A method for evaluating bias in global measurements of CO2 total columns from space.

We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO₂ (X_CO2) from space, and we illustrate the method by applying the method to the Atmospheric CO₂ Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) v2.8 data. The approach exploits the lack of large gradients in X_CO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the correlation between free-tropospheric temperature and X_CO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors. [ABSTRACT FROM AUTHOR]