Articles | Volume 13, issue 2
https://doi.org/10.5194/esd-13-833-2022
https://doi.org/10.5194/esd-13-833-2022
Research article
 | 
19 Apr 2022
Research article |  | 19 Apr 2022

Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products

Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han

Related authors

China Wildfire Emission (ChinaWED v1) for the period 2012–2022
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-170,https://doi.org/10.5194/gmd-2024-170, 2024
Preprint under review for GMD
Short summary
Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: Ground-based observations, TROPOMI data, inventory data and inversions
Pengfei Han, Ning Zeng, Bo Yao, Wen Zhang, Weijun Quan, Pucai Wang, Ting Wang, Minqiang Zhou, Qixiang Cai, Yuzhong Zhang, Ruosi Liang, Wanqi Sun, and Shengxiang Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2162,https://doi.org/10.5194/egusphere-2024-2162, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024,https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024,https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Precipitation-fire-functional interactions control biomass stocks and carbon exchanges across the world’s largest savanna
Mathew Williams, David T. Milodowski, Thomas Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
EGUsphere, https://doi.org/10.5194/egusphere-2024-2497,https://doi.org/10.5194/egusphere-2024-2497, 2024
Short summary

Related subject area

Earth system interactions with the biosphere: biogeochemical cycles
How does the phytoplankton–light feedback affect the marine N2O inventory?
Sarah Berthet, Julien Jouanno, Roland Séférian, Marion Gehlen, and William Llovel
Earth Syst. Dynam., 14, 399–412, https://doi.org/10.5194/esd-14-399-2023,https://doi.org/10.5194/esd-14-399-2023, 2023
Short summary
Time-varying changes and uncertainties in the CMIP6 ocean carbon sink from global to local scale
Parsa Gooya, Neil C. Swart, and Roberta C. Hamme
Earth Syst. Dynam., 14, 383–398, https://doi.org/10.5194/esd-14-383-2023,https://doi.org/10.5194/esd-14-383-2023, 2023
Short summary
Interannual global carbon cycle variations linked to atmospheric circulation variability
Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, and Ana Bastos
Earth Syst. Dynam., 13, 1505–1533, https://doi.org/10.5194/esd-13-1505-2022,https://doi.org/10.5194/esd-13-1505-2022, 2022
Short summary
Contrasting projections of the ENSO-driven CO2 flux variability in the equatorial Pacific under high-warming scenario
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022,https://doi.org/10.5194/esd-13-1097-2022, 2022
Short summary
Indian Ocean marine biogeochemical variability and its feedback on simulated South Asia climate
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022,https://doi.org/10.5194/esd-13-809-2022, 2022
Short summary

Cited articles

Alemohammad, S. H., Fang, B., Konings, A. G., Aires, F., Green, J. K., Kolassa, J., Miralles, D., Prigent, C., and Gentine, P.: Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence, Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, 2017. 
Anav, A., Friedlingstein, P., Beer, C., Ciais, P., Harper, A., Jones, C., Murray-Tortarolo, G., Papale, D., Parazoo, N. C., Peylin, P., Piao, S., Sitch, S., Viovy, N., Wiltshire, A., and Zhao, M.: Spatiotemporal patterns of terrestrial gross primary production: A review, Rev. Geophys., 53, 785–818, https://doi.org/10.1002/2015rg000483, 2015. 
Bacour, C., Maignan, F., MacBean, N., Porcar-Castell, A., Flexas, J., Frankenberg, C., Peylin, P., Chevallier, F., Vuichard, N., and Bastrikov, V.: Improving Estimates of Gross Primary Productivity by Assimilating Solar-Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process-Based SIF Model, J. Geophys. Res.-Biogeo., 124, 3281–3306, https://doi.org/10.1029/2019jg005040, 2019. 
Badgley, G., Field, C. B., and Berry, J. A.: Canopy near-infrared reflectance and terrestrial photosynthesis, Science Advances, 3, e1602244, https://doi.org/10.1126/sciadv.1602244, 2017. 
Badgley, G., Anderegg, L. D. L., Berry, J. A., and Field, C. B.: Terrestrial gross primary production: Using NIRV to scale from site to globe, Glob. Change Biol., 25, 3731–3740, https://doi.org/10.1111/gcb.14729, 2019. 
Download
Short summary
We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
Altmetrics
Final-revised paper
Preprint