Infrared atmospheric sounder interferometer radiometric noise assessment from spectral residuals.

The problem of characterizing and estimating the radiometric noise of satellite high spectral resolution infrared spectrometers from Earth views is addressed in this paper. A methodology has been devised which is based on the common concept of spectral residuals (Observations-Calculations) obtained after spectral radiance inversion for atmospheric and surface parameters. An in-depth analytical assessment of the statistical covariance matrix of the spectral residuals has been performed which is based on the optimal estimation theory. It has been mathematically demonstrated that the use of spectral residuals to assess instrument noise leads to an effective estimator, which is largely independent of possible departures of the observational covariance matrix from the true covariances. Application to the Infrared Atmospheric Sounder Interferometer has been considered. It is shown that Earth-view-derived observation errors agree with blackbody in-flight calibration. The spectral residuals approach also proved to be effective in characterizing noise features due to mechanical microvibrations of the beam splitter of the IASI instrument.

Spaceborne estimate of atmospheric CO2 column by use of the differential absorption method: error analysis.

For better knowledge of the carbon cycle, there is a need for spaceborne measurements of atmospheric CO2 concentration. Because the gradients are relatively small, the accuracy requirements are better than 1%. We analyze the feasibility of a CO2-weighted-column estimate, using the differential absorption technique, from high-resolution spectroscopic measurements in the 1.6- and 2-microm CO2 absorption bands. Several sources of uncertainty that can be neglected for other gases with less stringent accuracy requirements need to be assessed. We attempt a quantification of errors due to the radiometric noise, uncertainties in the temperature, humidity and surface pressure uncertainty, spectroscopic coefficients, and atmospheric scattering. Atmospheric scattering is the major source of error [5 parts per 10 (ppm) for a subvisual cirrus cloud with an assumed optical thickness of 0.03], and additional research is needed to properly assess the accuracy of correction methods. Spectroscopic data are currently a major source of uncertainty but can be improved with specific ground-based sunphotometry measurements. The other sources of error amount to several ppm, which is less than, but close to, the accuracy requirements. Fortunately, these errors are mostly random and will therefore be reduced by proper averaging.