Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-4201-2020
© Author(s) 2020. 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-14-4201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2020
Research article |
| 25 Nov 2020
| 25 Nov 2020
Analyzing links between simulated Laptev Sea sea ice and atmospheric conditions over adjoining landmasses using causal-effect networks
Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Bundesstraße 53, 20146 Hamburg, Germany
formerly at: Universität Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Anne Laura Niederdrenk
Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany
Lars Kaleschke
Alfred Wegener Institute, Klußmannstr. 3d, 27570 Bremerhaven, Germany
formerly at: Universität Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Lars Kutzbach
Universität Hamburg, Allende-Platz 2, 20146 Hamburg, Germany
Related authors
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
Short summary
Short summary
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.
Lutz Beckebanze, Zoé Rehder, David Holl, Christian Wille, Charlotta Mirbach, and Lars Kutzbach
Biogeosciences, 19, 1225–1244, https://doi.org/10.5194/bg-19-1225-2022, https://doi.org/10.5194/bg-19-1225-2022, 2022
Short summary
Short summary
Arctic permafrost landscapes feature many water bodies. In contrast to the terrestrial parts of the landscape, the water bodies release carbon to the atmosphere. We compare carbon dioxide and methane fluxes from small water bodies to the surrounding tundra and find not accounting for the carbon dioxide emissions leads to an overestimation of the tundra uptake by 11 %. Consequently, changes in hydrology and water body distribution may substantially impact the overall carbon budget of the Arctic.
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
Short summary
Short summary
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.
Ole Zeising, Tore Hattermann, Lars Kaleschke, Sophie Berger, Olaf Boebel, Reinhard Drews, M. Reza Ershadi, Tanja Fromm, Frank Pattyn, Daniel Steinhage, and Olaf Eisen
The Cryosphere, 19, 2837–2854, https://doi.org/10.5194/tc-19-2837-2025, https://doi.org/10.5194/tc-19-2837-2025, 2025
Short summary
Short summary
Basal melting of ice shelves impacts the mass loss of the Antarctic Ice Sheet. This study focuses on the Ekström Ice Shelf in East Antarctica, using multiyear data from an autonomous radar system. Results show a surprising seasonal pattern of high melt rates in winter and spring. The seasonalities of sea-ice growth and ocean density indicate that, in winter, dense water enhances plume activity and melt rates. Understanding these dynamics is crucial for improving future mass balance projections.
Lena Happ, Sonali Patil, Stefan Hendricks, Riccardo Fellegara, Lars Kaleschke, and Andreas Gerndt
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 333–340, https://doi.org/10.5194/isprs-annals-X-G-2025-333-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-333-2025, 2025
Lars Kaleschke, Xiangshan Tian-Kunze, Stefan Hendricks, and Robert Ricker
Earth Syst. Sci. Data, 16, 3149–3170, https://doi.org/10.5194/essd-16-3149-2024, https://doi.org/10.5194/essd-16-3149-2024, 2024
Short summary
Short summary
We describe a sea ice thickness dataset based on SMOS satellite measurements, initially designed for the Arctic but adapted for Antarctica. We validated it using limited Antarctic measurements. Our findings show promising results, with a small difference in thickness estimation and a strong correlation with validation data within the valid thickness range. However, improvements and synergies with other sensors are needed, especially for sea ice thicker than 1 m.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
Short summary
Short summary
Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
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
Short summary
Short summary
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.
Haokui Xu, Brooke Medley, Leung Tsang, Joel T. Johnson, Kenneth C. Jezek, Marco Brogioni, and Lars Kaleschke
The Cryosphere, 17, 2793–2809, https://doi.org/10.5194/tc-17-2793-2023, https://doi.org/10.5194/tc-17-2793-2023, 2023
Short summary
Short summary
The density profile of polar ice sheets is a major unknown in estimating the mass loss using lidar tomography methods. In this paper, we show that combing the active radar data and passive radiometer data can provide an estimation of density properties using the new model we implemented in this paper. The new model includes the short and long timescale variations in the firn and also the refrozen layers which are not included in the previous modeling work.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
Short summary
Short summary
In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Lutz Beckebanze, Benjamin R. K. Runkle, Josefine Walz, Christian Wille, David Holl, Manuel Helbig, Julia Boike, Torsten Sachs, and Lars Kutzbach
Biogeosciences, 19, 3863–3876, https://doi.org/10.5194/bg-19-3863-2022, https://doi.org/10.5194/bg-19-3863-2022, 2022
Short summary
Short summary
In this study, we present observations of lateral and vertical carbon fluxes from a permafrost-affected study site in the Russian Arctic. From this dataset we estimate the net ecosystem carbon balance for this study site. We show that lateral carbon export has a low impact on the net ecosystem carbon balance during the complete study period (3 months). Nevertheless, our results also show that lateral carbon export can exceed vertical carbon uptake at the beginning of the growing season.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
Short summary
Short summary
A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Lutz Beckebanze, Zoé Rehder, David Holl, Christian Wille, Charlotta Mirbach, and Lars Kutzbach
Biogeosciences, 19, 1225–1244, https://doi.org/10.5194/bg-19-1225-2022, https://doi.org/10.5194/bg-19-1225-2022, 2022
Short summary
Short summary
Arctic permafrost landscapes feature many water bodies. In contrast to the terrestrial parts of the landscape, the water bodies release carbon to the atmosphere. We compare carbon dioxide and methane fluxes from small water bodies to the surrounding tundra and find not accounting for the carbon dioxide emissions leads to an overestimation of the tundra uptake by 11 %. Consequently, changes in hydrology and water body distribution may substantially impact the overall carbon budget of the Arctic.
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
Short summary
Short summary
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.
Marek Muchow, Amelie U. Schmitt, and Lars Kaleschke
The Cryosphere, 15, 4527–4537, https://doi.org/10.5194/tc-15-4527-2021, https://doi.org/10.5194/tc-15-4527-2021, 2021
Short summary
Short summary
Linear-like openings in sea ice, also called leads, occur with widths from meters to kilometers. We use satellite images from Sentinel-2 with a resolution of 10 m to identify leads and measure their widths. With that we investigate the frequency of lead widths using two different statistical methods, since other studies have shown a dependency of heat exchange on the lead width. We are the first to address the sea-ice lead-width distribution in the Weddell Sea, Antarctica.
Verónica Pancotto, David Holl, Julio Escobar, María Florencia Castagnani, and Lars Kutzbach
Biogeosciences, 18, 4817–4839, https://doi.org/10.5194/bg-18-4817-2021, https://doi.org/10.5194/bg-18-4817-2021, 2021
Short summary
Short summary
We investigated the response of a wetland plant community to elevated temperature conditions in a cushion bog on Tierra del Fuego, Argentina. We measured carbon dioxide fluxes at experimentally warmed plots and at control plots. Warmed plant communities sequestered between 55 % and 85 % less carbon dioxide than untreated control cushions over the main growing season. Our results suggest that even moderate future warming could decrease the carbon sink function of austral cushion bogs.
Thomas Krumpen, Luisa von Albedyll, Helge F. Goessling, Stefan Hendricks, Bennet Juhls, Gunnar Spreen, Sascha Willmes, H. Jakob Belter, Klaus Dethloff, Christian Haas, Lars Kaleschke, Christian Katlein, Xiangshan Tian-Kunze, Robert Ricker, Philip Rostosky, Janna Rückert, Suman Singha, and Julia Sokolova
The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, https://doi.org/10.5194/tc-15-3897-2021, 2021
Short summary
Short summary
We use satellite data records collected along the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift to categorize ice conditions that shaped and characterized the floe and surroundings during the expedition. A comparison with previous years is made whenever possible. The aim of this analysis is to provide a basis and reference for subsequent research in the six main research areas of atmosphere, ocean, sea ice, biogeochemistry, remote sensing and ecology.
Cited articles
Bareiss, J. and Görgen, K.: Spatial and temporal variability of sea ice in
the Laptev Sea: Analyses and review of satellite passive-microwave data and
model results, 1979 to 2002, Global Planet. Change, 48, 28–54,
https://doi.org/10.1016/j.gloplacha.2004.12.004, 2005. a
Barton, N. P. and Veron, D. E.: Response of clouds and surface energy fluxes to
changes in sea-ice cover over the Laptev Sea (Arctic Ocean), Clim.
Res., 54, 69–84, https://doi.org/10.3354/cr01101, 2012. a
Bauer, M., Schröder, D., Heinemann, G., Willmes, S., and Ebner, L.:
Quantifying polynya ice production in the Laptev Sea with the COSMO model,
Polar Res., 32, 20922, https://doi.org/10.3402/polar.v32i0.20922, 2013. a
Bhatt, U. S., Alexander, M. A., Deser, C., Walsh, J. E., Miller, J. S., Timlin,
M. S., Scott, J., and Tomas, R. A.: The Atmospheric Response to Realistic
Reduced Summer Arctic Sea Ice Anomalies, Arctic Sea Ice Decline:
Observations, Projections, Mechanisms, and Implications, 180, 91–110,
https://doi.org/10.1029/180gm08, 2008. a
Deser, C., Walsh, J. E., and Timlin, M. S.: Arctic sea ice variability in the
context of recent atmospheric circulation trends, J. Climate, 13,
617–633, https://doi.org/10.1175/1520-0442(2000)013<0617:Asivit>2.0.Co;2, 2000. a, b
Fetterer, F., Knowles, K., Meier, W., Savoie, M., and Windnagel, A.: Sea ice
index, version 2., Boulder, CO: National Snow and Ice Data Center NSIDC, 119,
https://doi.org/10.7265/N5736NV7, 2016. a
Francis, J. A. and Hunter, E.: Changes in the fabric of the Arctic's greenhouse
blanket, Environ. Res. Lett., 2, 045011,
https://doi.org/10.1088/1748-9326/2/4/045011, 2007. a
Granger, C. W. J.: Investigating causal relations by econometric models and
cross-spectral methods, Econometrica: journal of the Econometric Society, 37,
424–438, https://doi.org/10.2307/1912791, 1969. a
Graversen, R. G., Langen, P. L., and Mauritsen, T.: Polar Amplification in
CCSM4: Contributions from the Lapse Rate and Surface Albedo Feedbacks,
J. Climate, 27, 4433–4450, https://doi.org/10.1175/Jcli-D-13-00551.1, 2014. a
Haas, C. and Eicken, H.: Interannual variability of summer sea ice thickness in
the Siberian and central Arctic under different atmospheric circulation
regimes, J. Geophys. Res.-Oceans, 106, 4449–4462,
https://doi.org/10.1029/1999jc000088, 2001. a, b
Huntington, T. G.: Evidence for intensification of the global water cycle:
Review and synthesis, J. Hydrol., 319, 83–95,
https://doi.org/10.1016/j.jhydrol.2005.07.003, 2006. a
Jacob, D.: A note to the simulation of the annual and inter-annual variability
of the water budget over the Baltic Sea drainage basin, Meteorol.
Atmos. Phys., 77, 61–73, https://doi.org/10.1007/s007030170017, 2001. a
Jacob, D. and Podzun, R.: Sensitivity studies with the regional climate model
REMO, Meteorol. Atmos. Phys., 63, 119–129, https://doi.org/10.1007/Bf01025368, 1997. a
Jaiser, R., Dethloff, K., Handorf, D., Rinke, A., and Cohen, J.: Impact of sea
ice cover changes on the Northern Hemisphere atmospheric winter circulation,
Tellus Series A, 64, 11595,
https://doi.org/10.3402/tellusa.v64i0.11595, 2012. a, b, c
Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., Matei, D.,
Mikolajewicz, U., Notz, D., and von Storch, J. S.: Characteristics of the
ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean
component of the MPI-Earth system model, J. Adv. Model.
Earth Syst., 5, 422–446, https://doi.org/10.1002/jame.20023, 2013. a
Kim, K.-Y., Hamlington, B. D., Na, H., and Kim, J.: Mechanism of seasonal Arctic sea ice evolution and Arctic amplification, The Cryosphere, 10, 2191–2202, https://doi.org/10.5194/tc-10-2191-2016, 2016. a
Kretschmer, M., Coumou, D., Donges, J. F., and Runge, J.: Using Causal Effect
Networks to Analyze Different Arctic Drivers of Midlatitude Winter
Circulation, J. Climate, 29, 4069–4081,
https://doi.org/10.1175/Jcli-D-15-0654.1, 2016. a
Krumpen, T., Janout, M., Hodges, K. I., Gerdes, R., Girard-Ardhuin, F., Hölemann, J. A., and Willmes, S.: Variability and trends in Laptev Sea ice outflow between 1992–2011, The Cryosphere, 7, 349–363, https://doi.org/10.5194/tc-7-349-2013, 2013. a
Lawrence, D. M., Slater, A. G., Tomas, R. A., Holland, M. M., and Deser, C.:
Accelerated Arctic land warming and permafrost degradation during rapid sea
ice loss, Geophys. Res. Lett., 35, L11506, https://doi.org/10.1029/2008gl033985, 2008. a, b
Lee, S., Gong, T., Feldstein, S. B., Screen, J. A., and Simmonds, I.:
Revisiting the Cause of the 1989–2009 Arctic Surface Warming Using the
Surface Energy Budget: Downward Infrared Radiation Dominates the Surface
Fluxes, Geophys. Res. Lett., 44, 10654–10661,
https://doi.org/10.1002/2017GL075375, 2017. a
Li, F. and Wang, H. J.: Autumn Sea Ice Cover, Winter Northern Hemisphere
Annular Mode, and Winter Precipitation in Eurasia, J. Climate, 26,
3968–3981, https://doi.org/10.1175/Jcli-D-12-00380.1, 2013. a
Li, M., Luo, D., Simmonds, I., Dai, A., Zhong, L., and Yao, Y.: Anchoring of
atmospheric teleconnection patterns by Arctic sea ice loss and its link to
winter cold anomalies in East Asia, Int. J. Climatol., 1–12,
https://doi.org/10.1002/joc.6637, 2020. a
Luo, B., Luo, D., Wu, L., Zhong, L., and Simmonds, I.: Atmospheric circulation
patterns which promote winter Arctic sea ice decline, Environ. Res.
Lett., 12, 054017, https://doi.org/10.1088/1748-9326/aa69d0, 2017. a
Luo, B., Wu, L., Luo, D., Dai, A., and Simmonds, I.: The winter
midlatitude-Arctic interaction: effects of North Atlantic SST and
high-latitude blocking on Arctic sea ice and Eurasian cooling, Clim.
Dynam., 52, 2981–3004, https://doi.org/10.1007/s00382-018-4301-5,
2019a. a
Luo, D., Chen, X., Overland, J., Simmonds, I., Wu, Y., and Zhang, P.: Weakened
Potential Vorticity Barrier Linked to Recent Winter Arctic Sea Ice Loss and
Midlatitude Cold Extremes, J. Climate, 32, 4235–4261,
https://doi.org/10.1175/JCLI-D-18-0449.1, 2019b. a
Macias-Fauria, M., Karlsen, S. R., and Forbes, B. C.: Disentangling the
coupling between sea ice and tundra productivity in Svalbard, Sci.
Rep., 7, 1–10, https://doi.org/10.1038/s41598-017-06218-8, 2017. a
Niederdrenk, A. L., Sein, D. V., and Mikolajewicz, U.: Interannual variability
of the Arctic freshwater cycle in the second half of the twentieth century in
a regionally coupled climate model, Clim. Dynam., 47, 3883–3900,
https://doi.org/10.1007/s00382-016-3047-1, 2016. a, b
Niederdrenk, L. and Mikolajewicz, U.: Wechselwirkungen zwischen verschiedenen
Komponenten des arktischen Klimasystems (bm0899),
available at: http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=DKRZ_lta_899 (last access: 18 November 2020),
2014. a
Ogi, M., Rysgaard, S., and Barber, D. G.: The influence of winter and summer
atmospheric circulation on the variability of temperature and sea ice around
Greenland, Tellus Series A, 68, 14,
https://doi.org/10.3402/tellusa.v68.31971, 2016. a, b
Olonscheck, D., Mauritsen, T., and Notz, D.: Arctic sea-ice variability is
primarily driven by atmospheric temperature fluctuations, Nat. Geosci.,
12, 430–434, https://doi.org/10.1038/s41561-019-0363-1, 2019. a
Overland, J. E. and Wang, M. Y.: Large-scale atmospheric circulation changes
are associated with the recent loss of Arctic sea ice, Tellus Series A, 62, 1–9,
https://doi.org/10.1111/j.1600-0870.2009.00421.x, 2010. a
Overland, J. E., Francis, J. A., Hanna, E., and Wang, M. Y.: The recent shift
in early summer Arctic atmospheric circulation, Geophys. Res. Lett.,
39, L19804, https://doi.org/10.1029/2012gl053268, 2012. a, b, c
Parmentier, F. J. W., Christensen, T. R., Sorensen, L. L., Rysgaard, S.,
McGuire, A. D., Miller, P. A., and Walker, D. A.: The impact of lower sea-ice
extent on Arctic greenhouse-gas exchange, Nat. Clim. Change, 3, 195–202,
https://doi.org/10.1038/Nclimate1784, 2013. a
Parmentier, F. J. W., Zhang, W. X., Mi, Y. J., Zhu, X. D., van Huissteden, J.,
Hayes, D. J., Zhuang, Q. L., Christensen, T. R., and McGuire, A. D.: Rising
methane emissions from northern wetlands associated with sea ice decline,
Geophys. Res. Lett., 42, 7214–7222, https://doi.org/10.1002/2015GL065013,
2015. a, b
Pearl, J.: Causality: Models, reasoning and inference, Cambridge University
Press, Cambridge, United Kingdom, 2000. a
Pithan, F. and Mauritsen, T.: Arctic amplification dominated by temperature
feedbacks in contemporary climate models, Nat. Geosci., 7, 181–184,
https://doi.org/10.1038/ngeo2071, 2014. a
Pithan, F., Medeiros, B., and Mauritsen, T.: Mixed-phase clouds cause climate
model biases in Arctic wintertime temperature inversions, Clim. Dynam.,
43, 289–303, https://doi.org/10.1007/s00382-013-1964-9, 2013. a
Post, E., Bhatt, U. S., Bitz, C. M., Brodie, J. F., Fulton, T. L., Hebblewhite,
M., Kerby, J., Kutz, S. J., Stirling, I., and Walker, D. A.: Ecological
consequences of sea-ice decline, Science, 341, 519–524,
https://doi.org/10.1126/science.1235225, 2013. a
Rigor, I. G., Wallace, J. M., and Colony, R. L.: Response of sea ice to the
Arctic oscillation, J. Climate, 15, 2648–2663,
https://doi.org/10.1175/1520-0442(2002)015<2648:Rositt>2.0.Co;2, 2002. a, b
Runge, J., Heitzig, J., Marwan, N., and Kurths, J.: Quantifying causal coupling
strength: A lag-specific measure for multivariate time series related to
transfer entropy, Phys. Rev. E, 86, 15,
https://doi.org/10.1103/PhysRevE.86.061121, 2012. a, b, c
Runge, J., Petoukhov, V., and Kurths, J.: Quantifying the Strength and Delay of
Climatic Interactions: The Ambiguities of Cross Correlation and a Novel
Measure Based on Graphical Models, J. Climate, 27, 720–739,
https://doi.org/10.1175/Jcli-D-13-00159.1, 2014. a, b, c
Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M.,
Hartman, D., Marwan, N., Palus, M., and Kurths, J.: Identifying causal
gateways and mediators in complex spatio-temporal systems, Nat.
Commun., 6, 8502, https://doi.org/10.1038/ncomms9502, 2015. a, b
Runge, J., Nowack, P., Kretschmer, M., Flaxman, S., and Sejdinovic, D.:
Detecting and quantifying causal associations in large nonlinear time series
datasets, Sci. Adv., 5, eaau4996, https://doi.org/10.1126/sciadv.aau4996, 2019. a
Samarasinghe, S. M., McGraw, M. C., Barnes, E. A., and Ebert-Uphoff, I.: A
study of links between the Arctic and the midlatitude jet stream using
Granger and Pearl causality, Environmetrics, 30, e2540,
https://doi.org/10.1002/env.2540, 2019. a
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in
recent Arctic temperature amplification, Nature, 464, 1334–1337,
https://doi.org/10.1038/nature09051, 2010. a, b
Screen, J. A., Simmonds, I., and Keay, K.: Dramatic interannual changes of
perennial Arctic sea ice linked to abnormal summer storm activity, J.
Geophys. Res., 116, D15105, https://doi.org/10.1029/2011JD015847, 2011. a
Screen, J. A., Deser, C., and Simmonds, I.: Local and remote controls on
observed Arctic warming, Geophys. Res. Lett., 39, L10709,
https://doi.org/10.1029/2012gl051598, 2012. a, b
Screen, J. A., Bracegirdle, T. J., and Simmonds, I.: Polar climate change as
manifest in atmospheric circulation, Curr. Clim. Change Rep., 4,
383–395, https://doi.org/10.1007/s40641-018-0111-4, 2018. a
Sein, D. V., Mikolajewicz, U., Groger, M., Fast, I., Cabos, W., Pinto, J. G.,
Hagemann, S., Semmler, T., Izquierdo, A., and Jacob, D.: Regionally coupled
atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and
validation, J. Adv. Model. Earth Syst., 7, 268–304,
https://doi.org/10.1002/2014ms000357, 2015. a
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic amplification:
A research synthesis, Global Planet. Change, 77, 85–96,
https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011. a, b, c
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland, M. M.: The emergence of surface-based Arctic amplification, The Cryosphere, 3, 11–19, https://doi.org/10.5194/tc-3-11-2009, 2009. a, b, c, d
Shaver, G. R., Canadell, J., Chapin, F. S., Gurevitch, J., Harte, J., Henry,
G., Ineson, P., Jonasson, S., Melillo, J., Pitelka, L., and Rustad, L.:
Global warming and terrestrial ecosystems: A conceptual framework for
analysis, Bioscience, 50, 871–882,
https://doi.org/10.1641/0006-3568(2000)050[0871:Gwatea]2.0.Co;2, 2000. a
Simmonds, I.: Comparing and contrasting the behaviour of Arctic and
Antarcticsea ice over the 35 year period 1979–2013, Ann. Glaciol.,
56, 18–28, https://doi.org/10.3189/2015AoG69A909, 2015. a
Simmonds, I. and Rudeva, I.: The great Arctic cyclone of August 2012,
Geophys. Res. Lett., 39, L23709, https://doi.org/10.1029/2012GL054259, 2012.
a
Simmonds, I. and Rudeva, I.: A comparison of tracking methods for extreme
cyclones in the Arctic basin, Tellus A,
66, 1, https://doi.org/10.3402/tellusa.v66.25252, 2014. a
Spirtes, P., Glymour, C. N., Scheines, R., and Heckerman, D.: Causation,
prediction, and search, MIT press, Cambridge, Massachusetts, United States, 2000. a
Stocker, T. F., Qin, D., Plattner, G. K., Alexander, L. V., Allen, S. K.,
Bindoff, N. L., Bréon, F. M., Church, J. A., Cubasch, U., Emori, S.,
Forster, P., Friedlingstein, P., Gillett, N., Gregory, J. M., Hartmann,
D. L., Jansen, E., Kirtman, B., Knutti, R., Kumar, K. K., Lemke, P.,
Marotzke, J., Masson-Delmotte, V., Meehl, G. A., Mokhov, I. I., Piao, S.,
Ramaswamy, V., Randall, D., Rhein, M., Rojas, M., Sabine, C., Shindell, D.,
Talley, L. D., Vaughan, D. G., and Xie, S. P.: Technical Summary, pp.
33–115, Cambridge University Press, Cambridge, United Kingdom, 2013. a
Titchner, H. A. and Rayner, N. A.: The Met Office Hadley Centre sea ice and sea
surface temperature data set, version 2:1. Sea ice concentrations, J.
Geophys. Res.-Atmos., 119, 2864–2889,
https://doi.org/10.1002/2013JD020316, 2014. a
Wang, J., Zhang, J. L., Watanabe, E., Ikeda, M., Mizobata, K., Walsh, J. E.,
Bai, X. Z., and Wu, B. Y.: Is the Dipole Anomaly a major driver to record
lows in Arctic summer sea ice extent?, Geophys. Res. Lett., 36, 5,
https://doi.org/10.1029/2008GL036706, 2009. a, b, c, d
Yang, W. C. and Magnusdottir, G.: Springtime extreme moisture transport into
the Arctic and its impact on sea ice concentration, J. Geophys.
Res.-Atmos., 122, 5316–5329, https://doi.org/10.1002/2016JD026324, 2017. a, b
Yao, Y., Luo, D., Dai, A., and Simmonds, I.: Increased quasi stationarity and
persistence of winter Ural blocking and Eurasian extreme cold events in
response to Arctic warming. Part I: Insights from observational analyses,
J. Climate, 30, 3549–3568, https://doi.org/10.1175/Jcli-D-16-0261.1, 2017. a
Short summary
To better understand the connection between sea ice and permafrost, we investigate how sea ice interacts with the atmosphere over the adjacent landmass in the Laptev Sea region using a climate model. Melt of sea ice in spring is mainly controlled by the atmosphere; in fall, feedback mechanisms are important. Throughout summer, lower-than-usual sea ice leads to more southward transport of heat and moisture, but these links from sea ice to the atmosphere over land are weak.
To better understand the connection between sea ice and permafrost, we investigate how sea ice...
