GloCE v1.0: Global CO2 Enhancement Dataset 2019-2023
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We present a globally consistent, satellite-derived dataset of CO_2 enhancement (ΔXCO_2), quantifying the spatially resolved excess in atmospheric CO_2 concentrations as a collective consequence of anthropogenic emissions and terrestrial carbon uptake. This dataset is generated from the deviations of NASA's OCO-3 satellite retrievals comprising 54 million observations across more than 200 countries from 2019 to 2023. The dataset is now encrypted and will be openly accessable once the article review process completes. If you are eager for early access of the dataset, please email <your name, affiliation, and data use> to yulunzhou@hku.hk. We will carefully consider your request. Dear reviewers, please download the datasets here and access using the password enclosed in the review documents. Many thanks! Data Descriptions ----------------------------------------- CO2_enhancement_global.nc contains all enhancement data globally. CO2_enhancement_cities.nc contains all enhancement data in global urban areas. Each data row contains the following columns: <latitude, longitude, time, xco2, co2_enhancement> Datasets are stored in netcdf files and can be accessed using the Python code below: # install pre-requests ! pip install netcdf4! pip install h5netcdf # read co2 enhancement dataimport xarray as xrfn = './CO2_Enhancements_Global.nc'data = xr.open_dataset(fn)type(data) please refer to xarray documentation for basic xarray operations. https://docs.xarray.dev/en/latest/generated/xarray.Dataset.html Please cite at least one of the following for any use of the CO2E dataset. Zhou, Y.*, Fan, P., Liu, J., Xu, Y., Huang, B., Webster, C. (2025). GloCE v1.0: Global CO2 Enhancement Dataset 2019-2023 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15209825 Fan, P., Liu, J., Xu, Y., Huang, B., Webster, C., & Zhou, Y*. (Under Review) A global dataset of CO2 enhancements during 2019-2023. For any data inquiries, please email Yulun Zhou at yulunzhou@hku.hk.
