Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-5627-2026
https://doi.org/10.5194/essd-18-5627-2026
Data description article
 | 
30 Jul 2026
Data description article |  | 30 Jul 2026

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, Christian Wille, Felix Nieberding, Manuel Helbig, and Torsten Sachs

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Assessing Carbon Flux Variability in an Alpine Steppe: Insights from Dual-Height Measurements
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EGUsphere, https://doi.org/10.5194/egusphere-2025-530,https://doi.org/10.5194/egusphere-2025-530, 2025
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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. 
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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.
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