Global land mapping of satellite-observed CO₂ total columns using spatio-temporal geostatistics

ABSTRACT

This study presents an approach for generating a global land mapping dataset of the satellite measurements of CO₂ total column (XCO₂) using spatio-temporal geostatistics, which makes full use of the joint spatial and temporal dependencies between observations. The mapping approach considers the latitude-zonal seasonal cycles and spatio-temporal correlation structure of XCO₂, and obtains global land maps of XCO₂, with a spatial grid resolution of 1° latitude by 1° longitude and temporal resolution of 3 days. We evaluate the accuracy and uncertainty of the mapping dataset in the following three ways: (1) in cross-validation, the mapping approach results in a high correlation coefficient of 0.94 between the predictions and observations, (2) in comparison with ground truth provided by the Total Carbon Column Observing Network (TCCON), the predicted XCO₂ time series and those from TCCON sites are in good agreement, with an overall bias of 0.01 ppm and a standard deviation of the difference of 1.22 ppm and (3) in comparison with model simulations, the spatio-temporal variability of XCO₂ between the mapping dataset and simulations from the CT2013 and GEOS-Chem are generally consistent. The generated mapping XCO₂ data in this study provides a new global geospatial dataset in global understanding of greenhouse gases dynamics and global warming.

KEYWORDS:

• XCO₂
• ACOS-GOSAT
• Spatio-temporal geostatistics
• global mapping
• geospatial dataset

Acknowledgements

We acknowledge John Robinson from National Institute of Water and Atmospheric Research in New Zealand for providing the Lauder TCCON data, and Laura T. Iraci from NASA Ames Research Center for providing the Influx TCCON data. The ACOS-GOSAT v3.3 data were produced by the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the ACOS/OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. We also acknowledge the GOSAT Project for acquiring the spectra. CarbonTracker CT2013 results are provided by NOAA ESRL, Boulder, Colorado, USA from the website at http://carbontracker.noaa.gov. The GEOS-Chem model (http://www.geos-chem.org/) is managed by the GEOS-Chem Support Team, based at Harvard University and Dalhousie University with support from the US NASA Earth Science Division and the Canadian National and Engineering Research Council.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Zhao-Cheng Zeng http://orcid.org/0000-0002-0008-6508