Pipeline *

    * The Level 3 maps shown here are generated by automating the processing of the data in a pipeline.

Data [1-3]

Data Origin:ACOS v3.4 release-3, which were produced by the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from Christopher O'Dell (CSU, ACOS/OCO-2 Algorithms Team). The filtered and bias-corrected XCO2 data were used for generating the Level 3 maps shown here.

Acknowledgement: We thank NASA and the ACOS/OCO-2 project for providing the data, the GOSAT Project for acquiring the spectra.

Methodology [4-6]

The geostatistical mapping methodology used here accounts for and exploits the spatial correlation of the examined random field at different locations. The basic idea is that, for each location at which an areal average estimate of the variable is required, subsampling, parameter inference and interpolation are updated using the sub-sampled set of measurements centered on each location. The development of the automatic mapping methodology itself comprises several interconnected steps:

  • Subsample the data with a sampling probability function (1/h2). A minimum of two observations is required within a minimum 2000 km radius around projection point where estimates can be obtained.
  • Choose the exponential model as the covariance function.
  • Infer local covariance parameters on 1° × 1° global grid.
  • Estimate XCO2 concentration on 1° × 1° spatial interval with a six-day aggregation period.


  1. Wunch et al. (2011) "A method for evaluating bias in global measurements of CO2 total columns from Space", Atmos. Chem. Phys., 11, 12317-12337, doi:10.5194/acp-11-12317-2011.
  2. O’Dell et al. (2012) "The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations", Atmos. Meas. Tech., 5, 99–121, doi:10.5194/amt-5-99-2012.
  3. Crisp et al. (2012) "The ACOS CO2 retrieval algorithm – Part II: Global XCO2 data characterization", Atmos. Meas. Tech., 5, 687-707, doi:10.5194/amt-5-687-2012.
  4. Tadić, J.M., X. Qiu, A.M. Michalak (2014) "New developments of satellite mapping methodology based on Moving Window Block Kriging", to be submitted.
  5. Hammerling, D.M., A.M. Michalak, S.R. Kawa (2012) “Mapping of CO2 at high spatiotemporal resolution using satellite observations: Global distributions from OCO-2”, Journal of Geophysical Research – Atmospheres, 117, D06306, doi:10.1029/2011JD017015.
  6. Hammerling, D.M., A.M. Michalak, C. O’Dell, S.R. Kawa (2012) “Global CO2 distributions over land from the Greenhouse Gases Observing Satellite (GOSAT)”, Geophysical Research Letters, 39, L08804, doi:10.1029/2012GL051203.