Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4929-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-4929-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Oct 2025
Research article |
| 23 Oct 2025
| 23 Oct 2025
Similarities between sea ice area variations and satellite-derived terrestrial biosphere and cryosphere parameters across the Arctic
b.geos, Industriestrasse 1, 2100 Korneuburg, Austria
Rodrigue Tanguy
b.geos, Industriestrasse 1, 2100 Korneuburg, Austria
Helena Bergstedt
b.geos, Industriestrasse 1, 2100 Korneuburg, Austria
Clemens von Baeckmann
b.geos, Industriestrasse 1, 2100 Korneuburg, Austria
Hans Tømmervik
Norwegian Institute for Nature Research, Fram – High North Research Centre for Climate and the Environment, 9296 Tromsø, Norway
Marc Macias-Fauria
Cambridge University, Cambridge, UK
Juha Lemmetyinen
Finnish Meteorological Institute, Helsinki, Finland
Kimmo Rautiainen
Finnish Meteorological Institute, Helsinki, Finland
Chiara Gruber
b.geos, Industriestrasse 1, 2100 Korneuburg, Austria
Bruce C. Forbes
Arctic Centre, University of Lapland, Rovaniemi, Finland
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This preprint is open for discussion and under review for The Cryosphere (TC).
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This study examines the impacts of wildfires on permafrost thaw in the Arctic and explores the potential of using radar satellite observations to enhance our understanding of environmental change. By assessing diverse high-latitude permafrost landscapes, we show that ground deformation anomalies after fires display similar patterns across regions, while radar backscatter varies depending on predominant ground temperatures.
Hong Lin, Jinyang Du, John S. Kimball, Xiao Cheng, J. Patrick Donnelly, Jennifer D. Watts, and Annett Bartsch
Earth Syst. Sci. Data, 18, 535–549, https://doi.org/10.5194/essd-18-535-2026, https://doi.org/10.5194/essd-18-535-2026, 2026
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Ella Kivimäki, Maria Tenkanen, Tuula Aalto, Michael Buchwitz, Kari Luojus, Jouni Pulliainen, Kimmo Rautiainen, Oliver Schneising, Anu-Maija Sundström, Johanna Tamminen, Aki Tsuruta, and Hannakaisa Lindqvist
Biogeosciences, 22, 5193–5230, https://doi.org/10.5194/bg-22-5193-2025, https://doi.org/10.5194/bg-22-5193-2025, 2025
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We study how environmental variables influencing natural methane fluxes explain the seasonal variability in satellite-observed methane in Northern Hemisphere high-latitude wetland areas. Using two atmospheric model set-ups, we assess consistency with satellite data. Methane loss through reaction with hydroxyl radicals and links with snow cover, temperature, and snowmelt had the strongest influence. Our study highlights the value of satellite observations for understanding large-scale wetland emissions.
Juliette Ortet, Arnaud Mialon, Alain Royer, Mike Schwank, Manu Holmberg, Kimmo Rautiainen, Simone Bircher-Adrot, Andreas Colliander, Yann Kerr, and Alexandre Roy
The Cryosphere, 19, 3571–3598, https://doi.org/10.5194/tc-19-3571-2025, https://doi.org/10.5194/tc-19-3571-2025, 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 temperature time series were evaluated over 21 reference sites in Northern Alaska and compared with ground temperatures obtained with global models. The method is extremely promising for monitoring ground temperature below the snowpack and studying the spatio-temporal variability thanks to 15 years of observations over the whole Arctic area.
Sara Hyvärinen, Maria Katariina Tenkanen, Aki Tsuruta, Anttoni Erkkilä, Kimmo Rautiainen, Hermanni Aaltonen, Motoki Sasakawa, and Tuula Aalto
EGUsphere, https://doi.org/10.5194/egusphere-2025-2794, https://doi.org/10.5194/egusphere-2025-2794, 2025
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We analyzed spring methane emissions from northern high-latitude wetlands using satellite thaw data and inverse modeling (2011–2021). Comparing region-based and grid-based approaches, we found that emissions varied with the length of the melting season, which depended on air temperature. We found spring melting season emissions ranged from 0.45 Tg to 1.83 Tg depending on the approach, with no clear trend over the period. Our methods allow for seasonal methane monitoring across different scales.
Constanze Reinken, Victor Brovkin, Philipp de Vrese, Ingmar Nitze, Helena Bergstedt, and Guido Grosse
EGUsphere, https://doi.org/10.5194/egusphere-2025-1817, https://doi.org/10.5194/egusphere-2025-1817, 2025
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Thermokarst lakes are dynamic features of ice-rich permafrost landscapes, altering energy, water and carbon cycles, but have so far mostly been modeled on site-level scale. A deterministic modelling approach would be challenging on larger scales due to the lack of extensive high-resolution data of sub-surface conditions. We therefore develop a conceptual stochastic model of thermokarst lake dynamics that treats the involved processes as probabilistic.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
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Short summary
We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Valeria Briones, Hélène Genet, Elchin E. Jafarov, Brendan M. Rogers, Jennifer D. Watts, Anna-Maria Virkkala, Annett Bartsch, Benjamin C. Maglio, Joshua Rady, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-226, https://doi.org/10.5194/essd-2025-226, 2025
Manuscript not accepted for further review
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Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
Short summary
Short summary
Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Annett Bartsch, Aleksandra Efimova, Barbara Widhalm, Xaver Muri, Clemens von Baeckmann, Helena Bergstedt, Ksenia Ermokhina, Gustaf Hugelius, Birgit Heim, and Marina Leibman
Hydrol. Earth Syst. Sci., 28, 2421–2481, https://doi.org/10.5194/hess-28-2421-2024, https://doi.org/10.5194/hess-28-2421-2024, 2024
Short summary
Short summary
Wetness gradients and landcover diversity for the entire Arctic tundra have been assessed using a novel satellite-data-based map. Patterns of lakes, wetlands, general soil moisture conditions and vegetation physiognomy are represented at 10 m. About 40 % of the area north of the treeline falls into three units of dry types, with limited shrub growth. Wetter regions have higher landcover diversity than drier regions.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
Justin Murfitt, Claude Duguay, Ghislain Picard, and Juha Lemmetyinen
The Cryosphere, 18, 869–888, https://doi.org/10.5194/tc-18-869-2024, https://doi.org/10.5194/tc-18-869-2024, 2024
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This research focuses on the interaction between microwave signals and lake ice under wet conditions. Field data collected for Lake Oulujärvi in Finland were used to model backscatter under different conditions. The results of the modelling likely indicate that a combination of increased water content and roughness of different interfaces caused backscatter to increase. These results could help to identify areas where lake ice is unsafe for winter transportation.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Carolina Voigt, Nick Rutter, Paul Mann, Jean-Daniel Sylvain, and Alexandre Roy
Biogeosciences, 20, 5087–5108, https://doi.org/10.5194/bg-20-5087-2023, https://doi.org/10.5194/bg-20-5087-2023, 2023
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We present an analysis of soil CO2 emissions in boreal and tundra regions during the non-growing season. We show that when the soil is completely frozen, soil temperature is the main control on CO2 emissions. When the soil is around the freezing point, with a mix of liquid water and ice, the liquid water content is the main control on CO2 emissions. This study highlights that the vegetation–snow–soil interactions must be considered to understand soil CO2 emissions during the non-growing season.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
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This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Annett Bartsch, Helena Bergstedt, Georg Pointner, Xaver Muri, Kimmo Rautiainen, Leena Leppänen, Kyle Joly, Aleksandr Sokolov, Pavel Orekhov, Dorothee Ehrich, and Eeva Mariatta Soininen
The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, https://doi.org/10.5194/tc-17-889-2023, 2023
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Rain-on-snow (ROS) events occur across many regions of the terrestrial Arctic in mid-winter. In extreme cases ice layers form which affect wildlife, vegetation and soils beyond the duration of the event. The fusion of multiple types of microwave satellite observations is suggested for the creation of a climate data record. Retrieval is most robust in the tundra biome, where records can be used to identify extremes and the results can be applied to impact studies at regional scale.
Pinja Venäläinen, Kari Luojus, Colleen Mortimer, Juha Lemmetyinen, Jouni Pulliainen, Matias Takala, Mikko Moisander, and Lina Zschenderlein
The Cryosphere, 17, 719–736, https://doi.org/10.5194/tc-17-719-2023, https://doi.org/10.5194/tc-17-719-2023, 2023
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Snow water equivalent (SWE) is a valuable characteristic of snow cover. In this research, we improve the radiometer-based GlobSnow SWE retrieval methodology by implementing spatially and temporally varying snow densities into the retrieval procedure. In addition to improving the accuracy of SWE retrieval, varying snow densities were found to improve the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Noriaki Ohara, Benjamin M. Jones, Andrew D. Parsekian, Kenneth M. Hinkel, Katsu Yamatani, Mikhail Kanevskiy, Rodrigo C. Rangel, Amy L. Breen, and Helena Bergstedt
The Cryosphere, 16, 1247–1264, https://doi.org/10.5194/tc-16-1247-2022, https://doi.org/10.5194/tc-16-1247-2022, 2022
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New variational principle suggests that a semi-ellipsoid talik shape (3D Stefan equation) is optimum for incoming energy. However, the lake bathymetry tends to be less ellipsoidal due to the ice-rich layers near the surface. Wind wave erosion is likely responsible for the elongation of lakes, while thaw subsidence slows the wave effect and stabilizes the thermokarst lakes. The derived 3D Stefan equation was compared to the field-observed talik thickness data using geophysical methods.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Torben Windirsch, Guido Grosse, Mathias Ulrich, Bruce C. Forbes, Mathias Göckede, Juliane Wolter, Marc Macias-Fauria, Johan Olofsson, Nikita Zimov, and Jens Strauss
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-227, https://doi.org/10.5194/bg-2021-227, 2021
Revised manuscript not accepted
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With global warming, permafrost thaw and associated carbon release are of increasing importance. We examined how large herbivorous animals affect Arctic landscapes and how they might contribute to reduction of these emissions. We show that over a short timespan of roughly 25 years, these animals have already changed the vegetation and landscape. On pastures in a permafrost area in Siberia we found smaller thaw depth and higher carbon content than in surrounding non-pasture areas.
Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
Frans-Jan W. Parmentier, Lennart Nilsen, Hans Tømmervik, and Elisabeth J. Cooper
Earth Syst. Sci. Data, 13, 3593–3606, https://doi.org/10.5194/essd-13-3593-2021, https://doi.org/10.5194/essd-13-3593-2021, 2021
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Satellites provide a global overview of Earth's ecosystems, but they have coarse resolutions and low revisit times. Small-scale vegetation patterns and sudden shifts in plant growth can easily be missed. In this paper, we show how to fill these gaps with vegetation indices obtained with ordinary time-lapse cameras deployed across a valley on Svalbard. We show how to adjust for unwanted camera movement and that vegetation indices from ordinary cameras compare well to those used by satellites.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Georg Pointner, Annett Bartsch, Yury A. Dvornikov, and Alexei V. Kouraev
The Cryosphere, 15, 1907–1929, https://doi.org/10.5194/tc-15-1907-2021, https://doi.org/10.5194/tc-15-1907-2021, 2021
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This study presents strong new indications that regions of anomalously low backscatter in C-band synthetic aperture radar (SAR) imagery of ice of Lake Neyto in northwestern Siberia are related to strong emissions of natural gas. Spatio-temporal dynamics and potential scattering and formation mechanisms are assessed. It is suggested that exploiting the spatial and temporal properties of Sentinel-1 SAR data may be beneficial for the identification of similar phenomena in other Arctic lakes.
Cited articles
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AMAP: Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, Tech. rep., Arctic Monitoring and Assessment Programme (AMAP), Oslo, xiv + 269 pp., https://www.amap.no/documents/doc/snow-water-ice-and-permafrost-in-the-arctic-swipa-2017/1610 (last access: 2 January 2022), 2017. a, b, c, d, e
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Anonymous: Referee Comment 1, Comment on egusphere-2025-1358, https://doi.org/10.5194/egusphere-2025-1358-rc1, 2025. a
Anttila, K., Manninen, T., Jääskeläinen, E., Riihelä, A., and Lahtinen, P.: The Role of Climate and Land Use in the Changes in Surface Albedo Prior to Snow Melt and the Timing of Melt Season of Seasonal Snow in Northern Land Areas of 40–80° N during 1982–2015, Remote Sensing, 10, 1619, https://doi.org/10.3390/rs10101619, 2018. a
Armstrong McKay, D. I., Staal, A., Abrams, J. F., Winkelmann, R., Sakschewski, B., Loriani, S., Fetzer, I., Cornell, S. E., Rockström, J., and Lenton, T. M.: Exceeding 1.5 °C global warming could trigger multiple climate tipping points, Science, 377, https://doi.org/10.1126/science.abn7950, 2022. a
Bartsch, A., Bergstedt, H., Pointner, G., Muri, X., Rautiainen, K., Leppänen, L., Joly, K., Sokolov, A., Orekhov, P., Ehrich, D., and Soininen, E. M.: Towards long-term records of rain-on-snow events across the Arctic from satellite data, The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, 2023a. a, b
Bartsch, A., Strozzi, T., and Nitze, I.: Permafrost Monitoring from Space, Surveys in Geophysics, https://doi.org/10.1007/s10712-023-09770-3, 2023b. a, b, c
Bartsch, A., Tanguy, R., Bergstedt, H., Muri, X., and von Baeckmann, C.: Similarities in Northern Hemisphere Permafrost Ground Temperature and Sea Ice Extent Change from 1997 to 2019, in: IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 134–137, https://doi.org/10.1109/igarss53475.2024.10642186, 2024. a, b
Bartsch, A., Bergstedt, H., Tømmervik, H., Lemmetyinen, J., and Rautiainen, K.: Selected Arctic Land Parameter Trends: Ground Temperature, Snow Water Equivalent, NDVI, LAI and Freeze Thaw Duration, Zenodo [data set], https://doi.org/10.5281/zenodo.14975145, 2025a. a
Bartsch, A., Muri, X., Hetzenecker, M., Rautiainen, K., Bergstedt, H., Wuite, J., Nagler, T., and Nicolsky, D.: Benchmarking passive-microwave-satellite-derived freeze–thaw datasets, The Cryosphere, 19, 459–483, https://doi.org/10.5194/tc-19-459-2025, 2025b. a
Bartsch, A., Tanguy, R., Tømmervik, H., Lemmetyinen, J., Bergstedt, H., and von Baeckmann, C.: Arctic Sea Ice and Land Parameter Correlations (ASILaC), Zenodo [data set], https://doi.org/10.5281/zenodo.14975004, 2025c. a, b
Berner, L. T., Massey, R., Jantz, P., Forbes, B. C., Macias-Fauria, M., Myers-Smith, I., Kumpula, T., Gauthier, G., Andreu-Hayles, L., Gaglioti, B. V., Burns, P., Zetterberg, P., D’Arrigo, R., and Goetz, S. J.: Summer warming explains widespread but not uniform greening in the Arctic tundra biome, Nature Communications, 11, https://doi.org/10.1038/s41467-020-18479-5, 2020. a
Bhatt, U. S., Walker, D. A., Raynolds, M. K., Comiso, J. C., Epstein, H. E., Jia, G., Gens, R., Pinzon, J. E., Tucker, C. J., Tweedie, C. E., and Webber, P. J.: Circumpolar Arctic Tundra Vegetation Change Is Linked to Sea Ice Decline, Earth Interactions, 14, 1–20, https://doi.org/10.1175/2010EI315.1, 2010. a, b, c, d, e
Bhatt, U. S., Walker, D. A., Raynolds, M. K., Bieniek, P. A., Epstein, H. E., Comiso, J. C., Pinzon, J. E., Tucker, C. J., Steele, M., Ermold, W., and Zhang, J.: Changing seasonality of panarctic tundra vegetation in relationship to climatic variables, Environmental Research Letters, 12, 055003, https://doi.org/10.1088/1748-9326/aa6b0b, 2017. a, b, c, d
Bhatt, U. S., Walker, D. A., Raynolds, M. K., Walsh, J. E., Bieniek, P. A., Cai, L., Comiso, J. C., Epstein, H. E., Frost, G. V., Gersten, R., Hendricks, A. S., Pinzon, J. E., Stock, L., and Tucker, C. J.: Climate drivers of Arctic tundra variability and change using an indicators framework, Environmental Research Letters, 16, 055019, https://doi.org/10.1088/1748-9326/abe676, 2021. a, b, c, d, e, f, g, h, i
Bjerke, J. W., López-Blanco, E., Tømmervik, H., Striberny, A., Davids, C., Ólafsdóttir, R., Karlsen, S. R., Sandström, P., Turunen, M., Rikkonen, T., Arneberg, M. K., Siikavuopio, S., Zinglersen, K., Lynge-Pedersen, K., Sandström, S., and Rautio, P.: Nordic boreo-arctic lands under rapid climatic change: A review of recent and future trends and extreme events, Earth-Science Reviews, 261, 105012, https://doi.org/10.1016/j.earscirev.2024.105012, 2025. a
Bokhorst, S. F., Bjerke, J. W., Tømmervik, H., Callaghan, T. V., and Phoenix, G. K.: Winter warming events damage sub‐Arctic vegetation: consistent evidence from an experimental manipulation and a natural event, Journal of Ecology, 97, 1408–1415, https://doi.org/10.1111/j.1365-2745.2009.01554.x, 2009. a
Brouillette, M.: How microbes in permafrost could trigger a massive carbon bomb, Nature, 591, 360–362, https://doi.org/10.1038/d41586-021-00659-y, 2021. a, b
Buchwal, A., Sullivan, P. F., Macias-Fauria, M., Post, E., Myers-Smith, I. H., Stroeve, J. C., Blok, D., Tape, K. D., Forbes, B. C., Ropars, P., Lévesque, E., Elberling, B., Angers-Blondin, S., Boyle, J. S., Boudreau, S., Boulanger-Lapointe, N., Gamm, C., Hallinger, M., Rachlewicz, G., Young, A., Zetterberg, P., and Welker, J. M.: Divergence of Arctic shrub growth associated with sea ice decline, Proceedings of the National Academy of Sciences, 117, 33334–33344, https://doi.org/10.1073/pnas.2013311117, 2020. a
Comiso, J. C. and Nishio, F.: Trends in the sea ice cover using enhanced and compatible AMSR‐E, SSM/I, and SMMR data, Journal of Geophysical Research: Oceans, 113, https://doi.org/10.1029/2007jc004257, 2008. a, b, c
Druckenmiller, M. L., Moon, T. A., Thoman, R. L., Ballinger, T. J., Berner, L. T., Bernhard, G. H., Bhatt, U. S., Bjerke, J. W., Box, J. E., Brown, R., Cappelen, J., Christiansen, H. H., Decharme, B., Derksen, C., Divine, D., Drozdov, D. S., Elias Chereque, A., Epstein, H. E., Farquharson, L. M., Farrell, S. L., Fausto, R. S., Fettweis, X., Fioletov, V. E., Forbes, B. C., Frost, G. V., Gargulinski, E., Gerland, S., Goetz, S. J., Grabinski, Z., Grooß, J.-U., Haas, C., Hanna, E., Hanssen-Bauer, I., Hendricks, S., Holmes, R. M., Ialongo, I., Isaksen, K., Jain, P., Johnsen, B., Kaleschke, L., Kholodov, A. L., Kim, S.-J., Korsgaard, N. J., Labe, Z., Lakkala, K., Lara, M. J., Loomis, B., Luojus, K., Macander, M. J., Malkova, G. V., Mankoff, K. D., Manney, G. L., McClelland, J. W., Meier, W. N., Mote, T., Mudryk, L., Müller, R., Nyland, K. E., Overland, J. E., Park, T., Pavlova, O., Perovich, D., Petty, A., Phoenix, G. K., Raynolds, M. K., Reijmer, C. H., Richter-Menge, J., Ricker, R., Romanovsky, V. E., Scott, L., Shapiro, H., Shiklomanov, A. I., Shiklomanov, N. I., Smeets, C. J. P. P., Smith, S. L., Soja, A., Spencer, R. G. M., Starkweather, S., Streletskiy, D. A., Suslova, A., Svendby, T., Tank, S. E., Tedesco, M., Tian-Kunze, X., Timmermans, M.-L., Tømmervik, H., Tretiakov, M., Tschudi, M., Vakhutinsky, S., van As, D., van de Wal, R. S. W., Veraverbeke, S., Walker, D. A., Walsh, J. E., Wang, M., Webster, M., Winton, O., Wood, K., York, A., and Ziel, R.: The Arctic, Bulletin of the American Meteorological Society, 102, S263–S316, https://doi.org/10.1175/bams-d-21-0086.1, 2021. a, b
Dupuis, S., Göttsche, F.-M., and Wunderle, S.: Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region, The Cryosphere, 18, 6027–6059, https://doi.org/10.5194/tc-18-6027-2024, 2024. a, b
Dutrieux, L. P., Bartholomeus, H., Herold, M., and Verbesselt, J.: Relationships between declining summer sea ice, increasing temperatures and changing vegetation in the Siberian Arctic tundra from MODIS time series (2000–11), Environmental Research Letters, 7, 044028, https://doi.org/10.1088/1748-9326/7/4/044028, 2012. a, b, c
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Frost, G. V., Bhatt, U. S., Macander, M. J., Berner, L. T., Walker, D. A., Raynolds, M. K., Magnusson, R. I., Bartsch, A., Bjerke, J. W., Epstein, H. E., Forbes, B. C., Goetz, S. J., Hoy, E. E., Karlsen, S. R., Kumpula, T., Lantz, T. C., Lara, M. J., López-Blanco, E., Montesano, P. M., Neigh, C. S. R., Nitze, I., Orndahl, K. M., Park, T., Phoenix, G. K., Rocha, A. V., Rogers, B. M., Schaepman-Strub, G., Tømmervik, H., Verdonen, M., Veremeeva, A., Virkkala, A.-M., and Waigl, C. F.: The changing face of the Arctic: four decades of greening and implications for tundra ecosystems, Frontiers in Environmental Science, 13, 2025, https://doi.org/10.3389/fenvs.2025.1525574, 2025. a, b, c, d, e, f, g, h, i, j, k
Gastineau, G., Frankignoul, C., Gao, Y., Liang, Y.-C., Kwon, Y.-O., Cherchi, A., Ghosh, R., Manzini, E., Matei, D., Mecking, J., Suo, L., Tian, T., Yang, S., and Zhang, Y.: Forcing and impact of the Northern Hemisphere continental snow cover in 1979–2014, The Cryosphere, 17, 2157–2184, https://doi.org/10.5194/tc-17-2157-2023, 2023. a, b
Heim, B., Lisovski, S., Wieczorek, M., Pellet, C., Delaloye, R., Bartsch, A., Jakober, D., Pointner, G., and Strozzi, T.: ESA CCI+ Product Validation and Intercomparison Report, v3.0, Tech. rep., https://climate.esa.int/documents/1520/CCI_PERMA_PVIR_v3.0_20210930.pdf (last access: 2 January 2025), 2021. a
Ingrosso, G., Ceccarelli, C., Giglio, F., Giordano, P., Hefter, J., Langone, L., Miserocchi, S., Mollenhauer, G., Nogarotto, A., Sabino, M., and Tesi, T.: Greening of Svalbard in the twentieth century driven by sea ice loss and glaciers retreat, Communications Earth & Environment, 6, https://doi.org/10.1038/s43247-025-01994-y, 2025. a
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Kerby, J. T. and Post, E.: Advancing plant phenology and reduced herbivore production in a terrestrial system associated with sea ice decline, Nature Communications, 4, https://doi.org/10.1038/ncomms3514, 2013. a
Kim, Y., Kimball, J. S., Glassy, J., and Du, J.: An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing, Earth Syst. Sci. Data, 9, 133–147, https://doi.org/10.5194/essd-9-133-2017, 2017. a
Kim, Y., Kimball, J., Du, J., and Glassy, J.: MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status, Version 5, National Snow and Ice Data Center [data set], https://doi.org/10.5067/LJ6SLXNJB2CQ, 2021. a, b
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Short summary
We identified similarities between sea ice dynamics and conditions on land across the Arctic, above 60° N, for 2000–2019. Significant correlations were more common for snow water equivalent and permafrost ground temperature than for the vegetation parameters. Changes across all the different parameters could specifically be determined for eastern Siberia. The results provide a baseline for future studies on common drivers of essential climate variables and causative effects across the Arctic.
We identified similarities between sea ice dynamics and conditions on land across the Arctic,...
