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Improved Retrievals of Carbon Dioxide from the Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm [Discussion paper]

Authors :
O'Dell, Christopher
Eldering, Annmarie
Wennberg, Paul O.
Crisp, David
Gunson, Michael R.
Fisher, Brendan
Frankenberg, Christian
Kiel, Matthaeus
Lindqvist, Hannakaisa
Mandrake, Lukas
Merrelli, Aronne
Natraj, Vijay
Nelson, Robert R.
Osterman, Gregory
Payne, Vivienne H.
Taylor, Thomas E.
Wunch, Debra
Drouin, Brian J.
Oyafuso, Fabiano
Chang, Albert
McDuffie, James
Smyth, Michael
Baker, David F.
Basu, Sourish
Chevallier, Frédéric
Crowell, Sean
Feng, Liang
Palmer, Paul I.
Dubey, Manvendra K.
García Rodríguez, Omaira Elena
Griffith, David W. T.
Hase, Frank
Iraci, Laura
Kivi, Rigel
Morino, Isamu
Notholt, Justus
Ohyama, Hirofumi
Petri, Christof
Roehl, Coleen M.
Sha, Mahesh Kumar
Strong, Kimberly
Sussmann, Ralf
Te, Yao
Uchino, Osamu
Velazco, Voltaire A.
Source :
ARCIMIS. Archivo Climatológico y Meteorológico Institucional (AEMET), Agencia Estatal de Meteorología (AEMET)
Publication Year :
2018
Publisher :
European Geosciences Union, 2018.

Abstract

Since September 2014, NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100,000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25%, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor quality measurements, and correct the remaining good quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regionalscale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20% over land and 40% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand. Part of this work was conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA) for the Orbiting Carbon Observatory-2 Project. Work at Colorado State University and the Geology and Planetary Sciences Department at the California Institute of Technology was supported by subcontracts from the OCO-2 Project.

Details

Language :
English
Database :
OpenAIRE
Journal :
ARCIMIS. Archivo Climatológico y Meteorológico Institucional (AEMET), Agencia Estatal de Meteorología (AEMET)
Accession number :
edsair.dedup.wf.001..fa774786ec7fb9241da0a8df37471572