Data from: Constraining a data-driven CO2 flux model by ecosystem and atmospheric observations using atmospheric transport

This dataset is a sample of the data from the paper 'Constraining a data-driven CO2 flux model by ecosystem andatmospheric observations using atmospheric transport' The data is a subset of daily mean NEE in $\mu mol CO_{2} m^{-2} s^{-1}$ downsampled form 0.05 to 0.25 deg spatial resolution for the years 2016-2020. Acknowledgements. We would like to thank the FLUXCOM team for their structural support, feedback and discussion. The authors wouldlike to thank the eddy covariance community, particularly FLUXNET and the associated regional networks, the European Integrated CarbonObservation System (ICOS) and AmeriFlux. We would like to thank Dr. Jost Lavric for the use of ATTO observational data. We wouldlike to thank Dieu Anh Tran and Dr. Sönke Zaehle for providing and facilitating our use of the ZOTTO observational data. The Authorswould like to thank the producers of the inversion data included in this study. We would like to thank Dr. Saqr Munassar and Dr. ThomasKoch for providing STILT footprint runs for the European domain. This research was funded by the European Research Council (ERC)Synergy Grant ’Understanding and modeling the Earth System with Machine Learning (USMILE)’ under the Horizon 2020 research andinnovation programme (Grant Agreement No. 855187). SB and the ATTO project were funded by the German Federal Ministry of Educationand Research (BMBF, contracts 01LB1001A and 01LK1602A). The ATTO project is furthermore funded by the Brazilian Ministério daCiência, Tecnologia e Inovação (MCTI/FINEP contract 01.11.01248.00) and the Max Planck Society.