Articles | Volume 11, issue 4
https://doi.org/10.5194/tc-11-1781-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-11-1781-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Aug 2017
Research article |
| 01 Aug 2017
Impact of MODIS sensor calibration updates on Greenland Ice Sheet surface reflectance and albedo trends
Kimberly A. Casey
CORRESPONDING AUTHOR
Thayer School of Engineering, Dartmouth College, Hanover, NH
03755, USA
Cryospheric Sciences Lab, NASA Goddard Space Flight Center,
Greenbelt, MD 20771, USA
now at: Land Remote Sensing Program, US
Geological Survey, Reston, VA 20192, USA
Chris M. Polashenski
Thayer School of Engineering, Dartmouth College, Hanover, NH
03755, USA
Cold Regions Research and Engineering Laboratory, Alaska Projects
Office, US Army Corps of Engineers, Fairbanks, AK 99709, USA
Justin Chen
Department of Computer Science, Stanford University, Stanford, CA 94305, USA
Marco Tedesco
Lamont–Doherty Earth Observatory, Columbia University, NY 10964,
USA
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
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We use repeat airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S. We find small–scale variability in snow accumulation based on the snow radar subsurface layering, indicating areas of strong wind redistribution are prevalent at 88° S. There is no slope–independent relationship between surface roughness and accumulation.
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The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Nicholas C. Wright, Chris M. Polashenski, Scott T. McMichael, and Ross A. Beyer
The Cryosphere, 14, 3523–3536, https://doi.org/10.5194/tc-14-3523-2020, https://doi.org/10.5194/tc-14-3523-2020, 2020
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This work presents a new dataset of sea ice surface fractions along NASA Operation IceBridge flight tracks created by processing hundreds of thousands of aerial images. These results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. We find preliminary evidence that first-year ice frequently has a lower melt pond fraction than adjacent multiyear ice, contrary to established knowledge in the sea ice community.
Michael Studinger, Brooke C. Medley, Kelly M. Brunt, Kimberly A. Casey, Nathan T. Kurtz, Serdar S. Manizade, Thomas A. Neumann, and Thomas B. Overly
The Cryosphere, 14, 3287–3308, https://doi.org/10.5194/tc-14-3287-2020, https://doi.org/10.5194/tc-14-3287-2020, 2020
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We use repeat airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S. We find small–scale variability in snow accumulation based on the snow radar subsurface layering, indicating areas of strong wind redistribution are prevalent at 88° S. There is no slope–independent relationship between surface roughness and accumulation.
Shujie Wang, Marco Tedesco, Patrick Alexander, Min Xu, and Xavier Fettweis
The Cryosphere, 14, 2687–2713, https://doi.org/10.5194/tc-14-2687-2020, https://doi.org/10.5194/tc-14-2687-2020, 2020
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Glacial algal blooms play a significant role in darkening the Greenland Ice Sheet during summertime. The dark pigments generated by glacial algae could substantially reduce the bare ice albedo and thereby enhance surface melt. We used satellite data to map the spatial distribution of glacial algae and characterized the seasonal growth pattern and interannual trends of glacial algae in southwestern Greenland. Our study is important for bridging microbial activities with ice sheet mass balance.
Kimberly A. Casey, Cecile S. Rousseaux, Watson W. Gregg, Emmanuel Boss, Alison P. Chase, Susanne E. Craig, Colleen B. Mouw, Rick A. Reynolds, Dariusz Stramski, Steven G. Ackleson, Annick Bricaud, Blake Schaeffer, Marlon R. Lewis, and Stéphane Maritorena
Earth Syst. Sci. Data, 12, 1123–1139, https://doi.org/10.5194/essd-12-1123-2020, https://doi.org/10.5194/essd-12-1123-2020, 2020
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An increase in spectral resolution in forthcoming remote-sensing missions will improve our ability to understand and characterize aquatic ecosystems. We organize and provide a global compilation of high spectral resolution inherent and apparent optical property data from polar, midlatitude, and equatorial open-ocean, estuary, coastal, and inland waters. The data are intended to aid in development of remote-sensing data product algorithms and to perform calibration and validation activities.
Colleen Mortimer, Lawrence Mudryk, Chris Derksen, Kari Luojus, Ross Brown, Richard Kelly, and Marco Tedesco
The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, https://doi.org/10.5194/tc-14-1579-2020, 2020
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Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Marco Tedesco and Xavier Fettweis
The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, https://doi.org/10.5194/tc-14-1209-2020, 2020
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Unprecedented atmospheric conditions occurring in the summer of 2019 over Greenland promoted new record or close-to-record values of mass loss. Summer of 2019 was characterized by an exceptional persistence of anticyclonic conditions that enhanced melting.
Marco Tedesco, Steven McAlpine, and Jeremy R. Porter
Nat. Hazards Earth Syst. Sci., 20, 907–920, https://doi.org/10.5194/nhess-20-907-2020, https://doi.org/10.5194/nhess-20-907-2020, 2020
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Quantifying the exposure of house property to extreme weather events is crucial to study their impact on economy. Here, we show that value of property exposed to Hurricane Florence in September 2018 was USD 52 billion vs. USD 10 billion that would have occurred at the beginning of the 19th century due to urban expansion that increased after 1950s and the increasing number of houses built near water, showing the importance of accounting for the distribution of new buildings in risk and exposure.
Dominic A. Winski, Tyler J. Fudge, David G. Ferris, Erich C. Osterberg, John M. Fegyveresi, Jihong Cole-Dai, Zayta Thundercloud, Thomas S. Cox, Karl J. Kreutz, Nikolas Ortman, Christo Buizert, Jenna Epifanio, Edward J. Brook, Ross Beaudette, Jeffrey Severinghaus, Todd Sowers, Eric J. Steig, Emma C. Kahle, Tyler R. Jones, Valerie Morris, Murat Aydin, Melinda R. Nicewonger, Kimberly A. Casey, Richard B. Alley, Edwin D. Waddington, Nels A. Iverson, Nelia W. Dunbar, Ryan C. Bay, Joseph M. Souney, Michael Sigl, and Joseph R. McConnell
Clim. Past, 15, 1793–1808, https://doi.org/10.5194/cp-15-1793-2019, https://doi.org/10.5194/cp-15-1793-2019, 2019
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A deep ice core was recently drilled at the South Pole to understand past variations in the Earth's climate. To understand the information contained within the ice, we present the relationship between the depth and age of the ice in the South Pole Ice Core. We found that the oldest ice in our record is from 54 302 ± 519 years ago. Our results show that, on average, 7.4 cm of snow falls at the South Pole each year.
Marilena Oltmanns, Fiammetta Straneo, and Marco Tedesco
The Cryosphere, 13, 815–825, https://doi.org/10.5194/tc-13-815-2019, https://doi.org/10.5194/tc-13-815-2019, 2019
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By combining reanalysis, weather station and satellite data, we show that increases in surface melt over Greenland are initiated by large-scale precipitation events year-round. Estimates from a regional climate model suggest that the initiated melting more than doubled between 1988 and 2012, amounting to ~28 % of the overall melt and revealing that, despite the involved mass gain, precipitation events are contributing to the ice sheet's decline.
Sandra L. LeGrand, Chris Polashenski, Theodore W. Letcher, Glenn A. Creighton, Steven E. Peckham, and Jeffrey D. Cetola
Geosci. Model Dev., 12, 131–166, https://doi.org/10.5194/gmd-12-131-2019, https://doi.org/10.5194/gmd-12-131-2019, 2019
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This paper reviews the history, code, and performance of the three dust emission schemes embedded in the WRF-Chem model, including the GOCART, AFWA, and UoC dust emission schemes, and provides the first full documentation of the AFWA scheme. A simulation case study is provided to explore differences in model output. Results highlight the relative strengths of each scheme, indicate reasons for disagreement, and demonstrate the need for improved terrain characterization in dust emission models.
Kang Yang, Laurence C. Smith, Leif Karlstrom, Matthew G. Cooper, Marco Tedesco, Dirk van As, Xiao Cheng, Zhuoqi Chen, and Manchun Li
The Cryosphere, 12, 3791–3811, https://doi.org/10.5194/tc-12-3791-2018, https://doi.org/10.5194/tc-12-3791-2018, 2018
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A high-resolution spatially lumped hydrologic surface routing model is proposed to simulate meltwater transport over bare ice surfaces. In an ice-covered catchment, meltwater is routed by slow interfluve flow (~10−3–10−4 m s−1) followed by fast open-channel flow (~10−1 m s−1). Seasonal evolution of supraglacial stream-river networks substantially alters the magnitude and timing of moulin discharge with implications for subglacial hydrology and ice dynamics.
Rajashree Tri Datta, Marco Tedesco, Cecile Agosta, Xavier Fettweis, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 12, 2901–2922, https://doi.org/10.5194/tc-12-2901-2018, https://doi.org/10.5194/tc-12-2901-2018, 2018
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Surface melting on the East Antarctic Peninsula (East AP) has been linked to ice shelf collapse, including the Larsen A (1995) and Larsen B (2002) ice shelves. Regional climate models (RCMs) are a valuable tool to understand how wind patterns and general warming can impact the stability of ice shelves through surface melt. Here, we evaluate one such RCM (Modèle Atmosphérique Régionale) over the East AP, including the remaining Larsen C ice shelf, by comparing it to satellite and ground data.
Aleksey Malinka, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski
The Cryosphere, 12, 1921–1937, https://doi.org/10.5194/tc-12-1921-2018, https://doi.org/10.5194/tc-12-1921-2018, 2018
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Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. The melt pond reflectance is modeled in the framework of the radiative transfer theory and validated with field observations. It improves understanding of melting sea ice and enables better parameterization of the surface in Arctic atmospheric remote sensing (clouds, aerosols, trace gases) and re-evaluating Arctic climatic feedbacks at a new accuracy level.
Achim Heilig, Olaf Eisen, Michael MacFerrin, Marco Tedesco, and Xavier Fettweis
The Cryosphere, 12, 1851–1866, https://doi.org/10.5194/tc-12-1851-2018, https://doi.org/10.5194/tc-12-1851-2018, 2018
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This paper presents data on temporal changes in snow and firn, which were not available before. We present data on water infiltration in the percolation zone of the Greenland Ice Sheet that improve our understanding of liquid water retention in snow and firn and mass transfer. We compare those findings with model simulations. It appears that simulated accumulation in terms of SWE is fairly accurate, while modeling of the individual parameters density and liquid water content is incorrect.
Nicholas C. Wright and Chris M. Polashenski
The Cryosphere, 12, 1307–1329, https://doi.org/10.5194/tc-12-1307-2018, https://doi.org/10.5194/tc-12-1307-2018, 2018
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Satellites, planes, and drones capture thousands of images of the Arctic sea ice cover each year. However, few methods exist to reliably and automatically process these images for scientifically usable information. In this paper, we take the next step towards a community standard for analyzing these images by presenting an open-source platform able to accurately classify sea ice imagery into several important surface types.
Julienne C. Stroeve, John R. Mioduszewski, Asa Rennermalm, Linette N. Boisvert, Marco Tedesco, and David Robinson
The Cryosphere, 11, 2363–2381, https://doi.org/10.5194/tc-11-2363-2017, https://doi.org/10.5194/tc-11-2363-2017, 2017
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As the sea ice has declined strongly in recent years there has been a corresponding increase in Greenland melting. While both are likely a result of changes in atmospheric circulation patterns that favor summer melt, this study evaluates whether or not sea ice reductions around the Greenland ice sheet are having an influence on Greenland summer melt through enhanced sensible and latent heat transport from open water areas onto the ice sheet.
Lora S. Koenig, Alvaro Ivanoff, Patrick M. Alexander, Joseph A. MacGregor, Xavier Fettweis, Ben Panzer, John D. Paden, Richard R. Forster, Indrani Das, Joesph R. McConnell, Marco Tedesco, Carl Leuschen, and Prasad Gogineni
The Cryosphere, 10, 1739–1752, https://doi.org/10.5194/tc-10-1739-2016, https://doi.org/10.5194/tc-10-1739-2016, 2016
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Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor surface mass balance in order to improve sea-level rise predictions. Here, we quantify the net annual accumulation over the Greenland Ice Sheet, which comprises the largest component of surface mass balance, at a higher spatial resolution than currently available using high-resolution, airborne-radar data.
Patrick M. Alexander, Marco Tedesco, Nicole-Jeanne Schlegel, Scott B. Luthcke, Xavier Fettweis, and Eric Larour
The Cryosphere, 10, 1259–1277, https://doi.org/10.5194/tc-10-1259-2016, https://doi.org/10.5194/tc-10-1259-2016, 2016
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We compared satellite-derived estimates of spatial and seasonal variations in Greenland Ice Sheet mass with a set of model simulations, revealing an agreement between models and satellite estimates for the ice-sheet-wide seasonal fluctuations in mass, but disagreement at finer spatial scales. The model simulations underestimate low-elevation mass loss. Improving the ability of models to capture variations and trends in Greenland Ice Sheet mass is important for estimating future sea level rise.
Marco Tedesco, Sarah Doherty, Xavier Fettweis, Patrick Alexander, Jeyavinoth Jeyaratnam, and Julienne Stroeve
The Cryosphere, 10, 477–496, https://doi.org/10.5194/tc-10-477-2016, https://doi.org/10.5194/tc-10-477-2016, 2016
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Summer surface albedo over Greenland decreased at a rate of 0.02 per decade between 1996 and 2012. The decrease is due to snow grain growth, the expansion of bare ice areas, and trends in light-absorbing impurities on snow and ice surfaces. Neither aerosol models nor in situ observations indicate increasing trends in impurities in the atmosphere over Greenland. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening.
M. Navari, S. A. Margulis, S. M. Bateni, M. Tedesco, P. Alexander, and X. Fettweis
The Cryosphere, 10, 103–120, https://doi.org/10.5194/tc-10-103-2016, https://doi.org/10.5194/tc-10-103-2016, 2016
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An ensemble batch smoother was used to assess the feasibility of generating a reanalysis estimate of the Greenland ice sheet (GrIS) surface mass fluxes (SMF) via integrating measured ice surface temperatures with a regional climate model estimate. The results showed that assimilation of IST were able to overcome uncertainties in meteorological forcings that drive the GrIS surface processes. We showed that the proposed methodology is able to generate posterior reanalysis estimates of the SMF.
L. S. Koenig, D. J. Lampkin, L. N. Montgomery, S. L. Hamilton, J. B. Turrin, C. A. Joseph, S. E. Moutsafa, B. Panzer, K. A. Casey, J. D. Paden, C. Leuschen, and P. Gogineni
The Cryosphere, 9, 1333–1342, https://doi.org/10.5194/tc-9-1333-2015, https://doi.org/10.5194/tc-9-1333-2015, 2015
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The Greenland Ice Sheet is storing meltwater through the winter season just below its surface in buried supraglacial lakes. Airborne radar from Operation IceBridge between 2009 and 2012 was used to detect buried lakes, distributed extensively around the margin of the ice sheet. The volume of retained water in the buried lakes is likely insignificant compared to the total mass loss from the ice sheet but has important implications for ice temperatures.
C. J. Legleiter, M. Tedesco, L. C. Smith, A. E. Behar, and B. T. Overstreet
The Cryosphere, 8, 215–228, https://doi.org/10.5194/tc-8-215-2014, https://doi.org/10.5194/tc-8-215-2014, 2014
M. Tedesco, X. Fettweis, T. Mote, J. Wahr, P. Alexander, J. E. Box, and B. Wouters
The Cryosphere, 7, 615–630, https://doi.org/10.5194/tc-7-615-2013, https://doi.org/10.5194/tc-7-615-2013, 2013
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Snow depth estimation on leadless landfast ice using Cryo2Ice satellite observations
Five decades of Abramov glacier dynamics reconstructed with multi-sensor optical remote sensing
Updated Arctic melt pond fraction dataset and trends 2002–2023 using ENVISAT and Sentinel-3 remote sensing data
Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data
Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region
Impact assessment of snow thickness, sea ice density and water density in CryoSat-2-derived sea ice thickness
The Pléiades Glacier Observatory: high-resolution digital elevation models and ortho-imagery to monitor glacier change
Multitemporal UAV lidar detects seasonal heave and subsidence on palsas
Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites
Pan-Arctic sea ice concentration from SAR and passive microwave
Land surface temperature trends derived from Landsat imagery in the Swiss Alps
A framework for automated supraglacial lake detection and depth retrieval in ICESat-2 photon data across the Greenland and Antarctic ice sheets
Evaluation of the Snow CCI Snow Covered Area Product within a Mountain Snow Water Equivalent Reanalysis
Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements
Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method
Land cover succession for recently drained lakes in permafrost on the Yamal Peninsula, Western Siberia
Assessing sea ice microwave emissivity up to submillimeter waves from airborne and satellite observations
Simulation of Arctic snow microwave emission in surface-sensitive atmosphere channels
AWI-ICENet1: a convolutional neural network retracker for ice altimetry
Monthly velocity and seasonal variations of the Mont Blanc glaciers derived from Sentinel-2 between 2016 and 2024
Retrieval of snow and soil properties for forward radiative transfer modeling of airborne Ku-band SAR to estimate snow water equivalent: the Trail Valley Creek 2018/19 snow experiment
Evaluating L-band InSAR snow water equivalent retrievals with repeat ground-penetrating radar and terrestrial lidar surveys in northern Colorado
Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar
Improved records of glacier flow instabilities using customized NASA autoRIFT (CautoRIFT) applied to PlanetScope imagery
Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data
The AutoICE Challenge
Brief communication: Not as dirty as they look, flawed airborne and satellite snow spectra
Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data
Multiple modes of shoreline change along the Alaskan Beaufort Sea observed using ICESat-2 altimetry and satellite imagery
Tower-based C-band radar measurements of an alpine snowpack
A study of sea ice topography in the Weddell and Ross seas using dual-polarimetric TanDEM-X imagery
Grounded Ridge Detection and Characterization along the Alaskan Arctic Coastline using ICESat-2 Surface Height Retrievals
Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models
Mapping surface hoar from near-infrared texture in a laboratory
Sentinel-1 detection of ice slabs on the Greenland Ice Sheet
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago, 2016–2022
SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Lake ice break-up in Greenland: timing and spatiotemporal variability
Mapping Seasonal Snow Melting in Karakoram Using SAR and Topographic Data
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
Importance of ice elasticity in simulating tide-induced grounding line variations along prograde bed slopes
MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Niklas Bohn, Edward H. Bair, Philip G. Brodrick, Nimrod Carmon, Robert O. Green, Thomas H. Painter, and David R. Thompson
The Cryosphere, 19, 1279–1302, https://doi.org/10.5194/tc-19-1279-2025, https://doi.org/10.5194/tc-19-1279-2025, 2025
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A new type of Earth-observing satellite is measuring reflected sunlight in all its colors. These measurements can be used to characterize snow properties, which give us important information about climate change. In our work, we emphasize the difficulties of obtaining these properties from rough mountainous regions and present a solution to the problem. Our research was inspired by the growing number of new satellite technologies and the increasing challenges associated with climate change.
Kirk M. Scanlan, Anja Rutishauser, and Sebastian B. Simonsen
The Cryosphere, 19, 1221–1239, https://doi.org/10.5194/tc-19-1221-2025, https://doi.org/10.5194/tc-19-1221-2025, 2025
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An ice sheet's surface modulates its response to climate change, and it is therefore critical to monitor how it evolves through time. Here, we investigate novel measurements of Greenland surface roughness based on the strength of reflected local airborne and pan-Greenland satellite radar signals. These measurements respond to roughness at scales typically larger than those considered in mass balance modelling while highlighting the scale dependency of surface roughness that is often overlooked.
Polona Itkin
The Cryosphere, 19, 1135–1151, https://doi.org/10.5194/tc-19-1135-2025, https://doi.org/10.5194/tc-19-1135-2025, 2025
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Radar satellite images of sea ice were analyzed to understand how sea ice moves and deforms. These data are noisy, especially when looking at small details. A method was developed to filter out the noise. The filtered data were used to monitor how ice plates stretch and compress over time, revealing slow healing of ice fractures. Cohesive clusters of ice plates that move together were studied too. These methods provide climate-relevant insights into the dynamic nature of winter sea ice cover.
Barbara Widhalm, Annett Bartsch, Tazio Strozzi, Nina Jones, Artem Khomutov, Elena Babkina, Marina Leibman, Rustam Khairullin, Mathias Göckede, Helena Bergstedt, Clemens von Baeckmann, and Xaver Muri
The Cryosphere, 19, 1103–1133, https://doi.org/10.5194/tc-19-1103-2025, https://doi.org/10.5194/tc-19-1103-2025, 2025
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Mapping soil moisture in Arctic permafrost regions is crucial for various activities, but it is challenging with typical satellite methods due to the landscape's diversity. Seasonal freezing and thawing cause the ground to periodically rise and subside. Our research demonstrates that this seasonal ground settlement, measured with Sentinel-1 satellite data, is larger in areas with wetter soils. This method helps to monitor permafrost degradation.
Annett Bartsch, Xaver Muri, Markus Hetzenecker, Kimmo Rautiainen, Helena Bergstedt, Jan Wuite, Thomas Nagler, and Dmitry Nicolsky
The Cryosphere, 19, 459–483, https://doi.org/10.5194/tc-19-459-2025, https://doi.org/10.5194/tc-19-459-2025, 2025
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We developed a robust freeze–thaw detection approach, applying a constant threshold to Copernicus Sentinel-1 data that is suitable for tundra regions. All global, coarser-resolution products, tested with the resulting benchmarking dataset, are of value for freeze–thaw retrieval, although differences were found depending on the seasons, particularly during the spring and autumn transition.
Monojit Saha, Julienne Stroeve, Dustin Isleifson, John Yackel, Vishnu Nandan, Jack Christopher Landy, and Hoi Ming Lam
The Cryosphere, 19, 325–346, https://doi.org/10.5194/tc-19-325-2025, https://doi.org/10.5194/tc-19-325-2025, 2025
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Snow on sea ice is vital for near-shore sea ice geophysical and biological processes. Past studies have measured snow depths using the satellite altimeters Cryosat-2 and ICESat-2 (Cryo2Ice), but estimating sea surface height from leadless landfast sea ice remains challenging. Snow depths from Cryo2Ice are compared to in situ data after adjusting for tides. Realistic snow depths are retrieved, but differences in roughness, satellite footprints, and snow geophysical properties are identified.
Enrico Mattea, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Atanu Bhattacharya, Sajid Ghuffar, Martina Barandun, and Martin Hoelzle
The Cryosphere, 19, 219–247, https://doi.org/10.5194/tc-19-219-2025, https://doi.org/10.5194/tc-19-219-2025, 2025
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We reconstruct the evolution of terminus position, ice thickness, and surface flow velocity of the reference Abramov glacier (Kyrgyzstan) from 1968 to present. We describe a front pulsation in the early 2000s and the multi-annual present-day buildup of a new pulsation. Such dynamic instabilities can challenge the representativity of Abramov as a reference glacier. For our work we used satellite‑based optical remote sensing from multiple platforms, including recently declassified archives.
Larysa Istomina, Hannah Niehaus, and Gunnar Spreen
The Cryosphere, 19, 83–105, https://doi.org/10.5194/tc-19-83-2025, https://doi.org/10.5194/tc-19-83-2025, 2025
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Melt water puddles, or melt ponds on top of the Arctic sea ice, are a good measure of the Arctic climate state. In the context of recent climate warming, the Arctic has warmed about 4 times faster than the rest of the world, and a long-term dataset of the melt pond fraction is needed to be able to model the future development of the Arctic climate. We present such a dataset, produce 2002–2023 trends and highlight a potential melt regime shift with drastic regional trends of + 20 % per decade.
Weiran Li, Sanne B. M. Veldhuijsen, and Stef Lhermitte
The Cryosphere, 19, 37–61, https://doi.org/10.5194/tc-19-37-2025, https://doi.org/10.5194/tc-19-37-2025, 2025
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This study used a machine learning approach to estimate the densities over the Antarctic Ice Sheet, particularly in the areas where the snow is usually dry. The motivation is to establish a link between satellite parameters to snow densities, as measurements are difficult for people to take on site. It provides valuable insights into the complexities of the relationship between satellite parameters and firn density and provides potential for further studies.
Sonia Dupuis, Frank-Michael Göttsche, and Stefan Wunderle
The Cryosphere, 18, 6027–6059, https://doi.org/10.5194/tc-18-6027-2024, https://doi.org/10.5194/tc-18-6027-2024, 2024
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The Arctic has experienced pronounced warming the last few decades. This warming threatens ecosystems, vegetation dynamics, snow cover duration, and permafrost. Traditional monitoring methods like stations and climate models lack the detail needed. Land surface temperature (LST) data derived from satellites offer high spatial and temporal coverage, perfect for studying changes in the Arctic. In particular, LST information from AVHRR provides a 40-year record, valuable for analysing trends.
Imke Sievers, Henriette Skourup, and Till A. S. Rasmussen
The Cryosphere, 18, 5985–6004, https://doi.org/10.5194/tc-18-5985-2024, https://doi.org/10.5194/tc-18-5985-2024, 2024
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To derive sea ice thickness (SIT) from satellite freeboard (FB) observations, assumptions about snow thickness, snow density, sea ice density and water density are needed. These parameters are impossible to observe alongside FB, so many existing products use empirical values. In this study, modeled values are used instead. The modeled values and otherwise commonly used empirical values are evaluated against in situ observations. In a further analysis, the influence on SIT is quantified.
Etienne Berthier, Jérôme Lebreton, Delphine Fontannaz, Steven Hosford, Joaquín Muñoz-Cobo Belart, Fanny Brun, Liss M. Andreassen, Brian Menounos, and Charlotte Blondel
The Cryosphere, 18, 5551–5571, https://doi.org/10.5194/tc-18-5551-2024, https://doi.org/10.5194/tc-18-5551-2024, 2024
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Repeat elevation measurements are crucial for monitoring glacier health and to understand how glaciers affect river flows and sea level. Until recently, high-resolution elevation data were mostly available for polar regions and High Mountain Asia. Our project, the Pléiades Glacier Observatory, now provides high-resolution topographies of 140 glacier sites worldwide. This is a novel and open dataset to monitor the impact of climate change on glaciers at high resolution and accuracy.
Cas Renette, Mats Olvmo, Sofia Thorsson, Björn Holmer, and Heather Reese
The Cryosphere, 18, 5465–5480, https://doi.org/10.5194/tc-18-5465-2024, https://doi.org/10.5194/tc-18-5465-2024, 2024
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We used a drone to monitor seasonal changes in the height of subarctic permafrost mounds (palsas). With five drone flights in 1 year, we found a seasonal fluctuation of ca. 15 cm as a result of freeze–thaw cycles. On one mound, a large area sank down between each flight as a result of permafrost thaw. The approach of using repeated high-resolution scans from such a drone is unique for such environments and highlights its effectiveness in capturing the subtle dynamics of permafrost landscapes.
Zachary Hoppinen, Ross T. Palomaki, George Brencher, Devon Dunmire, Eric Gagliano, Adrian Marziliano, Jack Tarricone, and Hans-Peter Marshall
The Cryosphere, 18, 5407–5430, https://doi.org/10.5194/tc-18-5407-2024, https://doi.org/10.5194/tc-18-5407-2024, 2024
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This study uses radar imagery from the Sentinel-1 satellite to derive snow depth from increases in the returning energy. These retrieved depths are then compared to nine lidar-derived snow depths across the western United State to assess the ability of this technique to be used to monitor global snow distributions. We also qualitatively compare the changes in underlying Sentinel-1 amplitudes against both the total lidar snow depths and nine automated snow monitoring stations.
Tore Wulf, Jørgen Buus-Hinkler, Suman Singha, Hoyeon Shi, and Matilde Brandt Kreiner
The Cryosphere, 18, 5277–5300, https://doi.org/10.5194/tc-18-5277-2024, https://doi.org/10.5194/tc-18-5277-2024, 2024
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Here, we present ASIP: a new and comprehensive deep-learning-based methodology to retrieve high-resolution sea ice concentration with accompanying well-calibrated uncertainties from satellite-based active and passive microwave observations at a pan-Arctic scale for all seasons. In a comparative study against pan-Arctic ice charts and well-established passive-microwave-based sea ice products, we show that ASIP generalizes well to the pan-Arctic region.
Deniz Tobias Gök, Dirk Scherler, and Hendrik Wulf
The Cryosphere, 18, 5259–5276, https://doi.org/10.5194/tc-18-5259-2024, https://doi.org/10.5194/tc-18-5259-2024, 2024
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We derived Landsat Collection 2 land surface temperature (LST) trends in the Swiss Alps using a harmonic model with a linear trend. Validation with LST data from 119 high-altitude weather stations yielded robust results, but Landsat LST trends are biased due to unstable acquisition times. The bias varies with topographic slope and aspect. We discuss its origin and propose a simple correction method in relation to modeled changes in shortwave radiation.
Philipp Sebastian Arndt and Helen Amanda Fricker
The Cryosphere, 18, 5173–5206, https://doi.org/10.5194/tc-18-5173-2024, https://doi.org/10.5194/tc-18-5173-2024, 2024
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We develop a method for ice-sheet-scale retrieval of supraglacial meltwater depths using ICESat-2 photon data. We report results for two drainage basins in Greenland and Antarctica during two contrasting melt seasons, where our method reveals a total of 1249 lake segments up to 25 m deep. The large volume and wide variety of accurate depth data that our method provides enable the development of data-driven models of meltwater volumes in satellite imagery.
Haorui Sun, Yiwen Fang, Steven Margulis, Colleen Mortimer, Lawrence Mudryk, and Chris Derksen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3213, https://doi.org/10.5194/egusphere-2024-3213, 2024
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The European Space Agency's Snow Climate Change Initiative (Snow CCI) developed a high-quality snow cover extent and snow water equivalent (SWE) Climate Data Record. However, gaps exist in complex terrain due to challenges in using passive microwave sensing and in-situ measurements. This study presents a methodology to fill the mountain SWE gap using Snow CCI Snow Cover Fraction within a Bayesian SWE reanalysis framework, with potential applications in untested regions and with other sensors.
Brenton A. Wilder, Joachim Meyer, Josh Enterkine, and Nancy F. Glenn
The Cryosphere, 18, 5015–5029, https://doi.org/10.5194/tc-18-5015-2024, https://doi.org/10.5194/tc-18-5015-2024, 2024
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Remotely sensed properties of snow are dependent on accurate terrain information, which for a lot of the cryosphere and seasonal snow zones is often insufficient in accuracy. However, as we show in this paper, we can bypass this issue by optimally solving for the terrain by utilizing the raw radiance data returned to the sensor. This method performed well when compared to validation datasets and has the potential to be used across a variety of different snow climates.
Benjamin J. Wallis, Anna E. Hogg, Yikai Zhu, and Andrew Hooper
The Cryosphere, 18, 4723–4742, https://doi.org/10.5194/tc-18-4723-2024, https://doi.org/10.5194/tc-18-4723-2024, 2024
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The grounding line, where ice begins to float, is an essential variable to understand ice dynamics, but in some locations it can be challenging to measure with established techniques. Using satellite data and a new method, Wallis et al. measure the grounding line position of glaciers and ice shelves in the Antarctic Peninsula and find retreats of up to 16.3 km have occurred since the last time measurements were made in the 1990s.
Clemens von Baeckmann, Annett Bartsch, Helena Bergstedt, Aleksandra Efimova, Barbara Widhalm, Dorothee Ehrich, Timo Kumpula, Alexander Sokolov, and Svetlana Abdulmanova
The Cryosphere, 18, 4703–4722, https://doi.org/10.5194/tc-18-4703-2024, https://doi.org/10.5194/tc-18-4703-2024, 2024
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Lakes are common features in Arctic permafrost areas. Land cover change following their drainage needs to be monitored since it has implications for ecology and the carbon cycle. Satellite data are key in this context. We compared a common vegetation index approach with a novel land-cover-monitoring scheme. Land cover information provides specific information on wetland features. We also showed that the bioclimatic gradients play a significant role after drainage within the first 10 years.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
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Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
Veit Helm, Alireza Dehghanpour, Ronny Hänsch, Erik Loebel, Martin Horwath, and Angelika Humbert
The Cryosphere, 18, 3933–3970, https://doi.org/10.5194/tc-18-3933-2024, https://doi.org/10.5194/tc-18-3933-2024, 2024
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We present a new approach (AWI-ICENet1), based on a deep convolutional neural network, for analysing satellite radar altimeter measurements to accurately determine the surface height of ice sheets. Surface height estimates obtained with AWI-ICENet1 (along with related products, such as ice sheet height change and volume change) show improved and unbiased results compared to other products. This is important for the long-term monitoring of ice sheet mass loss and its impact on sea level rise.
Fabrizio Troilo, Niccolò Dematteis, Francesco Zucca, Martin Funk, and Daniele Giordan
The Cryosphere, 18, 3891–3909, https://doi.org/10.5194/tc-18-3891-2024, https://doi.org/10.5194/tc-18-3891-2024, 2024
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The study of glacier sliding along slopes is relevant in many aspects of glaciology. We processed Sentinel-2 satellite optical images of Mont Blanc, obtaining surface velocities of 30 glaciers between 2016 and 2024. The study revealed different behaviours and velocity variations that have relationships with glacier morphology. A velocity anomaly was observed in some glaciers of the southern side in 2020–2022, but its origin needs to be investigated further.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
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Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Taha Sadeghi Chorsi, Franz J. Meyer, and Timothy H. Dixon
The Cryosphere, 18, 3723–3740, https://doi.org/10.5194/tc-18-3723-2024, https://doi.org/10.5194/tc-18-3723-2024, 2024
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The active layer thaws and freezes seasonally. The annual freeze–thaw cycle of the active layer causes significant surface height changes due to the volume difference between ice and liquid water. We estimate the subsidence rate and active-layer thickness (ALT) for part of northern Alaska for summer 2017 to 2022 using interferometric synthetic aperture radar and lidar. ALT estimates range from ~20 cm to larger than 150 cm in area. Subsidence rate varies between close points (2–18 mm per month).
Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle
The Cryosphere, 18, 3571–3590, https://doi.org/10.5194/tc-18-3571-2024, https://doi.org/10.5194/tc-18-3571-2024, 2024
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There are sometimes gaps in global glacier velocity records produced using satellite image feature-tracking algorithms during times of rapid glacier acceleration, which hinders the study of glacier flow processes. We present an open-source pipeline for customizing the feature-tracking parameters and for including images from an additional source. We applied it to five glaciers and found that it produced accurate velocity data that supplemented their velocity records during rapid acceleration.
Jordan N. Herbert, Mark S. Raleigh, and Eric E. Small
The Cryosphere, 18, 3495–3512, https://doi.org/10.5194/tc-18-3495-2024, https://doi.org/10.5194/tc-18-3495-2024, 2024
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Automated stations measure snow properties at a single point but are frequently used to validate data that represent much larger areas. We use lidar snow depth data to see how often the mean snow depth surrounding a snow station is within 10 cm of the snow station depth at different scales. We found snow stations overrepresent the area-mean snow depth in ~ 50 % of cases, but the direction of bias at a site is temporally consistent, suggesting a site could be calibrated to the surrounding area.
Andreas Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif Toudal Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando Jose Pena Cantu, Javier Noa Turnes, Jinman Park, Linlin Xu, Katharine Andrea Scott, David Anthony Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil Curtis Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan Nicolaas van Rijn, Jens Jakobsen, Martin Samuel James Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde Brandt Kreiner
The Cryosphere, 18, 3471–3494, https://doi.org/10.5194/tc-18-3471-2024, https://doi.org/10.5194/tc-18-3471-2024, 2024
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The AutoICE challenge encouraged the development of deep learning models to map multiple aspects of sea ice – the amount of sea ice in an area and the age and ice floe size – using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. Professionally drawn operational sea ice charts were used as a reference. A total of 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
Edward H. Bair, Dar A. Roberts, David R. Thompson, Philip G. Brodrick, Brenton A. Wilder, Niklas Bohn, Chris J. Crawford, Nimrod Carmon, Carrie M. Vuyovich, and Jeff Dozier
EGUsphere, https://doi.org/10.5194/egusphere-2024-1681, https://doi.org/10.5194/egusphere-2024-1681, 2024
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Key to the success of future satellite missions is understanding snowmelt in our warming climate, having implications for nearly 2 billion people. An obstacle is that an artifact, called the hook, is often mistaken for soot or dust. Instead it is caused by 3 amplifying effects: 1) a background reflectance that is too dark; 2) level terrain assumptions; 3) and differences in optical constants of ice. Sensor calibration and directional effects may also contribute. Solutions are presented.
Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
Marnie B. Bryant, Adrian A. Borsa, Claire C. Masteller, Roger J. Michaelides, Matthew R. Siegfried, Adam P. Young, and Eric J. Anderson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1656, https://doi.org/10.5194/egusphere-2024-1656, 2024
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We measure shoreline change across a 7-km stretch of coastline on the Alaskan Beaufort Sea Coast between 2019–2022 using multispectral imagery from Planet and satellite altimetry from ICESat-2. We find that shoreline change rates are high and variable, and that different shoreline types show distinct patterns of change in shoreline position and topography. We discuss how the observed changes may be driven by both time-varying ocean and air conditions and spatial variations in morphology.
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Mätzler, and Hans Lievens
The Cryosphere, 18, 3177–3193, https://doi.org/10.5194/tc-18-3177-2024, https://doi.org/10.5194/tc-18-3177-2024, 2024
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To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
Lanqing Huang and Irena Hajnsek
The Cryosphere, 18, 3117–3140, https://doi.org/10.5194/tc-18-3117-2024, https://doi.org/10.5194/tc-18-3117-2024, 2024
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Interferometric synthetic aperture radar can measure the total freeboard of sea ice but can be biased when radar signals penetrate snow and ice. We develop a new method to retrieve the total freeboard and analyze the regional variation of total freeboard and roughness in the Weddell and Ross seas. We also investigate the statistical behavior of the total freeboard for diverse ice types. The findings enhance the understanding of Antarctic sea ice topography and its dynamics in a changing climate.
Kennedy A. Lange, Alice C. Bradley, Kyle Duncan, and Sinéad L. Farrell
EGUsphere, https://doi.org/10.5194/egusphere-2024-1885, https://doi.org/10.5194/egusphere-2024-1885, 2024
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Grounded sea ice ridges stabilize nearshore sea ice by anchoring it in the seafloor. In this study, we develop a method to identify grounded ridges in satellite data, and measure the height, depth, distance from shore, and width of a thousand ridges across the Alaskan Arctic, finding regional differences in these metrics across the coastline. This method lays the groundwork for a better understanding of nearshore ice stability, holding importance for Arctic community food security and safety.
Michael Studinger, Benjamin E. Smith, Nathan Kurtz, Alek Petty, Tyler Sutterley, and Rachel Tilling
The Cryosphere, 18, 2625–2652, https://doi.org/10.5194/tc-18-2625-2024, https://doi.org/10.5194/tc-18-2625-2024, 2024
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We use green lidar data and natural-color imagery over sea ice to quantify elevation biases potentially impacting estimates of change in ice thickness of the polar regions. We complement our analysis using a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse. We find that biased elevations exist in airborne and spaceborne data products from green lidars.
James Dillon, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds
The Cryosphere, 18, 2557–2582, https://doi.org/10.5194/tc-18-2557-2024, https://doi.org/10.5194/tc-18-2557-2024, 2024
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Surface hoar crystals are snow grains that form when vapor deposits on a snow surface. They create a weak layer in the snowpack that can cause large avalanches to occur. Thus, determining when and where surface hoar forms is a lifesaving matter. Here, we developed a means of mapping surface hoar using remote-sensing technologies. We found that surface hoar displayed heightened texture, hence the variability of brightness. Using this, we created surface hoar maps with an accuracy upwards of 95 %.
Riley Culberg, Roger J. Michaelides, and Julie Z. Miller
The Cryosphere, 18, 2531–2555, https://doi.org/10.5194/tc-18-2531-2024, https://doi.org/10.5194/tc-18-2531-2024, 2024
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Ice slabs enhance meltwater runoff from the Greenland Ice Sheet. Therefore, it is important to understand their extent and change in extent over time. We present a new method for detecting ice slabs in satellite radar data, which we use to map ice slabs at 500 m resolution across the entire ice sheet in winter 2016–2017. Our results provide better spatial coverage and resolution than previous maps from airborne radar and lay the groundwork for long-term monitoring of ice slabs from space.
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, https://doi.org/10.5194/tc-18-2473-2024, 2024
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The total Arctic sea-ice area (SIA), which is an important climate indicator, is routinely monitored with the help of satellite measurements. Uncertainties in observations of sea-ice concentration (SIC) partly cancel out when summed up to the total SIA, but the degree to which this is happening has been unclear. Here we find that the uncertainty daily SIA estimates, based on uncertainties in SIC, are about 300 000 km2. The 2002 to 2017 September decline in SIA is approx. 105 000 ± 9000 km2 a−1.
Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
The Cryosphere, 18, 2257–2276, https://doi.org/10.5194/tc-18-2257-2024, https://doi.org/10.5194/tc-18-2257-2024, 2024
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We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest and when the Sun was behind the satellite. From this work, we learned that the position of the Sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024, https://doi.org/10.5194/tc-18-2207-2024, 2024
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A dataset of 20 radar satellite acquisitions and near-simultaneous helicopter-based surveys of the ice topography during the MOSAiC expedition is constructed and used to train a variety of deep learning algorithms. The results give realistic insights into the accuracy of retrieval of measured ice classes using modern deep learning models. The models able to learn from the spatial distribution of the measured sea ice classes are shown to have a clear advantage over those that cannot.
Christoph Posch, Jakob Abermann, and Tiago Silva
The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024, https://doi.org/10.5194/tc-18-2035-2024, 2024
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Radar beams from satellites exhibit reflection differences between water and ice. This condition, as well as the comprehensive coverage and high temporal resolution of the Sentinel-1 satellites, allows automatically detecting the timing of when ice cover of lakes in Greenland disappear. We found that lake ice breaks up 3 d later per 100 m elevation gain and that the average break-up timing varies by ±8 d in 2017–2021, which has major implications for the energy budget of the lakes.
Shiyi Li, Lanqing Huang, Philipp Bernhard, and Irena Hajnsek
EGUsphere, https://doi.org/10.5194/egusphere-2024-942, https://doi.org/10.5194/egusphere-2024-942, 2024
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This work presented an improved method for seasonal wet snow mapping in Karakoram. SAR and topographic data were effectively integrated for robust wet snow classification in complex mountainous terrain. Applying the method to large scale Sentinel-1 imagery, we have generated wet snow maps covering the three major water basins in Karakraom over four years (2017–2021). Critical snow variables were further derived from the maps and provided valuable insights on regional snow melting dynamics.
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere, 18, 1817–1834, https://doi.org/10.5194/tc-18-1817-2024, https://doi.org/10.5194/tc-18-1817-2024, 2024
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Understanding snow phenology (SP) and its possible feedback are important. We reveal spatiotemporal heterogeneous SP on the Tibetan Plateau (TP) and the mediating effects from meteorological, topographic, and environmental factors on it. The direct effects of meteorology on SP are much greater than the indirect effects. Topography indirectly effects SP, while vegetation directly effects SP. This study contributes to understanding past global warming and predicting future trends on the TP.
Natalya Maslennikova, Pietro Milillo, Kalyana Babu Nakshatrala, Roberto Ballarini, Aaron Stubblefield, and Luigi Dini
EGUsphere, https://doi.org/10.5194/egusphere-2024-875, https://doi.org/10.5194/egusphere-2024-875, 2024
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Analyzing remote sensing radar data over three Antarctic glaciers, we observe short-term grounding line migrations. We simulate this phenomenon using viscous and viscoelastic continuum mechanics models. We quantify the sensitivity of the grounding zone width to bedrock slope, glacier thickness, and ice flow speed. Comparisons of the models’ predictions with the observations highlight the necessity of including ice elasticity in non-Newtonian models of glacier ice.
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024, https://doi.org/10.5194/tc-18-1621-2024, 2024
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This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoICE challenge. Ablation studies revealed that incorporating brightness temperature data and spatial–temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
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Short summary
We analyzed Greenland Ice Sheet (GrIS) average summer surface reflectance and albedo (2001–2016). MODIS Collection 6 data show a decreased magnitude of change over time due to sensor calibration corrections. Spectral band maps provide insight into GrIS surface processes likely occurring. Correctly measuring albedo and surface reflectance changes over time is crucial to monitoring atmosphere–ice interactions and ice mass balance. The results are applicable to many long-term MODIS studies.
We analyzed Greenland Ice Sheet (GrIS) average summer surface reflectance and albedo...
