Global monthly atmospheric CO₂ carbon isoscapes dataset at 0.05° spatial resolution from 2001 to 2020

This dataset provides global monthly atmospheric CO2 carbon isotope isoscapes from 2001 to 2020 at 0.05° spatial resolution. The maps were generated using the GBM machine learning model integrating measurements from global atmospheric baseline observatories with CO2 derived from atmospheric transport modeling, and reanalysis data. If this data set is essential to your work, or if an important result or finding depends on the global atmospheric CO2 carbon isoscapes data, co-authorship may be appropriate. You must inform us of your analysis and publication plans well in advance of submission of a paper, give us an opportunity to read and intellectually contribute to the manuscript, and, if appropriate, offer co-authorship. Contact: Han Lin Feng ([e-mail]), Xiang Wang ([e-mail]) and Zheng Fu ([e-mail])