The Orbiting Carbon Observatory (OCO) mission (Crisp, D., et al., Adv. Space Res., 34, 700-709, 2004) will make the first global, space-based measurements of atmospheric CO2 with the precision and coverage needed to characterize CO2 sources and sinks on regional scales. During its 2-year mission, OCO will fly in a sun-synchronous orbit with a 16-day ground-track repeat time, just ahead of the EOS Aqua platform. OCO incorporates three bore-sighted high-resolution spectrometers (δν ≈ 0.3 cm-1) to measure reflected sunlight in the O2 A-band (0.76 μm) and two CO2 bands at 1.61 and 2.06 μm, respectively. Each sounding recorded in these three bands will be analyzed simultaneously to retrieve the column-averaged CO2 dry air mole fraction (XCO2) with a retrieval algorithm that incorporates an atmospheric radiative transfer model, an instrument simulator model, and an inverse method (Bösch, H., et al. J. Geophys. Res., 111, D23302, doi:10.1029/2006JD007080, 2006). In order to verify and improve the space-based CO2 measurements, the OCO project incorporates a comprehensive validation program based on ground-based Fourier Transform Spectrometers (FTS) measuring direct sunlight. These high-resolution measurements (δν = 0.011 cm-1; OPD = 45 cm) are ideally suited to OCO validation since their vertical sensitivities are very similar and the same O2 and CO2 absorption bands are used. As an important part of this strategy, solar-absorption spectra will be simultaneously acquired at JPL by an FTS and the OCO spectrometers during its first calibration tests planned in September, 2007. These measurements will be analyzed using the OCO retrieval algorithm as well as GFIT (an algorithm designed specifically for FTS analysis.) We will discuss the planned validation exercise (e.g., FTS vs OCO spectrometry, XCO2 inter-comparison), the solar-absorption measurement and present first results of the OCO instrument line shape (ILS) and the retrieved XCO2.
AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- 0394 Instruments and techniques;
- 1640 Remote sensing (1855)