Assessing variability in Orbiting Carbon Observatory-2 (OCO-2) XCO2 using high spatial resolution color slices and other retrieval parameters
Abstract
The Orbiting Carbon Observatory-2 (OCO-2) measures reflected sunlight in the Oxygen A-band (0.76 μm), Weak CO2 band (1.61 μm) and Strong CO2 band (2.06 μm) with resolving powers 18,000, 19,500 and 19,500, respectively. Soundings are collected at 3Hz, yielding 8 contiguous <1.3 km x 2.3 km footprints across a narrow (<0.8°) swath. After cloud screening, these high-resolution spectra are used in an optimal estimation retrieval to produce estimates of the column averaged carbon dioxide dry air mole fraction (XCO2). In the absence of strong CO2 absorbers, e.g., intense agricultural regions, or strong emitters, e.g., mega-cities, the variability of XCO2 over small scales, e.g., tens of kilometers, is expected to be less than 1 ppm. However, deviations on the order of +/- 2 ppm, or more, are often observed in the production Version 7 (B7) data product. We hypothesize that most of this variability is spurious, with contributions from both retrieval errors and undetected cloud and aerosol contamination. The contiguous nature of the OCO-2 spatial sampling allows for analysis of the variability in XCO2 and correlation with variables, such as the full spatial resolution "color slices" and other retrieved parameters. Color slices avoid the on-board averaging across the detector focal plane array, providing increased spatial information compared to the nominal spectra. This work explores the new B8 production data set using MODIS visible imagery from the CSU Vistool to provide visual context to the OCO-2 parameters. The large volume of data that has been collected since September 2014 allows for statistical analysis of parameters in relation to XCO2 variability. Some detailed case studies are presented.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A33G2474M
- Keywords:
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- 0325 Evolution of the atmosphere;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 1610 Atmosphere;
- GLOBAL CHANGE;
- 1626 Global climate models;
- GLOBAL CHANGE;
- 1640 Remote sensing;
- GLOBAL CHANGE