Articles | Volume 18, issue 12
https://doi.org/10.5194/tc-18-5865-2024
© Author(s) 2024. 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-18-5865-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Dec 2024
Research article |
| 13 Dec 2024
| 13 Dec 2024
Future permafrost degradation under climate change in a headwater catchment of central Siberia: quantitative assessment with a mechanistic modelling approach
Thibault Xavier
Geoscience Environnement Toulouse (GET), CNRS, UMR5563, Toulouse, France
Laurent Orgogozo
CORRESPONDING AUTHOR
Geoscience Environnement Toulouse (GET), CNRS, UMR5563, Toulouse, France
Anatoly S. Prokushkin
V. N. Sukachev Institute of Forest SB RAS, Krasnoyarsk, Russia
Esteban Alonso-González
Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Jaca, Spain
Simon Gascoin
Centre d'Etudes Spatiales de la Biosphère, Université de Toulouse, CNRS/CNES/IRD/INRA/UPS, Toulouse, France
Oleg S. Pokrovsky
Geoscience Environnement Toulouse (GET), CNRS, UMR5563, Toulouse, France
BIO-GEO-CLIM Laboratory, Tomsk State University, Tomsk, Russia
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Léon Roussel, Marie Dumont, Marion Réveillet, Delphine Six, Marin Kneib, Pierre Nabat, Kévin Fourteau, Diego Monteiro, Simon Gascoin, Emmanuel Thibert, Antoine Rabatel, Jean-Emmanuel Sicart, Mylène Bonnefoy, Luc Piard, Olivier Laarman, Bruno Jourdain, Mathieu Fructus, Matthieu Vernay, and Matthieu Lafaysse
The Cryosphere, 19, 5201–5230, https://doi.org/10.5194/tc-19-5201-2025, https://doi.org/10.5194/tc-19-5201-2025, 2025
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Saharan dust deposits frequently turn alpine glaciers orange. Mineral dust reduces snow albedo and increases snow and glaciers melt rate. Using physical modeling, we quantified the impact of dust on the Argentière Glacier over the period 2019–2022. We found that the contribution of mineral dust to the melt represents between 8 % and 16 % of Argentière Glacier summer melt. At specific locations, the impact of dust over one year can rise to an equivalent of 1.2 m of melted ice.
Anna-Maria Virkkala, Isabel Wargowsky, Judith Vogt, McKenzie A. Kuhn, Simran Madaan, Richard O'Keefe, Tiffany Windholz, Kyle A. Arndt, Brendan M. Rogers, Jennifer D. Watts, Kelcy Kent, Mathias Göckede, David Olefeldt, Gerard Rocher-Ros, Edward A. G. Schuur, David Bastviken, Kristoffer Aalstad, Kelly Aho, Joonatan Ala-Könni, Haley Alcock, Inge Althuizen, Christopher D. Arp, Jun Asanuma, Katrin Attermeyer, Mika Aurela, Sivakiruthika Balathandayuthabani, Alan Barr, Maialen Barret, Ochirbat Batkhishig, Christina Biasi, Mats P. Björkman, Andrew Black, Elena Blanc-Betes, Pascal Bodmer, Julia Boike, Abdullah Bolek, Frédéric Bouchard, Ingeborg Bussmann, Lea Cabrol, Eleonora Canfora, Sean Carey, Karel Castro-Morales, Namyi Chae, Andres Christen, Torben R. Christensen, Casper T. Christiansen, Housen Chu, Graham Clark, Francois Clayer, Patrick Crill, Christopher Cunada, Scott J. Davidson, Joshua F. Dean, Sigrid Dengel, Matteo Detto, Catherine Dieleman, Florent Domine, Egor Dyukarev, Colin Edgar, Bo Elberling, Craig A. Emmerton, Eugenie Euskirchen, Grant Falvo, Thomas Friborg, Michelle Garneau, Mariasilvia Giamberini, Mikhail V. Glagolev, Miquel A. Gonzalez-Meler, Gustaf Granath, Jón Guðmundsson, Konsta Happonen, Yoshinobu Harazono, Lorna Harris, Josh Hashemi, Nicholas Hasson, Janna Heerah, Liam Heffernan, Manuel Helbig, Warren Helgason, Michal Heliasz, Greg Henry, Geert Hensgens, Tetsuya Hiyama, Macall Hock, David Holl, Beth Holmes, Jutta Holst, Thomas Holst, Gabriel Hould-Gosselin, Elyn Humphreys, Jacqueline Hung, Jussi Huotari, Hiroki Ikawa, Danil V. Ilyasov, Mamoru Ishikawa, Go Iwahana, Hiroki Iwata, Marcin Antoni Jackowicz-Korczynski, Joachim Jansen, Järvi Järveoja, Vincent E. J. Jassey, Rasmus Jensen, Katharina Jentzsch, Robert G. Jespersen, Carl-Fredrik Johannesson, Chersity P. Jones, Anders Jonsson, Ji Young Jung, Sari Juutinen, Evan Kane, Jan Karlsson, Sergey Karsanaev, Kuno Kasak, Julia Kelly, Kasha Kempton, Marcus Klaus, George W. Kling, Natacha Kljun, Jacqueline Knutson, Hideki Kobayashi, John Kochendorfer, Kukka-Maaria Kohonen, Pasi Kolari, Mika Korkiakoski, Aino Korrensalo, Pirkko Kortelainen, Egle Koster, Kajar Koster, Ayumi Kotani, Praveena Krishnan, Juliya Kurbatova, Lars Kutzbach, Min Jung Kwon, Ethan D. Kyzivat, Jessica Lagroix, Theodore Langhorst, Elena Lapshina, Tuula Larmola, Klaus S. Larsen, Isabelle Laurion, Justin Ledman, Hanna Lee, A. Joshua Leffler, Lance Lesack, Anders Lindroth, David Lipson, Annalea Lohila, Efrén López-Blanco, Vincent L. St. Louis, Erik Lundin, Misha Luoto, Takashi Machimura, Marta Magnani, Avni Malhotra, Marja Maljanen, Ivan Mammarella, Elisa Männistö, Luca Belelli Marchesini, Phil Marsh, Pertti J. Martkainen, Maija E. Marushchak, Mikhail Mastepanov, Alex Mavrovic, Trofim Maximov, Christina Minions, Marco Montemayor, Tomoaki Morishita, Patrick Murphy, Daniel F. Nadeau, Erin Nicholls, Mats B. Nilsson, Anastasia Niyazova, Jenni Nordén, Koffi Dodji Noumonvi, Hannu Nykanen, Walter Oechel, Anne Ojala, Tomohiro Okadera, Sujan Pal, Alexey V. Panov, Tim Papakyriakou, Dario Papale, Sang-Jong Park, Frans-Jan W. Parmentier, Gilberto Pastorello, Mike Peacock, Matthias Peichl, Roman Petrov, Kyra St. Pierre, Norbert Pirk, Jessica Plein, Vilmantas Preskienis, Anatoly Prokushkin, Jukka Pumpanen, Hilary A. Rains, Niklas Rakos, Aleski Räsänen, Helena Rautakoski, Riika Rinnan, Janne Rinne, Adrian Rocha, Nigel Roulet, Alexandre Roy, Anna Rutgersson, Aleksandr F. Sabrekov, Torsten Sachs, Erik Sahlée, Alejandro Salazar, Henrique Oliveira Sawakuchi, Christopher Schulze, Roger Seco, Armando Sepulveda-Jauregui, Svetlana Serikova, Abbey Serrone, Hanna M. Silvennoinen, Sofie Sjogersten, June Skeeter, Jo Snöälv, Sebastian Sobek, Oliver Sonnentag, Emily H. Stanley, Maria Strack, Lena Strom, Patrick Sullivan, Ryan Sullivan, Anna Sytiuk, Torbern Tagesson, Pierre Taillardat, Julie Talbot, Suzanne E. Tank, Mario Tenuta, Irina Terenteva, Frederic Thalasso, Antoine Thiboult, Halldor Thorgeirsson, Fenix Garcia Tigreros, Margaret Torn, Amy Townsend-Small, Claire Treat, Alain Tremblay, Carlo Trotta, Eeva-Stiina Tuittila, Merritt Turetsky, Masahito Ueyama, Muhammad Umair, Aki Vähä, Lona van Delden, Maarten van Hardenbroek, Andrej Varlagin, Ruth K. Varner, Elena Veretennikova, Timo Vesala, Tarmo Virtanen, Carolina Voigt, Jorien E. Vonk, Robert Wagner, Katey Walter Anthony, Qinxue Wang, Masataka Watanabe, Hailey Webb, Jeffrey M. Welker, Andreas Westergaard-Nielsen, Sebastian Westermann, Jeffrey R. White, Christian Wille, Scott N. Williamson, Scott Zolkos, Donatella Zona, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-585, https://doi.org/10.5194/essd-2025-585, 2025
Preprint under review for ESSD
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This dataset includes monthly measurements of carbon dioxide and methane exchange between land, water, and the atmosphere from over 1,000 sites in Arctic and boreal regions. It combines measurements from a variety of ecosystems, including wetlands, forests, tundra, lakes, and rivers, gathered by over 260 researchers from 1984–2024. This dataset can be used to improve and reduce uncertainty in carbon budgets in order to strengthen our understanding of climate feedbacks in a warming world.
Marco Mazzolini, Kristoffer Aalstad, Esteban Alonso-González, Sebastian Westermann, and Désirée Treichler
The Cryosphere, 19, 3831–3848, https://doi.org/10.5194/tc-19-3831-2025, https://doi.org/10.5194/tc-19-3831-2025, 2025
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In this work, we showcase the use the satellite laser altimeter ICESat-2, which is able to retrieve snow depth in areas where snow amounts are still poorly estimated despite the importance of these water resources. We can update snow models with these observations through algorithms that spatially propagate the information beyond the satellite profiles. The positive results show the potential of the approach to improve snow simulations, in terms of average snow depth and spatial distribution.
Zacharie Barrou Dumont, Simon Gascoin, Jordi Inglada, Andreas Dietz, Jonas Köhler, Matthieu Lafaysse, Diego Monteiro, Carlo Carmagnola, Arthur Bayle, Jean-Pierre Dedieu, Olivier Hagolle, and Philippe Choler
The Cryosphere, 19, 2407–2429, https://doi.org/10.5194/tc-19-2407-2025, https://doi.org/10.5194/tc-19-2407-2025, 2025
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We generated annual maps of snow melt-out days at 20 m resolution over a period of 38 years from 10 different satellites. This study fills a knowledge gap regarding the evolution of mountain snow in Europe by covering a much longer period and characterizing trends at much higher resolutions than previous studies. We found a trend for earlier melt-out with average reductions of 5.51 d per decade over the French Alps and 4.04 d per decade over the Pyrenees for the period 1986–2023.
Esteban Alonso-González, Adrian Harpold, Jessica D. Lundquist, Cara Piske, Laura Sourp, Kristoffer Aalstad, and Simon Gascoin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2347, https://doi.org/10.5194/egusphere-2025-2347, 2025
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Simulating the snowpack is challenging, as there are several sources of uncertainty due to e.g. the meteorological forcing. Using data assimilation techniques, it is possible to improve the simulations by fusing models and snow observations. However in forests, observations are difficult to obtain, because they cannot be retrieved through the canopy. Here, we explore the possibility of propagating the information obtained in forest clearings to areas covered by the canopy.
Laura Sourp, Simon Gascoin, Lionel Jarlan, Vanessa Pedinotti, Kat J. Bormann, and Mohamed Wassim Baba
Hydrol. Earth Syst. Sci., 29, 597–611, https://doi.org/10.5194/hess-29-597-2025, https://doi.org/10.5194/hess-29-597-2025, 2025
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Accurate knowledge of the spatial distribution of snow masses across landscapes is important for water management in mountain catchments. We present a new tool for estimating snow water resources without ground measurements. We evaluate the output of this tool using accurate airborne measurements in the Sierra Nevada and find that it provides realistic estimates of snow mass and snow depth at the catchment scale.
Artem V. Chupakov, Natalia V. Neverova, Anna A. Chupakova, Svetlana A. Zabelina, Liudmila S. Shirokova, Taissia Ya. Vorobyeva, and Oleg S. Pokrovsky
Biogeosciences, 21, 5725–5743, https://doi.org/10.5194/bg-21-5725-2024, https://doi.org/10.5194/bg-21-5725-2024, 2024
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In the boreal humic waters of a forest lake and bog, the rate of dissolved organic matter photodegradation is 4 times higher than that of biodegradation. However, given the shallow, light-penetrating layer, the biodegradation provides the largest contribution to CO2 emissions from water surfaces. Trace metals were partially removed (1–10 %) during photodegradation and biodegradation via precipitation of Fe(III) hydroxides after destabilization of organoferric colloids and organic complexes.
Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine
Earth Syst. Sci. Data, 16, 3913–3934, https://doi.org/10.5194/essd-16-3913-2024, https://doi.org/10.5194/essd-16-3913-2024, 2024
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High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
Ange Haddjeri, Matthieu Baron, Matthieu Lafaysse, Louis Le Toumelin, César Deschamps-Berger, Vincent Vionnet, Simon Gascoin, Matthieu Vernay, and Marie Dumont
The Cryosphere, 18, 3081–3116, https://doi.org/10.5194/tc-18-3081-2024, https://doi.org/10.5194/tc-18-3081-2024, 2024
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Our study addresses the complex challenge of evaluating distributed alpine snow simulations with snow transport against snow depths from Pléiades stereo imagery and snow melt-out dates from Sentinel-2 and Landsat-8 satellites. Additionally, we disentangle error contributions between blowing snow, precipitation heterogeneity, and unresolved subgrid variability. Snow transport enhances the snow simulations at high elevations, while precipitation biases are the main error source in other areas.
Lahoucine Hanich, Ouiaam Lahnik, Simon Gascoin, Adnane Chakir, and Vincent Simonneaux
Proc. IAHS, 385, 387–391, https://doi.org/10.5194/piahs-385-387-2024, https://doi.org/10.5194/piahs-385-387-2024, 2024
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Using a dataset measured with the eddy covariance system (EC) for a period from September 2020 to January 2021 at the Tazaghart plateau, located in the High Atlas of Marrakech, the sublimation was estimated. The average daily sublimation rate measured was 0.41 mm per day. Measured sublimation accounted for 42 % and 40 % of snow ablation, based on the energy and water balances, respectively.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
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Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023, https://doi.org/10.5194/hess-27-4637-2023, 2023
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Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.
Esteban Alonso-González, Simon Gascoin, Sara Arioli, and Ghislain Picard
The Cryosphere, 17, 3329–3342, https://doi.org/10.5194/tc-17-3329-2023, https://doi.org/10.5194/tc-17-3329-2023, 2023
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Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.
Ixeia Vidaller, Eñaut Izagirre, Luis Mariano del Rio, Esteban Alonso-González, Francisco Rojas-Heredia, Enrique Serrano, Ana Moreno, Juan Ignacio López-Moreno, and Jesús Revuelto
The Cryosphere, 17, 3177–3192, https://doi.org/10.5194/tc-17-3177-2023, https://doi.org/10.5194/tc-17-3177-2023, 2023
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The Aneto glacier, the largest glacier in the Pyrenees, has shown continuous surface and ice thickness losses in the last decades. In this study, we examine changes in its surface and ice thickness for 1981–2022 and the remaining ice thickness in 2020. During these 41 years, the glacier has shrunk by 64.7 %, and the ice thickness has decreased by 30.5 m on average. The mean ice thickness in 2022 was 11.9 m, compared to 32.9 m in 1981. The results highlight the critical situation of the glacier.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Arthur Bayle, Bradley Z. Carlson, Anaïs Zimmer, Sophie Vallée, Antoine Rabatel, Edoardo Cremonese, Gianluca Filippa, Cédric Dentant, Christophe Randin, Andrea Mainetti, Erwan Roussel, Simon Gascoin, Dov Corenblit, and Philippe Choler
Biogeosciences, 20, 1649–1669, https://doi.org/10.5194/bg-20-1649-2023, https://doi.org/10.5194/bg-20-1649-2023, 2023
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Glacier forefields have long provided ecologists with a model to study patterns of plant succession following glacier retreat. We used remote sensing approaches to study early succession dynamics as it allows to analyze the deglaciation, colonization, and vegetation growth within a single framework. We found that the heterogeneity of early succession dynamics is deterministic and can be explained well by local environmental context. This work has been done by an international consortium.
Josep Bonsoms, Juan Ignacio López-Moreno, and Esteban Alonso-González
The Cryosphere, 17, 1307–1326, https://doi.org/10.5194/tc-17-1307-2023, https://doi.org/10.5194/tc-17-1307-2023, 2023
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This work analyzes the snow response to temperature and precipitation in the Pyrenees. During warm and wet seasons, seasonal snow depth is expected to be reduced by −37 %, −34 %, and −27 % per degree Celsius at low-, mid-, and high-elevation areas, respectively. The largest snow reductions are anticipated at low elevations of the eastern Pyrenees. Results anticipate important impacts on the nearby ecological and socioeconomic systems.
Simon Cazaurang, Manuel Marcoux, Oleg S. Pokrovsky, Sergey V. Loiko, Artem G. Lim, Stéphane Audry, Liudmila S. Shirokova, and Laurent Orgogozo
Hydrol. Earth Syst. Sci., 27, 431–451, https://doi.org/10.5194/hess-27-431-2023, https://doi.org/10.5194/hess-27-431-2023, 2023
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Moss, lichen and peat samples are reconstructed using X-ray tomography. Most samples can be cut down to a representative volume based on porosity. However, only homogeneous samples could be reduced to a representative volume based on hydraulic conductivity. For heterogeneous samples, a devoted pore network model is computed. The studied samples are mostly highly porous and water-conductive. These results must be put into perspective with compressibility phenomena occurring in field tests.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Artem G. Lim, Ivan V. Krickov, Sergey N. Vorobyev, Mikhail A. Korets, Sergey Kopysov, Liudmila S. Shirokova, Jan Karlsson, and Oleg S. Pokrovsky
Biogeosciences, 19, 5859–5877, https://doi.org/10.5194/bg-19-5859-2022, https://doi.org/10.5194/bg-19-5859-2022, 2022
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In order to quantify C transport and emission and main environmental factors controlling the C cycle in Siberian rivers, we investigated the largest tributary of the Ob River, the Ket River basin, by measuring spatial and seasonal variations in carbon CO2 and CH4 concentrations and emissions together with hydrochemical analyses. The obtained results are useful for large-scale modeling of C emission and export fluxes from permafrost-free boreal rivers of an underrepresented region of the world.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
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On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Sophia Walther, Simon Besnard, Jacob Allen Nelson, Tarek Sebastian El-Madany, Mirco Migliavacca, Ulrich Weber, Nuno Carvalhais, Sofia Lorena Ermida, Christian Brümmer, Frederik Schrader, Anatoly Stanislavovich Prokushkin, Alexey Vasilevich Panov, and Martin Jung
Biogeosciences, 19, 2805–2840, https://doi.org/10.5194/bg-19-2805-2022, https://doi.org/10.5194/bg-19-2805-2022, 2022
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Satellite observations help interpret station measurements of local carbon, water, and energy exchange between the land surface and the atmosphere and are indispensable for simulations of the same in land surface models and their evaluation. We propose generalisable and efficient approaches to systematically ensure high quality and to estimate values in data gaps. We apply them to satellite data of surface reflectance and temperature with different resolutions at the stations.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Nora Helbig, Michael Schirmer, Jan Magnusson, Flavia Mäder, Alec van Herwijnen, Louis Quéno, Yves Bühler, Jeff S. Deems, and Simon Gascoin
The Cryosphere, 15, 4607–4624, https://doi.org/10.5194/tc-15-4607-2021, https://doi.org/10.5194/tc-15-4607-2021, 2021
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The snow cover spatial variability in mountains changes considerably over the course of a snow season. In applications such as weather, climate and hydrological predictions the fractional snow-covered area is therefore an essential parameter characterizing how much of the ground surface in a grid cell is currently covered by snow. We present a seasonal algorithm and a spatiotemporal evaluation suggesting that the algorithm can be applied in other geographic regions by any snow model application.
Sergey N. Vorobyev, Jan Karlsson, Yuri Y. Kolesnichenko, Mikhail A. Korets, and Oleg S. Pokrovsky
Biogeosciences, 18, 4919–4936, https://doi.org/10.5194/bg-18-4919-2021, https://doi.org/10.5194/bg-18-4919-2021, 2021
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In order to quantify riverine carbon (C) exchange with the atmosphere in permafrost regions, we report a first assessment of CO2 and CH4 concentration and fluxes of the largest permafrost-affected river, the Lena River, during the peak of spring flow. The results allowed identification of environmental factors controlling GHG concentrations and emission in the Lena River watershed; this new knowledge can be used for foreseeing future changes in C balance in permafrost-affected Arctic rivers.
Esteban Alonso-González, Ethan Gutmann, Kristoffer Aalstad, Abbas Fayad, Marine Bouchet, and Simon Gascoin
Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, https://doi.org/10.5194/hess-25-4455-2021, 2021
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Snow water resources represent a key hydrological resource for the Mediterranean regions, where most of the precipitation falls during the winter months. This is the case for Lebanon, where snowpack represents 31 % of the spring flow. We have used models to generate snow information corrected by means of remote sensing snow cover retrievals. Our results highlight the high temporal variability in the snowpack in Lebanon and its sensitivity to further warming caused by its hypsography.
Esteban Alonso-González and Víctor Fernández-García
Earth Syst. Sci. Data, 13, 1925–1938, https://doi.org/10.5194/essd-13-1925-2021, https://doi.org/10.5194/essd-13-1925-2021, 2021
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We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area products. The database inludes monthly scenes with the dNBR, RdNBR and post-burn NBR spectral indices at 500 m spatial resolution from November 2000 onwards. Moreover, in this work we show that there is a close relationship between the burn severity metrics included in MOSEV and the same ones obtained from Landsat-8.
Andreas Kääb, Mylène Jacquemart, Adrien Gilbert, Silvan Leinss, Luc Girod, Christian Huggel, Daniel Falaschi, Felipe Ugalde, Dmitry Petrakov, Sergey Chernomorets, Mikhail Dokukin, Frank Paul, Simon Gascoin, Etienne Berthier, and Jeffrey S. Kargel
The Cryosphere, 15, 1751–1785, https://doi.org/10.5194/tc-15-1751-2021, https://doi.org/10.5194/tc-15-1751-2021, 2021
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Hardly recognized so far, giant catastrophic detachments of glaciers are a rare but great potential for loss of lives and massive damage in mountain regions. Several of the events compiled in our study involve volumes (up to 100 million m3 and more), avalanche speeds (up to 300 km/h), and reaches (tens of kilometres) that are hard to imagine. We show that current climate change is able to enhance associated hazards. For the first time, we elaborate a set of factors that could cause these events.
Ana Moreno, Miguel Bartolomé, Juan Ignacio López-Moreno, Jorge Pey, Juan Pablo Corella, Jordi García-Orellana, Carlos Sancho, María Leunda, Graciela Gil-Romera, Penélope González-Sampériz, Carlos Pérez-Mejías, Francisco Navarro, Jaime Otero-García, Javier Lapazaran, Esteban Alonso-González, Cristina Cid, Jerónimo López-Martínez, Belén Oliva-Urcia, Sérgio Henrique Faria, María José Sierra, Rocío Millán, Xavier Querol, Andrés Alastuey, and José M. García-Ruíz
The Cryosphere, 15, 1157–1172, https://doi.org/10.5194/tc-15-1157-2021, https://doi.org/10.5194/tc-15-1157-2021, 2021
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Our study of the chronological sequence of Monte Perdido Glacier in the Central Pyrenees (Spain) reveals that, although the intense warming associated with the Roman period or Medieval Climate Anomaly produced important ice mass losses, it was insufficient to make this glacier disappear. By contrast, recent global warming has melted away almost 600 years of ice accumulated since the Little Ice Age, jeopardising the survival of this and other southern European glaciers over the next few decades.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
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Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
Nora Helbig, Yves Bühler, Lucie Eberhard, César Deschamps-Berger, Simon Gascoin, Marie Dumont, Jesus Revuelto, Jeff S. Deems, and Tobias Jonas
The Cryosphere, 15, 615–632, https://doi.org/10.5194/tc-15-615-2021, https://doi.org/10.5194/tc-15-615-2021, 2021
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The spatial variability in snow depth in mountains is driven by interactions between topography, wind, precipitation and radiation. In applications such as weather, climate and hydrological predictions, this is accounted for by the fractional snow-covered area describing the fraction of the ground surface covered by snow. We developed a new description for model grid cell sizes larger than 200 m. An evaluation suggests that the description performs similarly well in most geographical regions.
Cited articles
Alonso-González, E., Aalstad, K., Baba, M. W., Revuelto, J., López-Moreno, J. I., Fiddes, J., Essery, R., and Gascoin, S.: The Multiple Snow Data Assimilation System (MuSA v1.0), Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, 2022.
Anisimov, O. A., Zhiltcova, Y. L., and Razzhivin, V. Y.: Predictive modeling of plant productivity in the Russian Arctic using satellite data, Izv. Atmos. Ocean. Phy.+, 51, 1051–1059, https://doi.org/10.1134/S0001433815090042, 2015.
Arndal, M. F. and Topp-Jørgensen, E. (Eds.): INTERACT Station Catalogue – 2020, DCE – Danish Centre for Environment and Energy, Aarhus University, Denmark, 190 pp., ISBN 978-87-93129-15-3, https://www.eu-interact.org (last access: 11 April 2024), 2020.
Auda, Y., Lundin, E. J., Gustafsson, J., Pokrovsky, O. S., Cazaurang, S., and Orgogozo, L.: A new land cover map of two watersheds under long-term environmental monitoring in the Swedish Arctic using Sentinel-2 data, Water, 15, 3311, https://doi.org/10.3390/w15183311, 2023.
Bartsch, A., Pointner, G., Nitze, I., Efimova, A., Jakober, D., Ley, S., Högström, E., Grosse, G., and Schweitzer, P.: Expanding infrastructure and growing anthropogenic impacts along Arctic coasts, Environ. Res. Lett., 16, 115013, https://doi.org/10.1088/1748-9326/ac3176, 2021.
Biskaborn, B. K., Smith, S. L., Noetzli, J., Matthes, H., Vieira, G., Streletskiy, D. A., Schoeneich, P., Romanovsky, V. E., Lewkowicz, A. G., Abramov, A., Allard, M., Boike, J., Cable, W. L., Christiansen, H. H., Delaloye R., Diekmann, B., Drozdov, D., Etzelmüller, B., Grosse, G., Guglielmin M., Ingeman-Nielsen, T., Isaksen, K., Ishikawa, M., Johansson, M., Johannson, H., Joo, A., Kaverin, D., Kholodov, A., Konstantinov, P., Kröger, T., Lambiel, C., Lanckman, J.-P., Luo, D., Malkova, G., Meiklejohn, I., Moskalenko, N., Oliva, M., Phillips, M., Ramos, M., Sannel, A. B. K., Sergeev, D., Seybold, C., Skryabin, P., Vasiliev, A., Wu, Q., Yoshikawa, K., Zheleznyak, M., and Lantuit, H.: Permafrost is warming at a global scale, Nat. Commun., 10, 264, https://doi.org/10.1038/s41467-018-08240-4, 2019.
Blok, D., Heijmans, M. M. P. D., Schaepman-Strub, G., Van Ruijven, F., Parmentier, F. J. W., and Maximov, T. C.: The cooling capacity of mosses: Controls on water and energy fluxes in a Siberian tundra site, Ecosystems, 14, 1055–1065, https://doi.org/10.1007/s10021-011-9463-5, 2011.
Braithwaite, R. J. and Olesen, O. B.: Calculation of glacier ablation from air temperature, West Greenland, in: Glacier Fluctuations and Climatic Change, edited by: Oerlemans, J., Kluwer Academic Publishers, 219–233, https://research.manchester.ac.uk/en/publications/calculation-of-glacier-ablation-from-air-temperature-west-greenla (last access: 10 December 2024), 1989.
Cable, W. L., Romanovsky, V. E., and Jorgenson, M. T.: Scaling-up permafrost thermal measurements in western Alaska using an ecotype approach, The Cryosphere, 10, 2517–2532, https://doi.org/10.5194/tc-10-2517-2016, 2016.
Cazaurang, S., Marcoux, M., Pokrovsky, O. S., Loiko, S. V., Lim, A. G., Audry, S., Shirokova, L. S., and Orgogozo, L.: Numerical assessment of morphological and hydraulic properties of moss, lichen and peat from a permafrost peatland, Hydrol. Earth Syst. Sci., 27, 431–451, https://doi.org/10.5194/hess-27-431-2023, 2023.
Clark, J. A., Tape, K. D., and Young-Robertson, J. M.: Quantifying evapotranspiration from dominant Arctic vegetation types using lysimeters, Ecohydrology, 16, e2484, https://doi.org/10.1002/eco.2484, 2023.
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.
Dominé, F., Fourteau, K., Picard, G., Lackner, G., Sarrazin, D., and Poirier, M.: Permafrost cooled in winter by thermal bridging through snow-covered shrub branches, Nat. Geosci., 15, 554–560, https://doi.org/10.1038/s41561-022-00979-2, 2022.
Duchkov, A. D., Sokolova, L. S., Balobaev, V. T., Devyatkin, V. N., Kononov, V. I., and Lysak, S. V.: Heat flow and geothermal field in Siberia, Geol. Geofiz., 38, 1716–1729, 1997.
Essery, R.: A factorial snowpack model (FSM 1.0), Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, 2015.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Fan, X., Duan, Q., Shen, C., Wu, Y., and Xing, C.: Global surface air temperatures in CMIP6: Historical performance and future changes, Environ. Res. Lett., 15, 104056, https://doi.org/10.1088/1748-9326/abb051, 2020.
Fedorov, A. N., Konstantinov, P. Y., Vasilyev, N. F., and Shestakova, A. A.: The influence of boreal forest dynamics on the current state of permafrost in Central Yakutia, Polar Sci., 22, 100483, https://doi.org/10.1016/j.polar.2019.100483, 2019.
Frolking, S.: Sensitivity of spruce/moss boreal forest net ecosystem productivity to seasonal anomalies in weather, J. Geophys. Res., 102, 29053–29064, https://doi.org/10.1029/96JD03707, 1997.
Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A. Z., and Schepaschenko, D. G.: Boreal forest health and global change, Science, 349, 819–822, https://doi.org/10.1126/science.aaa9092, 2015.
Gentsch, N.: Permafrost Soils in Central Siberia: Landscape Controls on Soil Organic Carbon Storage in a Light Taiga Biome, Akademische Verlagsgemeinschaft München, Munich, Germany, ISBN 978-3-86924-015-2, 2011.
Haesen, S., Lembrechts, J. J., De Frenne, P., Lenoir, J., Aalto, J., Ashcroft, M. B., Kopecký, M., Luoto, M., Maclean, I., Nijs, I., Niittynen, P., van den Hoogen, J., Arriga, N., Brůna, J., Buchmann, N., Čiliak, M., Collalti, A., De Lombaerde, E., Descombes, P., Gharun, M., Goded, I., Govaert, S., Greiser, C., Grelle, A., Gruening, C., Hederová, L., Hylander, K., Kreyling, J., Kruijt, B., Macek, M., Máliš, F., Man, M., Manca, G., Matula, R., Meeussen, C., Merinero, S., Minerbi, S., Montagnani, L., Muffler, L., Ogaya, R., Penuelas, J., Plichta, R., Portillo-Estrada, M., Schmeddes, J., Shekhar, A., Spicher, F., Ujházyová, M., Vangansbeke, P., Weigel, R., Wild, J., Zellweger, F., and Van Meerbeek, K.: ForestTemp – Sub-canopy microclimate temperatures of European forests, Global Change Biol., 27, 6307–6319, https://doi.org/10.1111/gcb.15892, 2021.
Hamm, A. and Frampton, A.: Impact of lateral groundwater flow on hydrothermal conditions of the active layer in a high-Arctic hillslope setting, The Cryosphere, 15, 4853–4871, https://doi.org/10.5194/tc-15-4853-2021, 2021.
Hamon, W. R.: Computation of direct runoff amounts from storm rainfall, International Association of Scientific Hydrological Sciences Publication, 63, 52–62, 1963.
Heijmans, M. M. P. D., Magnússon, R. Í. Lara, M. J., Frost, G. V., Myers-Smith, I. H., Van Huissteden, J., Jorgenson, M. T., Fedorov, A. N., Epstein, H. E., Lawrence, D. M., and Limpens, J.: Tundra vegetation change and impacts on permafrost, Nat. Rev. Earth Environ., 3, 68–84, https://doi.org/10.1038/s43017-021-00233-0, 2022.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hjort, J., Karjalainen, O., Aalto, J., Westermann, S., Romanovky, V. E., Nelson, F. E., Etzelmüller, B., and Luoto, M.: Degrading permafrost puts Arctic infrastructure at risk by mid-century, Nat. Commun., 9, 5147, https://doi.org/10.1038/s41467-018-07557-4, 2018.
Hjort, J., Streletskiy, D., Doré, G., Wu, Q., Bjella, K., and Luoto, M.: Impacts of permafrost degradation on infrastructure, Nat. Rev. Earth Environ., 3, 24–38, https://doi.org/10.1038/s43017-021-00247-8, 2022.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol., 282, 104–115, https://doi.org/10.1016/S0022-1694(03)00257-9, 2003.
Holloway, J. E., Lewkowicz, A. G., Douglas, T. A., Li, X., Turetsky, M. R., Baltzer, J. L., and Huijun, J.: Impact of wildfire on permafrost landscapes: A review of recent advances and future prospects, Permafrost Periglac., 31, 371–382, https://doi.org/10.1002/ppp.2048, 2020.
Hu, G., Zhao, L., Wu, T., Wu, X., Park, H., Li, R., Zhu, X., Ni, J., Zou, D., Hao, J., and Li, W.: Continued warming of the permafrost regions over the Northern Hemisphere under future climate change, Earths Future, 10, e2022EF002835, https://doi.org/10.1029/2022EF002835, 2022.
Hu, G., Zhao, L., Li, R., Park, H., Wu, X., Su, Y., Guggenberger, G., Wu, T., Zou, D., Zhu, X., Zhang, W., Wu, Y., and Hao, J.: Water and heat coupling processes and its simulation in frozen soils: Current status and future research directions, CATENA, 222, 106844, https://doi.org/10.1016/j.catena.2022.106844, 2023.
Iturbide, M., Fernández, J., Gutiérrez, J. M., Bedia, J., Cimadevilla, E., Díez-Sierra, J., Manzanas, R., Casanueva, A., Baño-Medina, J., Milovac, J., Herrera, S., Cofiño, A. S., San Martín, D., García-Díez, M., Hauser, M., Huard, D., and Yelekci, Ö.: Repository supporting the implementation of FAIR principles in the IPCC-WG1 Atlas, Zenodo, https://doi.org/10.5281/zenodo.3691645, 2022.
Jan, A.: Modeling the role of lateral surface flow in low-relief polygonal tundra, Permafrost Periglac., 33, 214–225, https://doi.org/10.1002/ppp.2145, 2022.
Jan, A. and Painter, S. L.: Permafrost thermal conditions are sensitive to shifts in snow timing, Environ. Res. Lett., 15, 084026, https://doi.org/10.1088/1748-9326/ab8ec4, 2020.
Ji, H., Nan, Z., Hu, J., Zhao, Y., and Zhang, Y.: On the spin-up strategy for spatial modeling of permafrost dynamics: A case study on the Qinghai-Tibet Plateau, J. Adv. Model. Earth Sy., 14, e2021MS002750, https://doi.org/10.1029/2021MS002750, 2022.
Jin, H., Huang, Y., Bense, V. F., Ma, Q., Marchenko, S. S., Shepelev, V. V., Hu, Y., Liang, S., Spektor, V. V., Jin, X., Li, X., and Li, X.: Permafrost degradation and its hydrogeological impacts, Water, 14, 372, https://doi.org/10.3390/w14030372, 2022.
Karjalainen, O., Aalto, J., Luoto, M., Westermann, S., Romanovsky, V. E., Nelson, F. E., Etzelmüller B., and Hjort J.: Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments, Sci. Data, 6, 190037, https://doi.org/10.1038/sdata.2019.37, 2019.
Karlsson, J., Serikova, S., Vorobyev, S. N., Rocher-Ros, G., Denfeld, B., and Pokrovsky, O. S.: Carbon emission from Western Siberian inland waters, Nat. Commun., 12, 825, https://doi.org/10.1038/s41467-021-21054-1, 2021.
Khani, H. M., Kinnard, C., Gascoin, S., and Lévesque, E.: Fine-scale environment control on ground surface temperature and thaw depth in a High Arctic tundra landscape, Permafrost Periglac., 34, 467–480, https://doi.org/10.1002/ppp.2203, 2023.
Kim, J.-S., Kug, J. S., Jeong, S. J., Park, H., and Schaepman-Strub, G.: Extensive fires in southeastern Siberian permafrost linked to preceding Arctic Oscillation, Sci. Adv., 6, eaax3308, https://doi.org/10.1126/sciadv.aax3308, 2020.
Kirdyanov, A. V., Saurer, M., Siegwolf, R., Knorre, A. A., Prokushkin, A. S., Churakova (Sidorova), O. V., Fonti, M. V., and Büntgen, U.: Long-term ecological consequences of forest fires in the continuous permafrost zone of Siberia, Environ. Res. Lett., 15, 034061, https://doi.org/10.1088/1748-9326/ab7469, 2020.
Kirdyanov, A. V., Saurer, M., Arzac, A., Knorre, A. A., Prokushkin, A. S., Churakova (Sidorova), O. V., Arosio, T., Bebchuk, T., Siegwolf, R., and Büntgen, U.: Thawing permafrost can mitigate warming-induced drought stress in boreal forest trees, Sci. Total Environ., 912, 168858, https://doi.org/10.1016/j.scitotenv.2023.168858, 2024.
Kurylyk, B. L.: Engineering challenges of warming, Nat. Clim. Change, 9, 807–808, https://doi.org/10.1038/s41558-019-0612-8, 2019.
Kurylyk, B. L. and Watanabe, K.: The mathematical representation of freezing and thawing processes in variably-saturated, non-deformable soils, Adv. Water Resour., 60, 160–177, https://doi.org/10.1016/j.advwatres.2013.07.016, 2013.
Lamontagne-Hallé, P., McKenzie, J. M., Kurylyk, B. L., and Zipper, S. C.: Changing groundwater discharge dynamics in permafrost regions, Environ. Res. Lett., 13, 084017, https://doi.org/10.1088/1748-9326/aad404, 2018.
Li, C., Wei, Y., Liu, Y., Li, L., Peng, L., Chen, J., Liu L., Dou, T., and Wu, X.: Active layer thickness in the Northern Hemisphere: Changes from 2000 to 2018 and future simulations, J. Geophys. Res.-Atmos., 127, e2022JD036785, https://doi.org/10.1029/2022JD036785, 2022.
Li, G., Zhang, M., Pei, W., Melnikov, A., Khristoforov, I., Li, R., and Yu, F.: Changes in permafrost extent and active layer thickness in the Northern Hemisphere from 1969 to 2018, Sci. Total Environ., 804, 150182, https://doi.org/10.1016/j.scitotenv.2021.150182, 2022.
Li, X.-Y., Jin, H.-J., Wang, H.-W., Marchenko, S. S., Shan, W., Luo, D.-L., He, R.-X., Spektor, V., Huang, Y.-D., Li, X.-Y., and Jia, N.: Influences of forest fires on the permafrost environment: A review, Advances in Climate Change Research, 12, 48–65, https://doi.org/10.1016/j.accre.2021.01.001, 2021.
Loranty, M. M., Abbott, B. W., Blok, D., Douglas, T. A., Epstein, H. E., Forbes, B. C., Jones, B. M., Kholodov, A. L., Kropp, H., Malhotra, A., Mamet, S. D., Myers-Smith, I. H., Natali, S. M., O'Donnell, J. A., Phoenix, G. K., Rocha, A. V., Sonnentag, O., Tape, K. D., and Walker, D. A.: Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions, Biogeosciences, 15, 5287–5313, https://doi.org/10.5194/bg-15-5287-2018, 2018.
Makarieva, O., Nesterova, N., Post, D. A., Sherstyukov, A., and Lebedeva, L.: Warming temperatures are impacting the hydrometeorological regime of Russian rivers in the zone of continuous permafrost, The Cryosphere, 13, 1635–1659, https://doi.org/10.5194/tc-13-1635-2019, 2019.
Mashukov, D. A., Benkova, A. V., Benkova, V. E., Shashkin, A., and Prokushkin, A.: Radial growth and anatomic structure of the trunk wood of healthy and stag-headed larch trees on permafrost, Contemp. Probl. Ecol., 14, 767–774, https://doi.org/10.1134/S1995425521070143, 2021.
Miner, K. R., Turetsky, M. R., Malina, E., Bartsch, A., Tamminen, J., McGuire, D., Fix, A., Sweeney, C., Elder, C. D., and Miller, C. E.: Permafrost carbon emissions in a changing Arctic, Nat. Rev. Earth Environ., 3, 55–67, https://doi.org/10.1038/s43017-021-00230-3, 2022.
Nitzbon, J., Krinner, G., Schneider von Deimling, T., Werner, M., and Langer, M.: First quantification of the permafrost heat sink in the Earth's climate system, Geophys. Res. Lett., 50, e2022GL102053, https://doi.org/10.1029/2022GL102053, 2023.
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.
Obu, J., Westermann, S., Bartsch, A., Berdnikov, N., Christiansen, H. H., Dashtseren, A., Delaloye, R., Elberling, B., Etzelmüller, B., Kholodov, A., Khomutov, A., Kääb, A., Leibman, M. O., Lewkowicz, A. G., Panda, S. K., Romanovsky, V., Way, R. G., Westergaard-Nielsen, A., Wu, T., Yamkhin, J., and Zou, D.: Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale, Earth-Sci. Rev., 193, 299–316, https://doi.org/10.1016/j.earscirev.2019.04.023, 2019.
Oehri, J., Schaepman-Strub, G., Kim, J. S., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E. S., Chacko, M. R., Muscari, G., Blanken, P. D., Dean, J. F., di Sarra, A., Harding, R. J., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N. B., Beringer, J., Lopez-Blanco, E., Stoy, P. C., Sullivan, R. C., Kejna, M., Parmentier, F. J. W., Gamon, J. A., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D. N., Quinton, W. L., Putkonen, J., van As, D., Christensen, T. R., Hakuba, M. Z., Stone, R. S., Metzger, S., Vandecrux, B., Frost, G. V., Wild, M., Hansen, B., Melonie, D., Domine, F., Te Beest, M., Sachs, T., Kalhori, A., Rocha, A. V., Williamson, S. N., Morris, S., Atchley, A. L., Essery, R., Runkle, B. R. K., Holl, D., Riihimaki, L. D., Iwata, H., Schuur, E. A. G., Cox, C. J., Grachev, A. A., McFadden, J. P., Fausto, R. S., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M. S., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C. W., Olofsson, J., and Chambers, S. D.: Vegetation type is an important predictor of the arctic summer land surface energy budget, Nat. Commun., 13, 6379, https://doi.org/10.1038/s41467-022-34049-3, 2022.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Orgogozo, L. and Xavier, T.: Permafrost mechanistical simulation with the permaFoam solver in the Kulingdakan watershed (Central Siberia) based on CMIP6 scenarios (2014–2100), Theia [data set], https://doi.org/10.6096/1026, 2024.
Orgogozo, L., Prokushkin, A. S., Pokrovsky, O. S., Grenier, C., Quintard, M., Viers, J., and Audry, S.: Water and energy transfer modeling in a permafrost-dominated, forested catchment of Central Siberia: The key role of rooting depth, Permafrost Periglac., 30, 75–89, https://doi.org/10.1002/ppp.1995, 2019.
Orgogozo, L., Xavier, T., Oulbani, H., and Grenier, C.: Permafrost modelling with OpenFOAM®: New advancements of the permaFoam solver, Comput. Phys. Commun., 282, 108541, https://doi.org/10.1016/j.cpc.2022.108541, 2023.
Park, H., Tanoue, M., Sugimoto, A., Ichiyanagi, K., Iwahana, G., and Hiyama, T.: Quantitative separation of precipitation and permafrost waters used for evapotranspiration in a boreal forest: A numerical study using tracer model, J. Geophys. Res.-Biogeo., 126, e2021JG006645, https://doi.org/10.1029/2021JG006645, 2021.
Park, S. W. and Kug, J. S.: A decline in atmospheric CO2 levels under negative emissions may enhance carbon retention in the terrestrial biosphere, Commun. Earth Environ., 3, 289, https://doi.org/10.1038/s43247-022-00621-4, 2022.
Park, S. W., Kim, J. S., and Kug, J. S.: The intensification of Arctic warming as a result of CO2 physiological forcing, Nat. Commun., 11, 2098, https://doi.org/10.1038/s41467-020-15924-3, 2020.
Pokrovsky, O. S., Schott, J. S., Kudryavtzev, D. I., and Dupré, B.: Basalt weathering in Central Siberia under permafrost conditions, Geochim. Cosmochim. Ac., 69, 5659–5680, 2005.
Porter, C., Howat, I., Noh, M.-J., Husby, E., Khuvis, S., Danish, E., Tomko, K., Gardiner, J., Negrete, A., Yadav, B., Klassen, J., Kelleher, C., Cloutier, M., Bakker, J., Enos, J., Arnold, G., Bauer, G., and Morin, P.: ArcticDEM – Mosaics, Version 4.1, Harvard Dataverse, V1, https://doi.org/10.7910/DVN/3VDC4W, 2023.
Prokushkin, A., Kajimoto, T., Prokushkin, S., McDowell, W., Abaimov, A. P., and Matsuura, Y.: Climatic factors influencing fluxes of dissolved organic carbon from the forest floor in a continuous-permafrost Siberian watershed, Can. J. Forest Res., 35, 2130–2140, https://doi.org/10.1139/x05-150, 2004.
Prokushkin, A. S., Gleixner, G., McDowell, W. H., Ruehlow, S., and Schulze, E.-D.: Source- and substrate-specific export of dissolved organic matter from permafrost-dominated forested watershed in central Siberia, Global Biogeochem. Cy., 21, GB4003, https://doi.org/10.1029/2007GB002938, 2007.
Ramage, J., Jungsberg, L., Wang, S., Westermann, S., Lantuit, H., and Heleniak, T.: Population living on permafrost in the Arctic, Popul. Environ., 43, 22–38, https://doi.org/10.1007/s11111-020-00370-6, 2021.
Revich, B. A., Eliseev, D. O., and Shaposhnikov, D. A.: Risks for public health and social infrastructure in Russian Arctic under climate change and permafrost degradation, Atmosphere-Basel, 13, 532, https://doi.org/10.3390/atmos13040532, 2022.
Rew, L. J., McDougall, K. L., Alexander, J. M., Daehler, C. C., Essl, F., Haider, S., Kueffer, C., Lenoir, J., Milbau, A., Nuñez, M. A., Pauchard, A., and Rabitsch, W.: Moving up and over: Redistribution of plants in alpine, Arctic, and Antarctic ecosystems under global change, Arct. Antarct. Alp. Res., 52, 651–665, https://doi.org/10.1080/15230430.2020.1845919, 2020.
Schneider von Deimling, T., Lee, H., Ingeman-Nielsen, T., Westermann, S., Romanovsky, V., Lamoureux, S., Walker, D. A., Chadburn, S., Trochim, E., Cai, L., Nitzbon, J., Jacobi, S., and Langer, M.: Consequences of permafrost degradation for Arctic infrastructure – bridging the model gap between regional and engineering scales, The Cryosphere, 15, 2451–2471, https://doi.org/10.5194/tc-15-2451-2021, 2021.
Schuur, E. A. G., Abbott, B. W., Commane, R., Ernakovich, J., Euskirchen, E., Hugelius, G., Grosse, G., Jones, M., Koven, C., Leshyk, V., Lawrence, D., Loranty, M. M., Mauritz, M., Olefeldt, D., Natali, S., Rodenhizer, H., Salmon, V., Schädel, C., Strauss, J., Treat, C., and Turetsky, M.: Permafrost and climate change: Carbon cycle feedbacks from the warming Arctic, Annu. Rev. Env. Resour., 47, 343–371, 2022.
Shiklomanov, N. I., Streletskiy, D. A., Swales, T. B., and Kokorev, V. A.: Climate change and stability of urban infrastructure in Russian permafrost regions: Prognostic assessment based on GCM climate projections, Geogr. Rev., 107, 125–142, https://doi.org/10.1111/gere.12214, 2017.
Sjöberg, Y., Coon, E., Sannel, A. B. K., Pannetier, R., Harp, D., Frampton, A., Painter, S. L., and Lyon, S. W.: Thermal effects of groundwater flow through subarctic fens: A case study based on field observations and numerical modeling, Water Resour. Res., 52, 1591–1606, https://doi.org/10.1002/2015WR017571, 2016.
Sonke, J. E., Teisserenc, R., Heimbürger-Boavida, L.-E., Petrova, M. V., Marusczak, N., Le Dantec, T., Chupakov, A. V., Li, C., Thackray, C. P., Sunderland, E. M., Tananaev, N., and Pokrovsky, O. S.: Eurasian river spring flood observations support net Arctic Ocean mercury export to the atmosphere and Atlantic Ocean, P. Natl. Acad. Sci. USA, 115, E11586–E11594, https://doi.org/10.1073/pnas.1811957115, 2018.
Speetjens, N. J., Hugelius, G., Gumbricht, T., Lantuit, H., Berghuijs, W. R., Pika, P. A., Poste, A., and Vonk, J. E.: The pan-Arctic catchment database (ARCADE), Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, 2023.
Streletskiy, D. A., Suter, L. J., Shiklomanov, N. I., Porfiriev, B. N., and Eliseev, D. O.: Assessment of climate change impacts on buildings, structures and infrastructure in the Russian regions on permafrost, Environ. Res. Lett., 14, 025003, https://doi.org/10.1088/1748-9326/aaf5e6, 2019.
Streletskiy, D. A., Clemens, S., Lanckman, J.-P., and Shiklomanov, N. I.: The costs of Arctic infrastructure damages due to permafrost degradation, Environ. Res. Lett., 18, 015006, https://doi.org/10.1088/1748-9326/acab18, 2023.
Stuenzi, S. M., Boike, J., Gädeke, A., Herzschuh, U., Kruse, S., Pestryakova, L. A., Westermann, S., and Langer, M.: Sensitivity of ecosystem-protected permafrost under changing boreal forest structures, Environ. Res. Lett., 16, 084045, https://doi.org/10.1088/1748-9326/ac153d, 2021.
van Vuuren, D. P., Edmonds, J., Thomson, A., Riahi, K., Kainuma, M., Matsui, T., Hurtt, G. C., Lamarque, J.-F., Meinshausen, M., Smith, S., Granier, C., Rose, S. K., and Hibbard, K. A.: The representative concentration pathways: An overview, Climatic Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Viers, J., Prokushkin, A. S., Pokrovsky, O. S., Auda, Y., Kirdyanov, A. V., Beaulieu, E., Zouiten, C., Oliva, P., and Dupré, B.: Seasonal and spatial variability of elemental concentrations in boreal forest larch foliage of Central Siberia on continuous permafrost, Biogeochemistry, 113, 435–449, https://doi.org/10.1007/s10533-012-9770-8, 2013.
Vitasse, Y., Porté, A. J., Kremer, A., Michalet, R., and Delzon, S.: Responses of canopy duration to temperature changes in four temperate tree species: Relative contributions of spring and autumn leaf phenology, Oecologia, 161, 187–198, https://doi.org/10.1007/s00442-009-1363-4, 2009.
Vitasse, Y., François, C., Delpierre, N., Dufrêne, E., Kremer, A., Chuine, I., and Delzon S.: Assessing the effects of climate change on the phenology of European temperate trees, Agr. Forest Meteorol., 151, 969–980, https://doi.org/10.1016/j.agrformet.2011.03.003, 2011.
Vonk, J. E., Speetjens, N. J., and Poste, A. E.: Small watersheds may play a disproportionate role in arctic land-ocean fluxes, Nat. Commun., 14, 3442, https://doi.org/10.1038/s41467-023-39209-7, 2023.
Walvoord, M. A. and Kurylyk, B. L.: Hydrologic impacts of thawing permafrost – A review, Vadose Zone J., 15, 1–20, https://doi.org/10.2136/vzj2016.01.0010, 2016.
Walvoord, M. A. and Striegl, R. G.: Complex vulnerabilities of the water and aquatic carbon cycles to permafrost thaw, Front. Clim., 3, 730402, https://doi.org/10.3389/fclim.2021.730402, 2021.
Wang, J. and Liu, D.: Vegetation green-up date is more sensitive to permafrost degradation than climate change in spring across the northern permafrost region, Global Change Biol., 28, 1569–1582, https://doi.org/10.1111/gcb.16011, 2022.
Weller, H. G., Tabor, G., Jasak, H., and Fureby, C.: A tensorial approach to computational continuum mechanics using object orientated techniques, Comput. Phys., 12, 620–631, https://doi.org/10.1063/1.168744, 1998.
Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G., Irrgang, A., Kääb, A. M., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T., Wegmüller, U., Wieczorek, M., and Wiesmann, A.: ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v4.0, NERC EDS Centre for Environmental Data Analysis, https://doi.org/10.5285/d34330ce3f604e368c06d76de1987ce5,, 24 April 2024.
Wright, S. N., Thompson, L. M., Olefeldt, D., Connon, R. F., Carpino, O. A., Beel, C. R., and Quinton, W. L.: Thaw-induced impacts on land and water in discontinuous permafrost: A review of the Taiga Plains and Taiga Shield, northwestern Canada, Earth-Sci. Rev., 232, 104104, https://doi.org/10.1016/j.earscirev.2022.104104, 2022.
Zellweger, F., Coomes, D., Lenoir, J., Depauw, L., Maes, S. L., Wulf, M., Kirby, K. J., Brunet, J., Kopecky, M., Malis, F., Schmidt, W., Heinrichs, S., den Ouden, J., Jaroszewicz, B., Buyse, G., Spicher, F., Verheyen, K., and De Frenne, P.: Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe, Global Ecol. Biogeogr., 28, 1774–1786, https://doi.org/10.1111/geb.12991, 2019.
Zellweger, F., De Frenne, P., Lenoir, J., Vangansbeke, P., Verheyen, K., Bernhardt-Römermann, M., Baeten, L., Hédl, R., Berki, I., Brunet, J., Van Calster, H., Chudomelova, M., Decocq, G., Dirnböck, T., Durak, T., Heinken, T., Jaroszewicz, B., Kopecky M., Malis, F., Macek, M., Malicki, M., Naaf, T., Nagel, A. T., Ortmann-Ajlai, A., Petrik, P., Pielech, R., Reczynska, K., Schmidt, W., Standovar, T., Swierkosz, K., Teleki, B., Vild, O., Wulf, M., and Coomes, D.: Forest microclimate dynamics drive plant responses to warming, Science, 368, 772–775, https://doi.org/10.1126/science.aba6880, 2020.
Short summary
Permafrost (permanently frozen soil at depth) is thawing as a result of climate change. However, estimating its future degradation is particularly challenging due to the complex multi-physical processes involved. In this work, we designed and ran numerical simulations for months on a supercomputer to quantify the impact of climate change in a forested valley of central Siberia. There, climate change could increase the thickness of the seasonally thawed soil layer in summer by up to 65 % by 2100.
Permafrost (permanently frozen soil at depth) is thawing as a result of climate change. However,...
