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A method for evaluating bias in global measurements of CO 2 total columns from space

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TLDR
In this paper, a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space is described, and applied to the v2.8 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land.
Abstract
. We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in XCO2 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 observed correlation between free-tropospheric potential temperature and XCO2 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, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed.

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Journal ArticleDOI

The ACOS CO 2 retrieval algorithm – Part 1: Description and validation against synthetic observations

TL;DR: In this paper, the authors describe the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm and its performance on highly realistic, simulated observations, and evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise.
Journal ArticleDOI

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X CO 2 measurements with TCCON

TL;DR: In this article, the first major release of the OCO2 retrieval algorithm (B7r) and X_(CO2) from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON) were compared.
References
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Journal ArticleDOI

A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation

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