Articles | Volume 9, issue 1
https://doi.org/10.5194/tc-9-357-2015
© 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-9-357-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Comparing C- and L-band SAR images for sea ice motion estimation
Finnish Meteorological Institute, Marine Research Programme, Helsinki, PB 503, 00101 Finland
S. Siiriä
Finnish Meteorological Institute, Marine Research Programme, Helsinki, PB 503, 00101 Finland
J. Karvonen
Finnish Meteorological Institute, Marine Research Programme, Helsinki, PB 503, 00101 Finland
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
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We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Martti Honkanen, Mika Aurela, Juha Hatakka, Lumi Haraguchi, Sami Kielosto, Timo Mäkelä, Jukka Seppälä, Simo-Matti Siiriä, Ken Stenbäck, Juha-Pekka Tuovinen, Pasi Ylöstalo, and Lauri Laakso
Biogeosciences, 21, 4341–4359, https://doi.org/10.5194/bg-21-4341-2024, https://doi.org/10.5194/bg-21-4341-2024, 2024
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The exchange of CO2 between the sea and the atmosphere was studied in the Archipelago Sea, Baltic Sea, in 2017–2021, using an eddy covariance technique. The sea acted as a net source of CO2 with an average yearly emission of 27.1 gC m-2 yr-1, indicating that the marine ecosystem respired carbon that originated elsewhere. The yearly CO2 emission varied between 18.2–39.2 gC m-2 yr-1, mostly due to the yearly variation of ecosystem carbon uptake.
Juha Karvonen, Eero Rinne, Heidi Sallila, Petteri Uotila, and Marko Mäkynen
The Cryosphere, 16, 1821–1844, https://doi.org/10.5194/tc-16-1821-2022, https://doi.org/10.5194/tc-16-1821-2022, 2022
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We propose a method to provide sea ice thickness (SIT) estimates over a test area in the Arctic utilizing radar altimeter (RA) measurement lines and C-band SAR imagery. The RA data are from CryoSat-2, and SAR imagery is from Sentinel-1. By combining them we get a SIT grid covering the whole test area instead of only narrow measurement lines from RA. This kind of SIT estimation can be extended to cover the whole Arctic (and Antarctic) for operational SIT monitoring.
Alexandru Gegiuc, Juha Karvonen, Jouni Vainio, Eero Rinne, Roman Bednarik, and Marko Mäkynen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-8, https://doi.org/10.5194/tc-2022-8, 2022
Publication in TC not foreseen
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Current users of operational ice charts call for quantitative uncertainty information, which the current ice charts lack. In this work we demonstrate for the first time the use of eye tracking methodology as a non-invasive way to identify elements behind uncertainties typically introduced during the process of visual mapping of sea ice information in satellite radar imagery. Uncertainty information would increase reliability of the manually produced ice charts and increase navigation safety.
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
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We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Juha Karvonen
The Cryosphere, 12, 2595–2607, https://doi.org/10.5194/tc-12-2595-2018, https://doi.org/10.5194/tc-12-2595-2018, 2018
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We have developed an algorithm for detecting LFI over a test area in the Kara and Barents seas using daily Sentinel-1 dual-polarized (HH/HV) SAR mosaics. Both SAR channels have been used jointly for reliably estimating the LFI area. We have generated daily LFI area estimates for a period ranging from Oct 2015 to Aug 2017. The data were also evaluated against Russian AARI ice charts, and the correspondence was rather good. According to this study the algorithm is suitable for operational use.
Alexandru Gegiuc, Markku Similä, Juha Karvonen, Mikko Lensu, Marko Mäkynen, and Jouni Vainio
The Cryosphere, 12, 343–364, https://doi.org/10.5194/tc-12-343-2018, https://doi.org/10.5194/tc-12-343-2018, 2018
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The paper demonstrates the use of SAR imagery in retrieving ice-ridging information for navigation. Based on image segmentation and several texture features extracted from SAR, we perform a classification into four ridging categories from level ice to heavily ridged ice. We compare our results with the manually drawn ice charts over the Baltic Sea. We conclude that the SAR-based product is more detailed than FIS and can be used by ships (non-icebreakers) to aid independent navigation.
J. Karvonen
The Cryosphere, 10, 29–42, https://doi.org/10.5194/tc-10-29-2016, https://doi.org/10.5194/tc-10-29-2016, 2016
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We present an algorithm for continuous ice drift estimation based on coastal and ship radar data. The ice dynamics are estimated based on automatically selected ice targets (virtual buoys, VBs) and an optical flow algorithm. VBs are added when necessary. We show some examples of the tracking and quantities derived from the VB motion.
J. Karvonen
The Cryosphere, 8, 1639–1650, https://doi.org/10.5194/tc-8-1639-2014, https://doi.org/10.5194/tc-8-1639-2014, 2014
Related subject area
Remote Sensing
Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass
New radar altimetry datasets of Greenland and Antarctic surface elevation, 1991–2012
Evaluating sensitivity of optical snow grain size retrievals to radiative transfer models, shape parameters, and inversion techniques
Detection and reconstruction of rock glacier kinematics over 24 years (2000–2024) from Landsat imagery
Brief communication: Not as dirty as they look, flawed airborne and satellite snow spectra
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
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UAV LiDAR surveys and machine learning improves snow depth and water equivalent estimates in the boreal landscapes
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Inland migration of near-surface crevasses in the Amundsen Sea Sector, West Antarctica
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Benchmarking passive-microwave-satellite-derived freeze–thaw datasets
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Julien Meloche, Nicolas R. Leroux, Benoit Montpetit, Vincent Vionnet, and Chris Derksen
The Cryosphere, 19, 2949–2962, https://doi.org/10.5194/tc-19-2949-2025, https://doi.org/10.5194/tc-19-2949-2025, 2025
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Measuring snow mass from radar measurements is possible with information on 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 layers yielding richer information but at increased computational cost. Here, we show the capabilities of a new method for simplifying a complex snowpack while preserving the scattering behavior of the snowpack and conserving its mass.
Maya Raghunath Suryawanshi, Malcolm McMillan, Jennifer Maddalena, Fanny Piras, Jérémie Aublanc, Jean-Alexis Daguzé, Clara Grau, and Qi Huang
The Cryosphere, 19, 2855–2880, https://doi.org/10.5194/tc-19-2855-2025, https://doi.org/10.5194/tc-19-2855-2025, 2025
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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 cryospheric applications.
James W. Dillon, Christopher P. Donahue, Evan N. Schehrer, and Kevin D. Hammonds
The Cryosphere, 19, 2913–2933, https://doi.org/10.5194/tc-19-2913-2025, https://doi.org/10.5194/tc-19-2913-2025, 2025
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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; 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.
Diego Cusicanqui, Pascal Lacroix, Xavier Bodin, Benjamin Aubrey Robson, Andreas Kääb, and Shelley MacDonell
The Cryosphere, 19, 2559–2581, https://doi.org/10.5194/tc-19-2559-2025, https://doi.org/10.5194/tc-19-2559-2025, 2025
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This study presents a robust methodological approach to detect and analyse rock glacier kinematics using Landsat 7/Landsat 8 imagery. In the semiarid Andes, 382 landforms were monitored, showing an average velocity of 0.37 ± 0.07 m yr⁻¹ over 24 years, with rock glaciers moving 23 % faster. Results demonstrate the feasibility of using medium-resolution optical imagery, combined with radar interferometry, to monitor rock glacier kinematics with widely available satellite datasets.
Edward H. Bair, Dar A. Roberts, David R. Thompson, Philip G. Brodrick, Brenton A. Wilder, Niklas Bohn, Christopher J. Crawford, Nimrod Carmon, Carrie M. Vuyovich, and Jeff Dozier
The Cryosphere, 19, 2315–2320, https://doi.org/10.5194/tc-19-2315-2025, https://doi.org/10.5194/tc-19-2315-2025, 2025
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Key to the success of future satellite missions is understanding snowmelt in our warming climate, as this has 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 three amplifying effects: (1) background reflectance that is too dark, (2) an assumption of level terrain, and (3) differences in optical constants of ice. Sensor calibration and directional effects may also contribute. Solutions are presented.
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.
Maiju Ylönen, Hannu Marttila, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, and Pertti Ala-Aho
EGUsphere, https://doi.org/10.5194/egusphere-2025-1297, https://doi.org/10.5194/egusphere-2025-1297, 2025
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We collected snow depth maps four times during the winter from two different sites and used them as input for a model to predict daily snow depth and snow water equivalent (SWE). Our results show similar snow depth patterns in different sites, where snow depths are the highest in forests and forest gaps and the lowest in open areas. The results can extend operational snow course measurements and their temporal and spatial coverage, helping hydrological forecasting and water resource management.
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.
Francesca Carletti, Carlo Marin, Chiara Ghielmini, Mathias Bavay, and Michael Lehning
EGUsphere, https://doi.org/10.5194/egusphere-2025-974, https://doi.org/10.5194/egusphere-2025-974, 2025
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This work presents the first high-resolution dataset of wet snow properties for satellite applications. With it, we validate links between Sentinel-1 backscattering and snowmelt stages, and investigate scattering mechanisms through a radiative transfer model. We disclose the influence of liquid water content and surface roughness at different melting stages and address future challenges, such as capturing large-scale scattering mechanisms and enhancing radiative transfer modules for wet snow.
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.
Andreas J. Dietz and Sebastian Roessler
EGUsphere, https://doi.org/10.5194/egusphere-2025-382, https://doi.org/10.5194/egusphere-2025-382, 2025
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The "Global SnowPack" product of the German Aerospace Center (DLR) contains binary information about the presence or absence of snow on a global scale since the year 2000. Now incorporating new input datasets, it was possible to increase the spatial resolution to 370 m. The detailed accuracy assessment proves the feasibility of the applied methods to remove data gaps caused by clouds and polar darkness.
Robert Ricker, Thomas Lavergne, Stefan Hendricks, Stephan Paul, Emily Down, Mari Anne Killie, and Marion Bocquet
EGUsphere, https://doi.org/10.5194/egusphere-2025-359, https://doi.org/10.5194/egusphere-2025-359, 2025
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We developed a new method to map Arctic sea ice thickness daily using satellite measurements. We address a problem similar to motion blur in photography. Traditional methods collect satellite data over one month to get a full picture of Arctic sea ice thickness. But like in photos of moving objects, long exposure leads to motion blur, making it difficult to identify certain features in the sea ice maps. Our method corrects for this motion blur, providing a sharper view of the evolving sea ice.
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.
Laurane Charrier, Amaury Dehecq, Lei Guo, Fanny Brun, Romain Millan, Nathan Lioret, Luke Copland, Nathan Maier, Christine Dow, and Paul Halas
EGUsphere, https://doi.org/10.5194/egusphere-2024-3409, https://doi.org/10.5194/egusphere-2024-3409, 2025
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While global annual glacier velocities are openly accessible, sub-annual velocity time series are still lacking. This hinders our ability to understand flow processes and the integration of these observations in numerical models. We introduce an open source Python package called TICOI to fuses multi-temporal and multi-sensor image-pair velocities produced by different processing chains to produce standardized sub-annual velocity products.
Christopher Horvat, Ellen M. Buckley, and Madelyn Stewart
EGUsphere, https://doi.org/10.5194/egusphere-2024-3864, https://doi.org/10.5194/egusphere-2024-3864, 2025
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Since the late 1970s, standard methods for observing sea ice area from satellite contrast its passive microwave emissions to that of the ocean. Since 2018, a new satellite, ICESat-2, may offer a unique and independent way to sample sea ice area at high skill and resolution, using laser altimetry. We develop a new product of sea ice area for the Arctic using ICESat-2 and constrain the biases associated with the use of altimetry instead of passive microwave emissions.
Juliette Ortet, Arnaud Mialon, Alain Royer, Mike Schwank, Manu Holmberg, Kimmo Rautiainen, Simone Bircher-Adrot, Andreas Colliander, Yann Kerr, and Alexandre Roy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3963, https://doi.org/10.5194/egusphere-2024-3963, 2025
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We propose a new method to determine the ground surface temperature under the snowpack in the Arctic area from satellite observations. The obtained ground temperatures time series were evaluated over 21 reference sites in Northern Alaska and compared with ground temperatures obtained with global models. The method is excessively promising for monitoring ground temperature below the snowpack and studying the spatiotemporal variability thanks to 15 years of observations over the whole Arctic area.
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.
Karl Kortum, Suman Singha, and Gunnar Spreen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3351, https://doi.org/10.5194/egusphere-2024-3351, 2024
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Improved sea ice observations are essential to understanding the processes that lead to the strong warming effect currently being observed in the Arctic. In this work, we combine complementary satellite measurement techniques and find remarkable correlations between the two observations. This allows us to expand the coverage of ice topography measurements to a scope and resolution that could not previously be observed.
Ellen M. Buckley, Christopher Horvat, and Pittayuth Yoosiri
EGUsphere, https://doi.org/10.5194/egusphere-2024-3861, https://doi.org/10.5194/egusphere-2024-3861, 2024
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Sea ice coverage is a key indicator of changes in polar and global climate. There is a long (40+ year) record of sea ice concentration and area from passive microwave measurements. In this work we show the biases in these data based on high resolution imagery. We also suggest the use of ICESat-2, a high resolution satellite laser, that can supplement the passive microwave estimates.
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.
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.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3251, https://doi.org/10.5194/egusphere-2024-3251, 2024
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Due to the melt events in recent decades, the snow condition over Greenland has been changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry, and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event has a long-lasting impact on the volume scattering of Greenland firn. This impact cannot fully recover due to the recent and more frequent melt events.
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.
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.
Jack C. Landy, Claude de Rijke-Thomas, Carmen Nab, Isobel Lawrence, Isolde A. Glissenaar, Robbie D. C. Mallett, Renée M. Fredensborg Hansen, Alek Petty, Michel Tsamados, Amy R. Macfarlane, and Anne Braakmann-Folgmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2904, https://doi.org/10.5194/egusphere-2024-2904, 2024
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In this study we use three satellites to test the planned remote sensing approach of the upcoming mission CRISTAL over sea ice: that its dual radars will accurately measure the heights of the top and base of snow sitting atop floating sea ice floes. Our results suggest that CRISTAL's dual radars won’t necessarily measure the snow top and base under all conditions. We find that accurate height measurements depend much more on surface roughness than on snow properties, as is commonly assumed.
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.
Zhimeng Zhang, Shannon Brown, and Andreas Colliander
EGUsphere, https://doi.org/10.5194/egusphere-2024-2578, https://doi.org/10.5194/egusphere-2024-2578, 2024
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Retrieving accurate water vapor and temperature profiles over land is challenging due to uncertainties in estimating surface emissions. To address this, we've developed an iterative method that combines atmospheric retrieval with surface emissions estimation. Using ATMS data across various microwave frequencies, we successfully tracked atmospheric temperature and humidity changes. Testing against Radiosonde data showed our method is efficient and accurate, especially in detecting melting events.
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.
Filippo Emilio Scarsi, Alessandro Battaglia, Maximilian Maahn, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2024-1917, https://doi.org/10.5194/egusphere-2024-1917, 2024
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Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), determining that WIVERN will provide much better estimates than CloudSat, and at much smaller spatial and temporal scales.
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.
Cited articles
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Short summary
Satellite radar images are used for detecting and quantifying the motion of sea ice. Traditionally C-band radar images have been used for this purpose. The technique has been shown to work with other frequency bands. This work compares C-band and L-band images for the Baltic Sea. We also show that two images of different bands can be used for sea ice motion estimation.
Satellite radar images are used for detecting and quantifying the motion of sea ice....