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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2018-366
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2018-366
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Nov 2018

Research article | 21 Nov 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

The Impact of Improved Aerosol Priors on Near-Infrared Measurements of Carbon Dioxide

Robert R. Nelson1 and Christopher W. O'Dell2 Robert R. Nelson and Christopher W. O'Dell
  • 1Colorado State University, Fort Collins, CO, USA
  • 2Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado, USA

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) was launched in 2014 with the goal of measuring the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with sufficient precision and accuracy to infer regional carbon sources and sinks. One of the primary sources of error in near-infrared measurements of XCO2 is the scattering effects of cloud and aerosol layers. In this work, we study the impact of ingesting intelligent aerosol priors from the Goddard Earth Observing System Model, Version 5 (GEOS-5) into the OCO-2 ACOS V8 retrieval algorithm with the objective of reducing the error in XCO2 from real measurements. Multiple levels of both aerosol setup complexity and uncertainty on the aerosol priors were tested, ranging from a mostly unconstrained aerosol optical depth (AOD) setup to ingesting full aerosol profiles with high confidence. We find that using co-located GEOS-5 aerosol types and AODs with low uncertainty results in a small improvement in the retrieved XCO2 against the Total Carbon Column Observing Network relative to V8. In contrast, attempting to use modeled vertical information in the aerosol prior to improve the XCO2 retrieval generally gives poor results, as aerosol models struggle with the vertical placement of aerosol layers. To assess regional differences in XCO2, we compare our results to a global CO2 model validation suite. We find that the GEOS-5 setup performs better than V8 over Northern Africa and Central Asia, with the standard deviation of the XCO2 error reduced from 2.12ppm to 1.83ppm, due to a combination of smaller prior AODs and lower prior uncertainty. In general, the use of more intelligent aerosol priors shows promise but is currently restricted by the accuracy of aerosol models.

Robert R. Nelson and Christopher W. O'Dell
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Robert R. Nelson and Christopher W. O'Dell
Robert R. Nelson and Christopher W. O'Dell
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Latest update: 18 Dec 2018
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Short summary
Accurate measurements of carbon dioxide are important to learn more about climate change. In this work, we try to improve measurements of carbon dioxide from the Orbiting Carbon Observatory-2 by using more intelligent information about particles in the air from an atmospheric model. We find that this makes the carbon dioxide measurements slightly better and that certain ways of using modeled particle information are more promising than others.
Accurate measurements of carbon dioxide are important to learn more about climate change. In...
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