Articles | Volume 12, issue 7
https://doi.org/10.5194/tc-12-2349-2018
© Author(s) 2018. 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-12-2349-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Jul 2018
Research article |
| 18 Jul 2018
| 18 Jul 2018
Circumpolar patterns of potential mean annual ground temperature based on surface state obtained from microwave satellite data
Christine Kroisleitner
Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
Austrian Polar Research Institute, Vienna, Austria
b.geos, Korneuburg, Austria
Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
Austrian Polar Research Institute, Vienna, Austria
b.geos, Korneuburg, Austria
Helena Bergstedt
Department of Geoinformatics – Z_GIS, University Salzburg, 5020 Salzburg, Austria
Austrian Polar Research Institute, Vienna, Austria
Related authors
No articles found.
Clemens von Baeckmann, Annett Bartsch, Helena Bergstedt, Aleksandra Efimova, Barbara Widhalm, Dorothee Ehrich, Timo Kumpula, Alexander Sokolov, and Svetlana Abdulmanova
EGUsphere, https://doi.org/10.5194/egusphere-2024-699, https://doi.org/10.5194/egusphere-2024-699, 2024
Short summary
Short summary
Lakes are common features in Arctic permafrost areas. Landcover 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 landcover monitoring scheme. Landcover information provides specifically information on wetland features. We also showed that the bioclimatic gradients play a significant role after drainage within the first 10 years.
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, Luke D. Schiferl, Clayton Elder, Olli Peltola, Annett Bartsch, Amanda Armstrong, 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 Discuss., https://doi.org/10.5194/essd-2024-84, https://doi.org/10.5194/essd-2024-84, 2024
Preprint under review for ESSD
Short summary
Short summary
We present daily methane fluxes of northern wetlands at 10-km resolution during 2016–2022 (WetCH4) derived from a novel machine-learning framework with improved accuracy. We estimated an average annual CH4 emissions of 20.8 ±2.1 Tg CH4 yr-1. Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variations coming from West Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-2926, https://doi.org/10.5194/egusphere-2023-2926, 2024
Short summary
Short summary
Computer models, like those used in climate change studies, are written by modelers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modeling as an example, we examine the process behind the decisions to understand what motivates or limits modelers in their decision-making. We found that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency into our research practice.
Annett Bartsch, Aleksandra Efimova, Barbara Widhalm, Xaver Muri, Clemens von Baeckmann, Helena Bergstedt, Ksenia Ermokhina, Gustaf Hugelius, Birgit Heim, and Marina Leibmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2295, https://doi.org/10.5194/egusphere-2023-2295, 2023
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
Short summary
Short summary
The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Jaroslav Obu, Sebastian Westermann, Gonçalo Vieira, Andrey Abramov, Megan Ruby Balks, Annett Bartsch, Filip Hrbáček, Andreas Kääb, and Miguel Ramos
The Cryosphere, 14, 497–519, https://doi.org/10.5194/tc-14-497-2020, https://doi.org/10.5194/tc-14-497-2020, 2020
Short summary
Short summary
Little is known about permafrost in the Antarctic outside of the few research stations. We used a simple equilibrium permafrost model to estimate permafrost temperatures in the whole Antarctic. The lowest permafrost temperature on Earth is −36 °C in the Queen Elizabeth Range in the Transantarctic Mountains. Temperatures are commonly between −23 and −18 °C in mountainous areas rising above the Antarctic Ice Sheet, between −14 and −8 °C in coastal areas, and up to 0 °C on the Antarctic Peninsula.
Sarah E. Chadburn, Gerhard Krinner, Philipp Porada, Annett Bartsch, Christian Beer, Luca Belelli Marchesini, Julia Boike, Altug Ekici, Bo Elberling, Thomas Friborg, Gustaf Hugelius, Margareta Johansson, Peter Kuhry, Lars Kutzbach, Moritz Langer, Magnus Lund, Frans-Jan W. Parmentier, Shushi Peng, Ko Van Huissteden, Tao Wang, Sebastian Westermann, Dan Zhu, and Eleanor J. Burke
Biogeosciences, 14, 5143–5169, https://doi.org/10.5194/bg-14-5143-2017, https://doi.org/10.5194/bg-14-5143-2017, 2017
Short summary
Short summary
Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
Sina Muster, Kurt Roth, Moritz Langer, Stephan Lange, Fabio Cresto Aleina, Annett Bartsch, Anne Morgenstern, Guido Grosse, Benjamin Jones, A. Britta K. Sannel, Ylva Sjöberg, Frank Günther, Christian Andresen, Alexandra Veremeeva, Prajna R. Lindgren, Frédéric Bouchard, Mark J. Lara, Daniel Fortier, Simon Charbonneau, Tarmo A. Virtanen, Gustaf Hugelius, Juri Palmtag, Matthias B. Siewert, William J. Riley, Charles D. Koven, and Julia Boike
Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
Short summary
Short summary
Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
Barbara Widhalm, Annett Bartsch, Marina Leibman, and Artem Khomutov
The Cryosphere, 11, 483–496, https://doi.org/10.5194/tc-11-483-2017, https://doi.org/10.5194/tc-11-483-2017, 2017
Short summary
Short summary
The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally. The relationship between active-layer thickness (ALT) and X-band SAR backscatter of TerraSAR-X has been investigated in order to explore the possibility of delineating ALT with continuous and larger spatial coverage.
Annett Bartsch, Barbara Widhalm, Peter Kuhry, Gustaf Hugelius, Juri Palmtag, and Matthias Benjamin Siewert
Biogeosciences, 13, 5453–5470, https://doi.org/10.5194/bg-13-5453-2016, https://doi.org/10.5194/bg-13-5453-2016, 2016
Short summary
Short summary
A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR) data from the ENVISAT satellite. It can be shown that measurements of C-band SAR under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. The approach provides the first spatially consistent account of soil organic carbon across the Arctic.
Klaus Haslinger and Annett Bartsch
Hydrol. Earth Syst. Sci., 20, 1211–1223, https://doi.org/10.5194/hess-20-1211-2016, https://doi.org/10.5194/hess-20-1211-2016, 2016
Short summary
Short summary
Gridded fields of daily max. and min. temperatures for the Austrian domain are used to calculate ET0 based on a re-calibrated Hargreaves method. Newly derived, station-based calibration parameters, with Penman–Monteith ET0 as a reference, show a distinct altitude and seasonal dependence. Theses features are used to interpolate the new calibration values in space and time onto the temperature grids. The ET0 is then calculated based on the entire gridded temperature data starting back in 1961.
I. Gouttevin, A. Bartsch, G. Krinner, and V. Naeimi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-11241-2013, https://doi.org/10.5194/hessd-10-11241-2013, 2013
Manuscript not accepted for further review
Related subject area
Discipline: Frozen ground | Subject: Arctic (e.g. Greenland)
Characterization of atmospheric methane release in the outer Mackenzie River delta from biogenic and thermogenic sources
Accelerated mobilization of organic carbon from retrogressive thaw slumps on the northern Taymyr Peninsula
The importance of freeze–thaw cycles for lateral tracer transport in ice-wedge polygons
Validation of Pan-Arctic Soil Temperatures in Modern Reanalysis and Data Assimilation Systems
The cryostratigraphy of the Yedoma cliff of Sobo-Sise Island (Lena delta) reveals permafrost dynamics in the central Laptev Sea coastal region during the last 52 kyr
Thermokarst lake inception and development in syngenetic ice-wedge polygon terrain during a cooling climatic trend, Bylot Island (Nunavut), eastern Canadian Arctic
The current state and 125 kyr history of permafrost on the Kara Sea shelf: modeling constraints
Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data
A distributed temperature profiling method for assessing spatial variability in ground temperatures in a discontinuous permafrost region of Alaska
New insights into the environmental factors controlling the ground thermal regime across the Northern Hemisphere: a comparison between permafrost and non-permafrost areas
Daniel Wesley, Scott Dallimore, Roger MacLeod, Torsten Sachs, and David Risk
The Cryosphere, 17, 5283–5297, https://doi.org/10.5194/tc-17-5283-2023, https://doi.org/10.5194/tc-17-5283-2023, 2023
Short summary
Short summary
The Mackenzie River delta (MRD) is an ecosystem with high rates of methane production from biologic and geologic sources, but little research has been done to determine how often geologic or biogenic methane is emitted to the atmosphere. Stable carbon isotope analysis was used to identify the source of CH4 at several sites. Stable carbon isotope (δ13C-CH4) signatures ranged from −42 to −88 ‰ δ13C-CH4, indicating that CH4 emission in the MRD is caused by biologic and geologic sources.
Philipp Bernhard, Simon Zwieback, and Irena Hajnsek
The Cryosphere, 16, 2819–2835, https://doi.org/10.5194/tc-16-2819-2022, https://doi.org/10.5194/tc-16-2819-2022, 2022
Short summary
Short summary
With climate change, Arctic hillslopes above ice-rich permafrost are vulnerable to enhanced carbon mobilization. In this work elevation change estimates generated from satellite observations reveal a substantial acceleration of carbon mobilization on the Taymyr Peninsula in Siberia between 2010 and 2021. The strong increase occurring in 2020 coincided with a severe Siberian heatwave and highlights that carbon mobilization can respond sharply and non-linearly to increasing temperatures.
Elchin E. Jafarov, Daniil Svyatsky, Brent Newman, Dylan Harp, David Moulton, and Cathy Wilson
The Cryosphere, 16, 851–862, https://doi.org/10.5194/tc-16-851-2022, https://doi.org/10.5194/tc-16-851-2022, 2022
Short summary
Short summary
Recent research indicates the importance of lateral transport of dissolved carbon in the polygonal tundra, suggesting that the freeze-up period could further promote lateral carbon transport. We conducted subsurface tracer simulations on high-, flat-, and low-centered polygons to test the importance of the freeze–thaw cycle and freeze-up time for tracer mobility. Our findings illustrate the impact of hydraulic and thermal gradients on tracer mobility, as well as of the freeze-up time.
Tyler C. Herrington, Christopher G. Fletcher, and Heather Kropp
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-5, https://doi.org/10.5194/tc-2022-5, 2022
Revised manuscript accepted for TC
Short summary
Short summary
Here we validate soil temperatures from eight reanalysis products across the pan-Arctic, and compare their performance to a newly calculated ensemble mean soil temperature product. We find that most products are biased cold by 2–7 K, especially in the cold season, and that the ensemble mean product outperforms individual reanalysis products. As such, we recommend the product for a wide range of applications – including validation of climate models, or as input to permafrost models.
Sebastian Wetterich, Alexander Kizyakov, Michael Fritz, Juliane Wolter, Gesine Mollenhauer, Hanno Meyer, Matthias Fuchs, Aleksei Aksenov, Heidrun Matthes, Lutz Schirrmeister, and Thomas Opel
The Cryosphere, 14, 4525–4551, https://doi.org/10.5194/tc-14-4525-2020, https://doi.org/10.5194/tc-14-4525-2020, 2020
Short summary
Short summary
In the present study, we analysed geochemical and sedimentological properties of relict permafrost and ground ice exposed at the Sobo-Sise Yedoma cliff in the eastern Lena delta in NE Siberia. We obtained insight into permafrost aggradation and degradation over the last approximately 52 000 years and the climatic and morphodynamic controls on regional-scale permafrost dynamics of the central Laptev Sea coastal region.
Frédéric Bouchard, Daniel Fortier, Michel Paquette, Vincent Boucher, Reinhard Pienitz, and Isabelle Laurion
The Cryosphere, 14, 2607–2627, https://doi.org/10.5194/tc-14-2607-2020, https://doi.org/10.5194/tc-14-2607-2020, 2020
Short summary
Short summary
We combine lake mapping, landscape observations and sediment core analyses to document the evolution of a thermokarst (thaw) lake in the Canadian Arctic over the last millennia. We conclude that temperature is not the only driver of thermokarst development, as the lake likely started to form during a cooler period around 2000 years ago. The lake is now located in frozen layers with an organic carbon content that is an order of magnitude higher than the usually reported values across the Arctic.
Anatoliy Gavrilov, Vladimir Pavlov, Alexandr Fridenberg, Mikhail Boldyrev, Vanda Khilimonyuk, Elena Pizhankova, Sergey Buldovich, Natalia Kosevich, Ali Alyautdinov, Mariia Ogienko, Alexander Roslyakov, Maria Cherbunina, and Evgeniy Ospennikov
The Cryosphere, 14, 1857–1873, https://doi.org/10.5194/tc-14-1857-2020, https://doi.org/10.5194/tc-14-1857-2020, 2020
Short summary
Short summary
The geocryological study of the Arctic shelf remains insufficient for economic activity. The article presents a study of its evolution by methods of math modeling of heat transfer in rocks. As a result, a model of the evolution and current state of the cryolithozone of the Kara shelf was created based on ideas about the history of its geocryological development over the past 125 kyr. The modeling results are correlated to the available field data and are presented as a geocryological map.
Elchin E. Jafarov, Dylan R. Harp, Ethan T. Coon, Baptiste Dafflon, Anh Phuong Tran, Adam L. Atchley, Youzuo Lin, and Cathy J. Wilson
The Cryosphere, 14, 77–91, https://doi.org/10.5194/tc-14-77-2020, https://doi.org/10.5194/tc-14-77-2020, 2020
Short summary
Short summary
Improved subsurface parameterization and benchmarking data are needed to reduce current uncertainty in predicting permafrost response to a warming climate. We developed a subsurface parameter estimation framework that can be used to estimate soil properties where subsurface data are available. We utilize diverse geophysical datasets such as electrical resistance data, soil moisture data, and soil temperature data to recover soil porosity and soil thermal conductivity.
Emmanuel Léger, Baptiste Dafflon, Yves Robert, Craig Ulrich, John E. Peterson, Sébastien C. Biraud, Vladimir E. Romanovsky, and Susan S. Hubbard
The Cryosphere, 13, 2853–2867, https://doi.org/10.5194/tc-13-2853-2019, https://doi.org/10.5194/tc-13-2853-2019, 2019
Short summary
Short summary
We propose a new strategy called distributed temperature profiling (DTP) for improving the estimation of soil thermal properties through the use of an unprecedented number of laterally and vertically distributed temperature measurements. We tested a DTP system prototype by moving it sequentially across a discontinuous permafrost environment. The DTP enabled high-resolution identification of near-surface permafrost location and covariability with topography, vegetation, and soil properties.
Olli Karjalainen, Miska Luoto, Juha Aalto, and Jan Hjort
The Cryosphere, 13, 693–707, https://doi.org/10.5194/tc-13-693-2019, https://doi.org/10.5194/tc-13-693-2019, 2019
Short summary
Short summary
Using a statistical modelling framework, we examined the environmental factors controlling ground thermal regimes inside and outside the Northern Hemisphere permafrost domain. We found that climatic factors were paramount in both regions, but with varying relative importance and effect size. The relationships were often non-linear, especially in permafrost conditions. Our results suggest that these non-linearities should be accounted for in future ground thermal models at the hemisphere scale.
Cited articles
André, C., Ottlé, C., Royer, A., and Maignan, F.: Land surface
temperature retrieval over circumpolar Arctic using SSM/I–SSMIS and MODIS
data, Remote Sens. Environ., 162, 1–10, https://doi.org/10.1016/j.rse.2015.01.028,
2015. a
AWI: ESA DUE GlobPermafrost project webgis and catalogue,
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung,
available at: http://maps.awi.de/map/map.html?cu=globpermafrost_arctic, last access: 6 March
2018. a
Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global land
cover mapping from Earth observation data, Int. J. Remote Sens., 26,
1959–1977, https://doi.org/10.1080/01431160412331291297, 2005. a
Bartsch, A.: Ten Years of SeaWinds on QuikSCAT for Snow Applications,
Remote Sens., 2, 1142–1156, https://doi.org/10.3390/rs2041142, 2010. a, b, c, d
Bartsch, A. and Seifert, F. M.: The ESA DUE Permafrost project – A service
for high latitude research, Int. Geosci. Remote Se., 5222–5225,
https://doi.org/10.1109/IGARSS.2012.6352432, 2012. a
Bartsch, A., Kidd, R. A., Wagner, W., and Bartalis, Z.: Temporal and Spatial
Variability of the Beginning and End of Daily Spring Freeze/Thaw Cycles
Derived from Scatterometer Data, Remote Sens. Environ., 106, 360–374,
https://doi.org/10.1016/j.rse.2006.09.004, 2007. a, b, c
Bartsch, A., Höfler, A., Kroisleitner, C., and Trofaier, A. M.: Land Cover
Mapping in Northern High Latitude Permafrost Regions with Satellite Data:
Achievements and Remaining Challenges, Remote Sens., 8, 979,
https://doi.org/10.3390/rs8120979, 2016a. a
Bartsch, A., Kroisleitner, C., and Heim, B.: Circumpolar Landscape
Units, links to GeoTIFFs, Pangaea, https://doi.org/10.1594/PANGAEA.864508, 2016b. a, b
Bartsch, A., Widhalm, B., Kuhry, P., Hugelius, G., Palmtag, J., and Siewert,
M. B.: Can C-band synthetic aperture radar be used to estimate soil organic
carbon storage in tundra?, Biogeosciences, 13, 5453–5470,
https://doi.org/10.5194/bg-13-5453-2016, 2016c. a
Bergstedt, H. and Bartsch, A.: Surface State across Scales; Temporal and
SpatialPatterns in Land Surface Freeze/Thaw Dynamics, Geosciences, 7, 65,
https://doi.org/10.3390/geosciences7030065, 2017. a, b, c
Biskaborn, B. K., Lanckman, J.-P., Lantuit, H., Elger, K., Streletskiy, D.
A., Cable, W. L., and Romanovsky, V. E.: The new database of the Global
Terrestrial Network for Permafrost (GTN-P), Earth Syst. Sci. Data, 7,
245–259, https://doi.org/10.5194/essd-7-245-2015, 2015. a, b
Bodri, L. and Cermak, V.: Borehole Climatology: a new method how to
reconstruct climate, Elsevier Science, 1st edn., 2007. a
Cheng, G. and Wu, T.: Responses of permafrost to climate change and their
environmental significance, Qinghai-Tibet Plateau, J. Geophys. Res.-Earth,
112, F02S03, https://doi.org/10.1029/2006JF000631, 2007. a
Dobinski, W.: Permafrost, Earth-Sci. Rev., 108, 158–169,
https://doi.org/10.1016/j.earscirev.2011.06.007, 2011. a
Figa-Saldaña, J., Wilson, J., Attema, E., Gelsthorpe, R., Drinkwater,
M., and Stoffelen, A.: The advanced scatterometer (ASCAT) on the
meteorological operational (MetOp) platform: A follow on for European wind
scatterometers, Can. J. Remote Sens., 28, 404–412, https://doi.org/10.5589/m02-035,
2002. a
Gruber, S.: Derivation and analysis of a high-resolution estimate of global
permafrost zonation, The Cryosphere, 6, 221–233,
https://doi.org/10.5194/tc-6-221-2012, 2012. a
GTN-P: Global Terrestrial Network for Permafrost Database: Permafrost
Temperature Data (TSP Thermal State of Permafrost), available at:
https://gtnp.arcticportal.org/, last access: 28 December 2016. a
Harris, S. A.: Distribution of zonal permafrost landforms with freezing and
thawing indices, Erdkunde, 35, 81–90, https://doi.org/10.3112/erdkunde.1981.02.01,
1981. a
Hayes, D. J., Kicklighter, D. W., McGuire, A. D., Chen, M., Zhuang, Q., Yuan,
F., Melillo, J. M., and Wullschleger, S. D.: The impacts of recent permafrost
thaw on land–atmosphere greenhouse gas exchange, Environ. Res. Lett., 9,
045005, https://doi.org/10.1088/1748-9326/9/4/045005, 2014. a
Hollinger, J. P., Peirce, J. L., and Poe, G. A.: SSM/I instrument evaluation,
IEEE T. Geosci. Remote, 28, 781–790, https://doi.org/10.1109/36.58964, 1990. a
Hugelius, G., Tarnocai, C., Broll, G., Canadell, J. G., Kuhry, P., and
Swanson, D. K.: The Northern Circumpolar Soil Carbon Database: spatially
distributed datasets of soil coverage and soil carbon storage in the northern
permafrost regions, Earth Syst. Sci. Data, 5, 3–13,
https://doi.org/10.5194/essd-5-3-2013, 2013. a, b
Hugelius, G., Strauss, J., Zubrzycki, S., Harden, J. W., Schuur, E. A. G.,
Ping, C.-L., Schirrmeister, L., Grosse, G., Michaelson, G. J., Koven, C. D.,
O'Donnell, J. A., Elberling, B., Mishra, U., Camill, P., Yu, Z., Palmtag, J.,
and Kuhry, P.: Estimated stocks of circumpolar permafrost carbon with
quantified uncertainty ranges and identified data gaps, Biogeosciences, 11,
6573–6593, https://doi.org/10.5194/bg-11-6573-2014, 2014. a, b
Kim, Y., Kimball, J. S., Zhang, K., and McDonald, K. C.: Satellite detection
of increasing Northern Hemisphere non-frozen seasons from 1979 to 2008:
Implications for regional vegetation growth, Remote Sens. Environ., 121,
472–487, https://doi.org/10.1016/j.rse.2012.02.014, 2012. a
Kim, Y., Kimball, J. S., Glassy, J., and McDonald, K. C.: MEaSUREs Global
Record of Daily Landscape Freeze/Thaw Status, Version 3,
https://doi.org/10.5067/MEASURES/CRYOSPHERE/nsidc-0477.003, 2014. a, b
Lachembruch, A. H. and Marshall, B. V.: Changing climate: geothermal evidence
from permafrost in the Alaskan Arctic, Science, 234, 689–696, 1986. a
Luoto, M., Fronzek, S., and Zuidhoff, F. S.: Spatial modelling of palsa mires
in relation to climate in northern Europe, Earth Surf. Proc. Land., 29,
1373–1387, https://doi.org/10.1002/esp.1099, 2004. a, b, c
Matthes, H., Rinke, A., Zhou, X., and Dethloff, K.: Uncertainties in coupled
regional Arctic climate simulations associated with the used land surface
model, J. Geophys. Res.-Atmos., 122, 7755–7771, https://doi.org/10.1002/2016JD026213,
2017. a
Metsämäki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann,
A., Solberg, R., Böttcher, K., Hiltunen, M., and Ripper, E.: Introduction
to GlobSnow Snow Extent products with considerations for accuracy assessment,
Remote Sens. Environ., 156, 96–108, https://doi.org/10.1016/j.rse.2014.09.018, 2015. a
Naeimi, V., Paulik, C., Bartsch, A., Wagner, W., Kidd, R., Boike, J., and
Elger, K.: ASCAT Surface State Flag (SSF): Extracting Information on
Surface Freeze/Thaw Conditions from Backscatter Data Using an Empirical
Threshold-Analysis Algorithm, IEEE T. Geosci. Remote, 50, 2566–2582,
https://doi.org/10.1109/TGRS.2011.2177667, 2012. a, b, c, d, e
National Research Council : Abrupt impacts of climate change: Anticipating
surprises, National Academies Press, 2013. a
Nelson, F. E. and Outcalt, S. I.: A Computational Method for Prediction and
Regionalization of Permafrost, Arctic Alpine Res., 19, 279–288, 1987. a
Nguyen, T., Burn, C., King, D., and Smith, S.: Estimating the extent of near
surface permafrost using remote sensing, Mackenzie Delta, Northwest
Territories, Permafrost Periglac., 20, 141–153, https://doi.org/10.1002/ppp.637, 2009. a
O'Connor, F. M., Boucher, O., Gedney, N., Jones, C. D., Folberth, G. A.,
Coppell, R., Friedlingstein, P., Collins, W. J., Chappellaz, J., Ridley, J.,
and Johnson, C. E.: Possible role of wetlands, permafrost, and methane
hydrates in the methane cycle under future climate change: A review, Rev.
Geophys., 48, RG4005, https://doi.org/10.1029/2010RG000326, 2010. a
O'Donnell, J. A., Jorgenson, M. T., Harden, J. W., McGuire, A. D., Kanevskiy,
M. Z., and Wickland, K. P.: The Effects of Permafrost Thaw on Soil
Hydrologic, Thermal, and Carbon Dynamics in an Alaskan Peatland, Ecosystems,
15, 213–229, https://doi.org/10.1007/s10021-011-9504-0, 2012. a
Park, H., Iijima, Y., Yabuki, H., Ohta, T., Walsh, J., Kodama, Y., and Ohata,
T.: The application of a coupled hydrological and biogeochemical model
(CHANGE) for modeling of energy, water, and CO2 exchanges over a larch forest
in eastern Siberia, J. Geophys. Res.-Atmos., 116, D15102,
https://doi.org/10.1029/2010JD015386, 2011a. a
Park, S.-E., Bartsch, A., Sabel, D., Wagner, W., Naeimi, V., and Yamaguchi,
Y.: Monitoring Freeze/Thaw Cycles Using ENVISAT ASAR Global Mode, Remote
Sens. Environ., 115, 3457–3467, https://doi.org/10.1016/j.rse.2011.08.009, 2011b. a, b
Park, H., Kim, Y., and Kimball, J.: Widespread permafrost vulnerability and
soil active layer increases over the high northern latitudes inferred from
satellite remote sensing and process model assessments, Remote Sens.
Environ., 175, 349–358, https://doi.org/10.1016/j.rse.2015.12.046, 2016. a, b, c, d, e, f, g, h
Paulik, C., Melzer, T., Hahn, S., Bartsch, A., Heim, B., Elger,
K., and Wagner, W.: Circumpolar surface soil moisture and freeze/thaw
surface status remote sensing products (version 4) with links to geotiff
images and NetCDF files (2007-01 to 2013-12), Pangaea,
https://doi.org/10.1594/PANGAEA.832153, 2014. a, b, c
Reschke, J., Bartsch, A., Schlaffer, S., and Schepaschenko, D.: Capability of
C-Band SAR for Operational Wetland Monitoring at High Latitudes, Remote
Sens., 4, 2923–2943, https://doi.org/10.3390/rs4102923, 2012. a
Romanovsky, V. E., Smith, S. L., and Christiansen, H. H.: Permafrost Thermal
State in the Polar Northern Hemisphere during the International Polar Year
2007–2009: a Synthesis, Permafrost Periglac., 21, 106–116,
https://doi.org/10.1002/ppp.689, 2010. a
Saito, K., Sueyoshi, T., Marchenko, S., Romanovsky, V., Otto-Bliesner, B.,
Walsh, J., Bigelow, N., Hendricks, A., and Yoshikawa, K.: LGM permafrost
distribution: how well can the latest PMIP multi-model ensembles perform
reconstruction?, Clim. Past, 9, 1697–1714,
https://doi.org/10.5194/cp-9-1697-2013, 2013. a, b
Schuur, E., Bockheim, J., Canadell, J., and Euskirchen, E.: Vulnerability of
permafrost carbon to climate change: Implications for the global carbon
cycle, BioScience, 58, 701–714, https://doi.org/10.1641/B580807, 2008. a
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J. W.,
Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M., Natali,
S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M. R., Treat,
C. C., and Vonk, J. E.: Climate change and the permafrost carbon feedback,
Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015. a
Seppälä, M.: The origin of palsas, Geogr. Ann., 68, 141,
https://doi.org/10.2307/521453, 1986. a
Smith, M. W. and Riseborough, D. W.: Climate and the limits of permafrost: a
zonal analysis, Permafrost Periglac., 13, 1–15, https://doi.org/10.1002/ppp.410, 2002. a
Soliman, A., Duguay, C., Saunders, W., and Hachem, S.: Pan-Arctic Land
Surface Temperature from MODIS and AATSR: Product Development and
Intercomparison, Remote Sens., 4, 3833–3856, https://doi.org/10.3390/rs4123833, 2012. a
Takala, M., Luojus, K., Pulliainen, J., Derksen, C., Lemmetyinen, J.,
Kärnä, J.-P., Koskinen, J., and Bojkov, B.: Estimating northern
hemisphere snow water equivalent for climate research through assimilation of
space-borne radiometer data and ground-based measurements, Remote Sens.
Environ., 115, 3517–3529, https://doi.org/10.1016/j.rse.2011.08.014, 2011. a
Trofaier, A. M., Westermann, S., and Bartsch, A.: Progress in space-borne
studies of permafrost for climate science: Towards a multi-ECV approach,
Remote Sens. Environ., 203, 55–70, https://doi.org/10.1016/j.rse.2017.05.021, 2017. a
Wang, L., Derksen, C., and Brown, R.: Detection of Pan-Arctic Terrestrial
Snowmelt from QuikSCAT, 2000–2005, Remote Sens. Environ., 112, 3794–3805,
https://doi.org/10.1016/j.rse.2008.05.017, 2008. a
Westermann, S., Østby, T. I., Gisnås, K., Schuler, T. V., and
Etzelmüller, B.: A ground temperature map of the North Atlantic
permafrost region based on remote sensing and reanalysis data, The
Cryosphere, 9, 1303–1319, https://doi.org/10.5194/tc-9-1303-2015, 2015.
a, b, c
Woo, M., Kane, D. L., Carey, S. K., and Yang, D.: Progress in permafrost
hydrology in the new millennium, Permafrost Periglac., 19, 237–254,
https://doi.org/10.1002/ppp.613, 2008. a
Zhang, T., Frauenfeld, O. W., Serreze, M. C., Etringer, A., Oelke, C.,
McCreight, J., Barry, R. G., Gilichinsky, D., Yang, D., Ye, H., Ling, F., and
Chudinova, S.: Spatial and temporal variability in active layer thickness
over the Russian Arctic drainage basin, J. Geophys. Res.-Atmos., 110, D16101,
https://doi.org/10.1029/2004JD005642, 2005. a, b, c, d
Zhang, T., Barry, R., Knowles, K., Heginbottom, J., and Brown, J.: Statistics
and characteristics of permafrost and ground-ice distribution in the Northern
Hemisphere, Polar Geography, 31, 47–68, https://doi.org/10.1080/10889370802175895,
2008. a
Zwieback, S., Paulik, C., and Wagner, W.: Frozen Soil Detection Based on
Advanced Scatterometer Observations and Air Temperature Data as Part of Soil
Moisture Retrieval, Remote Sens., 7, 3206–3231, https://doi.org/10.3390/rs70303206,
2015. a
Short summary
Knowledge about permafrost extent is required with respect to climate change. We used borehole temperature records from across the Arctic for the assessment of surface status information (frozen or unfrozen) derived from space-borne microwave sensors for permafrost extent mapping. The comparison to mean annual ground temperature (MAGT) at the coldest sensor depth revealed that not only extent but also temperature can be obtained from C-band-derived surface state with a residual error of 2.22 °C.
Knowledge about permafrost extent is required with respect to climate change. We used borehole...
