Effects of data selection on the assimilation of AIRS data

The Atmospheric InfraRed Sounder (AIRS), flying aboard NASA's Earth Observing System (EOS) Aqua satellite with the Advanced Microwave Sounding Unit-A (AMSU-A), has been providing data for use in numerical weather prediction (NWP) and data assimilation systems (DAS) for over three years. The full AIRS data set is currently not transmitted in near-real-time (NRT) to the NWP centers. Instead, data sets with reduced spatial and spectral information are produced and made available in NRT. In this paper, we evaluate the use of different channel selections and error specifications. We achieved significant positive impact from the Aqua AIRS/AMSU-A combination in both hemispheres during our experimental time period of January 2003. The best results were obtained using a set of 156 channels that did not include any in the 6.7micron water vapor band. The latter have a large influence on both temperature and humidity analyses. If observation and background errors are not properly specified, the partitioning of temperature and humidity information from these channels will not be correct, and this can lead to a degradation in forecast skill. We found that changing the specified channel errors had a significant effect on the amount of data that entered into the analysis as a result of quality control thresholds that are related to the errors. However, changing the channel errors within a relatively small window did not significantly impact forecast skill with the 155 channel set. We also examined the effects of different types of spatial data reduction on assimilated data sets and NWP forecast skill. Whether we picked the center or the warmest AIRS pixel in a 3x3 array affected the amount of data ingested by the analysis but had a negligible impact on the forecast skill