| description abstract | Spectral characteristics of the future Orbiting Carbon Observatory (OCO) sensor, which will be launched in January 2009, were used to infer the carbon dioxide column-averaged mixing ratio over liquid water clouds over ocean by means of radiative transfer simulations and an inversion process based on optimal estimation theory. Before retrieving the carbon dioxide column-averaged mixing ratio over clouds, cloud properties such as cloud optical depth, cloud effective radius, and cloud-top pressure must be known. Cloud properties were not included in the prior in the inversion but are retrieved within the algorithm. The high spectral resolution of the OCO bands in the oxygen absorption spectral region around 0.76 ?m, the weak CO2 absorption band around 1.61 ?m, and the strong CO2 absorption band around 2.06 ?m were used. The retrieval of all parameters relied on an optimal estimation technique that allows an objective selection of the channels needed to reach OCO?s requirement accuracy. The errors due to the radiometric noise, uncertainties in temperature profile, surface pressure, spectral shift, and presence of cirrus above the liquid water clouds were quantified. Cirrus clouds and spectral shifts are the major sources of errors in the retrieval. An accurate spectral characterization of the OCO bands and an effective mask for pixels contaminated by cirrus would mostly eliminate these errors. | |
