Articles | Volume 9, issue 4
https://doi.org/10.5194/tc-9-1567-2015
© Author(s) 2015. 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-9-1567-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Aug 2015
Research article |
| 12 Aug 2015
Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 2: Case studies and trends of sea ice albedo and melt ponds in the Arctic for years 2002–2011
L. Istomina
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen, Bremen, Germany
G. Heygster
Institute of Environmental Physics, University of Bremen, Bremen, Germany
M. Huntemann
Institute of Environmental Physics, University of Bremen, Bremen, Germany
H. Marks
Institute of Environmental Physics, University of Bremen, Bremen, Germany
C. Melsheimer
Institute of Environmental Physics, University of Bremen, Bremen, Germany
E. Zege
B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus
A. Malinka
B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus
A. Prikhach
B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus
I. Katsev
B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus
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Aleksey Malinka, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski
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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.
Peng Lu, Matti Leppäranta, Bin Cheng, Zhijun Li, Larysa Istomina, and Georg Heygster
The Cryosphere, 12, 1331–1345, https://doi.org/10.5194/tc-12-1331-2018, https://doi.org/10.5194/tc-12-1331-2018, 2018
Short summary
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It is the first time that the color of melt ponds on Arctic sea ice was quantitatively and thoroughly investigated. We answer the question of why the color of melt ponds can change and what the physical and optical reasons are that lead to such changes. More importantly, melt-pond color was provided as potential data in determining ice thickness, especially under the summer conditions when other methods such as remote sensing are unavailable.
Raul Cristian Scarlat, Christian Melsheimer, and Georg Heygster
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An obstacle in achieving reliable satellite measurements of atmospheric water vapour in the Arctic is the presence of sea ice. Here we have built on a previous method that achieves consistent atmospheric measurements over sea-ice-covered regions. The main focus was to adapt the method for better coverage in shallow-ice-covered and ice-free areas by accounting for the signal from the open-ocean surface. This approach extends the coverage from the central Arctic to the entire Arctic region.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Johannes Freitag, Georg Heygster, Larysa Istomina, Sepp Kipfstuhl, Anaïs Orsi, Michael Schäfer, and Manfred Wendisch
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The optical size of snow grains (ropt) affects the reflectivity of snow surfaces and thus the local surface energy budget in particular in polar regions. The temporal evolution of ropt retrieved from ground-based, airborne, and spaceborne remote sensing could reproduce optical in situ measurements for a 2-month period in central Antarctica (2013/14). The presented validation study provided a unique testbed for retrievals of ropt under Antarctic conditions where in situ data are scarce.
André Ehrlich, Eike Bierwirth, Larysa Istomina, and Manfred Wendisch
Atmos. Meas. Tech., 10, 3215–3230, https://doi.org/10.5194/amt-10-3215-2017, https://doi.org/10.5194/amt-10-3215-2017, 2017
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In the Arctic, uncertainties in passive solar remote sensing of cloud properties arise from uncertainties in the assumed spectral surface albedo, mainly determined by the generally unknown effective snow grain size. Therefore, a retrieval method is presented that simultaneously derives liquid water cloud and snow surface parameters, including cloud optical thickness, droplet effective radius, and effective snow grain size. Airborne measurements were used to test the retrieval procedure.
Aleksey Malinka, Eleonora Zege, Georg Heygster, and Larysa Istomina
The Cryosphere, 10, 2541–2557, https://doi.org/10.5194/tc-10-2541-2016, https://doi.org/10.5194/tc-10-2541-2016, 2016
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The number of melt ponds on Arctic summer sea ice and its reflectance are required for better climate modeling and weather prediction. In order to derive these quantities from optical satellite observations, simple analytical formulas for the bidirectional reflectance factor and albedo at direct and diffuse incidence are derived from basic assumptions and verified with in situ measurements made during the expedition ARK-XXVII/3 of research vessel Polarstern in 2012.
N. Ivanova, L. T. Pedersen, R. T. Tonboe, S. Kern, G. Heygster, T. Lavergne, A. Sørensen, R. Saldo, G. Dybkjær, L. Brucker, and M. Shokr
The Cryosphere, 9, 1797–1817, https://doi.org/10.5194/tc-9-1797-2015, https://doi.org/10.5194/tc-9-1797-2015, 2015
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Thirty sea ice algorithms are inter-compared and evaluated systematically over low and high sea ice concentrations, as well as in the presence of thin ice and melt ponds. A hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approach consists of a combination of two algorithms plus the implementation of a dynamic tie point and atmospheric correction of input brightness temperatures.
L. Istomina, G. Heygster, M. Huntemann, P. Schwarz, G. Birnbaum, R. Scharien, C. Polashenski, D. Perovich, E. Zege, A. Malinka, A. Prikhach, and I. Katsev
The Cryosphere, 9, 1551–1566, https://doi.org/10.5194/tc-9-1551-2015, https://doi.org/10.5194/tc-9-1551-2015, 2015
M. Huntemann, G. Heygster, L. Kaleschke, T. Krumpen, M. Mäkynen, and M. Drusch
The Cryosphere, 8, 439–451, https://doi.org/10.5194/tc-8-439-2014, https://doi.org/10.5194/tc-8-439-2014, 2014
Related subject area
Remote Sensing
Grounded ridge detection and characterization along the Alaska Arctic coastline using ICESat-2 surface height retrievals
Importance of ice elasticity in simulating tide-induced grounding line variations along prograde bed slopes
Evaluation of the Snow Climate Change Initiative (Snow CCI) snow-covered area product within a mountain snow water equivalent reanalysis
Multiple modes of shoreline change along the Alaskan Beaufort Sea observed using ICESat-2 altimetry and satellite imagery
Mapping seasonal snow melting in Karakoram using SAR and topographic data
Inland migration of near-surface crevasses in the Amundsen Sea Sector, West Antarctica
Do we still need reflectance? From radiance to snow properties in mountainous terrain: a case study with the EMIT imaging spectrometer
Greenland Ice Sheet surface roughness from Ku- and Ka-band radar altimetry surface echo strengths
Novel methods to study sea ice deformation, linear kinematic features and coherent dynamic clusters from imaging remote sensing data
InSAR-derived seasonal subsidence reflects spatial soil moisture patterns in Arctic lowland permafrost regions
Benchmarking passive-microwave-satellite-derived freeze–thaw datasets
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
Seasonality in Terminus Ablation Rates for the Glaciers in Kalaallit Nunaat (Greenland)
New Radar Altimetry Datasets of Greenland and Antarctic Surface Elevation, 1991–2012
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
Comparing High-Resolution Snow Mapping Approaches in Palsa Mires: UAS LiDAR vs. Machine Learning
Evaluating sensitivity of optical snow grain size retrievals to radiative transfer models, shape parameters, and inversion techniques
Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements
Radar Equivalent Snowpack: reducing the number of snow layers while retaining its microwave properties and bulk snow mass
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
Exploring microwave penetration into snow on Antarctic summer sea ice along CryoSat-2 and ICESat-2 (CRYO2ICE) orbit from multi-frequency air- and spaceborne altimetry
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
Detection and reconstruction of rock glaciers kinematic over 24 years (2000–2024) from Landsat imagery
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
Contrasting patterns of change in snowline altitude across five Himalayan catchments
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
Optimizing rock glaciers activity classification in South Tyrol (North-East Italy): integrating multisource data with statistical modelling
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
Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models
Kennedy A. Lange, Alice C. Bradley, Kyle Duncan, and Sinéad L. Farrell
The Cryosphere, 19, 2045–2065, https://doi.org/10.5194/tc-19-2045-2025, https://doi.org/10.5194/tc-19-2045-2025, 2025
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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 Alaska 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.
Natalya Ross, Pietro Milillo, Kalyana Nakshatrala, Roberto Ballarini, Aaron Stubblefield, and Luigi Dini
The Cryosphere, 19, 1995–2015, https://doi.org/10.5194/tc-19-1995-2025, https://doi.org/10.5194/tc-19-1995-2025, 2025
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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.
Haorui Sun, Yiwen Fang, Steven A. Margulis, Colleen Mortimer, Lawrence Mudryk, and Chris Derksen
The Cryosphere, 19, 2017–2036, https://doi.org/10.5194/tc-19-2017-2025, https://doi.org/10.5194/tc-19-2017-2025, 2025
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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.
Marnie B. Bryant, Adrian A. Borsa, Eric J. Anderson, Claire C. Masteller, Roger J. Michaelides, Matthew R. Siegfried, and Adam P. Young
The Cryosphere, 19, 1825–1847, https://doi.org/10.5194/tc-19-1825-2025, https://doi.org/10.5194/tc-19-1825-2025, 2025
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We measure shoreline change across a 7 km stretch of coastline on the Alaskan Beaufort Sea coast between 2019 and 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.
Shiyi Li, Lanqing Huang, Philipp Bernhard, and Irena Hajnsek
The Cryosphere, 19, 1621–1639, https://doi.org/10.5194/tc-19-1621-2025, https://doi.org/10.5194/tc-19-1621-2025, 2025
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This work presents an improved method for seasonal wet snow mapping in Karakoram using synthetic aperture radar (SAR) data and topographic data. This method enables robust wet snow classification in complex mountainous terrain. Large-scale wet snow maps were generated using the proposed method, covering three major water basins in Karakoram over 4 years (2017–2021). Crucial snow variables were further derived from the maps and provided valuable insights on regional snow melting dynamics.
Andrew O. Hoffman, Knut Christianson, Ching-Yao Lai, Ian Joughin, Nicholas Holschuh, Elizabeth Case, Jonathan Kingslake, and the GHOST science team
The Cryosphere, 19, 1353–1372, https://doi.org/10.5194/tc-19-1353-2025, https://doi.org/10.5194/tc-19-1353-2025, 2025
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We use satellite and ice-penetrating radar technology to segment crevasses in the Amundsen Sea Embayment. Inspection of satellite time series reveals inland expansion of crevasses where surface stresses have increased. We develop a simple model for the strength of densifying snow and show that these crevasses are likely restricted to the near surface. This result bridges discrepancies between satellite and lab experiments and reveals the importance of porosity on surface crevasse formation.
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.
Aman KC, Ellyn M. Enderlin, Dominik Fahrner, Twila Moon, and Dustin Carroll
EGUsphere, https://doi.org/10.5194/egusphere-2024-3543, https://doi.org/10.5194/egusphere-2024-3543, 2024
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The sum of ice flowing towards a glacier’s terminus and changes in the position of the terminus over time collectively make up terminus ablation. We found that terminus ablation has more seasonal variability than previously estimated from flux-based estimates of ice discharge. The findings are of importance in understanding timing and location of the freshwater input to the fjords, and surrounding ocean basins affecting local and regional ecosystems and ocean properties.
Maya Raghunath Suryawanshi, Malcolm McMillan, Jennifer Maddalena, Fanny Piras, Jérémie Aublanc, Jean-Alexis Daguzé, Clara Grau, and Qi Huang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3446, https://doi.org/10.5194/egusphere-2024-3446, 2024
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Increasing melting rates of the polar Ice Sheets are contributing more and more to sea level rise. Due to the remoteness and expanse of ice sheets these changes are mainly observed using satellites. However, the accuracy of these measurements depends on the processing of these datasets. Here we use advanced algorithms to provide improved historical ice sheet elevation measurements, derived from satellite altimeters flying between 1991 and 2012, which will benefit to cryospheric applications.
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.
Alexander Störmer, Timo Kumpula, Miguel Villoslada, Pasi Korpelainen, Henning Schumacher, and Benjamin Burkhard
EGUsphere, https://doi.org/10.5194/egusphere-2024-2862, https://doi.org/10.5194/egusphere-2024-2862, 2024
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Snow has a major impact on palsa development, yet understanding its distribution at small scale remains limited. We used LiDAR UAS and ground truth data in combination with machine learning to model snow distribution at three palsa sites. We identified extremes in snow depth corresponding to palsa topography, providing insights into the influence of snow distribution on their formation. The results demonstrate the applicability of machine learning for modeling snow distribution at a small scale.
James W. Dillon, Christopher P. Donahue, Evan N. Schehrer, and Kevin D. Hammonds
EGUsphere, https://doi.org/10.5194/egusphere-2024-3141, https://doi.org/10.5194/egusphere-2024-3141, 2024
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The optical grain size of snow controls albedo, playing a key role in Earth's energy balance. This parameter varies substantially in time and space, and thus accurate estimates are vital. Reflectance measurements can be used to map grain size, although results differ considerably depending on the algorithm and model used during retrieval. We perform a novel laboratory comparison to determine the optimal model, shape parameters, and retrieval algorithm for accurately estimating grain size.
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.
Julien Meloche, Nicolas R. Leroux, Benoit Montpetit, Vincent Vionnet, and Chris Derksen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3169, https://doi.org/10.5194/egusphere-2024-3169, 2024
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Measuring the snow mass from radar measurements is possible with information on the snow and a radar model to link the measurements to snow. A key variable in a retrieval is the number of snow layers, with more layer yielding richer information but at increased computational cost. Here, we show the capabilities of a new method to simplify a complex snowpack, while preserving the scattering behavior of the snowpack and conserving the mass.
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.
Renée M. Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut V. Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian B. Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ G. D. Casal
EGUsphere, https://doi.org/10.5194/egusphere-2024-2854, https://doi.org/10.5194/egusphere-2024-2854, 2024
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In December 2022, an airborne campaign collected unprecedented coincident multi-frequency radar and lidar data over sea ice along a CryoSat-2 and ICESat-2 (CRYO2ICE) orbit in the Weddell Sea useful for evaluating microwave penetration. We found limited snow penetration at Ka- and Ku-bands, with significant contributions from the air-snow interface, contradicting traditional assumptions. These findings challenge current methods for comparing air- and spaceborne altimeter estimates of sea ice.
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.
Diego Cusicanqui, Pascal Lacroix, Xavier Bodin, Benjamin Aubrey Robson, Andreas Kääb, and Shelley MacDonell
EGUsphere, https://doi.org/10.5194/egusphere-2024-2393, https://doi.org/10.5194/egusphere-2024-2393, 2024
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This study presents for the first time a robust methodological approach to detect and analyse rock glacier kinematics using 24 years of Landsat 7/8 imagery. Within a small region in the semi-arid andes, 382 movements were monitored showing an average velocity of 0.3 ± 0.07 m yr-1, with rock glaciers moving faster. We highlight the value of integrating optical imagery and radar interferometry supporting monitoring of rock glacier kinematics, using available medium-resolution optical imagery.
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.
Orie Sasaki, Evan Stewart Miles, Francesca Pellicciotti, Akiko Sakai, and Koji Fujita
EGUsphere, https://doi.org/10.5194/egusphere-2024-2026, https://doi.org/10.5194/egusphere-2024-2026, 2024
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This study proposes a new method to detect snowline altitude (SLA) using the Google Earth Engine platform with high-resolution satellite imagery, applicable anywhere in the world. Applying this method to five glaciated watersheds in the Himalayas reveals regional consistencies and differences in snow dynamics. We also investigate the primary controls of these dynamics by analyzing climatic factors and topographic characteristics.
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.
Chiara Crippa, Stefan Steger, Giovanni Cuozzo, Francesca Bearzot, Volkmar Mair, and Claudia Notarnicola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1511, https://doi.org/10.5194/egusphere-2024-1511, 2024
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Our study, focused on South Tyrol (NE Italy), develops an updated and comprehensive activity classification system for all rock glaciers in the current regional inventory. Using multisource products, we integrate climatic, morphological and DInSAR data in replicable routines and multivariate statistical methods producing a comprehensive classification based on the updated RGIK 2023 guidelines. Results leave only 3.5% of the features non-classified respect to the 13–18.5% of the previous studies.
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.
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.
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