Although the visible channel of the Imagers carried by NOAA's operational Geostationary Operational Environmental Satellites (GOES) has no onboard calibration device, the decrease in the responsivity of this channel over time must be known if we are to make the data in this channel useful for detecting trends in the signals from the Earth. Therefore, some external method is required to provide this information. In this paper, we examine an external technique for monitoring responsivity changes based on empirical distribution functions (EDFs) of observations of the Earth's full disk. A time series of instrument outputs (in digital counts) at fixed levels at the tops of the EDFs is produced. A nonlinear least squares technique is then employed to adjust the time series for solar and seasonal effects and to fit it with an exponential, whose argument provides the rate of degradation of the responsivity. This technique assumes that the probabilistic structure of the signal from the earth does not change over time. The resulting time series and estimated responsivity degradation rates for the visible channels of GOES-8 and -10 Imagers will be presented. These results are similar to those obtained earlier with a star-based technique, thus increasing our confidence in the results of both techniques. The EDF technique and the star-based technique are synergistic, as they use very different approaches and data sets. Also, the star based technique works at the low end of the Imager's output signal range, whereas the EDF technique works at the high end.
The AIRS instrument was launched on the Aqua satellite in May of
2002. In addition to the core level 2 products, that include cloud
cleared radiances; temperature, moisture, and ozone profiles; surface
skin temperature; NDVI (from AIRS visible channels); surface spectral
emissivity and reflectivity; and cloud products, the AIRS science team is also developing research algorithms for the retrieval of carbon monoxide (CO), methane (CH4), and carbon dioxide (CO2). These algorithms are being tested by the National Oceanographic and Atmosphere Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) in simulation and applied to real AIRS radiances. The trace gas retrievals require cloud free infrared radiances. In practice, we observe that AIRS measurements without cloud contamination occur less than 5% of the time. A key feature of the AIRS algorithm is the utilization of cloud cleared radiances that removes the effects of clouds and increases the yield of trace gas products to 50-60%. The increased yield should allow a better assessment of sources and sinks of these gases. Determination of sources and sinks of these trace gas requires an unprecedented precision for a remote sounding measurement. In addition, both the variability and errors in the trace gas products tend to be correlated with variability and errors in other products (e.g., clouds, temperature, moisture, and ozone profile). Multi-spectral, high-resolution measurements can minimize the effects of this correlation. Currently, for the AIRS products, we estimate a precision of 15% for CO, 0.5% for CO2 and 1% for CH4. The remote sounding methodology for these trace gases is discussed in detail. The METOP IASI and NPOESS CrIS instruments can extend the continuity of these trace gas products over the next two decades. Simulation experiments are used to assess the relative performance of the trace gas retrievals from these sounders.
The AIRS instrument has a large number (2378) of potential channels. For use for observing meteorological parameters, several methods have been proposed and/or used. These include selecting a subset of channels, using eigenvectors, and using "super channels", which are averages of channels which view similar atmospheric features. The channels are selected using a constraint on the wavelength range to be covered, then selecting all the channels that have similar transmittances to be combined in one "super channel". Super channels have a number of features that make them attractive. They use all the information to reduce the noise and are efficient to use since both rapid transmittance models and equivalent Planck functions can be generated. This means that it requires the same effort to calculate the radiance for one super channel as for a single AIRS channel. Super channels and Planck function have been calculated for AIRS instrument and a rapid transmittance model is being used to generate coefficients to allow a rapid calculation of the corresponding transmittances. Results using the super channels compared to measures of the truth from forecast models and radiosondes will be shown.