14-935-2020, https://doi.org/10.5194/tc-14-935-2020, 2020
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In this paper, we use for the first time the synthetic aperture radar (SAR) time series acquired by Sentinel-1 to monitor snowmelt dynamics in alpine regions. We found that the multitemporal SAR allows the identification of the three phases that characterize the melting process, i.e., moistening, ripening and runoff, in a spatial distributed way. We believe that the presented investigation could have relevant applications for monitoring and predicting the snowmelt progress over large regions.
Edward H. Bair, Karl Rittger, Jawairia A. Ahmad, and Doug Chabot
The Cryosphere, 14, 331–347, https://doi.org/10.5194/tc-14-331-2020, https://doi.org/10.5194/tc-14-331-2020, 2020
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Ice and snowmelt feed the Indus River and Amu Darya, but validation of estimates from satellite sensors has been a problem until recently, when we were given daily snow depth measurements from these basins. Using these measurements, estimates of snow on the ground were created and compared with models. Estimates of water equivalent in the snowpack were mostly in agreement. Stratigraphy was also modeled and showed 1 year with a relatively stable snowpack but another with multiple weak layers.
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
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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.
Alexandre R. Bevington, Hunter E. Gleason, Vanessa N. Foord, William C. Floyd, and Hardy P. Griesbauer
The Cryosphere, 13, 2693–2712, https://doi.org/10.5194/tc-13-2693-2019, https://doi.org/10.5194/tc-13-2693-2019, 2019
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We investigate the influence of ocean–atmosphere teleconnections on the start, end, and duration of snow cover in British Columbia, Canada. We do this using daily satellite imagery from 2002 to 2018 and assess the accuracy of our methods using reported snow cover at 60 weather stations. We found that there are very strong relationships that vary by region and elevation. This improves our understanding of snow cover distribution and could be used to predict snow cover from ocean–climate indices.
Anne Braakmann-Folgmann and Craig Donlon
The Cryosphere, 13, 2421–2438, https://doi.org/10.5194/tc-13-2421-2019, https://doi.org/10.5194/tc-13-2421-2019, 2019
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Snow on sea ice is a fundamental climate variable. We propose a novel approach to estimate snow depth on sea ice from satellite microwave radiometer measurements at several frequencies using neural networks (NNs). We evaluate our results with airborne snow depth measurements and compare them to three other established snow depth algorithms. We show that our NN results agree better with the airborne data than the other algorithms. This is also advantageous for sea ice thickness calculation.
Jie Deng, Tao Che, Cunde Xiao, Shijin Wang, Liyun Dai, and Akynbekkyzy Meerzhan
The Cryosphere, 13, 2149–2167, https://doi.org/10.5194/tc-13-2149-2019, https://doi.org/10.5194/tc-13-2149-2019, 2019
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The Chinese ski industry is rapidly booming driven by enormous market demand and government support with the coming 2022 Beijing Winter Olympics. We evaluate the locational suitability of ski areas in China by integrating the natural and socioeconomic conditions. Corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.
Isobel R. Lawrence, Michel C. Tsamados, Julienne C. Stroeve, Thomas W. K. Armitage, and Andy L. Ridout
The Cryosphere, 12, 3551–3564, https://doi.org/10.5194/tc-12-3551-2018, https://doi.org/10.5194/tc-12-3551-2018, 2018
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In this paper we estimate the thickness of snow cover on Arctic sea ice from space. We use data from two radar altimeter satellites, AltiKa and CryoSat-2, that have been operating synchronously since 2013. We produce maps of monthly average snow depth for the four growth seasons (October to April): 2012–2013, 2013–2014, 2014–2015, and 2015–2016. Snow depth estimates are essential for the accurate retrieval of sea ice thickness from satellite altimetry.
Richard Fernandes, Christian Prevost, Francis Canisius, Sylvain G. Leblanc, Matt Maloley, Sarah Oakes, Kiyomi Holman, and Anders Knudby
The Cryosphere, 12, 3535–3550, https://doi.org/10.5194/tc-12-3535-2018, https://doi.org/10.5194/tc-12-3535-2018, 2018
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The use of lightweight UAV-based surveys of surface elevation to map snow depth and weekly snow depth change was evaluated over five study areas spanning a range of topography and vegetation cover. Snow depth was estimated with an accuracy of better than 10 cm in the vertical and 3 cm in the horizontal. Vegetation in the snow-free elevation map was a major source of error. As a result, the snow depth change between two dates with snow cover was estimated with an accuracy of better than 4 cm.
Todd A. N. Redpath, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 12, 3477–3497, https://doi.org/10.5194/tc-12-3477-2018, https://doi.org/10.5194/tc-12-3477-2018, 2018
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A remotely piloted aircraft system (RPAS) is evaluated for mapping seasonal snow depth across an alpine basin. RPAS photogrammetry performs well at providing maps of snow depth at high spatial resolution, outperforming field measurements for resolving spatial variability. Uncertainty and error analysis reveal limitations and potential pitfalls of photogrammetric surface-change analysis. Ultimately, RPAS can be a useful tool for understanding snow processes and improving snow modelling efforts.
Alexander Kokhanovsky, Maxim Lamare, Biagio Di Mauro, Ghislain Picard, Laurent Arnaud, Marie Dumont, François Tuzet, Carsten Brockmann, and Jason E. Box
The Cryosphere, 12, 2371–2382, https://doi.org/10.5194/tc-12-2371-2018, https://doi.org/10.5194/tc-12-2371-2018, 2018
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This work presents a new technique with which to derive the snow microphysical and optical properties from snow spectral reflectance measurements. The technique is robust and easy to use, and it does not require the extraction of snow samples from a given snowpack. It can be used in processing satellite imagery over extended fresh dry, wet and polluted snowfields.
Stefan Härer, Matthias Bernhardt, Matthias Siebers, and Karsten Schulz
The Cryosphere, 12, 1629–1642, https://doi.org/10.5194/tc-12-1629-2018, https://doi.org/10.5194/tc-12-1629-2018, 2018
Short summary
Short summary
The paper presents an approach which can be used to process satellite-based snow cover maps with a higher-than-today accuracy at the local scale. Many of the current satellite-based snow maps are using the NDSI with a threshold as a tool for deciding if there is snow on the ground or not. The presented study has shown that, firstly, using the standard threshold of 0.4 can result in significant derivations at the local scale and that, secondly, the deviations become smaller for coarser scales.
Cited articles
Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017. a
Bartsch, A.: Spring snowmelt and midwinter thaw and refreeze north of 60∘ N based
on Seawinds QuikScat 2000–2009, supplement to: Bartsch, Annett (2010): Ten
Years of SeaWinds on QuikSCAT for Snow Applications, Remote Sens., 2,
1142–1156, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.834198, 2010a. a
Bartsch, A.: Monitoring of Terrestrial Hydrology at High Latitudes with
Scatterometer Data, in: Geoscience and Remote Sensing, New Achievements,
edited by: Imperatore, P. and Riccio, D., Intechweb, Vokuvar, 247–262, ISBN 9789537619978, 2010c. a
Bartsch, A., Kidd, R. A., Wagner, W., and Bartalis, Z.: Temporal and Spatial
Variability of the Beginning and End of Daily Spring Freeze/Thaw Cycles
Derived from Scatterometer Data, Remote Sens. Environ., 106,
360–374, https://doi.org/10.1016/j.rse.2006.09.004, 2007. a, b
Bartsch, A., Wagner, W., and Kidd, R.: Remote Sensing of Spring Snowmelt in
Siberia, in: Environmental Change in Siberia, Earth Observation, Field
Studies and Modelling, edited by: Balzter, H., Springer, 135–155,
https://doi.org/10.1007/978-90-481-8641-9_9, 2010b. a
Bartsch, A., Höfler, A., Kroisleitner, C., and Trofaier, A. M.: Land Cover
Mapping in Northern High Latitude Permafrost Regions with Satellite Data:
Achievements and Remaining Challenges, Remote Sens., 8, 979,
https://doi.org/10.3390/rs8120979, 2016. a
Bartsch, A., Widhalm, B., Leibman, M., Ermokhina, K., Kumpula, T., Skarin, A.,
Wilcox, E. J., Jones, B. M., Frost, G. V., Hofler, A., and Pointner, G.:
Feasibility of tundra vegetation height retrieval from Sentinel-1 and
Sentinel-2 data, Remote Sens. Environ., 237, 111515,
https://doi.org/10.1016/j.rse.2019.111515, 2020. a
Bartsch, A., Pointner, G., Bergstedt, H., Widhalm, B., Wendleder, A., and Roth,
A.: Utility of Polarizations Available from Sentinel-1 for Tundra Mapping,
in: 2021 IEEE International Geoscience and Remote Sensing Symposium
IGARSS, IEEE, Brussels, Belgium, 2021, 1452–1455, https://doi.org/10.1109/igarss47720.2021.9553993, 2021. a
Bartsch, A., Bergstedt, H., Pointner, G., Muri, X., and Rautiainen, K.:
Circumpolar mid-winter thaw and refreeze based on fusion of Metop ASCAT and
SMOS, 2011/2012–2021/2022, Zenodo [data set], https://doi.org/10.5281/zenodo.7575927, 2023. a
Bergstedt, H., Zwieback, S., Bartsch, A., and Leibman, M.: Dependence of C-Band
Backscatter on Ground Temperature, Air Temperature and Snow Depth in Arctic
Permafrost Regions, Remote Sens., 10, 142, https://doi.org/10.3390/rs10010142, 2018. a, b
Bergstedt, H., Bartsch, A., Neureiter, A., Hofler, A., Widhalm, B., Pepin, N.,
and Hjort, J.: Deriving a Frozen Area Fraction From Metop ASCAT Backscatter
Based on Sentinel-1, IEEE Transactions on Geoscience and Remote Sensing,
58, 6008–6019, https://doi.org/10.1109/tgrs.2020.2967364, 2020. a, b, c
Bjerke, J. W., Treharne, R., Vikhamar-Schuler, D., Karlsen, S. R., Ravolainen,
V., Bokhorst, S., Phoenix, G. K., Bochenek, Z., and Tømmervik, H.:
Understanding the drivers of extensive plant damage in boreal and Arctic
ecosystems: Insights from field surveys in the aftermath of damage, Sci. Total Environ., 599–600, 1965–1976,
https://doi.org/10.1016/j.scitotenv.2017.05.050, 2017. a
Derksen, C., Xu, X., Dunbar, R. S., Colliander, A., Kim, Y., Kimball, J. S.,
Black, T. A., Euskirchen, E., Langlois, A., Loranty, M. M., Marsh, P.,
Rautiainen, K., Roy, A., Royer, A., and Stephens, J.: Retrieving landscape
freeze/thaw state from Soil Moisture Active Passive (SMAP) radar and
radiometer measurements, Remote Sens. Environ., 194, 48–62,
https://doi.org/10.1016/j.rse.2017.03.007, 2017. a, b
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. a, b, c
Ehrich, D., Cerezo, M., Rodnikova, A. Y., Sokolova, N. A., Fuglei, E., Shtro,
V. G., and Sokolov, A. A.: Vole abundance and reindeer carcasses determine
breeding activity of Arctic foxes in low Arctic Yamal, Russia, BMC Ecology,
17, 32, https://doi.org/10.1186/s12898-017-0142-z, 2017. a, b
Figa-Saldaña, J., Wilson, J., Attema, E., Gelsthorpe, R., Drinkwater, M.,
and Stoffelen, A.: The advanced scatterometer (ASCAT) on the meteorological
operational (MetOp) platform: A follow on for European wind scatterometers,
Can. J. Remote Sens., 28, 404–412, https://doi.org/10.5589/m02-035,
2002. a
Forbes, B. C., Kumpula, T., Meschtyb, N., Laptander, R., Macias-Fauria, M.,
Zetterberg, P., Verdonen, M., Skarin, A., Kim, K.-Y., Boisvert, L. N.,
Stroeve, J. C., and Bartsch, A.: Sea ice, rain-on-snow and tundra reindeer
nomadism in Arctic Russia, Biol. Lett., 12, 20160466, https://doi.org/10.1098/rsbl.2016.0466, 2016. a, b, c, d, e, f, g, h, i, j, k, l
Freund, K. and Bartsch, A.: Midwinter thaw events over Greenland derived from
Seawinds QuikScat 2000–2008, Pangaea [data set], https://doi.org/10.1594/PANGAEA.911298, 2020. a
Grenfell, T. C. and Putkonen, J.: A Method for the Detection of the Severe
Rain-on-Snow Event on Banks Island, October 2003, Using Passive
Microwave Remote Sensing, Water Resour. Res., 44, W03425, https://doi.org/10.1029/2007WR005929, 2008. a, b
Hallikainen, M., Ulaby, F., and Abdelrazik, M.: Dielectric properties of snow
in the 3 to 37 GHz range, IEEE T. Antenn. Propag.,
34, 1329–1340, https://doi.org/10.1109/tap.1986.1143757, 1986. a
Joly, K., Couriot, O., Cameron, M. D., and Gurarie, E.: Behavioral,
Physiological, Demographic and Ecological Impacts of Hematophagous and
Endoparasitic Insects on an Arctic Ungulate, Toxins, 12, 334,
https://doi.org/10.3390/toxins12050334, 2020. a
Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J.,
Giustarini, L., Broc kmann, C., Wevers, J., Defourny, P., and Arino, O.:
Compilation and Validation of SAR and Optical Data Products for a Complete
and Global Map of Inland/Ocean Water Tailored to the Climate Modeling
Community, Remote Sens., 9, 36, https://doi.org/10.3390/rs9010036, 2017. a
Langlois, A., Johnson, C.-A., Montpetit, B., Royer, A., Blukacz-Richards, E.,
Neave, E., Dolant, C., Roy, A., Arhonditsis, G., Kim, D.-K., Kaluskar, S.,
and Brucker, L.: 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/10.1016/j.rse.2016.11.006, 2017. a, b, c, d, e
Lemmetyinen, J., Schwank, M., Rautiainen, K., Kontu, A., Parkkinen, T.,
Mätzler, C., Wiesmann, A., Wegmüller, U., Derksen, C., Toose, P.,
Roy, A., and Pulliainen, J.: Snow density and ground permittivity retrieved
from L-band radiometry: Application to experimental data, Remote Sens.
Environ., 180, 377–391, https://doi.org/10.1016/j.rse.2016.02.002, 2016. a, b
Leppänen, L., Kontu, A., Hannula, H.-R., Sjöblom, H., and Pulliainen,
J.: Sodankylä manual snow survey program, Geoscientific Instrumentation,
Methods and Data Systems, 5, 163–179, https://doi.org/10.5194/gi-5-163-2016, 2016. a
Lindsley, R. D. and Long, D. G.: Enhanced-Resolution Reconstruction of ASCAT
Backscatter Measurements, IEEE T. Geosci. Remote, 54, 2589–2601, https://doi.org/10.1109/tgrs.2015.2503762, 2016. a
Long, D. G.: Comparison of SeaWinds Backscatter Imaging Algorithms, IEEE
J. Sel. Top. Appl.,
10, 2214–2231, https://doi.org/10.1109/jstars.2016.2626966, 2017. a
Mousavi, M., Colliander, A., Miller, J. Z., Entekhabi, D., Johnson, J. T.,
Shuman, C. A., Kimball, J. S., and Courville, Z. R.: Evaluation of Surface
Melt on the Greenland Ice Sheet Using SMAP L-Band Microwave Radiometry,
IEEE J. Sel. Top. Appl., 14, 11439–11449, https://doi.org/10.1109/jstars.2021.3124229, 2021. a, b, c
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An
Improved Soil Moisture Retrieval Algorithm for ERS and METOP
Scatterometer Observations, IEEE Trans. Geosci. Remote Sens., 47, 1999–2013, https://doi.org/10.1109/tgrs.2008.2011617, 2009. a, b
Naeimi, V., Paulik, C., Bartsch, A., Wagner, W., Kidd, R., Park, S. E., Elger,
K., and Boike, J.: ASCAT Surface State Flag (SSF):
Extracting Information on Surface Freeze/Thaw Conditions From
Backscatter Data Using an Empirical Threshold-Analysis
Algorithm, IEEE Trans. Geosci. Remote Sens., 50,
2566–2582, https://doi.org/10.1109/TGRS.2011.2177667, 2012. a, b, c
Nagler, T. and Rott, H.: Retrieval of Wet Snow by Means of Multitemporal SAR
Data, IEEE Trans. Geosci. Remote Sens., 38, 754–765, https://doi.org/10.1109/36.842004, 2000. a, b
Nagler, T., Rott, H., Ripper, E., Bippus, G., and Hetzenecker, M.: Advancements
for Snowmelt Monitoring by Means of Sentinel-1 SAR, Remote Sens., 8, 348,
https://doi.org/10.3390/rs8040348, 2016. a
Pellarin, T., Mialon, A., Biron, R., Coulaud, C., Gibon, F., Kerr, Y.,
Lafaysse, M., Mercier, B., Morin, S., Redor, I., Schwank, M., and
Völksch, I.: Three years of L-band brightness temperature measurements in
a mountainous area: Topography, vegetation and snowmelt issues, Remote Sens. Environ., 180, 85–98, https://doi.org/10.1016/j.rse.2016.02.047, 2016. a
Potin, P.: Sentinel-1 User Handbook, ESA, issue 1, https://sedas.satapps.org/wp-content/uploads/2015/07/Sentinel-1_User_Handbook.pdf (last access: 6 February 2023), 2013. a
Potin, P., Rosich, B., Roeder, J., and Bargellini, P.: Sentinel-1 Mission
operations concept, in: 2014 IEEE Geosci. Remote Se., 1465–1468, https://doi.org/10.1109/IGARSS.2014.6946713, 2014. a
Putkonen, J. and Roe, G.: Rain-on-Snow Events Impact Soil Temperatures and
Affect Ungulate Survival, Geophys. Res. Lett., 30, 1188, https://doi.org/10.1029/2002GL016326, 2003. a, b, c
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A.,
Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., Langer, M.,
Drusch, M., and Pulliainen, J.: SMOS prototype algorithm for detecting
autumn soil freezing, Remote Sens. Environ., 180, 346–360,
https://doi.org/10.1016/j.rse.2016.01.012, 2016. a
Raynolds, M. K., Walker, D. A., Balser, A., Bay, C., Campbell, M., Cherosov,
M. M., Daniëls, F. J., Eidesen, P. B., Ermokhina, K. A., Frost, G. V.,
Jedrzejek, B., Jorgenson, M. T., Kennedy, B. E., Kholod, S. S., Lavrinenko,
I. A., Lavrinenko, O. V., Magnússon, B., Matveyeva, N. V.,
Metúsalemsson, S., Nilsen, L., Olthof, I., Pospelov, I. N., Pospelova,
E. B., Pouliot, D., Razzhivin, V., Schaepman-Strub, G., Šibík,
J., Telyatnikov, M. Y., and Troeva, E.: A raster version of the Circumpolar
Arctic Vegetation Map (CAVM), Remote Sens. Environ., 232, 111297,
https://doi.org/10.1016/j.rse.2019.111297, 2019. a, b, c, d
Schubert, A., Miranda, N., Geudtner, D., and Small, D.: Sentinel-1A/B Combined
Product Geolocation Accuracy, Remote Sens., 9, 607,
https://doi.org/10.3390/rs9060607, 2017. a
Schwank, M., Mätzler, C., Wiesmann, A., Wegmäller, U., Pulliainen, J.,
Lemmetyinen, J., Rautiainen, K., Derksen, C., Toose, P., and Drusch, M.: Snow
Density and Ground Permittivity Retrieved from L-Band Radiometry: A
Synthetic Analysis, IEEE J. Sel. Top. Appl., 8, 3833–3845,
https://doi.org/10.1109/jstars.2015.2422998, 2015. a, b
Serreze, M. C., Gustafson, J., Barrett, A. P., Druckenmiller, M. L., Fox, S.,
Voveris, J., Stroeve, J., Sheffield, B., Forbes, B. C., Rasmus, S.,
Laptander, R., Brook, M., Brubaker, M., Temte, J., McCrystall, M. R., and
Bartsch, A.: Arctic rain on snow events: bridging observations to understand
environmental and livelihood impacts, Environ. Res. Lett., 16,
105009, https://doi.org/10.1088/1748-9326/ac269b, 2021. a, b, c, d, e
Spreen, G., Kaleschke, L., and Heygster, G.: Sea ice remote sensing using
AMSR-E 89-GHz channels, J. Geophys. Res., 113, C02S03,
https://doi.org/10.1029/2005jc003384, 2008. a, b, c, d
Tao, S., Ao, Z., Wigneron, J.-P., Saatchi, S., Ciais, P., Chave, J., Le Toan, T., Frison, P.-L., Hu, X., Chen, C., Fan, L., Wang, M., Zhu, J., Zhao, X., Li, X., Liu, X., Su, Y., Hu, T., Guo, Q., Wang, Z., Tang, Z., Liu, Y., and Fang, J.: C-band Scatterometer (CScat): the first global long-term satellite radar backscatter data set with a C-band signal dynamic, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2022-264, in review, 2022. a
Treharne, R., Bjerke, J. W., Tømmervik, H., and Phoenix, G. K.: Extreme
event impacts on CO2 fluxes across a range of high latitude,
shrub-dominated ecosystems, Environ. Res. Lett., 15, 104084,
https://doi.org/10.1088/1748-9326/abb0b1, 2020. a
Tsang, L., Durand, M., Derksen, C., Barros, A. P., Kang, D.-H., Lievens, H., Marshall, H.-P., Zhu, J., Johnson, J., King, J., Lemmetyinen, J., Sandells, M., Rutter, N., Siqueira, P., Nolin, A., Osmanoglu, B., Vuyovich, C., Kim, E., Taylor, D., Merkouriadi, I., Brucker, L., Navari, M., Dumont, M., Kelly, R., Kim, R. S., Liao, T.-H., Borah, F., and Xu, X.: Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing, The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, 2022. a
Ulaby, F. T., Moore, R. K., and Fung, A. K.: Microwave Remote Sensing,
Active and Passive, Vol. III, Artech House, Inc, ISBN 0890061920, 1986. a
Vickers, H., Malnes, E., and Eckerstorfer, M.: A Synthetic Aperture Radar Based
Method for Long Term Monitoring of Seasonal Snowmelt and Wintertime
Rain-On-Snow Events in Svalbard, Front. Earth Sci., 10, 868945,
https://doi.org/10.3389/feart.2022.868945, 2022.
a
Westermann, S., Boike, J., Langer, M., Schuler, T. V., and Etzelmüller, B.: Modeling the impact of wintertime rain events on the thermal regime of permafrost, The Cryosphere, 5, 945–959, https://doi.org/10.5194/tc-5-945-2011, 2011. a
Wilson, R. R., Bartsch, A., Joly, K., Reynolds, J. H., Orlando, A., and Loya,
W. M.: Frequency, timing, extent, and size of winter thaw-refreeze events in
Alaska 2001–2008 detected by remotely sensed microwave
backscatter data, Polar Biol., 36, 419–426,
https://doi.org/10.1007/s00300-012-1272-6, 2012. a, b, c, d
Woodhouse, I. H.: Introduction to Microwave Remote Sensing, Taylor & Francis, New York, p. 400, https://doi.org/10.1201/9781315272573, 2006. a
Short summary
Rain-on-snow (ROS) events occur across many regions of the terrestrial Arctic in mid-winter. In extreme cases ice layers form which affect wildlife, vegetation and soils beyond the duration of the event. The fusion of multiple types of microwave satellite observations is suggested for the creation of a climate data record. Retrieval is most robust in the tundra biome, where records can be used to identify extremes and the results can be applied to impact studies at regional scale.
Rain-on-snow (ROS) events occur across many regions of the terrestrial Arctic in mid-winter. In...
