Articles | Volume 9, issue 10
https://doi.org/10.5194/amt-9-5227-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-5227-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Quantification of uncertainties in OCO-2 measurements of XCO2: simulations and linear error analysis
Brian Connor
CORRESPONDING AUTHOR
BC Scientific Consulting, Stony Brook, NY, USA
Hartmut Bösch
EOS Group, Department of Physics and Astronomy, University
of Leicester, Leicester, UK
National Centre for Earth Observation NCEO, University of Leicester,
Leicester, UK
James McDuffie
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Tommy Taylor
Cooperative Institute for Research in the Atmosphere, Fort Collins,
CO, USA
Dejian Fu
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Christian Frankenberg
California Institute of Technology, Pasadena, CA, USA
Chris O'Dell
Cooperative Institute for Research in the Atmosphere, Fort Collins,
CO, USA
Vivienne H. Payne
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Michael Gunson
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Randy Pollock
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Jonathan Hobbs
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Fabiano Oyafuso
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Yibo Jiang
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
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- Satellite-Based Reconstruction of Atmospheric CO2 Concentration over China Using a Hybrid CNN and Spatiotemporal Kriging Model Y. Hua et al. 10.3390/rs16132433
- The fingerprint of the summer 2018 drought in Europe on ground-based atmospheric CO2measurements M. Ramonet et al. 10.1098/rstb.2019.0513
- Evaluation of single-footprint AIRS CH<sub>4</sub> profile retrieval uncertainties using aircraft profile measurements S. Kulawik et al. 10.5194/amt-14-335-2021
- Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR version 1 product N. Saitoh et al. 10.5194/amt-10-3877-2017
- Impacts of MOPITT cloud detection revisions on observation frequency and mapping of highly polluted scenes M. Deeter et al. 10.1016/j.rse.2021.112516
- Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm T. Taylor et al. 10.5194/amt-16-3173-2023
- Application of a PCA‐Based Fast Radiative Transfer Model to XCO2 Retrievals in the Shortwave Infrared P. Somkuti et al. 10.1002/2017JD027013
- Assessing accuracy and precision for space‐based measurements of carbon dioxide: An associated statistical methodology revisited Z. Su et al. 10.1002/2016EA000228
- Aerosols in OCO-2/GOSAT retrievals of XCO2: An information content and error analysis S. Sanghavi et al. 10.1016/j.rse.2020.112053
- The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty G. McGarragh et al. 10.5194/amt-17-1091-2024
- The Orbiting Carbon Observatory-2: first 18 months of science data products A. Eldering et al. 10.5194/amt-10-549-2017
- Monitoring methane emissions from oil and gas operations‡ W. Collins et al. 10.1364/OE.464421
- Post hoc Uncertainty Quantification for Remote Sensing Observing Systems A. Braverman et al. 10.1137/19M1304283
- Direct retrieval of isoprene from satellite-based infrared measurements D. Fu et al. 10.1038/s41467-019-11835-0
- Quantifying strong point sources emissions of CO2 using spaceborne LiDAR: Method development and potential analysis T. Shi et al. 10.1016/j.enconman.2023.117346
Latest update: 23 Nov 2024
Short summary
We present an analysis of uncertainties in global measurements of the column-averaged dry-air mole fraction of CO2 (XCO2) by the satellite OCO-2. The analysis is based on our best estimates for uncertainties in the OCO-2 operational algorithm and its inputs. From these results we estimate the "variable error", which differs between soundings, to infer the error in the difference of XCO2 between any two soundings. Variable errors are usually < 1 ppm over ocean and ~ 0.5–2 ppm over land.
We present an analysis of uncertainties in global measurements of the column-averaged dry-air...