The Orbiting Carbon Observatory-2: first 18 months of science data products
By Annmarie Eldering, Christopher W. O'Dell, Paul O. Wennberg, David Crisp, Michael R. Gunson, C. Viatte, C. Avis, A. Braverman, R. Castaño, A. Chang and 31 more. 2016
265 citations recorded by the source corpus.
The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO_2) with the accuracy, resolution, and coverage needed to quantify CO_2 fluxes (sources and sinks) on regional scales. OCO-2 was successfully launched on 2 July 2014 and has gathered more than 2 years of observations. The v7/v7r operational data products from September 2014 to January 2016 are discussed here. On monthly timescales, 7 to 12 % of these measurements are sufficiently cloud and aerosol free to yield estimates of the column-averaged atmospheric CO_2 dry air mole fraction, X_(CO)_2, that pass all quality tests. During the first year of operations, the observing strategy, instrument calibration, and retrieval algorithm were optimized to improve both the data yield and the accuracy of the products. With these changes, global maps of X_(CO)_2 derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes X_(CO)_2 enhancements co-located with intense fossil fuel emissions in eastern US and eastern China, which are most obvious between October and December, when the north–south X_(CO)_2 gradient is small. Enhanced X_(CO)_2 coincident with biomass burning in the Amazon, central Africa, and Indonesia is also evident in this season. In May and June, when the north–south X_(CO)_2 gradient is largest, these sources are less apparent in global maps. During this part of the year, OCO-2 maps show a more than 10 ppm reduction in X_(CO)_2 across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO_2. As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart X_(CO)_2 changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/ff99cbeab99c75728f0ba06fded0265c5fbbdcdc
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In Atmospheric Science
- Paul O. Wennberg
- David Crisp
- Christopher W. O'Dell
- Brendan M. Fisher
- Annmarie Eldering
- Matthäus Kiel
- Paul I. Palmer
- Liang Feng
In Global and Planetary Change
- Paul I. Palmer
- Liang Feng
- Paul O. Wennberg
- David Crisp
- Christopher W. O'Dell
- Brendan M. Fisher
- Annmarie Eldering
- Matthäus Kiel
Citations in the corpus
- How bias correction goes wrong: measurement of XCO2 affected by erroneous surface pressure estimates (2019, methodology): “(2010) CarbonTracker CT2015,CT-NRT.v2016-1 CASA EnKF TM5 Peters et al. (2007) TM5-4DVar-NOAA 2016 SiB-CASA 4D-Var TM5 Basu et al. (2013) OU 2016 CASA 4D-Var TM5 Crowell et al. (2018) Baker CASA-GFEDv3 4D-Var PCTM Baker et al. (2010) CMS-Flux CASA-GFEDv3 4D-Var GEOS-CHEM Liu et al.”
- Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm (2018, methodology): “The construction of the operational OCO-2 filtering and bias correction for B7 is described in detail in Mandrake et al. (2015), with updates for B8 described in an online user’s guide (Eldering et al., 2017b).”