The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below.

1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, the AIRS Version 5 temperature profile retrieval step uses only 15 micron CO2 radiances for those channels sensitive to atmospheric emission in the stratosphere. Tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Tropospheric sounding 15 micron CO2 observations are used heavily in the determination of the parameters necessary to generate for all sounding channels. This approach allows for the generation of accurate values of and T(p) under most cloud conditions.

2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances . These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profile is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. As Quality Control thresholds (three separate thresholds are used in the determination of pg) are tightened, spatial coverage of temperatures called accepted for data assimilation at a given pressure level decreases, while the RMS accuracy of the temperatures increases (lower errors).

We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM, at a spatial resolution of 0.5 deg by 0.5 deg. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated.