Articles | Volume 20, issue 4
https://doi.org/10.5194/tc-20-1967-2026
© Author(s) 2026. 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-20-1967-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Apr 2026
Research article |
| 10 Apr 2026
| 10 Apr 2026
Stochastic modelling of thermokarst lakes: size distributions and dynamic regimes
Constanze Reinken
CORRESPONDING AUTHOR
Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Bundesstraße 53, 20146 Hamburg, Germany
Victor Brovkin
Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Philipp de Vrese
Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Ingmar Nitze
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Telegrafenberg A45, 14473 Potsdam, Germany
Helena Bergstedt
b.geos GmbH, Industriestrasse 1, Korneuburg, 2100, Niederösterreich, Austria
Guido Grosse
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Telegrafenberg A45, 14473 Potsdam, Germany
University of Potsdam, Institute of Geosciences, Karl-Liebknecht-Str. 24–25, 14476 Potsdam, Germany
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Annabeth McCall, Martin Hieronymi, P. Paul Overduin, Lisa Bröder, Julie Lattaud, Rüdiger Röttgers, Irina Overeem, Anne Morgenstern, Guido Grosse, and Bennet Juhls
Biogeosciences, 23, 5921–5942, https://doi.org/10.5194/bg-23-5921-2026, https://doi.org/10.5194/bg-23-5921-2026, 2026
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This study examines how carbon and sediments move from the Mackenzie River, through its delta, and into the Beaufort Sea. We use data from 2009–2024 and show that major changes in carbon concentrations unfold in low-salinity mixing zones. As the optical properties of the water also shift, satellite estimates of carbon will require more tailored methods. These findings will improve our understanding of Arctic carbon fluxes and influences on the greater Arctic Ocean carbon budget.
Carl Stadie, Ingmar Nitze, Begüm Demir, Martin Stefan Brandt, and Guido Grosse
EGUsphere, https://doi.org/10.5194/egusphere-2026-4074, https://doi.org/10.5194/egusphere-2026-4074, 2026
This preprint is open for discussion and under review for Earth Observation (EO).
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Driftwood piles up along Arctic coasts, storing carbon and shaping habitats, but mapping it automatically is difficult. We compared three artificial intelligence models on aerial photos and satellite images, repeating each test many times to capture natural training variation. Image resolution mattered far more than which model was used, and testing only once, as is common, gave misleading results. Our approach offers a more reliable way to choose mapping tools for similar Arctic features.
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel A. Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas L. Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
Geosci. Model Dev., 19, 6941–6966, https://doi.org/10.5194/gmd-19-6941-2026, https://doi.org/10.5194/gmd-19-6941-2026, 2026
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We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Matthias Cuntz, Stephan Thober, Anne Verhoef, Yijian Zeng, Aaron Boone, Agnès Ducharne, Sujan Koirala, David M. Lawrence, Philipp de Vrese, Carsten Montzka, Sonia I. Seneviratne, Harry Vereecken, Dani Or, Salma Tafasca, Naoki Mizukami, Rich Ellis, Patrick C. McGuire, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2026-4223, https://doi.org/10.5194/egusphere-2026-4223, 2026
Preprint archived
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Land surface models (LSMs) are essential tools to analyze future climate change. Here we pushed state-of-the-art LSMs out of their comfort zone revealing hidden connections between processes encoded into the models. The LSMs reacted differently due to complex, sometimes counter-intuitive interactions of different water fluxes. We identified surface runoff and soil evaporation as the two main reasons behind model differences, which should be improved by using more mechanistic descriptions.
Thomas Kleinen, Helena Bergstedt, Philipp de Vrese, Tobias Stacke, and Victor Brovkin
EGUsphere, https://doi.org/10.5194/egusphere-2026-3098, https://doi.org/10.5194/egusphere-2026-3098, 2026
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The Arctic holds a large amount of carbon in frozen permafrost soils. Climate change will thaw the permafrost, leading to carbon decomposition and CO2 emission. Using a land surface model, we tested the effect of plant distribution changes in low, medium and high warming futures. If the plant distribution is allowed to adapt to a changed climate, biomass increases strongly, limiting carbon losses to ~70 PgC under high warming, and even a small net gain of carbon in low warming scenarios.
Fabian Seemann, Michael Zech, Maren Jenrich, Guido Grosse, Benjamin M. Jones, Claire Treat, Lutz Schirrmeister, Susanne Liebner, and Jens Strauss
Biogeosciences, 23, 3675–3695, https://doi.org/10.5194/bg-23-3675-2026, https://doi.org/10.5194/bg-23-3675-2026, 2026
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Arctic coastal landscapes, like those in northernmost Alaska, are often characterized by saline permafrost which is prone to thawing. We studied six sediment cores to understand how thawing and salinity affect organic matter breakdown and landscape change. Our results show that salinity accelerates organic matter degradation when permafrost thaws. This highlights the overlooked risk of salinity in shaping Arctic landscapes and carbon mineralization as the climate continues to warm.
Benjamin M. Sanderson, Marit Sandstad, Alejandro Romero-Prieto, Stuart Jenkins, Charles Koven, Glen Peters, Roland Séfèrian, Andrew H. MacDougall, Ashwin Seshadri, Victor Brovkin, John Dunne, Abigail L. S. Swann, Torben Koenigk, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Hongmei Li, Peter Lawrence, Spencer Liddicoat, Nadine Mengis, Anastasia Romanou, Lori T. Sentman, Chris Smith, Norman J. Steinert, Jerry Tjiputra, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2026-1875, https://doi.org/10.5194/egusphere-2026-1875, 2026
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When humanity stops emitting carbon dioxide, will temperatures keep rising, stabilize, or fall? Our study reveals in most models, temperatures remain nearly stable, but this hides a balance between the warming in response to radiation imbalance, and the cooling due to uptake of carbon in the land and ocean. Understanding this balance helps refine how much more CO2 we can safely emit.
Luana S. Basso, Goran Georgievski, Victor Brovkin, Christian Beer, Christian Rödenbeck, and Mathias Göckede
Biogeosciences, 23, 2815–2830, https://doi.org/10.5194/bg-23-2815-2026, https://doi.org/10.5194/bg-23-2815-2026, 2026
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This study examines how combining atmospheric inversion with process-based modelling can reduce discrepancies in estimates of Arctic wetland CH4 emissions. We conducted a series of inversion experiments, each incorporating CH4 wetland fluxes from process-based models with different CH4 production parameterizations. Our results showed that no single parameterization captures the complexity of Arctic–Boreal emissions; instead, region-specific adjustments are needed to reduce discrepancies.
Abigail L. S. Swann, Charles D. Koven, Cristian Proistosecu, Rosie A. Fisher, Benjamin M. Sanderson, Victor Brovkin, Tomohiro Hajima, Chris D. Jones, Nancy Y. Kiang, David M. Lawrence, Spencer Liddicoat, Hannah Liddy, Anastasia Romanou, Roland Séférian, Lori T. Sentman, Norman J. Steinert, Jerry Tjiputra, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2026-1673, https://doi.org/10.5194/egusphere-2026-1673, 2026
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We analyzed simulations from Earth system models (ESM) with a constant rate of emissions, zero emissions, and negative emissions of CO2 to quantify the response of land carbon sinks. We found that under positive emissions vegetation in the tropics gained carbon. Under zero emissions and negative emissions most ESMs lost carbon from vegetation in the tropics but gained carbon in mid- and high-latitudes, mostly in soils. Our findings imply that tropical carbon is vulnerable under zero emissions.
Tamara Emmerichs, Fabrice Lacroix, Victor Brovkin, Sönke Zaehle, Cheng Gong, Yu Zhu, Sofie Sjogersten, Carolina Voigt, Klaus Steenberg Larsen, and Eeva-Stiina Tuitila
EGUsphere, https://doi.org/10.5194/egusphere-2026-1514, https://doi.org/10.5194/egusphere-2026-1514, 2026
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Shrubs use water and carbon differently and are expanding in warming tundra and grasslands, yet global models lack accuracy. We added two shrub types to a vegetation model including soil nutrients and carbon exchange. Half of the modeled shrubs showed good performance whereas their growth is 40 % higher as at grasses. Deciduous shrubs reduce nitrogen more than evergreens. Including shrubs improves Arctic carbon cycle predictions, revealing nitrogen limits cause underestimation in global models.
Marius Moser, Lara Kaiser, Victor Brovkin, and Christian Beer
Biogeosciences, 23, 605–621, https://doi.org/10.5194/bg-23-605-2026, https://doi.org/10.5194/bg-23-605-2026, 2026
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Arctic warming might lead to increased carbon dioxide and methane emissions. Process-based prediction of their ratio is important for projecting the future carbon cycle. However, land surface models often assume a constant ratio. To overcome this limitation, we identify three core processes for representing methanogenesis accurately in land surface models: fermentation, acetoclastic methanogenesis, and hydrogenotrophic methanogenesis.
Kseniia Ivanova, Anna-Maria Virkkala, Victor Brovkin, Tobias Stacke, Barbara Widhalm, Annett Bartsch, Carolina Voigt, Oliver Sonnentag, and Mathias Göckede
Biogeosciences, 23, 233–262, https://doi.org/10.5194/bg-23-233-2026, https://doi.org/10.5194/bg-23-233-2026, 2026
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We measured over 13,000 methane fluxes at a site in the Canadian Arctic and linked them with drone and free satellite images. We tested four machine-learning methods and two map scales. Metre-scale maps captured small wet and dry features that strongly affect methane release, while coarser maps blurred them. Different models shifted the monthly methane estimate. This helps choose the right data and tools to map methane, design monitoring networks, and check climate models.
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblueh, Clarissa A. Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
Geosci. Model Dev., 18, 9385–9415, https://doi.org/10.5194/gmd-18-9385-2025, https://doi.org/10.5194/gmd-18-9385-2025, 2025
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We provide a new Earth System model configuration framed into the ICON architecture, which provides the baseline for the next generation of climate predictions and projections (hereafter ICON XPP). Two resolutions of ICON XPP are presented that show high runtime performances making it suitable to run long integrations and large-ensemble experiments. ICON XPP similarly perform to CMIP6-class of climate models making it a good basis for climate forecasts and projections, and climate research.
Félix García-Pereira, Jesús Fidel González-Rouco, Nagore Meabe-Yanguas, Philipp de Vrese, Norman Julius Steinert, Johann Jungclaus, and Stephan Lorenz
The Cryosphere, 19, 5959–5981, https://doi.org/10.5194/tc-19-5959-2025, https://doi.org/10.5194/tc-19-5959-2025, 2025
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This work shows that changing the hydrological state of permafrost produces differences of up to 3 °C in the annual ground temperature, 1–2 m in the active layer thickness, and 5 million km2 in the permafrost extent. Including a deeper vertical thermal scheme reduces the extent decline by more than 2 million km2 in the highest radiative emission scenario. This is shown for the first time in fully-coupled experiments with an Earth System Model.
Victor Brovkin, Benjamin M. Sanderson, Noel G. Brizuela, Tomohiro Hajima, Tatiana Ilyina, Chris D. Jones, Charles Koven, David Lawrence, Peter Lawrence, Hongmei Li, Spencer Liddcoat, Anastasia Romanou, Roland Séférian, Lori T. Sentman, Abigail L. S. Swann, Jerry Tjiputra, Tilo Ziehn, and Alexander J. Winkler
Earth Syst. Dynam., 16, 2021–2034, https://doi.org/10.5194/esd-16-2021-2025, https://doi.org/10.5194/esd-16-2021-2025, 2025
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Idealized experiments with Earth system models provide a basis for understanding the response of the carbon cycle to emissions. We show that most models exhibit a quasi-linear relationship between cumulative carbon uptake on land and in the ocean and hypothesize that this relationship does not depend on emission pathways. We reduce the coupled system to only one differential equation, which represents a powerful simplification of the Earth system dynamics as a function of fossil fuel emissions.
Philipp de Vrese, Tobias Stacke, Veronika Gayler, Helena Bergstedt, Clemens von Baeckmann, Melanie Thurner, Christian Beer, and Victor Brovkin
EGUsphere, https://doi.org/10.5194/egusphere-2025-4031, https://doi.org/10.5194/egusphere-2025-4031, 2025
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The spatial variability in the land surface properties is often not captured by the resolution of land surface models. To overcome this limitation, most models subdivide the grid cells into fractions with homogeneous characteristics, for which the land processes are calculated separately. In reality, the fractions interact via the lateral exchange of water and heat, and the present manuscript details an approach to include these fluxes in the land component of the ICON modeling framework.
Nina Nesterova, Ilia Tarasevich, Marina Leibman, Artem Khomutov, Alexander Kizyakov, Ingmar Nitze, and Guido Grosse
Earth Syst. Sci. Data, 17, 5707–5727, https://doi.org/10.5194/essd-17-5707-2025, https://doi.org/10.5194/essd-17-5707-2025, 2025
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We created the first detailed map of retrogressive thaw slump (RTS) landforms across a large area of the West Siberian Arctic. RTSs are key features of abrupt permafrost thaw accelerated by climate change. Using satellite images and field data, we identified and classified over 6000 RTSs. This dataset helps scientists better understand how warming is changing Arctic landscapes and provides a trusted reference for training artificial intelligence to detect these landforms in the future.
Annett Bartsch, Rodrigue Tanguy, Helena Bergstedt, Clemens von Baeckmann, Hans Tømmervik, Marc Macias-Fauria, Juha Lemmetyinen, Kimmo Rautiainen, Chiara Gruber, and Bruce C. Forbes
The Cryosphere, 19, 4929–4967, https://doi.org/10.5194/tc-19-4929-2025, https://doi.org/10.5194/tc-19-4929-2025, 2025
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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.
Nathaelle Bouttes, Lester Kwiatkowski, Elodie Bougeot, Manon Berger, Victor Brovkin, and Guy Munhoven
Biogeosciences, 22, 4531–4544, https://doi.org/10.5194/bg-22-4531-2025, https://doi.org/10.5194/bg-22-4531-2025, 2025
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Coral reefs are under threat due to warming and ocean acidification. It is difficult to project future coral reef production due to uncertainties in climate models, socioeconomic scenarios and coral adaptation to warming. Here we have included a coral reef module within a climate model for the first time to evaluate the range of possible futures. We show that coral reef production decreases in most future scenarios, but in some cases coral reef carbonate production can persist.
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, https://doi.org/10.5194/gmd-18-5699-2025, 2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
Stiig Wilkenskjeld, Thomas Kleinen, Tobias Stacke, and Victor Brovkin
EGUsphere, https://doi.org/10.5194/egusphere-2025-3601, https://doi.org/10.5194/egusphere-2025-3601, 2025
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Methane is the second most important greenhouse gas with high potential for short term reductions of human induced global warming. We model methane emissions from the most important and most uncertain natural source: wetlands. We investigate how a number of assumptions, including human impact on natural wetlands, influences the wetlands and their methane emissions. Of the tested influences we find the most important to be how humans are altering the soil surface.
Lutz Schirrmeister, Margret C. Fuchs, Thomas Opel, Andrei Andreev, Frank Kienast, Andrea Schneider, Larisa Nazarova, Larisa Frolova, Svetlana Kuzmina, Tatiana Kuznetsova, Vladimir Tumskoy, Heidrun Matthes, Gerrit Lohmann, Guido Grosse, Viktor Kunitsky, Hanno Meyer, Heike H. Zimmermann, Ulrike Herzschuh, Thomas Böhmer, Stuart Umbo, Sevi Modestou, Sebastian F. M. Breitenbach, Anfisa Pismeniuk, Georg Schwamborn, Stephanie Kusch, and Sebastian Wetterich
Clim. Past, 21, 1143–1184, https://doi.org/10.5194/cp-21-1143-2025, https://doi.org/10.5194/cp-21-1143-2025, 2025
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Geochronological, cryolithological, paleoecological, and modeling data reconstruct the Last Interglacial (LIG) climate around the New Siberian Islands and reveal significantly warmer conditions compared to today. The critical challenges in predicting future ecosystem responses lie in the fact that the land–ocean distribution during the LIG was markedly different from today, affecting the degree of continentality, which played a major role in modulating climate and ecosystem dynamics.
Frieda P. Giest, Maren Jenrich, Guido Grosse, Benjamin M. Jones, Kai Mangelsdorf, Torben Windirsch, and Jens Strauss
Biogeosciences, 22, 2871–2887, https://doi.org/10.5194/bg-22-2871-2025, https://doi.org/10.5194/bg-22-2871-2025, 2025
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Climate warming causes permafrost to thaw, releasing greenhouse gases and affecting ecosystems. We studied sediments from Arctic coastal landscapes, including land, lakes, lagoons, and the ocean, finding that organic carbon storage and quality vary with landscape features and saltwater influence. Freshwater and land areas store more carbon, while saltwater reduces its quality. These findings improve predictions of Arctic responses to climate change and their impact on global carbon cycling.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
Earth Syst. Dynam., 16, 803–840, https://doi.org/10.5194/esd-16-803-2025, https://doi.org/10.5194/esd-16-803-2025, 2025
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Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the Land Use Model Intercomparison Project (LUMIP) and the Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that LUC-induced carbon emissions contribute to a BGC warming of 0.21 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasize the need for improved representations of LUC processes.
Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data, 17, 1707–1730, https://doi.org/10.5194/essd-17-1707-2025, https://doi.org/10.5194/essd-17-1707-2025, 2025
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The Lena Delta is the largest river delta in the Arctic and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Maren Jenrich, Juliane Wolter, Susanne Liebner, Christian Knoblauch, Guido Grosse, Fiona Giebeler, Dustin Whalen, and Jens Strauss
Biogeosciences, 22, 2069–2086, https://doi.org/10.5194/bg-22-2069-2025, https://doi.org/10.5194/bg-22-2069-2025, 2025
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Climate warming in the Arctic is causing the erosion of permafrost coasts and the transformation of permafrost lakes into lagoons. To understand how this affects greenhouse gas (GHG) emissions, we studied carbon dioxide (CO₂) and methane (CH₄) production in lagoons with varying sea connections. Younger lagoons produce more CH₄, while CO₂ increases under more marine conditions. Flooding of permafrost lowlands due to rising sea levels may lead to higher GHG emissions from Arctic coasts in future.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris D. Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
Biogeosciences, 22, 1447–1473, https://doi.org/10.5194/bg-22-1447-2025, https://doi.org/10.5194/bg-22-1447-2025, 2025
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This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations (CO2 concentration- and emission-driven experiments). We successfully identified problems with regard to the global carbon budget in each model. We also found urgent issues with regard to land use change CO2 emissions that should be solved in the latest generation of models.
Barbara Widhalm, Annett Bartsch, Tazio Strozzi, Nina Jones, Artem Khomutov, Elena Babkina, Marina Leibman, Rustam Khairullin, Mathias Göckede, Helena Bergstedt, Clemens von Baeckmann, and Xaver Muri
The Cryosphere, 19, 1103–1133, https://doi.org/10.5194/tc-19-1103-2025, https://doi.org/10.5194/tc-19-1103-2025, 2025
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Mapping soil moisture in Arctic permafrost regions is crucial for various activities, but it is challenging with typical satellite methods due to the landscape's diversity. Seasonal freezing and thawing cause the ground to periodically rise and subside. Our research demonstrates that this seasonal ground settlement, measured with Sentinel-1 satellite data, is larger in areas with wetter soils. This method helps to monitor permafrost degradation.
Annett Bartsch, Xaver Muri, Markus Hetzenecker, Kimmo Rautiainen, Helena Bergstedt, Jan Wuite, Thomas Nagler, and Dmitry Nicolsky
The Cryosphere, 19, 459–483, https://doi.org/10.5194/tc-19-459-2025, https://doi.org/10.5194/tc-19-459-2025, 2025
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We developed a robust freeze–thaw detection approach, applying a constant threshold to Copernicus Sentinel-1 data that is suitable for tundra regions. All global, coarser-resolution products, tested with the resulting benchmarking dataset, are of value for freeze–thaw retrieval, although differences were found depending on the seasons, particularly during the spring and autumn transition.
Tabea Rettelbach, Ingmar Nitze, Inge Grünberg, Jennika Hammar, Simon Schäffler, Daniel Hein, Matthias Gessner, Tilman Bucher, Jörg Brauchle, Jörg Hartmann, Torsten Sachs, Julia Boike, and Guido Grosse
Earth Syst. Sci. Data, 16, 5767–5798, https://doi.org/10.5194/essd-16-5767-2024, https://doi.org/10.5194/essd-16-5767-2024, 2024
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Permafrost landscapes in the Arctic are rapidly changing due to climate warming. Here, we publish aerial images and elevation models with very high spatial detail that help study these landscapes in northwestern Canada and Alaska. The images were collected using the Modular Aerial Camera System (MACS). This dataset has significant implications for understanding permafrost landscape dynamics in response to climate change. It is publicly available for further research.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernardello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
Earth Syst. Dynam., 15, 1591–1628, https://doi.org/10.5194/esd-15-1591-2024, https://doi.org/10.5194/esd-15-1591-2024, 2024
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The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.
Lydia Stolpmann, Ingmar Nitze, Ingeborg Bussmann, Benjamin M. Jones, Josefine Lenz, Hanno Meyer, Juliane Wolter, and Guido Grosse
EGUsphere, https://doi.org/10.5194/egusphere-2024-2822, https://doi.org/10.5194/egusphere-2024-2822, 2024
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We combine hydrochemical and lake change data to show consequences of permafrost thaw induced lake changes on hydrochemistry, which are relevant for the global carbon cycle. We found higher methane concentrations in lakes that do not freeze to the ground and show that lagoons have lower methane concentrations than lakes. Our detailed lake sampling approach show higher concentrations in Dissolved Organic Carbon in areas of higher erosion rates, that might increase under the climate warming.
Nina Nesterova, Marina Leibman, Alexander Kizyakov, Hugues Lantuit, Ilya Tarasevich, Ingmar Nitze, Alexandra Veremeeva, and Guido Grosse
The Cryosphere, 18, 4787–4810, https://doi.org/10.5194/tc-18-4787-2024, https://doi.org/10.5194/tc-18-4787-2024, 2024
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Retrogressive thaw slumps (RTSs) are widespread in the Arctic permafrost landforms. RTSs present a big interest for researchers because of their expansion due to climate change. There are currently different scientific schools and terminology used in the literature on this topic. We have critically reviewed existing concepts and terminology and provided clarifications to present a useful base for experts in the field and ease the introduction to the topic for scientists who are new to it.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
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We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
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.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Soraya Kaiser, Julia Boike, Guido Grosse, and Moritz Langer
Earth Syst. Sci. Data, 16, 3719–3753, https://doi.org/10.5194/essd-16-3719-2024, https://doi.org/10.5194/essd-16-3719-2024, 2024
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Arctic warming, leading to permafrost degradation, poses primary threats to infrastructure and secondary ecological hazards from possible infrastructure failure. Our study created a comprehensive Alaska inventory combining various data sources with which we improved infrastructure classification and data on contaminated sites. This resource is presented as a GeoPackage allowing planning of infrastructure damage and possible implications for Arctic communities facing permafrost challenges.
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
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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.
Félix García-Pereira, Jesús Fidel González-Rouco, Camilo Melo-Aguilar, Norman Julius Steinert, Elena García-Bustamante, Philip de Vrese, Johann Jungclaus, Stephan Lorenz, Stefan Hagemann, Francisco José Cuesta-Valero, Almudena García-García, and Hugo Beltrami
Earth Syst. Dynam., 15, 547–564, https://doi.org/10.5194/esd-15-547-2024, https://doi.org/10.5194/esd-15-547-2024, 2024
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According to climate model estimates, the land stored 2 % of the system's heat excess in the last decades, while observational studies show it was around 6 %. This difference stems from these models using land components that are too shallow to constrain land heat uptake. Deepening the land component does not affect the surface temperature. This result can be used to derive land heat uptake estimates from different sources, which are much closer to previous observational reports.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Félix García-Pereira, Jesús Fidel González-Rouco, Thomas Schmid, Camilo Melo-Aguilar, Cristina Vegas-Cañas, Norman Julius Steinert, Pedro José Roldán-Gómez, Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, and Philipp de Vrese
SOIL, 10, 1–21, https://doi.org/10.5194/soil-10-1-2024, https://doi.org/10.5194/soil-10-1-2024, 2024
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This work addresses air–ground temperature coupling and propagation into the subsurface in a mountainous area in central Spain using surface and subsurface data from six meteorological stations. Heat transfer of temperature changes at the ground surface occurs mainly by conduction controlled by thermal diffusivity of the subsurface, which varies with depth and time. A new methodology shows that near-surface diffusivity and soil moisture content changes with time are closely related.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
Zoé Rehder, Thomas Kleinen, Lars Kutzbach, Victor Stepanenko, Moritz Langer, and Victor Brovkin
Biogeosciences, 20, 2837–2855, https://doi.org/10.5194/bg-20-2837-2023, https://doi.org/10.5194/bg-20-2837-2023, 2023
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We use a new model to investigate how methane emissions from Arctic ponds change with warming. We find that emissions increase substantially. Under annual temperatures 5 °C above present temperatures, pond methane emissions are more than 3 times higher than now. Most of this increase is caused by an increase in plant productivity as plants provide the substrate microbes used to produce methane. We conclude that vegetation changes need to be included in predictions of pond methane emissions.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Thomas Kleinen, Sergey Gromov, Benedikt Steil, and Victor Brovkin
Clim. Past, 19, 1081–1099, https://doi.org/10.5194/cp-19-1081-2023, https://doi.org/10.5194/cp-19-1081-2023, 2023
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We modelled atmospheric methane continuously from the last glacial maximum to the present using a state-of-the-art Earth system model. Our model results compare well with reconstructions from ice cores and improve our understanding of a very intriguing period of Earth system history, the deglaciation, when atmospheric methane changed quickly and strongly. Deglacial methane changes are driven by emissions from tropical wetlands, with wetlands in high northern latitudes being secondary.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, https://doi.org/10.5194/tc-17-2095-2023, 2023
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The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the Max Planck Institute (MPI) Earth System Model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of this inter-model spread and have pronounced impacts on important elements of Earth systems as far to the south as the tropics.
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.
Mauricio Arboleda-Zapata, Michael Angelopoulos, Pier Paul Overduin, Guido Grosse, Benjamin M. Jones, and Jens Tronicke
The Cryosphere, 16, 4423–4445, https://doi.org/10.5194/tc-16-4423-2022, https://doi.org/10.5194/tc-16-4423-2022, 2022
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We demonstrate how we can reliably estimate the thawed–frozen permafrost interface with its associated uncertainties in subsea permafrost environments using 2D electrical resistivity tomography (ERT) data. In addition, we show how further analyses considering 1D inversion and sensitivity assessments can help quantify and better understand 2D ERT inversion results. Our results illustrate the capabilities of the ERT method to get insights into the development of the subsea permafrost.
Loeka L. Jongejans, Kai Mangelsdorf, Cornelia Karger, Thomas Opel, Sebastian Wetterich, Jérémy Courtin, Hanno Meyer, Alexander I. Kizyakov, Guido Grosse, Andrei G. Shepelev, Igor I. Syromyatnikov, Alexander N. Fedorov, and Jens Strauss
The Cryosphere, 16, 3601–3617, https://doi.org/10.5194/tc-16-3601-2022, https://doi.org/10.5194/tc-16-3601-2022, 2022
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Large parts of Arctic Siberia are underlain by permafrost. Climate warming leads to permafrost thaw. At the Batagay megaslump, permafrost sediments up to ~ 650 kyr old are exposed. We took sediment samples and analysed the organic matter (e.g. plant remains). We found distinct differences in the biomarker distributions between the glacial and interglacial deposits with generally stronger microbial activity during interglacial periods. Further permafrost thaw enhances greenhouse gas emissions.
Jan Nitzbon, Damir Gadylyaev, Steffen Schlüter, John Maximilian Köhne, Guido Grosse, and Julia Boike
The Cryosphere, 16, 3507–3515, https://doi.org/10.5194/tc-16-3507-2022, https://doi.org/10.5194/tc-16-3507-2022, 2022
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The microstructure of permafrost soils contains clues to its formation and its preconditioning to future change. We used X-ray computed tomography (CT) to measure the composition of a permafrost drill core from Siberia. By combining CT with laboratory measurements, we determined the the proportions of pore ice, excess ice, minerals, organic matter, and gas contained in the core at an unprecedented resolution. Our work demonstrates the potential of CT to study permafrost properties and processes.
Mateo Duque-Villegas, Martin Claussen, Victor Brovkin, and Thomas Kleinen
Clim. Past, 18, 1897–1914, https://doi.org/10.5194/cp-18-1897-2022, https://doi.org/10.5194/cp-18-1897-2022, 2022
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Using an Earth system model of intermediate complexity, we quantify contributions of the Earth's orbit, greenhouse gases (GHGs) and ice sheets to the strength of Saharan greening during late Quaternary African humid periods (AHPs). Orbital forcing is found as the dominant factor, having a critical threshold and accounting for most of the changes in the vegetation response. However, results suggest that GHGs may influence the orbital threshold and thus may play a pivotal role for future AHPs.
Matthias Fuchs, Juri Palmtag, Bennet Juhls, Pier Paul Overduin, Guido Grosse, Ahmed Abdelwahab, Michael Bedington, Tina Sanders, Olga Ogneva, Irina V. Fedorova, Nikita S. Zimov, Paul J. Mann, and Jens Strauss
Earth Syst. Sci. Data, 14, 2279–2301, https://doi.org/10.5194/essd-14-2279-2022, https://doi.org/10.5194/essd-14-2279-2022, 2022
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We created digital, high-resolution bathymetry data sets for the Lena Delta and Kolyma Gulf regions in northeastern Siberia. Based on nautical charts, we digitized depth points and isobath lines, which serve as an input for a 50 m bathymetry model. The benefit of this data set is the accurate mapping of near-shore areas as well as the offshore continuation of the main deep river channels. This will improve the estimation of river outflow and the nutrient flux output into the coastal zone.
Charlotte Haugk, Loeka L. Jongejans, Kai Mangelsdorf, Matthias Fuchs, Olga Ogneva, Juri Palmtag, Gesine Mollenhauer, Paul J. Mann, P. Paul Overduin, Guido Grosse, Tina Sanders, Robyn E. Tuerena, Lutz Schirrmeister, Sebastian Wetterich, Alexander Kizyakov, Cornelia Karger, and Jens Strauss
Biogeosciences, 19, 2079–2094, https://doi.org/10.5194/bg-19-2079-2022, https://doi.org/10.5194/bg-19-2079-2022, 2022
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Buried animal and plant remains (carbon) from the last ice age were freeze-locked in permafrost. At an extremely fast eroding permafrost cliff in the Lena Delta (Siberia), we found this formerly frozen carbon well preserved. Our results show that ongoing degradation releases substantial amounts of this carbon, making it available for future carbon emissions. This mobilisation at the studied cliff and also similarly eroding sites bear the potential to affect rivers and oceans negatively.
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.
Stiig Wilkenskjeld, Frederieke Miesner, Paul P. Overduin, Matteo Puglini, and Victor Brovkin
The Cryosphere, 16, 1057–1069, https://doi.org/10.5194/tc-16-1057-2022, https://doi.org/10.5194/tc-16-1057-2022, 2022
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Thawing permafrost releases carbon to the atmosphere, enhancing global warming. Part of the permafrost soils have been flooded by rising sea levels since the last ice age, becoming subsea permafrost (SSPF). The SSPF is less studied than the part on land. In this study we use a global model to obtain rates of thawing of SSPF under different future climate scenarios until the year 3000. After the year 2100 the scenarios strongly diverge, closely connected to the eventual disappearance of sea ice.
István Dunkl, Aaron Spring, Pierre Friedlingstein, and Victor Brovkin
Earth Syst. Dynam., 12, 1413–1426, https://doi.org/10.5194/esd-12-1413-2021, https://doi.org/10.5194/esd-12-1413-2021, 2021
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The variability in atmospheric CO2 is largely controlled by terrestrial carbon fluxes. These land–atmosphere fluxes are predictable for around 2 years, but the mechanisms providing the predictability are not well understood. By decomposing the predictability of carbon fluxes into individual contributors we were able to explain the spatial and seasonal patterns and the interannual variability of CO2 flux predictability.
Aaron Spring, István Dunkl, Hongmei Li, Victor Brovkin, and Tatiana Ilyina
Earth Syst. Dynam., 12, 1139–1167, https://doi.org/10.5194/esd-12-1139-2021, https://doi.org/10.5194/esd-12-1139-2021, 2021
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Numerical carbon cycle prediction models usually do not start from observed carbon states due to sparse observations. Instead, only physical climate is reconstructed, assuming that the carbon cycle follows indirectly. Here, we test in an idealized framework how well this indirect and direct reconstruction with perfect observations works. We find that indirect reconstruction works quite well and that improvements from the direct method are limited, strengthening the current indirect use.
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, Theodore J. Bohn, John Connolly, Patrick Crill, Eugénie S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O'Donnell, Frans-Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire Treat, Ruth K. Varner, Tarmo Virtanen, Rebecca K. Warren, and Jennifer D. Watts
Earth Syst. Sci. Data, 13, 5127–5149, https://doi.org/10.5194/essd-13-5127-2021, https://doi.org/10.5194/essd-13-5127-2021, 2021
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Wetlands, lakes, and rivers are important sources of the greenhouse gas methane to the atmosphere. To understand current and future methane emissions from northern regions, we need maps that show the extent and distribution of specific types of wetlands, lakes, and rivers. The Boreal–Arctic Wetland and Lake Dataset (BAWLD) provides maps of five wetland types, seven lake types, and three river types for northern regions and will improve our ability to predict future methane emissions.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
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.
Cited articles
Anderson, L., Edwards, M., Shapley, M. D., Finney, B. P., and Langdon, C.: Holocene Thermokarst Lake Dynamics in Northern Interior Alaska: The Interplay of Climate, Fire, and Subsurface Hydrology, Front. Earth Sci., 7, https://doi.org/10.3389/feart.2019.00053, 2019. a, b
Anthony, K. M. W., Zimov, S. A., Grosse, G., Jones, M. C., Anthony, P. M., Chapin III, F. S., Finlay, J. C., Mack, M. C., Davydov, S., Frenzel, P., and Frolking, S.: A shift of thermokarst lakes from carbon sources to sinks during the Holocene epoch, Nature, 511, 452–456, https://doi.org/10.1038/nature13560, 2014. a
Arp, C. D., Jones, B. M., Schmutz, J. A., Urban, F. E., and Jorgenson, M. T.: Two mechanisms of aquatic and terrestrial habitat change along an Alaskan Arctic coastline, Polar Biol., 33, 1629–1640, https://doi.org/10.1007/s00300-010-0800-5, 2010. a
Arp, C. D., Jones, B. M., Liljedahl, A. K., Hinkel, K. M., and Welker, J. A.: Depth, ice thickness, and ice-out timing cause divergent hydrologic responses among Arctic lakes, Water Resour. Res., 51, 9379–9401, https://doi.org/10.1002/2015WR017362, 2015. a
Arp, C. D., Jones, B. M., Melanie Engram, V. A. A., Lei Cai, A. P., Hinkel, K., Bondurant, A. C., and Creighton, A.: Contrasting lake ice responses to winter climate indicate future variability and trends on the Alaskan Arctic Coastal Plain, Environ. Res. Lett., 13, https://doi.org/10.1088/1748-9326/aae994, 2018. a
Bergstedt, H., Jones, B. M., Hinkel, K., Farquharson, L., Gaglioti, B. V., Parsekian, A. D., Kanevskiy, M., Ohara, N., Breen, A. L., Rangel, R. C., Grosse, G., and Nitze, I.: Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska, Remote Sens.-Basel, 13, 2539, https://doi.org/10.3390/rs13132539, 2021. a, b, c
Bockheim, J. G., Hinkel, K. M., Eisner, W. R., and Dai, X. Y.: Carbon Pools and Accumulation Rates in an Age-Series of Soils in Drained Thaw-Lake Basins, Arctic Alaska, Soil Sci. Soc. Am. J., 68, 697–704, https://doi.org/10.2136/sssaj2004.6970, 2004. a, b
Boike, J., Georgi, C., Kirilin, G., Muster, S., Abramova, K., Fedorova, I., Chetverova, A., Grigoriev, M., Bornemann, N., and Langer, M.: Thermal processes of thermokarst lakes in the continuous permafrost zone of northern Siberia – observations and modeling (Lena River Delta, Siberia), Biogeosciences, 12, 5941–5965, https://doi.org/10.5194/bg-12-5941-2015, 2015. a
Bouchard, F., MacDonald, L. A., Turner, K. W., Thienpont, J. R., Medeiros, A. S., Biskaborn, B. K., Korosi, J., Hall, R. I., Pienitz, R., and Wolfe, B. B.: Paleolimnology of thermokarst lakes: a window into permafrost landscape evolution, Arctic Science, 3, 91–117, https://doi.org/10.1139/as-2016-0022, 2017. a, b
Brosius, L. S., Treat, C. C., Walter Anthony, K. M., Lenz, J., Jones, M. C., and Grosse, G.: High-latitude Lake Basal Ages and Origins – link to datafile, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.894737, 2018. a
Brosius, L. S., Anthony, K. M. W., Treat, C. C., Lenz, J., Jones, M. C., Bret-Harte, M. S., and Grosse, G.: Spatiotemporal patterns of northern lake formation since the Last Glacial Maximum, Quaternary Sci. Rev., 253, 106773, https://doi.org/10.1016/j.quascirev.2020.106773, 2021. a, b, c
Brosius, L. S., Walter Anthony, K. M., Treat, C. C., Jones, M. C., Dyonisius, M., and Grosse, G.: Panarctic lakes exerted a small positive feedback on early Holocene warming due to deglacial release of methane, Communications Earth & Environment, 4, 1–11, https://doi.org/10.1038/s43247-023-00930-2, 2023. a
Brovkin, V., Bartsch, A., Hugelius, G., Calamita, E., Lever, J. J., Goo, E., Kim, H., Stacke, T., and de Vrese, P.: Permafrost and Freshwater Systems in the Arctic as Tipping Elements of the Climate System, Surv. Geophys., 46, 303–326, https://doi.org/10.1007/s10712-025-09885-9, 2025. a
Chiu, S. N., Stoyan, D., Kendall, W. S., and Mecke, J.: Random closed sets I – The Boolean model, in: Stochastic Geometry and its Applications, chap. 3, John Wiley & Sons, Ltd, 64–107, https://doi.org/10.1002/9781118658222.ch03, 2013. a
Cooley, S. W., Smith, L. C., Ryan, J. C., Pitcher, L. H., and Pavelsky, T. M.: Arctic-Boreal Lake Dynamics Revealed Using CubeSat Imagery, Geophys. Res. Lett., 46, 2111–2120, https://doi.org/10.1029/2018GL081584, 2019. a
Côté, M. M. and Burn, C. R.: The oriented lakes of Tuktoyaktuk Peninsula, Western Arctic Coast, Canada: a GIS-based analysis, Permafrost. Periglac., 13, 61–70, https://doi.org/10.1002/ppp.407, 2002. a
Cowell, F. A. and Flachaire, E.: Statistical Methods for Distributional Analysis, in: Handbook of Income Distribution, vol. 2, edited by: Atkinson, A. B. and Bourguignon, F., Elsevier, 359–465, https://doi.org/10.1016/B978-0-444-59428-0.00007-2, 2015. a, b
de Vrese, P., Georgievski, G., Gonzalez Rouco, J. F., Notz, D., Stacke, T., Steinert, N. J., Wilkenskjeld, S., and Brovkin, V.: Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate, The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, 2023. a
de Vrese, P., Stacke, T., Gayler, V., and Brovkin, V.: Permafrost Cloud Feedback May Amplify Climate Change, Geophys. Res. Lett., 51, e2024GL109034, https://doi.org/10.1029/2024GL109034, 2024. a
Dirac, P. A. M.: The physical interpretation of the quantum dynamics Free, Proc. R. Soc. Lond. Ser.-A, 113, https://doi.org/10.1098/rspa.1927.0012, 1927. a
Edwards, M., Grosse, G., Jones, B. M., and McDowell, P.: The evolution of a thermokarst-lake landscape: Late Quaternary permafrost degradation and stabilization in interior Alaska, Sediment. Geol., 340, 3–14, https://doi.org/10.1016/j.sedgeo.2016.01.018, 2016. a
Fedorov, A. N., Gavriliev, P. P., Konstantinov, P. Y., Hiyama, T., Iijima, Y., and Iwahana, G.: Estimating the water balance of a thermokarst lake in the middle of the Lena River basin, eastern Siberia, Ecohydrology, 7, 188–196, https://doi.org/10.1002/eco.1378, 2014. a
Freitas, N. L., Walter Anthony, K., Lenz, J., Porras, R. C., and Torn, M. S.: Substantial and overlooked greenhouse gas emissions from deep Arctic lake sediment, Nat. Geosci., 18, 65–71, https://doi.org/10.1038/s41561-024-01614-y, 2025. a
Fuchs, M., Lenz, J., Jock, S., Nitze, I., Jones, B. M., Strauss, J., Günther, F., and Grosse, G.: Organic Carbon and Nitrogen Stocks Along a Thermokarst Lake Sequence in Arctic Alaska, J. Geophys. Res.-Biogeo., 124, 1230–1247, https://doi.org/10.1029/2018JG004591, 2019. a, b
Heslop, J. K., Walter Anthony, K. M., Winkel, M., Sepulveda-Jauregui, A., Martinez-Cruz, K., Bondurant, A., Grosse, G., and Liebner, S.: A synthesis of methane dynamics in thermokarst lake environments, Earth-Sci. Rev., 210, 103365, https://doi.org/10.1016/j.earscirev.2020.103365, 2020. a
Hinkel, K. M., Frohn, R. C., Nelson, F. E., Eisner, W. R., and Beck, R. A.: Morphometric and spatial analysis of thaw lakes and drained thaw lake basins in the western Arctic Coastal Plain, Alaska, Permafrost. Periglac., 16, 327–341, https://doi.org/10.1002/ppp.532, 2005. a, b
Hinkel, K. M., Jones, B. M., Eisner, W. R., Cuomo, C. J., Beck, R. A., and Frohn, R.: Methods to assess natural and anthropogenic thaw lake drainage on the western Arctic coastal plain of northern Alaska, J. Geophys. Res.-Earth, 112, https://doi.org/10.1029/2006JF000584, 2007. a, b
Hopkins, D. M.: Thaw Lakes and Thaw Sinks in the Imuruk Lake Area, Seward Peninsula, Alaska, J. Geol., 57, 119–131, https://doi.org/10.1086/625591, 1949. a, b
Jones, B. M., Arp, C. D., Hinkel, K. M., Beck, R. A., Schmutz, J. A., and Winston, B.: Arctic Lake Physical Processes and Regimes with Implications for Winter Water Availability and Management in the National Petroleum Reserve Alaska, Environ. Manage., 43, 1071–1084, https://doi.org/10.1007/s00267-008-9241-0, 2009. a, b
Jones, B. M., Arp, C. D., Grosse, G., Nitze, I., Lara, M. J., Whitman, M. S., Farquharson, L. M., Kanevskiy, M., Parsekian, A. D., Breen, A. L., Ohara, N., Rangel, R. C., and Hinkel, K. M.: Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska, Permafrost. Periglac., 31, 110–127, https://doi.org/10.1002/ppp.2038, 2020. a, b, c, d
Jones, B. M., Grosse, G., Farquharson, L. M., Roy-Léveillée, P., Veremeeva, A., Kanevskiy, M. Z., Gaglioti, B. V., Breen, A. L., Parsekian, A. D., Ulrich, M., and Hinkel, K. M.: Lake and drained lake basin systems in lowland permafrost regions, Nature Reviews Earth & Environment, 3, 85–98, https://doi.org/10.1038/s43017-021-00238-9, 2022. a, b, c, d
Jones, M. C., Grosse, G., Jones, B. M., and Walter Anthony, K.: Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska, J. Geophys. Res.-Biogeo., 117, https://doi.org/10.1029/2011JG001766, 2012. a, b, c
Jorgenson, M., Romanovsky, V., Harden, J., Shur, Y., O'Donnell, J., Schuur, E., Kanevskiy, M., and Marchenko, S.: Resilience and vulnerability of permafrost to climate change, Can. J. Forest Res., 40, 1219–1236, https://doi.org/10.1139/X10-060, 2010. a
Jorgenson, M. T. and Shur, Y.: Evolution of lakes and basins in northern Alaska and discussion of the thaw lake cycle, J. Geophys. Res.-Earth, 112, https://doi.org/10.1029/2006JF000531, 2007. a, b
Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V., Brüggemann, N., Chegini, F., Crüger, T., De-Vrese, P., Gayler, V., Giorgetta, M. A., Gutjahr, O., Haak, H., Hagemann, S., Hanke, M., Ilyina, T., Korn, P., Kröger, J., Linardakis, L., Mehlmann, C., Mikolajewicz, U., Müller, W. A., Nabel, J. E. M. S., Notz, D., Pohlmann, H., Putrasahan, D. A., Raddatz, T., Ramme, L., Redler, R., Reick, C. H., Riddick, T., Sam, T., Schneck, R., Schnur, R., Schupfner, M., Storch, J.-S., Wachsmann, F., Wieners, K.-H., Ziemen, F., Stevens, B., Marotzke, J., and Claussen, M.: The ICON Earth System Model Version 1.0, J. Adv. Model. Earth Sy., 14, https://doi.org/10.1029/2021ms002813, 2022. a
Juutinen, S., Rantakari, M., Kortelainen, P., Huttunen, J. T., Larmola, T., Alm, J., Silvola, J., and Martikainen, P. J.: Methane dynamics in different boreal lake types, Biogeosciences, 6, 209–223, https://doi.org/10.5194/bg-6-209-2009, 2009. a
Kaufman, D.: Holocene thermal maximum in the western Arctic (0–180°W), Quaternary Sci. Rev., 23, 529–560, https://doi.org/10.1016/j.quascirev.2003.09.007, 2004. a
Kessler, M. A., Plug, L. J., and Walter Anthony, K. M.: Simulating the decadal- to millennial-scale dynamics of morphology and sequestered carbon mobilization of two thermokarst lakes in NW Alaska, J. Geophys. Res.-Biogeo., 117, https://doi.org/10.1029/2011JG001796, 2012. a
Kirillin, G., Hochschild, J., Mironov, D., Terzhevik, A., Golosov, S., and Nützmann, G.: FLake-Global: Online lake model with worldwide coverage, Environ. Modell. Softw., 26, 683–684, https://doi.org/10.1016/j.envsoft.2010.12.004, 2011. a
Knoblauch, C., Spott, O., Evgrafova, S., Kutzbach, L., and Pfeiffer, E.-M.: Regulation of methane production, oxidation, and emission by vascular plants and bryophytes in ponds of the northeast Siberian polygonal tundra, J. Geophys. Res.-Biogeo., 120, 2525–2541, https://doi.org/10.1002/2015JG003053, 2015. a
Kutzbach, L., Wagner, D., and Pfeiffer, E.-M.: Effect of microrelief and vegetation on methane emission from wet polygonal tundra, Lena Delta, Northern Siberia, Biogeochemistry, 69, 341–362, https://doi.org/10.1023/B:BIOG.0000031053.81520.db, 2004. a
Lachenbruch, A. H., Brewer, M. C., Greene, G. W., and Marshall, B. V.: Temperatures in Permafrost, in: Temperature, Its Measurement and Control in Science and Industry, chap. 80, edited by: Herzfeld, C., Reinhold Publishing Co, New York, 791–803, 1962. a
Lange, S., Menz, C., Gleixner, S., Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Schmied, H. M., Hersbach, H., Buontempo, C., and Cagnazzo, C.: WFDE5 over land merged with ERA5 over the ocean (W5E5 v2.0), ISIMIP Repository, https://doi.org/10.48364/ISIMIP.342217, 2021. a, b
Langer, M., Westermann, S., Boike, J., Kirillin, G., Grosse, G., Peng, S., and Krinner, G.: Rapid degradation of permafrost underneath waterbodies in tundra landscapes–Toward a representation of thermokarst in land surface models, J. Geophys. Res.-Earth, 121, 2446–2470, https://doi.org/10.1002/2016JF003956, 2016. a
Lara, M. and Chipman, M.: Periglacial Lake Origin Influences the Likelihood of Lake Drainage in Northern Alaska, Remote Sens.-Basel, 13, https://doi.org/10.3390/rs13050852, 2021. a, b
Lenz, J., Wetterich, S., Jones, B. M., Meyer, H., Bobrov, A., and Grosse, G.: Evidence of multiple thermokarst lake generations from an 11 800 year-old permafrost core on the northern Seward Peninsula, Alaska, Boreas, 45, 584–603, https://doi.org/10.1111/bor.12186, 2016. a
Liljedahl, A., Witharana, C., and Manos, E.: The capillaries of the Arctic tundra, Nat. Water, 2, 611–614, https://doi.org/10.1038/s44221-024-00276-9, 2024. a, b
Lindgren, P., Grosse, G., Jones, M., Jones, B., and Walter Anthony, K.: Characterizing Post-Drainage Succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI Data, Remote Sens.-Basel, 4, 3741–3765, https://doi.org/10.3390/rs4123741, 2012. a, b, c
Ling, F. and Zhang, T.: Numerical simulation of permafrost thermal regime and talik development under shallow thaw lakes on the Alaskan Arctic Coastal Plain, J. Geophys. Res.-Atmos., 108, https://doi.org/10.1029/2002JD003014, 2003. a
Ling, F. and Zhang, T.: Modeling study of talik freeze-up and permafrost response under drained thaw lakes on the Alaskan Arctic Coastal Plain, J. Geophys. Res., 109, https://doi.org/10.1029/2003JD003886, 2004. a
Luo, J., Niu, F., Lin, Z., Liu, M., Yin, G., and Gao, Z.: Abrupt increase in thermokarst lakes on the central Tibetan Plateau over the last 50 years, Catena, 217, 106497, https://doi.org/10.1016/j.catena.2022.106497, 2022. a, b, c
Mann, D. H., Peteet, D. M., Reanier, R. E., and Kunz, M. L.: Responses of an arctic landscape to Lateglacial and early Holocene climatic changes: the importance of moisture, Quaternary Sci. Rev., 21, 997–1021, https://doi.org/10.1016/S0277-3791(01)00116-0, 2002. a
Matthes, H., Damseaux, A., Westermann, S., Beer, C., Boone, A., Burke, E., Decharme, B., Genet, H., Jafarov, E., Langer, M., Parmentier, F.-J., Porada, P., Gagne-Landmann, A., Huntzinger, D., Rogers, B. M., Schädel, C., Stacke, T., Wells, J., and Wieder, W. R.: Advances in Permafrost Representation: Biophysical Processes in Earth System Models and the Role of Offline Models, Permafrost. Periglac., 36, 302–318, https://doi.org/10.1002/ppp.2269, 2025. a
Meredith, M., Sommerkorn, M., Cassotta, S., Derksen, C., Ekaykin, A., Hollowed, A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert, M. M. C., Ottersen, G., Pritchard, H., and Schuur, E. A. G.: Polar Regions, in: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N., Cambridge Univ. Press, https://doi.org/10.1017/9781009157964.005, 2019. a
Mironov, D., Kirillin, G., Heise, E., Golosov, S., Terzhevik, A., and Zverev, I.: Parameterization of Lakes in Numerical Models for Environmental Applications, paper presented at 7th Workshop on Physical Processes in Natural Water, 135–143, 2003. a
Montero, D.: eemont: A Python package that extends Google Earth Engine, Journal of Open Source Software, 6, 3168, https://doi.org/10.21105/joss.03168, 2021. a
Morgenstern, A., Grosse, G., Günther, F., Fedorova, I., and Schirrmeister, L.: Spatial analyses of thermokarst lakes and basins in Yedoma landscapes of the Lena Delta, The Cryosphere, 5, 849–867, https://doi.org/10.5194/tc-5-849-2011, 2011. a
Mullen, A. L., Watts, J. D., Rogers, B. M., Carroll, M. L., Elder, C. D., Noomah, J., Williams, Z., Caraballo-Vega, J. A., Bredder, A., Rickenbaugh, E., Levenson, E., Cooley, S. W., Hung, J. K. Y., Fiske, G., Potter, S., Yang, Y., Miller, C. E., Natali, S. M., Douglas, T. A., and Kyzivat, E. D.: Using High-Resolution Satellite Imagery and Deep Learning to Track Dynamic Seasonality in Small Water Bodies, Geophys. Res. Lett., 50, e2022GL102327, https://doi.org/10.1029/2022GL102327, 2023. a
Muster, S., Roth, K., Langer, M., Lange, S., Cresto Aleina, F., Bartsch, A., Morgenstern, A., Grosse, G., Jones, B., Sannel, A. B. K., Sjöberg, Y., Günther, F., Andresen, C., Veremeeva, A., Lindgren, P. R., Bouchard, F., Lara, M. J., Fortier, D., Charbonneau, S., Virtanen, T. A., Hugelius, G., Palmtag, J., Siewert, M. B., Riley, W. J., Koven, C. D., and Boike, J.: PeRL: a circum-Arctic Permafrost Region Pond and Lake database, Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, 2017. a, b, c
Nitzbon, J., Westermann, S., Langer, M., Martin, L. C. P., Strauss, J., Laboor, S., and Boike, J.: Fast response of cold ice-rich permafrost in northeast Siberia to a warming climate, Nat. Commun., 11, 2201, https://doi.org/10.1038/s41467-020-15725-8, 2020. a
Nitze, I., Grosse, G., Jones, B. M., Arp, C. D., Ulrich, M., Fedorov, A., and Veremeeva, A.: Landsat-Based Trend Analysis of Lake Dynamics across Northern Permafrost Regions, Remote Sens.-Basel, 9, 640, https://doi.org/10.3390/rs9070640, 2017. a, b, c, d
Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E., and Boike, J.: Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic, Nat. Commun., 9, 5423, https://doi.org/10.1038/s41467-018-07663-3, 2018. a
Nitze, I., Cooley, S. W., Duguay, C. R., Jones, B. M., and Grosse, G.: The catastrophic thermokarst lake drainage events of 2018 in northwestern Alaska: fast-forward into the future, The Cryosphere, 14, 4279–4297, https://doi.org/10.5194/tc-14-4279-2020, 2020. a, b
Ohara, N., Jones, B. M., Parsekian, A. D., Hinkel, K. M., Yamatani, K., Kanevskiy, M., Rangel, R. C., Breen, A. L., and Bergstedt, H.: A new Stefan equation to characterize the evolution of thermokarst lake and talik geometry, The Cryosphere, 16, 1247–1264, https://doi.org/10.5194/tc-16-1247-2022, 2022. a
Olefeldt, D., Goswami, S., Grosse, G., Hayes, D., Hugelius, G., Kuhry, P., McGuire, A. D., Romanovsky, V. E., Sannel, A., Schuur, E., and Turetsky, M. R.: Circumpolar distribution and carbon storage of thermokarst landscapes, Nat. Commun., 7, https://doi.org/10.1038/ncomms13043, 2016. a
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., and Kassem, K. R.: Terrestrial Ecoregions of the World: A New Map of Life on Earth, Bioscience, 51, 933–938, https://doi.org/10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2, 2001. a
Olthof, I., Fraser, R. H., van der Sluijs, J., and Travers-Smith, H.: Detecting long-term Arctic surface water changes, Nat. Clim. Change, 13, 1191–1193, https://doi.org/10.1038/s41558-023-01836-9, 2023. a
Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, https://doi.org/10.1038/nature20584, 2016. a, b, c
Pickens, A. H., Hansen, M. C., Hancher, M., Stehman, S. V., Tyukavina, A., Potapov, P., Marroquin, B., and Sherani, Z.: Mapping and sampling to characterize global inwland water dynamics from 1999 to 2018 with full Landsat time-series, Remote Sens. Environ., 243, https://doi.org/10.1016/j.rse.2020.111792, 2020. a, b
Pinsky, M. A. and Karlin, S.: An Introduction to Stochastic Modeling, 4th edn., Academic Press, https://doi.org/10.1016/C2009-1-61171-0, 2011. a, b
Plug, L. J. and West, J. J.: Thaw lake expansion in a two-dimensional coupled model of heat transfer, thaw subsidence, and mass movement, J. Geophys. Res.-Earth, 114, https://doi.org/10.1029/2006JF000740, 2009. a, b
Polishchuk, Y. M., Bogdanov, A. N., Muratov, I. N., Polishchuk, V. Y., Lim, A., Manasypov, R. M., Shirokova, L. S., and Pokrovsky, O. S.: Minor contribution of small thaw ponds to the pools of carbon and methane in the inland waters of the permafrost-affected part of the Western Siberian Lowland, Environ. Res. Lett., 13, 045002, https://doi.org/10.1088/1748-9326/aab046, 2018. a
Rehder, Z., Zaplavnova, A., and Kutzbach, L.: Identifying Drivers Behind Spatial Variability of Methane Concentrations in East Siberian Ponds, Front. Earth Sci., 9, https://doi.org/10.3389/feart.2021.617662, 2021. a
Rehder, Z., Kleinen, T., Kutzbach, L., Stepanenko, V., Langer, M., and Brovkin, V.: Simulated methane emissions from Arctic ponds are highly sensitive to warming, Biogeosciences, 20, 2837–2855, https://doi.org/10.5194/bg-20-2837-2023, 2023. a
Reick, C. H., Gayler, V., Goll, D., Hagemann, S., Heidkamp, M., Nabel, J. E. M. S., Raddatz, T., Roeckner, E., Schnur, R., and Wilkenskjeld, S.: JSBACH 3 – The land component of the MPI Earth System Model: documentation of version 3.2, Berichte zur Erdsystemforschung, https://doi.org/10.17617/2.3279802, 2021. a
Reinken, C., Brovkin, V., and de Vrese, P.: Stochastic Thermokarst Lake Model (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.19053374, 2026. a
Rowland, J. C., Travis, B. J., and Wilson, C. J.: The role of advective heat transport in talik development beneath lakes and ponds in discontinuous permafrost, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL048497, 2011. a
Roy-Léveillée, P. and Burn, C.: Old Crow Flats: Thermokarst Lakes in the Forest–Tundra Transition, in: Landscapes and Landforms of Western Canada, edited by: Slaymaker, O., Springer, Cham, 267–276, https://doi.org/10.1007/978-3-319-44595-3_19, 2017. a, b
Schädel, C., Rogers, B. M., Lawrence, D. M., Koven, C. D., Brovkin, V., Burke, E. J., Genet, H., Huntzinger, D. N., Jafarov, E., McGuire, A. D., Riley, W. J., and Natali, S. M.: Earth system models must include permafrost carbon processes, Nat. Clim. Change, 1–3, https://doi.org/10.1038/s41558-023-01909-9, 2024. a
Schlaffer, S., Sabel, D., Bartsch, A., and Wagner, W.: Regional water bodies remote sensing products with links to geotiff images, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.779754, 2012. a
Smith, N. D., Burke, E. J., Aas, K. S., Althuizen, I. H. J., Boike, J., Christiansen, C. T., Etzelmüller, B., Friborg, T., Lee, H., Rumbold, H., Turton, R. H., Westermann, S., and Chadburn, S. E.: Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography), Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, 2022. a
Stojkoski, V., Sandev, T., Basnarkov, L., Kocarev, L., and Metzler, R.: Generalised Geometric Brownian Motion: Theory and Applications to Option Pricing, Entropy, 22, 1432, https://doi.org/10.3390/e22121432, 2020. a
Strauss, J., Schirrmeister, L., Grosse, G., Fortier, D., Hugelius, G., Knoblauch, C., Romanovsky, V., Schädel, C., Schneider von Deimling, T., Schuur, E. A. G., Shmelev, D., Ulrich, M., and Veremeeva, A.: Deep Yedoma permafrost: A synthesis of depositional characteristics and carbon vulnerability, Earth-Sci. Rev., 172, 75–86, https://doi.org/10.1016/j.earscirev.2017.07.007, 2017. a
Surdu, C. M., Duguay, C. R., Brown, L. C., and Prieto, D. F.: Response of ice cover on shallow lakes of the North Slope of Alaska to contemporary climate conditions (1950–2011): radar remote-sensing and numerical modeling data analysis, The Cryosphere, 8, 167–180, https://doi.org/10.5194/tc-8-167-2014, 2014. a
Turetsky, M. R., Abbott, B. W., Jones, M. C., Anthony, K. W., Olefeldt, D., Schnuur, E. A. G., Grosse, G., Kuhry, P., Hugelius, G., Koven, C., Lawrence, D. M., Gibson, C., Sannel, A. B. K., and McGuire, A. D.: Carbon release through abrupt permafrost thaw, Nat. Geosci., 13, 138–143, https://doi.org/10.1038/s41561-019-0526-0, 2020. a, b
van Huissteden, J., Berrittella, C., Parmentier, F. J. W., Mi, Y., Maximov, T. C., and Dolman, A. J.: Methane emissions from permafrost thaw lakes limited by lake drainage, Nat. Clim. Change, 1, 119–123, https://doi.org/10.1038/nclimate1101, 2011. a, b, c, d
Velichko, A., Catto, N., Drenova, A., Klimanov, V., Kremenetski, K., and Nechaev, V.: Climate changes in East Europe and Siberia at the Late glacial–holocene transition, Quatern. Int., 91, 75–99, https://doi.org/10.1016/S1040-6182(01)00104-5, 2002. a
Veremeeva, A., Nitze, I., Günther, F., Grosse, G., and Rivkina, E.: Geomorphological and Climatic Drivers of Thermokarst Lake Area Increase Trend (1999–2018) in the Kolyma Lowland Yedoma Region, North-Eastern Siberia, Remote Sens.-Basel, 13, 178, https://doi.org/10.3390/rs13020178, 2021. a
Victorov, A. S., Kapralova, V. N., and Arkhipova, M. V.: Modeling of the Morphological Pattern Development for Thermokarst Plains with Fluvial Erosion Based on Remote Sensing Data, Izv. Atmos. Ocean. Phy.+, 55, 1338–1345, https://doi.org/10.1134/S000143381909055X, 2019a. a, b
Victorov, A. S., Orlov, T. V., Kapralova, V. N., Trapeznikova, O. N., Sadkov, S. A., and Zverev, A. V.: Stochastic Modeling of Natural Lacustrine Thermokarst Under Stable and Unstable Climate, in: Natural Hazards and Risk Research in Russia, edited by: Svalova, V., Innovation and Discovery in Russian Science and Engineering, Springer International Publishing, Cham, 241–267, https://doi.org/10.1007/978-3-319-91833-4_18, 2019b. a, b, c, d, e, f, g, h, i, j, k, l
Victorov, A. S., Kapralova, V. N., and Orlov, T. V.: Developing a Model of the Morphological Pattern for Thermokarst Plains with Fluvial Erosion Involving Remote Sensing Data, Izv. Atmos. Ocean. Phy.+, 59, 1239–1248, https://doi.org/10.1134/S0001433823090220, 2023. a, b
von Baeckmann, C., Bartsch, A., Bergstedt, H., Efimova, A., Widhalm, B., Ehrich, D., Kumpula, T., Sokolov, A., and Abdulmanova, S.: Land cover succession for recently drained lakes in permafrost on the Yamal Peninsula, Western Siberia, The Cryosphere, 18, 4703–4722, https://doi.org/10.5194/tc-18-4703-2024, 2024. a, b
Walter, K. M., Edwards, M. E., Grosse, G., Zimov, S. A., and Chapin, F. S.: Thermokarst lakes as a source of atmospheric CH4 during the last deglaciation, Science, 318, 633–636, https://doi.org/10.1126/science.1142924, 2007. a
Walter Anthony, K., Schneider von Deimling, T., Nitze, I., Frolking, S., Emond, A., Daanen, R., Anthony, P., Lindgren, P., Jones, B., and Grosse, G.: 21st-century modeled permafrost carbon emissions accelerated by abrupt thaw beneath lakes, Nat. Commun., 9, 3262, https://doi.org/10.1038/s41467-018-05738-9, 2018. a, b
Wang, J., Sheng, Y., Hinkel, K. M., and Lyons, E. A.: Drained thaw lake basin recovery on the western Arctic Coastal Plain of Alaska using high-resolution digital elevation models and remote sensing imagery, Remote Sens. Environ., 119, 325–336, https://doi.org/10.1016/j.rse.2011.10.027, 2012. a
Webb, E. and Liljedahl, A.: Diminishing lake area across the northern permafrost zone, Nat. Geosci., 16, 202–209, https://doi.org/10.1038/s41561-023-01128-z, 2023. a, b
Webb, E. E., Liljedahl, A. K., Cordeiro, J. A., Loranty, M. M., Witharana, C., and Lichstein, J. W.: Permafrost thaw drives surface water decline across lake-rich regions of the Arctic, Nat. Clim. Change, 12, 841–846, https://doi.org/10.1038/s41558-022-01455-w, 2022. a
Webb, E. E., Liljedahl, A. K., Loranty, M. M., Witharana, C., and Lichstein, J. W.: Reply to: Detecting long-term Arctic surface water changes, Nat. Clim. Change, 13, 1194–1196, https://doi.org/10.1038/s41558-023-01837-8, 2023. a
Weller, M. W. and Derksen, D. V.: The Geomorphology of Teshekpuk Lake in Relation to Coastline Configuration of Alaska's Coastal Plain, Arctic, 32, 152–160, https://www.jstor.org/stable/40508958 (last access: 27 January 2025), 1979. a
West, J. and Plug, L.: Time-dependent morphology of thaw lakes and taliks in deep and shallow ground ice, J. Geophys. Res., 113, https://doi.org/10.1029/2006JF000696, 2008. a
Westermann, S., Langer, M., Boike, J., Heikenfeld, M., Peter, M., Etzelmüller, B., and Krinner, G.: Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3, Geosci. Model Dev., 9, 523–546, https://doi.org/10.5194/gmd-9-523-2016, 2016. a
Wik, M., Varner, R. K., Anthony, K. W., MacIntyre, S., and Bastviken, D.: Climate-sensitive northern lakes and ponds are critical components of methane release, Nat. Geosci., 9, 99–105, https://doi.org/10.1038/ngeo2578, 2016. a
Wu, Q.: geemap: A Python package for interactive mapping with Google Earth Engine, Journal of Open Source Software, 5, 2305, https://doi.org/10.21105/joss.02305, 2020. a
Yoshikawa, K. and Hinzman, L. D.: Shrinking thermokarst ponds and groundwater dynamics in discontinuous permafrost near council, Alaska, Permafrost. Periglac., 14, 151–160, https://doi.org/10.1002/ppp.451, 2003. a
Zhang, T., Heginbottom, J., Barry, R., and Brown, J.: Further statistics on the distribution of permafrost and ground ice in the Northern Hemisphere, Polar Geography, 24, 126–131, https://doi.org/10.1080/10889370009377692, 2000. a
Zhou, G., Liu, W., Xie, C., Song, X., Zhang, Q., Li, Q., Liu, G., Li, Q., and Luo, B.: Accelerating thermokarst lake changes on the Qinghai–Tibetan Plateau, Sci. Rep.-UK, 14, 2985, https://doi.org/10.1038/s41598-024-52558-7, 2024. a
Short summary
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.
Thermokarst lakes are dynamic features of ice-rich permafrost landscapes, altering energy, water...
