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Volume 9, issue 4
Atmos. Meas. Tech., 9, 1671–1684, 2016
https://doi.org/10.5194/amt-9-1671-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 9, 1671–1684, 2016
https://doi.org/10.5194/amt-9-1671-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 15 Apr 2016

Research article | 15 Apr 2016

The potential of clear-sky carbon dioxide satellite retrievals

Robert R. Nelson1, Christopher W. O'Dell2, Thomas E. Taylor2, Lukas Mandrake3, and Mike Smyth3 Robert R. Nelson et al.
  • 1Colorado State University, Fort Collins, CO, USA
  • 2Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, USA
  • 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

Abstract. Since the launch of the Greenhouse Gases Observing Satellite (GOSAT) in 2009, retrieval algorithms designed to infer the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from hyperspectral near-infrared observations of reflected sunlight have been greatly improved. They now generally include the scattering effects of clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with optically thin cloud or aerosol layers. However, these “full-physics” retrievals tend to be computationally expensive and may incur biases from trying to deduce the properties of clouds and aerosols when there are none present. Additionally, algorithms are now available that can quickly and effectively identify and remove most scenes in which cloud or aerosol scattering plays a significant role.

In this work, we test the hypothesis that non-scattering, or “clear-sky”, retrievals may perform as well as full-physics retrievals for sufficiently clear scenes. Clear-sky retrievals could potentially avoid errors and biases brought about by trying to infer properties of clouds and aerosols when none are present. Clear-sky retrievals are also desirable because they are orders of magnitude faster than full-physics retrievals. Here we use a simplified version of the Atmospheric Carbon Observations from Space (ACOS) XCO2 retrieval algorithm that does not include the scattering and absorption effects of clouds or aerosols. It was found that for simulated Orbiting Carbon Observatory-2 (OCO-2) measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had errors 0–20 % larger than the full-physics retrieval over land and errors roughly 20–35 % larger over ocean, depending on filtration level. In general, the clear-sky retrieval had XCO2 root-mean-square errors (RMSEs) of less than 2.0 ppm, relative to Total Carbon Column Observing Network (TCCON) measurements and a suite of CO2 models, when adequately filtered through the use of a custom genetic algorithm filtering system. These results imply that non-scattering XCO2 retrievals are potentially more useful than previous literature suggests, as the filtering methods we employ are able to remove measurements in which scattering can cause significant errors. Additionally, the computational benefits of non-scattering retrievals means they may be useful for certain applications that require large amounts of data but have less stringent error requirements.

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In this work, we test the hypothesis that clear-sky retrievals may perform as well as full-physics retrievals for very clear scenes. It was found that for simulated OCO-2 measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had errors 0–20 % larger than the full-physics retrieval over land and 20–35 % larger over ocean. This work implies that clear-sky retrievals may be more useful than previously assumed.
In this work, we test the hypothesis that clear-sky retrievals may perform as well as...
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