Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-5627-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-5627-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A year-long eddy covariance dataset over an Alpine Steppe on the central Tibetan Plateau: a landscape perspective on carbon and energy fluxes
Nithin D. Pillai
CORRESPONDING AUTHOR
GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Institute of Geosystems and Bioindication, Technische Universität Braunschweig, Braunschweig, Germany
Christian Wille
GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Felix Nieberding
Agrosphere Institute (IBG-3), Forschungszentrum Jülich, Wilhelm-Johne-Str., 5242 Jülich, Germany
Manuel Helbig
GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Institute of Geoecology, Technische Universität Braunschweig, Braunschweig, Germany
Related authors
Nithin D. Pillai, Christian Wille, Felix Nieberding, Manuel Helbig, and Torsten Sachs
EGUsphere, https://doi.org/10.5194/egusphere-2025-530, https://doi.org/10.5194/egusphere-2025-530, 2025
Preprint archived
Short summary
Short summary
The Tibetan Plateau is warming rapidly, affecting carbon cycles in its ecosystems. Using two measurement heights (3 m and 19 m) in an alpine steppe near Nam Co, we explored how spatial scale impacts CO2 fluxes. CO2 fluxes varied with spatial scale due to landscape heterogeneity. This variability shows that the measurement scale can shift the ecosystem's carbon balance from CO2 sink to either carbon neutral or CO2 source, highlighting the importance of considering spatial scale in carbon studies.
Judith Vogt, Tarek S. El-Madany, Christian Burgold, Abdullah Bolek, Elliot Pratt, Torsten Sachs, Christian Wille, Manuel Helbig, Maximilian P. Lau, Sebastian Zug, Jörg Matschullat, and Mathias Göckede
EGUsphere, https://doi.org/10.5194/egusphere-2026-2262, https://doi.org/10.5194/egusphere-2026-2262, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
We developed BlueMinerva, an integrated autonomous platform designed to monitor carbon exchange between water and air, water temperature, chemistry, depth, and weather conditions with high spatial coverage. The platform was tested at two lakes and yielded reliable high-quality data on carbon dynamics, demonstrating its potential for widespread use and adaptation by scientists and stakeholders.
Michael W. Thayne, Karl Kemper, Christian Wille, Aram Kalhori, and Torsten Sachs
Biogeosciences, 23, 477–495, https://doi.org/10.5194/bg-23-477-2026, https://doi.org/10.5194/bg-23-477-2026, 2026
Short summary
Short summary
This study examines methane (CH4) emissions across an Arctic catchment on Disko Island, Greenland. Using over 700 floating-chamber measurements collected during two summer seasons, we show that methane fluxes vary strongly between lakes, streams, and shorelines and change over time. Early-season emissions are mainly driven by weather and hydrology, while later patterns reflect water chemistry and biological processes.
Amanda Sellmaier, Ellen Damm, Torsten Sachs, Benjamin Kirbus, Inge Wiekenkamp, Annette Rinke, Falk Pätzold, Daiki Nomura, Astrid Lampert, and Markus Rex
Atmos. Chem. Phys., 25, 17685–17700, https://doi.org/10.5194/acp-25-17685-2025, https://doi.org/10.5194/acp-25-17685-2025, 2025
Short summary
Short summary
This study presents continuous ship-borne measurements of methane (CH4) concentration and isotopic composition monitored during an ice drift expedition in 2020. Using trajectory analysis, we linked atmospheric CH4 variabilities to air mass pathways transported over open water or sea-ice. The study highlights the potential of ship-borne observations to fill significant data gaps in the high 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
Revised manuscript accepted 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.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
Short summary
Short summary
We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Nithin D. Pillai, Christian Wille, Felix Nieberding, Manuel Helbig, and Torsten Sachs
EGUsphere, https://doi.org/10.5194/egusphere-2025-530, https://doi.org/10.5194/egusphere-2025-530, 2025
Preprint archived
Short summary
Short summary
The Tibetan Plateau is warming rapidly, affecting carbon cycles in its ecosystems. Using two measurement heights (3 m and 19 m) in an alpine steppe near Nam Co, we explored how spatial scale impacts CO2 fluxes. CO2 fluxes varied with spatial scale due to landscape heterogeneity. This variability shows that the measurement scale can shift the ecosystem's carbon balance from CO2 sink to either carbon neutral or CO2 source, highlighting the importance of considering spatial scale in carbon studies.
Inge Wiekenkamp, Anna Katharina Lehmann, Alexander Bütow, Jörg Hartmann, Stefan Metzger, Thomas Ruhtz, Christian Wille, Mathias Zöllner, and Torsten Sachs
Atmos. Meas. Tech., 18, 749–772, https://doi.org/10.5194/amt-18-749-2025, https://doi.org/10.5194/amt-18-749-2025, 2025
Short summary
Short summary
Airborne eddy covariance platforms are crucial to measure three-dimensional wind and turbulent matter and energy transport between the surface and the atmosphere at larger scales. In this study, we introduce a new airborne eddy covariance platform (Schleicher ASK-16) and demonstrate that this platform is able to accurately measure turbulent fluxes and wind vectors. Data from this platform can help to build bridges between local tower measurements and remote-sensing-based products.
Tabea Rettelbach, Ingmar Nitze, Inge Grünberg, Jennika Hammar, Simon Schäffler, Daniel Hein, Matthias Gessner, Tilman Bucher, Jörg Brauchle, Jörg Hartmann, Torsten Sachs, Julia Boike, and Guido Grosse
Earth Syst. Sci. Data, 16, 5767–5798, https://doi.org/10.5194/essd-16-5767-2024, https://doi.org/10.5194/essd-16-5767-2024, 2024
Short summary
Short summary
Permafrost landscapes in the Arctic are rapidly changing due to climate warming. Here, we publish aerial images and elevation models with very high spatial detail that help study these landscapes in northwestern Canada and Alaska. The images were collected using the Modular Aerial Camera System (MACS). This dataset has significant implications for understanding permafrost landscape dynamics in response to climate change. It is publicly available for further research.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Pia Gottschalk, Aram Kalhori, Zhan Li, Christian Wille, and Torsten Sachs
Biogeosciences, 21, 3593–3616, https://doi.org/10.5194/bg-21-3593-2024, https://doi.org/10.5194/bg-21-3593-2024, 2024
Short summary
Short summary
To improve the accuracy of spatial carbon exchange estimates, we evaluated simple linear models for net ecosystem exchange (NEE) and gross primary productivity (GPP) and how they can be used to upscale the CO2 exchange of agricultural fields. The models are solely driven by Sentinel-2-derived vegetation indices (VIs). Evaluations show that different VIs have variable power to estimate NEE and GPP of crops in different years. The overall performance is as good as results from complex crop models.
Daniel Wesley, Scott Dallimore, Roger MacLeod, Torsten Sachs, and David Risk
The Cryosphere, 17, 5283–5297, https://doi.org/10.5194/tc-17-5283-2023, https://doi.org/10.5194/tc-17-5283-2023, 2023
Short summary
Short summary
The Mackenzie River delta (MRD) is an ecosystem with high rates of methane production from biologic and geologic sources, but little research has been done to determine how often geologic or biogenic methane is emitted to the atmosphere. Stable carbon isotope analysis was used to identify the source of CH4 at several sites. Stable carbon isotope (δ13C-CH4) signatures ranged from −42 to −88 ‰ δ13C-CH4, indicating that CH4 emission in the MRD is caused by biologic and geologic sources.
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.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
Short summary
Short summary
We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
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.
Cited articles
Anslan, S., Azizi Rad, M., Buckel, J., Echeverria Galindo, P., Kai, J., Kang, W., Keys, L., Maurischat, P., Nieberding, F., Reinosch, E., Tang, H., Tran, T. V., Wang, Y., and Schwalb, A.: Reviews and syntheses: How do abiotic and biotic processes respond to climatic variations in the Nam Co catchment (Tibetan Plateau)?, Biogeosciences, 17, 1261–1279, https://doi.org/10.5194/bg-17-1261-2020, 2020.
Aubinet, M., Vesala, T., and Papale, D. (Eds.): Eddy Covariance: A Practical Guide to Measurement and Data Analysis, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-007-2351-1, 2012.
Baldocchi, D.: Measuring fluxes of trace gases and energy between ecosystems and the atmosphere – the state and future of the eddy covariance method, Global Change Biol., 20, 3600–3609, https://doi.org/10.1111/gcb.12649, 2014.
Baldocchi, D. D.: Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future, Global Change Biol., 9, 479–492, https://doi.org/10.1046/j.1365-2486.2003.00629.x, 2003.
Baldocchi, D. D.: How eddy covariance flux measurements have contributed to our understanding of Global Change Biology, Global Change Biol., 26, 242–260, https://doi.org/10.1111/gcb.14807, 2020.
Biermann, T., Babel, W., Ma, W., Chen, X., Thiem, E., Ma, Y., and Foken, T.: Turbulent flux observations and modelling over a shallow lake and a wet grassland in the Nam Co basin, Tibetan Plateau, Theor. Appl. Climatol., 116, 301–316, https://doi.org/10.1007/s00704-013-0953-6, 2014.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Brutsaert, W.: On a derivable formula for long‐wave radiation from clear skies, Water Resour. Res., 11, 742–744, https://doi.org/10.1029/WR011i005p00742, 1975.
Burba, G. G. and Anderson, D. J.: A Brief Practical Guide to Eddy Covariance Flux Measurements: Principles and Workflow Examples for Scientific and Industrial Applications, LI-COR Biosciences, https://doi.org/10.13140/RG.2.1.1626.4161, 2010.
Cai, W., Xu, L., Wen, D., Zhou, Z., Li, M., Wang, T., and He, N.: The carbon sequestration potential of vegetation over the Tibetan Plateau, Renew. Sustain. Energ. Rev., 207, 114937, https://doi.org/10.1016/j.rser.2024.114937, 2025.
Chu, H., Baldocchi, D. D., Poindexter, C., Abraha, M., Desai, A. R., Bohrer, G., Arain, M. A., Griffis, T., Blanken, P. D., O'Halloran, T. L., Thomas, R. Q., Zhang, Q., Burns, S. P., Frank, J. M., Christian, D., Brown, S., Black, T. A., Gough, C. M., Law, B. E., Lee, X., Chen, J., Reed, D. E., Massman, W. J., Clark, K., Hatfield, J., Prueger, J., Bracho, R., Baker, J. M., and Martin, T. A.: Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks, Geophys. Res. Lett., 45, 9275–9287, https://doi.org/10.1029/2018GL079306, 2018.
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., and Zona, D.: Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites, Agr. Forest Meteorol., 301–302, 108350, https://doi.org/10.1016/j.agrformet.2021.108350, 2021.
Copernicus Climate Change Service: ERA5-Land monthly averaged data from 1950 to present, Copernicus Climate Change Service [data set], https://doi.org/10.24381/CDS.68D2BB30, 2019.
C3S: ERA5 hourly data on single levels from 1940 to present, C3S [data set], https://doi.org/10.24381/CDS.ADBB2D47, 2018.
Falge, E., Baldocchi, D., Olson, R., Anthoni, P., Aubinet, M., Bernhofer, C., Burba, G., Ceulemans, R., Clement, R., Dolman, H., Granier, A., Gross, P., Grünwald, T., Hollinger, D., Jensen, N.-O., Katul, G., Keronen, P., Kowalski, A., Lai, C. T., Law, B. E., Meyers, T., Moncrieff, J., Moors, E., Munger, J. W., Pilegaard, K., Rannik, Ü., Rebmann, C., Suyker, A., Tenhunen, J., Tu, K., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: Gap filling strategies for defensible annual sums of net ecosystem exchange, Agr. Forest Meteorol., 107, 43–69, https://doi.org/10.1016/S0168-1923(00)00225-2, 2001.
Finkelstein, P. L. and Sims, P. F.: Sampling error in eddy correlation flux measurements, J. Geophys. Res., 106, 3503–3509, https://doi.org/10.1029/2000jd900731, 2001.
Foken, T.: The energy balance closure problem: an overview, Ecol. Appl., 18, 1351–1367, https://doi.org/10.1890/06-0922.1, 2008.
Foken, T., Göockede, M., Mauder, M., Mahrt, L., Amiro, B., and Munger, W.: Post-Field Data Quality Control, in: Handbook of Micrometeorology, vol. 29, edited by: Lee, X., Massman, W., and Law, B., Kluwer Academic Publishers, Dordrecht, 181–208, https://doi.org/10.1007/1-4020-2265-4_9, 2005.
Foken, T., Aubinet, M., Finnigan, J. J., Leclerc, M. Y., Mauder, M., and Paw U, K. T.: Results Of A Panel Discussion About The Energy Balance Closure Correction For Trace Gases, B. Am. Meteorol. Soc., 92, ES13–ES18, https://doi.org/10.1175/2011BAMS3130.1, 2011.
Hiller, R., Zeeman, M. J., and Eugster, W.: Eddy-Covariance Flux Measurements in the Complex Terrain of an Alpine Valley in Switzerland, Bound.-Lay. Meteorol., 127, 449–467, https://doi.org/10.1007/s10546-008-9267-0, 2008.
Irvin, J., Zhou, S., McNicol, G., Lu, F., Liu, V., Fluet-Chouinard, E., Ouyang, Z., Knox, S. H., Lucas-Moffat, A., Trotta, C., Papale, D., Vitale, D., Mammarella, I., Alekseychik, P., Aurela, M., Avati, A., Baldocchi, D., Bansal, S., Bohrer, G., Campbell, D. I., Chen, J., Chu, H., Dalmagro, H. J., Delwiche, K. B., Desai, A. R., Euskirchen, E., Feron, S., Goeckede, M., Heimann, M., Helbig, M., Helfter, C., Hemes, K. S., Hirano, T., Iwata, H., Jurasinski, G., Kalhori, A., Kondrich, A., Lai, D. Y., Lohila, A., Malhotra, A., Merbold, L., Mitra, B., Ng, A., Nilsson, M. B., Noormets, A., Peichl, M., Rey-Sanchez, A. C., Richardson, A. D., Runkle, B. R., Schäfer, K. V., Sonnentag, O., Stuart-Haëntjens, E., Sturtevant, C., Ueyama, M., Valach, A. C., Vargas, R., Vourlitis, G. L., Ward, E. J., Wong, G. X., Zona, D., Alberto, Ma. C. R., Billesbach, D. P., Celis, G., Dolman, H., Friborg, T., Fuchs, K., Gogo, S., Gondwe, M. J., Goodrich, J. P., Gottschalk, P., Hörtnagl, L., Jacotot, A., Koebsch, F., Kasak, K., Maier, R., Morin, T. H., Nemitz, E., Oechel, W. C., Oikawa, P. Y., Ono, K., Sachs, T., Sakabe, A., Schuur, E. A., Shortt, R., Sullivan, R. C., Szutu, D. J., Tuittila, E.-S., Varlagin, A., Verfaillie, J. G., Wille, C., Windham-Myers, L., Poulter, B., and Jackson, R. B.: Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands, Agr. Forest Meteorol., 308–309, 108528, https://doi.org/10.1016/j.agrformet.2021.108528, 2021.
Joiner, J. and Yoshida, Y.: Vegetation CollectionGlobal MODIS and FLUXNET-derived Daily Gross Primary Production, V2, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1835, 2021.
Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001–2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
Kalhori, A., Wille, C., Gottschalk, P., Li, Z., Hashemi, J., Kemper, K., and Sachs, T.: Temporally dynamic carbon dioxide and methane emission factors for rewetted peatlands, Commun. Earth Environ., 5, https://doi.org/10.1038/s43247-024-01226-9, 2024.
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP), Geosci. Model Dev., 8, 3695–3713, https://doi.org/10.5194/gmd-8-3695-2015, 2015.
Kormann, R. and Meixner, F. X.: An Analytical Footprint Model For Non-Neutral Stratification, Bound.-Lay. Meteorol., 99, 207–224, https://doi.org/10.1023/A:1018991015119, 2001.
Lasslop, G., Reichstein, M., Papale, D., Richardson, A. D., Arneth, A., Barr, A., Stoy, P., and Wohlfahrt, G.: Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation, Global Change Biol., 16, 187–208, https://doi.org/10.1111/j.1365-2486.2009.02041.x, 2010.
Leclerc, M. Y. and Foken, T.: Footprints in Micrometeorology and Ecology, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-54545-0, 2014.
Li, M., Babel, W., Chen, X., Zhang, L., Sun, F., Wang, B., Ma, Y., Hu, Z., and Foken, T.: A 3-year dataset of sensible and latent heat fluxes from the Tibetan Plateau, derived using eddy covariance measurements, Theor. Appl. Climatol., 122, 457–469, https://doi.org/10.1007/s00704-014-1302-0, 2015.
Liu, Y., Zhang, X., Du, X., Du, Z., and Sun, M.: Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture, Sci. Total Environ., 916, 169995, https://doi.org/10.1016/j.scitotenv.2024.169995, 2024.
Loescher, H. W., Law, B. E., Mahrt, L., Hollinger, D. Y., Campbell, J., and Wofsy, S. C.: Uncertainties in, and interpretation of, carbon flux estimates using the eddy covariance technique, J. Geophys. Res., 111, https://doi.org/10.1029/2005jd006932, 2006.
Ma, C., Duan, S.-B., Xu, C., Qin, W., Wang, F., and He, L.: Spatio-temporal simulation of net ecosystem productivity in the Tibetan Plateau region using multi-scale data assimilation for terrestrial ecosystem process model, Agr. Forest Meteorol., 366, 110471, https://doi.org/10.1016/j.agrformet.2025.110471, 2025.
Ma, Y., Wang, Y., Wu, R., Hu, Z., Yang, K., Li, M., Ma, W., Zhong, L., Sun, F., Chen, X., Zhu, Z., Wang, S., and Ishikawa, H.: Recent advances on the study of atmosphere-land interaction observations on the Tibetan Plateau, Hydrol. Earth Syst. Sci., 13, 1103–1111, https://doi.org/10.5194/hess-13-1103-2009, 2009.
Mauder, M. and Foken, T.: Impact of post-field data processing on eddy covariance flux estimates and energy balance closure, Meteorol. Z., 15, 597–609, https://doi.org/10.1127/0941-2948/2006/0167, 2006.
Mauder, M., Foken, T., Aubinet, M., and Ibrom, A.: Eddy-Covariance Measurements, in: Springer Handbook of Atmospheric Measurements, edited by: Foken, T., Springer International Publishing, Cham, 1473–1504, https://doi.org/10.1007/978-3-030-52171-4_55, 2021.
Melaas, E. K., Richardson, A. D., Friedl, M. A., Dragoni, D., Gough, C. M., Herbst, M., Montagnani, L., and Moors, E.: Using FLUXNET data to improve models of springtime vegetation activity onset in forest ecosystems, Agr. Forest Meteorol., 171–172, 46–56, https://doi.org/10.1016/j.agrformet.2012.11.018, 2013.
Moncrieff, J., Clement, R., Finnigan, J., and Meyers, T.: Averaging, Detrending, and Filtering of Eddy Covariance Time Series, in: Handbook of Micrometeorology, vol. 29, edited by: Lee, X., Massman, W., and Law, B., Kluwer Academic Publishers, Dordrecht, 7–31, https://doi.org/10.1007/1-4020-2265-4_2, 2005.
Moncrieff, J. B., Massheder, J. M., De Bruin, H., Elbers, J., Friborg, T., Heusinkveld, B., Kabat, P., Scott, S., Soegaard, H., and Verhoef, A.: A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide, J. Hydrol., 188–189, 589–611, https://doi.org/10.1016/S0022-1694(96)03194-0, 1997.
Nieberding, F., Wille, C., Fratini, G., Asmussen, M. O., Wang, Y., Ma, Y., and Sachs, T.: A long-term (2005–2019) eddy covariance data set of CO2 and H2O fluxes from the Tibetan alpine steppe, Earth Syst. Sci. Data, 12, 2705–2724, https://doi.org/10.5194/essd-12-2705-2020, 2020a.
Nieberding, F., Ma, Y., Wille, C., Fratini, G., Asmussen, M. O., Wang, Y., Ma, W., and Sachs, T.: A long term hourly eddy covariance dataset of consistently processed CO2 and H2O Fluxes from the Tibetan Alpine Steppe at Nam Co (2005–2019), Zenodo [data set], https://doi.org/10.5281/zenodo.3733202, 2020b (data also available at: https://doi.org/10.11888/Meteoro.tpdc.270333).
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Pillai, N. D., Wille, C., Nieberding, F., Helbig, M., and Sachs, T.: Year-long eddy covariance measurements of carbon and energy fluxes in an alpine steppe on the Tibetan Plateau, GFZ Data Services [data set], https://doi.org/10.5880/GFZ.TKVR.2026.001, 2026.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biol., 11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J., Flanagan, L. B., Katul, G. G., William Munger, J., Ricciuto, D. M., Stoy, P. C., Suyker, A. E., Verma, S. B., and Wofsy, S. C.: A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes, Agr. Forest Meteorol., 136, 1–18, https://doi.org/10.1016/j.agrformet.2006.01.007, 2006.
Sabbatini, S., Mammarella, I., Arriga, N., Fratini, G., Graf, A., Hörtnagl, L., Ibrom, A., Longdoz, B., Mauder, M., Merbold, L., Metzger, S., Montagnani, L., Pitacco, A., Rebmann, C., Sedlák, P., Šigut, L., Vitale, D., and Papale, D.: Eddy covariance raw data processing for CO2 and energy fluxes calculation at ICOS ecosystem stations, Inte. Agrophys., 32, 495–515, https://doi.org/10.1515/intag-2017-0043, 2018.
Schmid, H. P.: Footprint modeling for vegetation atmosphere exchange studies: a review and perspective, Agr. Forest Meteorol., 113, 159–183, https://doi.org/10.1016/S0168-1923(02)00107-7, 2002.
Stekhoven, D. J. and Bühlmann, P.: MissForest – non-parametric missing value imputation for mixed-type data, Bioinformatics, 28, 112–118, https://doi.org/10.1093/bioinformatics/btr597, 2012.
Tuovinen, J.-P., Aurela, M., Hatakka, J., Räsänen, A., Virtanen, T., Mikola, J., Ivakhov, V., Kondratyev, V., and Laurila, T.: Interpreting eddy covariance data from heterogeneous Siberian tundra: land-cover-specific methane fluxes and spatial representativeness, Biogeosciences, 16, 255–274, https://doi.org/10.5194/bg-16-255-2019, 2019.
Turner, D. P., Ollinger, S. V., and Kimball, J. S.: Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle, BioScience, 54, 573, https://doi.org/10.1641/0006-3568(2004)054[0573:IRSAEP]2.0.CO;2, 2004.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol., 103, 279–300, https://doi.org/10.1016/S0168-1923(00)00123-4, 2000.
Vesala, T., Kljun, N., Rannik, Ü., Rinne, J., Sogachev, A., Markkanen, T., Sabelfeld, K., Foken, Th., and Leclerc, M. Y.: Flux and concentration footprint modelling: State of the art, Environ. Pollut., 152, 653–666, https://doi.org/10.1016/j.envpol.2007.06.070, 2008.
Vickers, D. and Mahrt, L.: Quality Control and Flux Sampling Problems for Tower and Aircraft Data, J. Atmos. Ocean. Tech., 14, 512–526, https://doi.org/10.1175/1520-0426(1997)014<0512:QCAFSP>2.0.CO;2, 1997.
Wang, B., Ma, Y., Hu, Z., Li, X., Ma, W., Chen, X., Han, C., Xie, Z., Wang, Y., Li, M., Ma, B., Shi, X., Li, W., and Cai, Z.: Quantifying the spatial-seasonal patterns of land–atmosphere water, heat and CO2 flux exchange over the Tibetan Plateau from an observational perspective, Earth Syst. Sci. Data, 18, 1147–1164, https://doi.org/10.5194/essd-18-1147-2026, 2026.
Wang, T., Zhang, Y., Yue, C., Wang, Y., Wang, X., Lyu, G., Wei, J., Yang, H., and Piao, S.: Progress and challenges in remotely sensed terrestrial carbon fluxes, Geo-spatial Inform. Sci., 28, 1–21, https://doi.org/10.1080/10095020.2024.2336599, 2025a.
Wang, X., Che, T., Xiao, J., Wang, T., Tan, J., Zhang, Y., Ren, Z., Geng, L., Wang, H., Xu, Z., Liu, S., and Li, X.: A post-processed carbon flux dataset for 34 eddy covariance flux sites across the Heihe River basin, China, Earth Syst. Sci. Data, 17, 1329–1346, https://doi.org/10.5194/essd-17-1329-2025, 2025b.
Wang, Y., Zhu, Z., Ma, Y., and Yuan, L.: Carbon and water fluxes in an alpine steppe ecosystem in the Nam Co area of the Tibetan Plateau during two years with contrasting amounts of precipitation, Int. J. Biometeorol., 64, 1183–1196, https://doi.org/10.1007/s00484-020-01892-2, 2020.
Wang, Y., Xiao, J., Ma, Y., Luo, Y., Hu, Z., Li, F., Li, Y., Gu, L., Li, Z., and Yuan, L.: Carbon fluxes and environmental controls across different alpine grassland types on the Tibetan Plateau, Agr. Forest Meteorol., 311, 108694, https://doi.org/10.1016/j.agrformet.2021.108694, 2021.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements for density effects due to heat and water vapour transfer, Q. J. Roy. Meteorool. Soc., 106, 85–100, https://doi.org/10.1002/qj.49710644707, 1980.
Wu, T.: The Qinghai–Tibetan Plateau: How High Do Tibetans Live?, High Altit. Med. Biol., 2, 489–499, https://doi.org/10.1089/152702901753397054, 2001.
Wutzler, T., Lucas-Moffat, A., Migliavacca, M., Knauer, J., Sickel, K., Šigut, L., Menzer, O., and Reichstein, M.: Basic and extensible post-processing of eddy covariance flux data with REddyProc, Biogeosciences, 15, 5015–5030, https://doi.org/10.5194/bg-15-5015-2018, 2018.
Xiao, J., Davis, K. J., Urban, N. M., Keller, K., and Saliendra, N. Z.: Upscaling carbon fluxes from towers to the regional scale: Influence of parameter variability and land cover representation on regional flux estimates, J. Geophys. Res., 116, G03027, https://doi.org/10.1029/2010JG001568, 2011.
Xiao, J., Chen, J., Davis, K. J., and Reichstein, M.: Advances in upscaling of eddy covariance measurements of carbon and water fluxes, J. Geophys. Res., 117, 2011JG001889, https://doi.org/10.1029/2011JG001889, 2012.
Yao, J., Zhao, L., Gu, L., Qiao, Y., and Jiao, K.: The surface energy budget in the permafrost region of the Tibetan Plateau, Atmos. Res., 102, 394–407, https://doi.org/10.1016/j.atmosres.2011.09.001, 2011.
Yuan, Q., Wang, X., Che, T., and Li, J.: Global carbon flux dataset generated by fusing remote sensing and multiple flux networks observation, Sci. Data, 12, 1359, https://doi.org/10.1038/s41597-025-05672-8, 2025.
Zhang, J., Duan, Z., Zhou, S., Li, Y., and Gao, Z.: Gap filling of turbulent heat fluxes over rice–wheat rotation croplands using the random forest model, Atmos. Meas. Tech., 16, 2197–2207, https://doi.org/10.5194/amt-16-2197-2023, 2023.
Zhu, Z., Ma, Y., Li, M., Hu, Z., Xu, C., Zhang, L., Han, C., Wang, Y., and Ichiro, T.: Carbon dioxide exchange between an alpine steppe ecosystem and the atmosphere on the Nam Co area of the Tibetan Plateau, Agr. Forest Meteorol., 203, 169–179, https://doi.org/10.1016/j.agrformet.2014.12.013, 2015.
Short summary
We present a continuous dataset of carbon and energy fluxes measured over an alpine steppe in the Tibetan Plateau using the Eddy Covariance technique at 19 m. Covering a larger footprint (~ 30 ha) than the existing long-term 3 m measurements, it enables landscape-scale flux estimation, improved alignment with satellite observations, and supports studies of ecosystem modelling and satellite product validation.
We present a continuous dataset of carbon and energy fluxes measured over an alpine steppe in...
Altmetrics
Final-revised paper
Preprint