X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Nelson, Jacob A., Walther, Sophia, Gans, Fabian, Kraft, Basil, Weber, Ulrich, Novick, Kimberly, Buchmann, Nina, Migliavacca, Mirco, Wohlfahrt, Georg, Šigut, Ladislav, Ibrom, Andreas, Papale, Dario, Göckede, Mathias, Duveiller, Gregory, Knohl, Alexander, Hörtnagl, Lukas, Scott, Russell L., Zhang, Weijie, Hamdi, Zayd Mahmoud, Reichstein, Markus, Aranda-Barranco, Sergio, Ardö, Jonas, de Beeck, Maarten Op, Billesbach, Dave, Bowling, David, Bracho, Rosvel, Brümmer, Christian, Camps-Valls, Gustau, Chen, Shiping, Cleverly, Jamie Rose, Desai, Ankur, Dong, Gang, El-Madany, Tarek S., Euskirchen, Eugenie Susanne, Feigenwinter, Iris, Galvagno, Marta, Gerosa, Giacomo A., Gielen, Bert, Goded, Ignacio, Goslee, Sarah, Gough, Christopher Michael, Heinesch, Bernard, Ichii, Kazuhito, Jackowicz-Korczynski, Marcin Antoni, Klosterhalfen, Anne, Knox, Sara, Kobayashi, Hideki, Kohonen, Kukka Maaria, Korkiakoski, Mika, Mammarella, Ivan, Gharun, Mana, Marzuoli, Riccardo, Matamala, Roser, Metzger, Stefan, Montagnani, Leonardo, Nicolini, Giacomo, O’Halloran, Thomas, Ourcival, Jean Marc, Peichl, Matthias, Pendall, Elise, Reverter, Borja Ruiz, Roland, Marilyn, Sabbatini, Simone, Sachs, Torsten, Schmidt, Marius, Schwalm, Christopher R., Shekhar, Ankit, Silberstein, Richard, Silveira, Maria Lucia, Spano, Donatella, Tagesson, Torbern, Tramontana, Gianluca, Trotta, Carlo, Turco, Fabio, Vesala, Timo, Vincke, Caroline, Vitale, Domenico, Vivoni, Enrique R., Wang, Yi, Woodgate, William, Yepez, Enrico A., Zhang, Junhui, Zona, Donatella, and Jung, Martin (2024) X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences, 21 (22). pp. 5079-5115.

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Abstract

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO<inf>2</inf> net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ET<inf>T</inf>), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr<sup>−1</sup> for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr<sup>−1</sup> for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7 × 10<sup>3</sup> ± 0.9×10<sup>3</sup> km<sup>3</sup> globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Item ID: 87167
Item Type: Article (Research - C1)
ISSN: 1726-4189
Copyright Information: © Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License.
Date Deposited: 27 Nov 2025 06:23
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4105 Pollution and contamination > 410501 Environmental biogeochemistry @ 100%
SEO Codes: 19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1901 Adaptation to climate change > 190102 Ecosystem adaptation to climate change @ 100%
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