Articles | Volume 5, issue 1
https://doi.org/10.5194/tc-5-271-2011
© Author(s) 2011. 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-5-271-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Mar 2011
Research article |
| 29 Mar 2011
Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change
C. Nuth
Department of Geosciences, University of Oslo, 0316 Oslo, Norway
A. Kääb
Department of Geosciences, University of Oslo, 0316 Oslo, Norway
Related subject area
Remote Sensing
Towards long-term records of rain-on-snow events across the Arctic from satellite data
Aerial observations of sea ice breakup by ship waves
Monitoring Arctic thin ice: a comparison between CryoSat-2 SAR altimetry data and MODIS thermal-infrared imagery
The effects of surface roughness on the calculated, spectral, conical–conical reflectance factor as an alternative to the bidirectional reflectance distribution function of bare sea ice
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval
Evaluation of E3SM land model snow simulations over the western United States
Landsat, MODIS, and VIIRS snow cover mapping algorithm performance as validated by airborne lidar datasets
Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients
Inter-comparison and evaluation of Arctic sea ice type products
Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems
Climatic control on seasonal variations of glacier surface velocity
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval
Ice ridge density signatures in high-resolution SAR images
Glacier extraction based on high-spatial-resolution remote-sensing images using a deep-learning approach with attention mechanism
Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)
Seasonal land-ice-flow variability in the Antarctic Peninsula
Quantifying the effects of background concentrations of crude oil pollution on sea ice albedo
Brief communication: A continuous formulation of microwave scattering from fresh snow to bubbly ice from first principles
Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing
Automated avalanche mapping from SPOT 6/7 satellite imagery with deep learning: results, evaluation, potential and limitations
TermPicks: a century of Greenland glacier terminus data for use in scientific and machine learning applications
Surge dynamics of Shisper Glacier revealed by time-series correlation of optical satellite images and their utility to substantiate a generalized sliding law
Offset of MODIS land surface temperatures from in situ air temperatures in the upper Kaskawulsh Glacier region (St. Elias Mountains) indicates near-surface temperature inversions
Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau
Incorporating InSAR kinematics into rock glacier inventories: insights from 11 regions worldwide
Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica
Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers
Three different glacier surges at a spot: what satellites observe and what not
Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV-lidar
Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements
High-resolution debris cover mapping using UAV-derived thermal imagery: limits and opportunities
A leading-edge-based method for correction of slope-induced errors in ice-sheet heights derived from radar altimetry
Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation
Snowmelt Characterization from Optical and Synthetic Aperture Radar Observations in the Lajoie Basin, British Columbia
Characterizing the sea-ice floe size distribution in the Canada Basin from high-resolution optical satellite imagery
Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture
Snow water equivalent change mapping from slope-correlated synthetic aperture radar interferometry (InSAR) phase variations
Generating large-scale sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission using the Environment and Climate Change Canada automated sea ice tracking system
Rotational drift in Antarctic sea ice: pronounced cyclonic features and differences between data products
Glacier and rock glacier changes since the 1950s in the La Laguna catchment, Chile
Sentinel-1 time series for mapping snow cover depletion and timing of snowmelt in Arctic periglacial environments: case study from Zackenberg and Kobbefjord, Greenland
Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data
Cross-platform classification of level and deformed sea ice considering per-class incident angle dependency of backscatter intensity
Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
An empirical algorithm to map perennial firn aquifers and ice slabs within the Greenland Ice Sheet using satellite L-band microwave radiometry
Brief communication: Increased glacier mass loss in the Russian High Arctic (2010–2017)
Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals
Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements
Assessing volumetric change distributions and scaling relations of retrogressive thaw slumps across the Arctic
Annett Bartsch, Helena Bergstedt, Georg Pointner, Xaver Muri, Kimmo Rautiainen, Leena Leppänen, Kyle Joly, Aleksandr Sokolov, Pavel Orekhov, Dorothee Ehrich, and Eeva Mariatta Soininen
The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, https://doi.org/10.5194/tc-17-889-2023, 2023
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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.
Elie Dumas-Lefebvre and Dany Dumont
The Cryosphere, 17, 827–842, https://doi.org/10.5194/tc-17-827-2023, https://doi.org/10.5194/tc-17-827-2023, 2023
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By changing the shape of ice floes, wave-induced sea ice breakup dramatically affects the large-scale dynamics of sea ice. As this process is also the trigger of multiple others, it was deemed relevant to study how breakup itself affects the ice floe size distribution. To do so, a ship sailed close to ice floes, and the breakup that it generated was recorded with a drone. The obtained data shed light on the underlying physics of wave-induced sea ice breakup.
Felix L. Müller, Stephan Paul, Stefan Hendricks, and Denise Dettmering
The Cryosphere, 17, 809–825, https://doi.org/10.5194/tc-17-809-2023, https://doi.org/10.5194/tc-17-809-2023, 2023
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Thinning sea ice has significant impacts on the energy exchange between the atmosphere and the ocean. In this study we present visual and quantitative comparisons of thin-ice detections obtained from classified Cryosat-2 radar reflections and thin-ice-thickness estimates derived from MODIS thermal-infrared imagery. In addition to good comparability, the results of the study indicate the potential for a deeper understanding of sea ice in the polar seas and improved processing of altimeter data.
Maxim L. Lamare, John D. Hedley, and Martin D. King
The Cryosphere, 17, 737–751, https://doi.org/10.5194/tc-17-737-2023, https://doi.org/10.5194/tc-17-737-2023, 2023
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The reflectivity of sea ice is crucial for modern climate change and for monitoring sea ice from satellites. The reflectivity depends on the angle at which the ice is viewed and the angle illuminated. The directional reflectivity is calculated as a function of viewing angle, illuminating angle, thickness, wavelength and surface roughness. Roughness cannot be considered independent of thickness, illumination angle and the wavelength. Remote sensors will use the data to image sea ice from space.
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.
Xingdong Li, Di Long, Yanhong Cui, Tingxi Liu, Jing Lu, Mohamed A. Hamouda, and Mohamed M. Mohamed
The Cryosphere, 17, 349–369, https://doi.org/10.5194/tc-17-349-2023, https://doi.org/10.5194/tc-17-349-2023, 2023
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This study blends advantages of altimetry backscattering coefficients and waveforms to estimate ice thickness for lakes without in situ data and provides an improved water level estimation for ice-covered lakes by jointly using different threshold retracking methods. Our results show that a logarithmic regression model is more adaptive in converting altimetry backscattering coefficients into ice thickness, and lake surface snow has differential impacts on different threshold retracking methods.
Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen
The Cryosphere, 17, 279–308, https://doi.org/10.5194/tc-17-279-2023, https://doi.org/10.5194/tc-17-279-2023, 2023
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Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.
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.
Connor J. Shiggins, James M. Lea, and Stephen Brough
The Cryosphere, 17, 15–32, https://doi.org/10.5194/tc-17-15-2023, https://doi.org/10.5194/tc-17-15-2023, 2023
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Iceberg detection is spatially and temporally limited around the Greenland Ice Sheet. This study presents a new, accessible workflow to automatically detect icebergs from timestamped ArcticDEM strip data. The workflow successfully produces comparable output to manual digitisation, with results revealing new iceberg area-to-volume conversion equations that can be widely applied to datasets where only iceberg outlines can be extracted (e.g. optical and SAR imagery).
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
EGUsphere, https://doi.org/10.5194/egusphere-2022-1035, https://doi.org/10.5194/egusphere-2022-1035, 2022
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Glacier movement can be measured with satellite images. Over weeks to months, this movement is often too little compared to noise. We analyze thousands of images and retrieve, for 7 years, 10-day velocity changes over 48 glaciers in the Pamir. We capture their responses to rapid meteorological changes. In spring, strong glacier accelerations propagate upglacier. In autumn, accelerations propagate downglacier. Both result from changes in meltwater input to the glacier bed.
James Anheuser, Yinghui Liu, and Jeffrey R. Key
The Cryosphere, 16, 4403–4421, https://doi.org/10.5194/tc-16-4403-2022, https://doi.org/10.5194/tc-16-4403-2022, 2022
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A prominent part of the polar climate system is sea ice, a better understanding of which would lead to better understanding Earth's climate. Newly published methods for observing the temperature of sea ice have made possible a new method for estimating daily sea ice thickness growth from space using an energy balance. The method compares well with existing sea ice thickness observations.
Mikko Lensu and Markku Similä
The Cryosphere, 16, 4363–4377, https://doi.org/10.5194/tc-16-4363-2022, https://doi.org/10.5194/tc-16-4363-2022, 2022
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Ice ridges form a compressing ice cover. From above they appear as walls of up to few metres in height and extend even kilometres across the ice. Below they may reach tens of metres under the sea surface. Ridges need to be observed for the purposes of ice forecasting and ice information production. This relies mostly on ridging signatures discernible in radar satellite (SAR) images. New methods to quantify ridging from SAR have been developed and are shown to agree with field observations.
Xinde Chu, Xiaojun Yao, Hongyu Duan, Cong Chen, Jing Li, and Wenlong Pang
The Cryosphere, 16, 4273–4289, https://doi.org/10.5194/tc-16-4273-2022, https://doi.org/10.5194/tc-16-4273-2022, 2022
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The available remote-sensing data are increasingly abundant, and the efficient and rapid acquisition of glacier boundaries based on these data is currently a frontier issue in glacier research. In this study, we designed a complete solution to automatically extract glacier outlines from the high-resolution images. Compared with other methods, our method achieves the best performance for glacier boundary extraction in parts of the Tanggula Mountains, Kunlun Mountains and Qilian Mountains.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
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Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Karla Boxall, Frazer D. W. Christie, Ian C. Willis, Jan Wuite, and Thomas Nagler
The Cryosphere, 16, 3907–3932, https://doi.org/10.5194/tc-16-3907-2022, https://doi.org/10.5194/tc-16-3907-2022, 2022
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Using high-spatial- and high-temporal-resolution satellite imagery, we provide the first evidence for seasonal flow variability of land ice draining to George VI Ice Shelf (GVIIS), Antarctica. Ultimately, our findings imply that other glaciers in Antarctica may be susceptible to – and/or currently undergoing – similar ice-flow seasonality, including at the highly vulnerable and rapidly retreating Pine Island and Thwaites glaciers.
Benjamin Heikki Redmond Roche and Martin D. King
The Cryosphere, 16, 3949–3970, https://doi.org/10.5194/tc-16-3949-2022, https://doi.org/10.5194/tc-16-3949-2022, 2022
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Sea ice is bright, playing an important role in reflecting incoming solar radiation. The reflectivity of sea ice is affected by the presence of pollutants, such as crude oil, even at low concentrations. Modelling how the brightness of three types of sea ice is affected by increasing concentrations of crude oils shows that the type of oil, the type of ice, the thickness of the ice, and the size of the oil droplets are important factors. This shows that sea ice is vulnerable to oil pollution.
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.
Sophie Goliber, Taryn Black, Ginny Catania, James M. Lea, Helene Olsen, Daniel Cheng, Suzanne Bevan, Anders Bjørk, Charlie Bunce, Stephen Brough, J. Rachel Carr, Tom Cowton, Alex Gardner, Dominik Fahrner, Emily Hill, Ian Joughin, Niels J. Korsgaard, Adrian Luckman, Twila Moon, Tavi Murray, Andrew Sole, Michael Wood, and Enze Zhang
The Cryosphere, 16, 3215–3233, https://doi.org/10.5194/tc-16-3215-2022, https://doi.org/10.5194/tc-16-3215-2022, 2022
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Terminus traces have been used to understand how Greenland's glaciers have changed over time; however, manual digitization is time-intensive, and a lack of coordination leads to duplication of efforts. We have compiled a dataset of over 39 000 terminus traces for 278 glaciers for scientific and machine learning applications. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for the Greenland Ice Sheet.
Flavien Beaud, Saif Aati, Ian Delaney, Surendra Adhikari, and Jean-Philippe Avouac
The Cryosphere, 16, 3123–3148, https://doi.org/10.5194/tc-16-3123-2022, https://doi.org/10.5194/tc-16-3123-2022, 2022
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Understanding sliding at the bed of glaciers is essential to understand the future of sea-level rise and glacier-related hazards. Yet there is currently no universal law to describe this mechanism. We propose a universal glacier sliding law and a method to qualitatively constrain it. We use satellite remote sensing to create velocity maps over 6 years at Shisper Glacier, Pakistan, including its recent surge, and show that the observations corroborate the generalized theory.
Ingalise Kindstedt, Kristin M. Schild, Dominic Winski, Karl Kreutz, Luke Copland, Seth Campbell, and Erin McConnell
The Cryosphere, 16, 3051–3070, https://doi.org/10.5194/tc-16-3051-2022, https://doi.org/10.5194/tc-16-3051-2022, 2022
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We show that neither the large spatial footprint of the MODIS sensor nor poorly constrained snow emissivity values explain the observed cold offset in MODIS land surface temperatures (LSTs) in the St. Elias. Instead, the offset is most prominent under conditions associated with near-surface temperature inversions. This work represents an advance in the application of MODIS LSTs to glaciated alpine regions, where we often depend solely on remote sensing products for temperature information.
Lingxiao Wang, Lin Zhao, Huayun Zhou, Shibo Liu, Erji Du, Defu Zou, Guangyue Liu, Yao Xiao, Guojie Hu, Chong Wang, Zhe Sun, Zhibin Li, Yongping Qiao, Tonghua Wu, Chengye Li, and Xubing Li
The Cryosphere, 16, 2745–2767, https://doi.org/10.5194/tc-16-2745-2022, https://doi.org/10.5194/tc-16-2745-2022, 2022
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Selin Co has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau in the past decades. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation since terrain surface settlement provides a
windowto detect the subsurface ground ice melting. Results reveal that ground ice meltwater contributed ~ 12 % of the lake volume increase during 2017–2020.
Aldo Bertone, Chloé Barboux, Xavier Bodin, Tobias Bolch, Francesco Brardinoni, Rafael Caduff, Hanne H. Christiansen, Margaret M. Darrow, Reynald Delaloye, Bernd Etzelmüller, Ole Humlum, Christophe Lambiel, Karianne S. Lilleøren, Volkmar Mair, Gabriel Pellegrinon, Line Rouyet, Lucas Ruiz, and Tazio Strozzi
The Cryosphere, 16, 2769–2792, https://doi.org/10.5194/tc-16-2769-2022, https://doi.org/10.5194/tc-16-2769-2022, 2022
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We present the guidelines developed by the IPA Action Group and within the ESA Permafrost CCI project to include InSAR-based kinematic information in rock glacier inventories. Nine operators applied these guidelines to 11 regions worldwide; more than 3600 rock glaciers are classified according to their kinematics. We test and demonstrate the feasibility of applying common rules to produce homogeneous kinematic inventories at global scale, useful for hydrological and climate change purposes.
Tian Li, Geoffrey J. Dawson, Stephen J. Chuter, and Jonathan L. Bamber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-129, https://doi.org/10.5194/tc-2022-129, 2022
Revised manuscript accepted for TC
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The Totten and Moscow University glaciers in East Antarctica have the potential to make a significant contribution to future sea-level rise. We used a combination of different satellite measurements to show that the grounding lines have been retreating along the fast-flowing ice streams across these two glaciers. We also found two tide-modulated ocean channels that might open new pathways for the warm ocean water to enter the ice shelf cavity.
Thomas R. Chudley, Ian M. Howat, Bidhyananda Yadav, and Myoung-Jong Noh
The Cryosphere, 16, 2629–2642, https://doi.org/10.5194/tc-16-2629-2022, https://doi.org/10.5194/tc-16-2629-2022, 2022
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Sentinel-2 images are subject to distortion due to orthorectification error, which makes it difficult to extract reliable glacier velocity fields from images from different orbits. Here, we use a complete record of velocity fields at four Greenlandic outlet glaciers to empirically estimate the systematic error, allowing us to correct cross-track glacier velocity fields to a comparable accuracy to other medium-resolution satellite datasets.
Frank Paul, Livia Piermattei, Désirée Treichler, Lin Gilbert, Luc Girod, Andreas Kääb, Ludivine Libert, Thomas Nagler, Tazio Strozzi, and Jan Wuite
The Cryosphere, 16, 2505–2526, https://doi.org/10.5194/tc-16-2505-2022, https://doi.org/10.5194/tc-16-2505-2022, 2022
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Glacier surges are widespread in the Karakoram and have been intensely studied using satellite data and DEMs. We use time series of such datasets to study three glacier surges in the same region of the Karakoram. We found strongly contrasting advance rates and flow velocities, maximum velocities of 30 m d−1, and a change in the surge mechanism during a surge. A sensor comparison revealed good agreement, but steep terrain and the two smaller glaciers caused limitations for some of them.
Vasana Dharmadasa, Christophe Kinnard, and Michel Baraër
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-124, https://doi.org/10.5194/tc-2022-124, 2022
Revised manuscript accepted for TC
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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 process-based models for accurate snowpack estimates.
Bas Altena, Andreas Kääb, and Bert Wouters
The Cryosphere, 16, 2285–2300, https://doi.org/10.5194/tc-16-2285-2022, https://doi.org/10.5194/tc-16-2285-2022, 2022
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Repeat overflights of satellites are used to estimate surface displacements. However, such products lack a simple error description for individual measurements, but variation in precision occurs, since the calculation is based on the similarity of texture. Fortunately, variation in precision manifests itself in the correlation peak, which is used for the displacement calculation. This spread is used to make a connection to measurement precision, which can be of great use for model inversion.
Deniz Tobias Gök, Dirk Scherler, and Leif Stefan Anderson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-113, https://doi.org/10.5194/tc-2022-113, 2022
Revised manuscript accepted for TC
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High resolution debris thickness mapping using land surface temperature (LST) measured from an unpiloted aerial vehicle (UAV) at various times of a day. LSTs from UAVs require calibration that varies in time. We test two approaches to quantify supraglacial debris cover and we find find that the non-linearity of the relationship between LST and debris thickness increases with LST. Choosing the best model to predict debris thickness depends on the time of the day and the terrain aspect.
Weiran Li, Cornelis Slobbe, and Stef Lhermitte
The Cryosphere, 16, 2225–2243, https://doi.org/10.5194/tc-16-2225-2022, https://doi.org/10.5194/tc-16-2225-2022, 2022
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This study proposes a new method for correcting the slope-induced errors in satellite radar altimetry. The slope-induced errors can significantly affect the height estimations of ice sheets if left uncorrected. This study applies the method to radar altimetry data (CryoSat-2) and compares the performance with two existing methods. The performance is assessed by comparison with independent height measurements from ICESat-2. The assessment shows that the method performs promisingly.
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.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-89, https://doi.org/10.5194/tc-2022-89, 2022
Revised manuscript accepted for TC
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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 landcover types, and 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.
Alexis Anne Denton and Mary-Louise Timmermans
The Cryosphere, 16, 1563–1578, https://doi.org/10.5194/tc-16-1563-2022, https://doi.org/10.5194/tc-16-1563-2022, 2022
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Arctic sea ice has a distribution of ice sizes that provides insight into the physics of the ice. We examine this distribution from satellite imagery from 1999 to 2014 in the Canada Basin. We find that it appears as a power law whose power becomes less negative with increasing ice concentrations and has a seasonality tied to that of ice concentration. Results suggest ice concentration be considered in models of this distribution and are important for understanding sea ice in a warming Arctic.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony Paul Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-86, https://doi.org/10.5194/tc-2022-86, 2022
Revised manuscript accepted for TC
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Sea ice maps are produced to cover the Arctic expedition MOSAiC (2019–2020), and divides sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset, and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect, and achieve good results as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
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.
Stephen E. L. Howell, Mike Brady, and Alexander S. Komarov
The Cryosphere, 16, 1125–1139, https://doi.org/10.5194/tc-16-1125-2022, https://doi.org/10.5194/tc-16-1125-2022, 2022
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We describe, apply, and validate the Environment and Climate Change Canada automated sea ice tracking system (ECCC-ASITS) that routinely generates large-scale sea ice motion (SIM) over the pan-Arctic domain using synthetic aperture radar (SAR) images. The ECCC-ASITS was applied to the incoming image streams of Sentinel-1AB and the RADARSAT Constellation Mission from March 2020 to October 2021 using a total of 135 471 SAR images and generated new SIM datasets (i.e., 7 d 25 km and 3 d 6.25 km).
Wayne de Jager and Marcello Vichi
The Cryosphere, 16, 925–940, https://doi.org/10.5194/tc-16-925-2022, https://doi.org/10.5194/tc-16-925-2022, 2022
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Ice motion can be used to better understand how weather and climate change affect the ice. Antarctic sea ice extent has shown large variability over the observed period, and dynamical features may also have changed. Our method allows for the quantification of rotational motion caused by wind and how this may have changed with time. Cyclonic motion dominates the Atlantic sector, particularly from 2015 onwards, while anticyclonic motion has remained comparatively small and unchanged.
Benjamin Aubrey Robson, Shelley MacDonell, Álvaro Ayala, Tobias Bolch, Pål Ringkjøb Nielsen, and Sebastián Vivero
The Cryosphere, 16, 647–665, https://doi.org/10.5194/tc-16-647-2022, https://doi.org/10.5194/tc-16-647-2022, 2022
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This work uses satellite and aerial data to study glaciers and rock glacier changes in La Laguna catchment within the semi-arid Andes of Chile, where ice melt is an important factor in river flow. The results show the rate of ice loss of Tapado Glacier has been increasing since the 1950s, which possibly relates to a dryer, warmer climate over the previous decades. Several rock glaciers show high surface velocities and elevation changes between 2012 and 2020, indicating they may be ice-rich.
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.
Stefan Kern, Thomas Lavergne, Leif Toudal Pedersen, Rasmus Tage Tonboe, Louisa Bell, Maybritt Meyer, and Luise Zeigermann
The Cryosphere, 16, 349–378, https://doi.org/10.5194/tc-16-349-2022, https://doi.org/10.5194/tc-16-349-2022, 2022
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High-resolution clear-sky optical satellite imagery has rarely been used to evaluate satellite passive microwave sea-ice concentration products beyond case-study level. By comparing 10 such products with sea-ice concentration estimated from > 350 such optical images in both hemispheres, we expand results of earlier evaluation studies for these products. Results stress the need to look beyond precision and accuracy and to discuss the evaluation data’s quality and filters applied in the products.
Wenkai Guo, Polona Itkin, Johannes Lohse, Malin Johansson, and Anthony Paul Doulgeris
The Cryosphere, 16, 237–257, https://doi.org/10.5194/tc-16-237-2022, https://doi.org/10.5194/tc-16-237-2022, 2022
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This study uses radar satellite data categorized into different sea ice types to detect ice deformation, which is significant for climate science and ship navigation. For this, we examine radar signal differences of sea ice between two similar satellite sensors and show an optimal way to apply categorization methods across sensors, so more data can be used for this purpose. This study provides a basis for future reliable and constant detection of ice deformation remotely through satellite data.
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.
Julie Z. Miller, Riley Culberg, David G. Long, Christopher A. Shuman, Dustin M. Schroeder, and Mary J. Brodzik
The Cryosphere, 16, 103–125, https://doi.org/10.5194/tc-16-103-2022, https://doi.org/10.5194/tc-16-103-2022, 2022
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We use L-band brightness temperature imagery from NASA's Soil Moisture Active Passive (SMAP) satellite to map the extent of perennial firn aquifer and ice slab areas within the Greenland Ice Sheet. As Greenland's climate continues to warm and seasonal surface melting increases in extent, intensity, and duration, quantifying the possible rapid expansion of perennial firn aquifers and ice slab areas has significant implications for understanding the stability of the Greenland Ice Sheet.
Christian Sommer, Thorsten Seehaus, Andrey Glazovsky, and Matthias H. Braun
The Cryosphere, 16, 35–42, https://doi.org/10.5194/tc-16-35-2022, https://doi.org/10.5194/tc-16-35-2022, 2022
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Arctic glaciers have been subject to extensive warming due to global climate change, yet their contribution to sea level rise has been relatively small in the past. In this study we provide mass changes of most glaciers of the Russian High Arctic (Franz Josef Land, Severnaya Zemlya, Novaya Zemlya). We use TanDEM-X satellite measurements to derive glacier surface elevation changes. Our results show an increase in glacier mass loss and a sea level rise contribution of 0.06 mm/a (2010–2017).
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.
Philipp Bernhard, Simon Zwieback, Nora Bergner, and Irena Hajnsek
The Cryosphere, 16, 1–15, https://doi.org/10.5194/tc-16-1-2022, https://doi.org/10.5194/tc-16-1-2022, 2022
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We present an investigation of retrogressive thaw slumps in 10 study sites across the Arctic. These slumps have major impacts on hydrology and ecosystems and can also reinforce climate change by the mobilization of carbon. Using time series of digital elevation models, we found that thaw slump change rates follow a specific type of distribution that is known from landslides in more temperate landscapes and that the 2D area change is strongly related to the 3D volumetric change.
Cited articles
Anderson, B., Lawson, W., Owens, I., and Goodsell, B.: Past and future mass balance of "Ka Roimata o Hine Hukatere" Franz Josef Glacier, New Zealand, J. Glaciol., 52, 597–607, https://doi.org/10.3189/172756506781828449, 2006.
Berthier, E.: Volume loss from Bering Glacier, Alaska, 1972–2003: comment on Muskett and others (2009), J. Glaciol., 56, 558–559, https://doi.org/10.3189/002214310792447716, 2010.
Berthier, E. and Toutin, T.: SPOT5-HRS digital elevation models and the monitoring of glacier elevation changes in North-West Canada and South-East Alaska, Remote Sens. Environ., 112, 2443–2454, https://doi.org/10.1016/j.rse.2007.11.004, 2008.
Berthier, E., Arnaud, Y., Baratoux, D., Vincent, C., and R{é}my, F.: Recent rapid thinning of the "Mer de Glace" glacier derived from satellite optical images, Geophys. Res. Lett., 31, L17401, https://doi.org/10.1029/2004GL020706, 2004.
Berthier, E., Arnaud, Y., Vincent, C., and R{é}my, F.: Biases of SRTM in high-mountain areas: Implications for the monitoring of glacier volume changes, Geophys. Res. Lett., 33, L08502, https://doi.org/10.1029/2006GL025862, 2006.
Berthier, E., Arnaud, Y., Kumar, R., Ahmad, S., Wagnon, P., and Chevallier, P.: Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India), Remote Sens. Environ., 108, 327–338, https://doi.org/10.1016/j.rse.2006.11.017, 2007.
Berthier, E., Schiefer, E., Clarke, G. K. C., Menounos, B., and Remy, F.: Contribution of Alaskan glaciers to sea-level rise derived from satellite imagery, Nat. Geosci., 3, 92–95, https://doi.org/10.1038/ngeo737, 2010.
Bolch, T., Buchroithner, M., Pieczonka, T., and Kunert, A.: Planimetric and volumetric glacier changes in the Khumbu Himal, Nepal, since 1962 using Corona, Landsat TM and ASTER data, J. Glaciol., 54, 592–600, https://doi.org/10.3189/002214308786570782, 2008.
Bouillon, A., Bernard, M., Gigord, P., Orsoni, A., Rudowski, V., and Baudoin, A.: SPOT 5 HRS geometric performances: Using block adjustment as a key issue to improve quality of DEM generation, ISPRS J. Photogramm. Remote S., 60, 134–146, https://doi.org/10.1016/j.isprsjprs.2006.03.002, 2006.
Brenner, A. C., DiMarzio, J. R., and Zwally, H. J.: Precision and accuracy of satellite radar and laser altimeter data over the continental ice sheets, IEEE T. Geosci. Remote, 45, 321–331, https://doi.org/10.1109/TGRS.2006.887172, 2007.
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., and Bladé, I.: The Effective Number of Spatial Degrees of Freedom of a Time-Varying Field, J. Climate, 12, 1990–2009, 1999.
Burrough, P., McDonnell, R., and Burrough, P.: Principles of geographical information systems, Oxford University Press, Oxford, 1998.
Davis, J. C.: Statistics and data analysis in geology, J. Wiley, New York, 2002.
Dowdeswell, J. A. and Benham, T. J.: A surge of Perseibreen, Svalbard, examined using aerial photography and ASTER high resolution satellite imagery, Polar Res., 22, 373–383, https://doi.org/10.1111/j.1751-8369.2003.tb00118.x, 2003.
ERSDAC: ASTER User's Guide Part III, DEM Product (L4A01), Ver.1.1, Tech. rep., Earth Remote Sensing Data Analysis Center (ERSDAC), http://www.science.aster.ersdac.or.jp/en/documnts/users_guide/index.html (last access: 1 October 2010), 2005.
ERSDAC: ASTER User's Guide Part II Level 1 Data Products, Ver.5.1, Tech. rep., Earth Remote Sensing Data Analysis Center (ERSDAC), http://www.science.aster.ersdac.or.jp/en/documnts/users_guide/index.html (last access: 1 October 2010), 2007.
Etzelm{ü}ller, B.: On the Quantification of Surface Changes using Grid-based Digital Elevation Models (DEMs), Transact. GIS, 4, 129–143, https://doi.org/10.1111/1467-9671.00043, 2000.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183, 2007.
Fisher, P.: Improved Modeling of Elevation Error with Geostatistics, GeoInformatica, 2, 215–233, https://doi.org/10.1023/A:1009717704255, 1998.
Fitzharris, B., Lawson, W., and Owens, I.: Research on glaciers and snow in New Zealand, Prog. Phys. Geogr., 23, 469–500, https://doi.org/10.1177/030913339902300402, 1999.
Fricker, H. A., Borsa, A., Minster, B., Carabajal, C., Quinn, K., and Bills, B.: Assessment of ICESat performance at the Salar de Uyuni, Bolivia, Geophys. Res. Lett., 32(5), L21S06, https://doi.org/10.1029/2005GL023423, 2005.
Fujisada, H., Bailey, G., Kelly, G., Hara, S., and Abrams, M.: ASTER DEM performance, Geoscience and Remote Sensing, IEEE Transact., 43, 2707–2714, https://doi.org/10.1109/TGRS.2005.847924, 2005.
GADM: GADM database of Global Administrative Areas, http://www.gadm.org (last access: 21 September 2010), 2010.
Gjermundsen, E. F.: Recent changes in glacier area in the Central Southern Alps of New Zealand, Master's thesis, University of Oslo, 2007.
Gorokhovich, Y. and Voustianiouk, A.: Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data from USA and Thailand and its relation to the terrain characteristics, Remote Sens. Environ., 104, 409–415, https://doi.org/10.1016/j.rse.2006.05.012, 2006.
Gruen, A. and Akca, D.: Least squares 3D surface and curve matching, ISPRS J. Photogramm. Remote S., 59, 151–174, https://doi.org/10.1016/j.isprsjprs.2005.02.006, 2005.
Herman, F., Anderson, B., and Leprince, S.: Mountain glacier velocity variation during a retreat/advance cycle quantified using sub-pixel analysis of ASTER images, J. Glaciol., 57, 197–207, 2011.
Hirano, A., Welch, R., and Lang, H.: Mapping from ASTER stereo image data: DEM validation and accuracy assessment, ISPRS J. Photogramm. Remote S., 57, 356–370, https://doi.org/10.1016/S0924-2716(02)00164-8, 2003.
Hisdal, V.: Geography of Svalbard, vol. 2, Norwegian Polar Institue, Oslo, 1985.
Hochstein, M. P., Claridge, D., Henrys, S. A., Pyne, A., Nobes, D. C., and Leary, S. F.: Downwasting of the Tasman Glacier, South Island, New-zealand – Changes In the Terminus Region Between 1971 and 1993, New Zeal. J. Geol. Geop., 38, 1–16, https://doi.org/10.1080/00288306.1995.9514635, 1995.
Howat, I. M., Smith, B. E., Joughin, I., and Scambos, T. A.: Rates of southeast Greenland ice volume loss from combined ICESat and ASTER observations, Geophys. Res. Lett., 35, L17505, https://doi.org/10.1029/2008GL034496, 2008.
Iwasaki, A. and Fujisada, H.: ASTER geometric performance, Geoscience and Remote Sensing, IEEE Transact., 43, 2700–2706, https://doi.org/10.1109/TGRS.2005.849055, 2005.
K{ä}{ä}b, A.: Remote Sensing of Mountain Glaciers and Permafrost Creep, Geographisches Institut der Universit{ü}rich, Z{ü}rich, 2005.
K{ä}{ä}b, A.: Glacier Volume Changes Using ASTER Satellite Stereo and ICESat GLAS Laser Altimetry, A Test Study on Edgeøya, Eastern Svalbard, IEEE Int. Geosci. Remote, 46, 2823–2830, https://doi.org/10.1109/TGRS.2008.2000627, 2008.
K{ä}{ä}b, A., Huggel, C., Paul, F., Wessels, R., Raup, B., Kieffer, H., and Kargel, J.: Glacier monitoring from ASTER imagery: Accuracy and Applications, in: Proceedings of EARSeL-LISSIG-Workshop Observing our Cryosphere from Space, 2002.
Kirkbride, M. P.: Relationships Between Temperature and Ablation On the Tasman Glacier, Mount Cook National-park, New-zealand, New Zeal. J. Geol. Geop., 38, 17–27, https://doi.org/10.1080/00288306.1995.9514636, 1995.
Kn{ö}pfle, W., Strunz, G., and Roth, A.: Mosaicking of Digital Elevation Models derived by SAR interferometry, ISPRS Commission IV Symposium on GIS – Between Visions and Applications, 32, 1998.
Koblet, T., Gärtner-Roer, I., Zemp, M., Jansson, P., Thee, P., Haeberli, W., and Holmlund, P.: Reanalysis of multi-temporal aerial images of Storglaciären, Sweden (1959-99) - Part 1: Determination of length, area, and volume changes, The Cryosphere, 4, 333–343, https://doi.org/10.5194/tc-4-333-2010, 2010.
Korona, J., Berthier, E., Bernard, M., R{é}my, F., and Thouvenot, E.: SPIRIT. SPOT 5 stereoscopic survey of Polar Ice: Reference Images and Topographies during the fourth International Polar Year (2007–2009), ISPRS J. Photogramm. Remote S., 64, 204–212, https://doi.org/10.1016/j.isprsjprs.2008.10.005, 2009.
Larsen, C. F., Motyka, R. J., Arendt, A. A., Echelmeyer, K. A., and Geissler, P. E.: Glacier changes in southeast Alaska and northwest British Columbia and contribution to sea level rise, J. Geophys. Res.-Earth, 112, F01007, https://doi.org/10.1029/2006JF000586, 2007.
Leprince, S., Ayoub, F., Klingert, Y., and Avouac, J.-P.: Co-Registration of Optically Sensed Images and Correlation (COSI-Corr): an operational methodology for ground deformation measurements, in: Geoscience and Remote Sensing Symposium, 2007, IGARSS 2007, IEEE International, 1943–1946, https://doi.org/10.1109/IGARSS.2007.4423207, 2007.
Li, Z. L.: On the Measure of Digital Terrain Model Accuracy, Photogramm. Rec. 12, 873–877, https://doi.org/10.1111/j.1477-9730.1988.tb00636.x, 1988.
Lillesand, T., Kiefer, R., and Chipman, J.: Remote Sensing and Image Interpretation, 5 editon, John Wiley & Sons, Inc., Hoboken, NJ, 2004.
Luthcke, S. B., Rowlands, D. D., Williams, T. A., and Sirota, M.: Reduction of ICESat systematic geolocation errors and the impact on ice sheet elevation change detection, Geophys. Res. Lett., 32(4), L21S05, https://doi.org/10.1029/2005GL023689, 2005.
Magruder, L., Silverberg, E., Webb, C., and Schutz, B.: In situ timing and pointing verification of the ICESat altimeter using a ground-based system, Geophys. Res. Lett., 32(5), L21S04, https://doi.org/10.1029/2005GL023504, 2005.
METI/NASA/USGS: ASTER Global DEM Validation Summary Report, Tech. rep., METI/ERSDAC, NASA/LPDAAC, USGS/EROS, 2009.
Miller, P. E., Kunz, M., Mills, J. P., King, M. A., Murray, T., James, T. D., and Marsh, S. H.: Assessment of Glacier Volume Change Using ASTER-Based Surface Matching of Historical Photography, IEEE T. Geosci. Remote, 47, 1971–1979, https://doi.org/10.1109/TGRS.2009.2012702, 2009.
Moholdt, G., Hagen, J. O., Eiken, T., and Schuler, T. V.: Geometric changes and mass balance of the Austfonna ice cap, Svalbard, The Cryosphere, 4, 21–34, https://doi.org/10.5194/tc-4-21-2010, 2010a.
Moholdt, G., Nuth, C., Hagen, J., and Kohler, J.: Recent elevation changes of Svalbard glaciers derived from ICESat laser altimetry, Remote Sens. Environ., 114, 2756–2767, https://doi.org/10.1016/j.rse.2010.06.008, 2010b.
M{ü}ller, K.: Microwave penetration in polar snow and ice: Implications for GPR and SAR, Department of Geosciences, University of Oslo, 2011.
Muskett, R. R., Lingle, C. S., Sauber, J. M., Post, A. S., Tangborn, W. V., Rabus, B. T., and Echelmeyer, K. A.: Airborne and spaceborne DEM- and laser altimetry-derived surface elevation and volume changes of the Bering Glacier system, Alaska, USA, and Yukon, Canada, 1972–2006, J. Glaciol., 55, 316–326, https://doi.org/10.3189/002214309788608750, 2009.
NASA, NGA, DLR, and ASI: Shuttle Radar Topography Mission (SRTM) Elevation Data Set, http://seamless.usgs.gov (last access: 12 August 2010), 2002.
Nuth, C.: Quantification and interpretation of glacier elevation changes, Ph.D. thesis, Dept. of Geosciences, University of Oslo, 2011.
Nuth, C., Kohler, J., Aas, H. F., Brandt, O., and Hagen, J. O.: Glacier geometry and elevation changes on Svalbard (1936–90): a baseline dataset, Ann. Glaciol., 46, 106–116, https://doi.org/10.3189/172756407782871440, 2007.
Nuth, C., Moholdt, G., Kohler, J., Hagen, J. O., and K{ä}{ä}b, A.: Svalbard glacier elevation changes and contribution to sea level rise, J. Geophys. Res.-Earth, 115, F01008, https://doi.org/10.1029/2008JF001223, 2010.
Oerlemans, J., Bassford, R. P., Chapman, W., Dowdeswell, J. A., Glazovsky, A. F., Hagen, J. O., Melvold, K., de Wildt, M. D., and van de Wal, R. S. W.: Estimating the contribution of Arctic glaciers to sea-level change in the next 100 years, Ann. Glaciol., 42, 230–236, https://doi.org/10.3189/172756405781812745, 2005.
Paul, F.: Calculation of glacier elevation changes with SRTM: is there an elevation-dependent bias?, J. Glaciol., 54, 945–946, https://doi.org/10.3189/002214308787779960, 2008.
Paul, F. and Haeberli, W.: Spatial variability of glacier elevation changes in the Swiss Alps obtained from two digital elevation models, Geophys. Res. Lett., 35, L21502, https://doi.org/10.1029/2008GL034718, 2008.
Peduzzi, P., Herold, C., and Silverio, W.: Assessing high altitude glacier thickness, volume and area changes using field, GIS and remote sensing techniques: the case of Nevado Coropuna (Peru), The Cryosphere, 4, 313–323, https://doi.org/10.5194/tc-4-313-2010, 2010.
Pritchard, H. D., Arthern, R. J., Vaughan, D. G., and Edwards, L. A.: Extensive dynamic thinning on the margins of the Greenland and Antarctic ice sheets, Nature, 461, 971–975, https://doi.org/10.1038/nature08471, 2009.
Quincey, D. J. and Glasser, N. F.: Morphological and ice-dynamical changes on the Tasman Glacier, New Zealand, 1990–2007, Global Planet. Change, 68, 185–197, https://doi.org/10.1016/j.gloplacha.2009.05.003, 2009.
Rabus, B., Eineder, M., Roth, A., and Bamler, R.: The shuttle radar topography mission – a new class of digital elevation models acquired by spaceborne radar, ISPRS J. Photogramm. Remote S., 57, 241–262, https://doi.org/10.1016/S0924-2716(02)00124-7, 2003.
Racoviteanu, A. E., Manley, W. F., Arnaud, Y., and Williams, M. W.: Evaluating digital elevation models for glaciologic applications: An example from Nevado Coropuna, Peruvian Andes, Global Planet. Change, 59, 110–125, https://doi.org/10.1016/j.gloplacha.2006.11.036, 2007.
Rignot, E., Echelmeyer, K., and Krabill, W.: Penetration depth of interferometric synthetic-aperture radar signals in snow and ice, Geophys. Res. Lett., 28, 3501–3504, https://doi.org/10.1029/2000GL012484, 2001.
Rignot, E., Rivera, A., and Casassa, G.: Contribution of the Patagonia Icefields of South America to sea level rise, Science, 302, 434–437, https://doi.org/10.1126/science.1087393, 2003.
Rodriguez, E., Morris, C. S., and Belz, J. E.: A global assessment of the SRTM performance, Photogramm. Eng. Rem. S., 72, 249–260, 2006.
Rolstad, C., Haug, T., and Denby, B.: Spatially integrated geodetic glacier mass balance and its uncertainty based on geostatistical analysis: application to the western Svartisen ice cap, Norway, J. Glaciol., 55, 666–680, https://doi.org/10.3189/002214309789470950, 2009.
Rosen, P. A., Hensley, S., Joughin, I. R., Li, F. K., Madsen, S. N., Rodriguez, E., and Goldstein, R. M.: Synthetic aperture radar interferometry – Invited paper, Proceedings IEEE, 88, 333–382, https://doi.org/10.1109/5.838084, 2000.
Schenk, T.: Digital Photogrammetry, vol. 1, TerraScience, Laurelville, Ohio, 1999.
Schenk, T., Csatho, B., van der Veen, C. J., Brecher, H., Ahn, Y., and Yoon, T.: Registering imagery to ICESat data for measuring elevation changes on Byrd Glacier, Antarctica, Geophys. Res. Lett., 32(4), L23S05, https://doi.org/10.1029/2005GL024328, 2005.
Schiefer, E., Menounos, B., and Wheate, R.: Recent volume loss of British Columbian glaciers, Canada, Geophys. Res. Lett., 34, L16503, https://doi.org/10.1029/2007GL030780, 2007.
Shuman, C. A., Zwally, H. J., Schutz, B. E., Brenner, A. C., DiMarzio, J. P., Suchdeo, V. P., and Fricker, H. A.: ICESat Antarctic elevation data: Preliminary precision and accuracy assessment, Geophys. Res. Lett., 33(4), L07501, https://doi.org/10.1029/2005GL025227, 2006.
Skinner, B.: Measurement of twentieth century ice loss on the Tasman Glacier, New Zealand, New Zealand, J. Geol. Geophys., 7, 796–803, 1964.
Sund, M., Eiken, T., Hagen, J. O., and K{ä}{ä}b, A.: Svalbard surge dynamics derived from geometric changes, Ann. Glaciol., 50, 50-60, https://doi.org/10.3189/172756409789624265, 2009.
Surazakov, A. B. and Aizen, V. B.: Estimating volume change of mountain glaciers using SRTM and map-based topographic data, IEEE T. Geosci. Remote, 44, 2991–2995, https://doi.org/10.1109/TGRS.2006.875357, 2006.
Toutin, T.: Three-dimensional topographic mapping with ASTER stereo data in rugged topography, IEEE T. Geosci. Remote, 40, 2241–2247, https://doi.org/10.1109/TGRS.2002.80287, 2002.
Toutin, T.: Review article: Geometric processing of remote sensing images: models, algorithms and methods, Int. J. Remote Sens., 25, 1893–1924, https://doi.org/10.1080/0143116031000101611, 2004.
Toutin, T.: ASTER DEMs for geomatic and geoscientific applications: a review, Int. J. Remote Sens., 29, 1855–1875, https://doi.org/10.1080/01431160701408477, 2008.
Van Niel, T. G., McVicar, T. R., Li, L. T., Gallant, J. C., and Yang, Q. K.: The impact of misregistration on SRTM and DEM image differences, Remote Sens. Environ., 112, 2430–2442, https://doi.org/10.1016/j.rse.2007.11.003, 2008.
Wilson, J. and Gallant, J.: Terrain Analysis, Principles and Applications, John Wiley & Sons, Inc., New York, 2000.
Zwally, H. J., Schutz, R., Bentley, C., Bufton, J., Herring, T., Minster, J., Spinhirne, J., and Thomas, R.: GLAS/ICESat L2 Global ElevationData V031, Febuary 2003 to November 2009, http://nsidc.org/data/icesat/index.html, last access: 1 September 2010, Digital Media, National Snow and Ice Data Center, 2010a.
Zwally, H. J., Schutz, R., Bentley, C., Bufton, J., Herring, T., Minster, J., Spinhirne, J., and Thomas., R.: GLAS/ICESat L2 Global Land Surface Altimetry Data V531, Febuary 2003 to November 2009, http://nsidc.org/data/icesat/index.html, last access: 1 September 2010, Digital Media, National Snow and Ice Data Center, 2010b.
Zwally, H. J., Schutz, B., Abdalati, W., Abshire, J., Bentley, C., Brenner, A., Bufton, J., Dezio, J., Hancock, D., Harding, D., Herring, T., Minster, B., Quinn, K., Palm, S., Spinhirne, J., and Thomas, R.: ICESat's laser measurements of polar ice, atmosphere, ocean, and land, J. Geodynam., 34, 405–445, https://doi.org/10.1016/S0264-3707(02)00042-X, 2002.
