Articles | Volume 19, issue 11
https://doi.org/10.5194/tc-19-6127-2025
© 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-19-6127-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Nov 2025
Research article |
| 24 Nov 2025
| 24 Nov 2025
Object-based ensemble estimation of snow depth and snow water equivalent over multiple months in Sodankylä, Finland
David Brodylo
CORRESPONDING AUTHOR
U.S. Army Cold Regions Research and Engineering Laboratory, Fort Wainwright, AK 99709, USA
Lauren V. Bosche
U.S. Army Cold Regions Research and Engineering Laboratory, Fort Wainwright, AK 99709, USA
Ryan R. Busby
U.S. Army Construction Engineering Research Laboratory, Champaign, IL 61826, USA
Elias J. Deeb
U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH 03755, USA
Thomas A. Douglas
U.S. Army Cold Regions Research and Engineering Laboratory, Fort Wainwright, AK 99709, USA
Juha Lemmetyinen
Finnish Meteorological Institute, 00101 Helsinki, Finland
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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
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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.
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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.
Thomas A. Douglas, Christopher A. Hiemstra, John E. Anderson, Robyn A. Barbato, Kevin L. Bjella, Elias J. Deeb, Arthur B. Gelvin, Patricia E. Nelsen, Stephen D. Newman, Stephanie P. Saari, and Anna M. Wagner
The Cryosphere, 15, 3555–3575, https://doi.org/10.5194/tc-15-3555-2021, https://doi.org/10.5194/tc-15-3555-2021, 2021
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Permafrost is actively degrading across high latitudes due to climate warming. We combined thousands of end-of-summer active layer measurements, permafrost temperatures, geophysical surveys, deep borehole drilling, and repeat airborne lidar to quantify permafrost warming and thawing at sites across central Alaska. We calculate the mass of permafrost soil carbon potentially exposed to thaw over the past 7 years (0.44 Pg) is similar to the yearly carbon dioxide emissions of Australia.
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.
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Short summary
We combined field-based snow depth and snow water equivalent (SWE) measurements, remote sensing data, and machine learning to estimate snow depth and SWE over a 10 km2 local scale area in Sodankylä, Finland. Associations were found for snow depth and SWE with carbon- and mineral-based forest surface soils, alongside dry and wet peatbogs. This approach to upscale field-based snow depth and SWE measurements to a local scale can be used in regions that regularly experience snowfall.
We combined field-based snow depth and snow water equivalent (SWE) measurements, remote sensing...
