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Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability

Wang, Kai and Bastos, Ana and Ciais, Philippe and Wang, Xuhui and Rödenbeck, Christian and Gentine, Pierre and Chevallier, Frédéric and Humphrey, Vincent W. and Huntingford, Chris and O’Sullivan, Michael and Seneviratne, Sonia I. and Sitch, Stephen and Piao, Shilong (2022) Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability. Nature Communications, 13 . Art. No. 3469. ISSN 2041-1723. PMCID PMC9203577. doi:10.1038/s41467-022-31175-w.

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Global fluctuations in annual land carbon uptake (NEEIAV) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, we quantify regional and seasonal contributions to the correlations of globally-averaged NEEIAV against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEEIAV, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEEIAV and discuss their implications for future carbon–climate feedbacks.

Item Type:Article
Related URLs:
URLURL TypeDescription!/dataset/cams-global-greenhouse-gas-inversionRelated ItemNet land carbon fluxes of CAMS atmospheric inversions ItemJena CarboScope inversions results ItemSimulations from TRENDY DGVMs ItemFLUXCOM ensemble of carbon fluxes ItemMonthly gridded air temperature, precipitation, and potential evapotranspiration data TWS dataset based on GRACE observations ItemCO₂ mole fraction data CentralArticle
Wang, Kai0000-0001-6269-3517
Bastos, Ana0000-0002-7368-7806
Ciais, Philippe0000-0001-8560-4943
Wang, Xuhui0000-0003-0818-9816
Gentine, Pierre0000-0002-0845-8345
Chevallier, Frédéric0000-0002-4327-3813
Humphrey, Vincent W.0000-0002-2541-6382
Huntingford, Chris0000-0002-5941-7770
O’Sullivan, Michael0000-0002-6278-3392
Seneviratne, Sonia I.0000-0001-9528-2917
Sitch, Stephen0000-0003-1821-8561
Piao, Shilong0000-0001-8057-2292
Additional Information:© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Received 02 November 2020; Accepted 30 May 2022; Published 16 June 2022. We thank Dr. Martin Jung for his helpful comments on the manuscript and help in data preparation. We would like to thank the TRENDYv7 modelers for their simulations. We also thank Dr. Pieter Tans and Dr. Ed Dlugokencky for providing the CO2 mole fraction data. S.P. acknowledges the support from the National Natural Science Foundation of China (41988101), the Second Tibetan Plateau Scientific Expedition and Research Program (Grant No. 2019QZKK0208), and the Xplorer Prize. A.B., P.C., F.C., M.O., and S.S. acknowledge the support from the European Space Agency Climate Change Initiative RECCAP2 project (contract no. 4000123002/18/I-NB). V.H. acknowledges the support from the Swiss National Science Foundation (grants no. P400P2_180784 and P4P4P2_194464). Data availability: The net land carbon fluxes of CAMS atmospheric inversions are available at!/dataset/cams-global-greenhouse-gas-inversion. The Jena CarboScope inversions results are available from the Jena CarboScope website The simulations from TRENDY DGVMs are available at The FLUXCOM ensemble of carbon fluxes is available at Monthly gridded air temperature, precipitation, and potential evapotranspiration data from the Climatic Research Unit can be accessed at The reconstructed TWS dataset based on GRACE observations is accessible at The CO2 mole fraction data from the Greenhouse Gas Marine Boundary Layer Reference of the NOAA ESRL is available at Code availability: All computer codes for the analysis of the data are available from the corresponding author on reasonable request. Contributions: S.P., P.C., A.B., and X.W. designed the study. K.W. performed the analysis. K.W., S.P., A.B., and P.C. drafted the paper with contributions by X.W., C.R., P.G., F.C., V.W.H., C.H., M.O., S.I.S., and S.S. P.C. and A.B. contributed equally to this work. All authors contributed to the interpretation of the results. The authors declare no competing interests. Peer review information: Nature Communications thanks Kirsten Thonicke and the anonymous reviewer(s) for their contribution to the peer review of this work.
Funding AgencyGrant Number
National Natural Science Foundation of China41988101
Second Tibetan Plateau Scientific Expedition and Research2019QZKK0208
European Space Agency (ESA)4000123002/18/I-NB
Swiss National Science Foundation (SNSF)P400P2_180784
Swiss National Science Foundation (SNSF)P4P4P2_194464
PubMed Central ID:PMC9203577
Record Number:CaltechAUTHORS:20220621-833619600
Persistent URL:
Official Citation:Wang, K., Bastos, A., Ciais, P. et al. Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability. Nat Commun 13, 3469 (2022).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115207
Deposited By: Tony Diaz
Deposited On:21 Jun 2022 17:28
Last Modified:28 Jun 2022 21:31

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