Satellite data coverage and associated issues with bias correction are key challenges for the assimilation of the AIRS (and other satellite) data within a rapidly cycling regional model with a short data cutoff period. In addition, the radiance data assimilated in the RR regional system are further constrained because the RR has a lower model top and fewer levels in the stratosphere compared to many global models, and there is no ozone information. This may result in unrealistic contributions to the analysis increments from some AIRS channels. To examine these issues for the RR system, we have begun with a base-line retrospective experiment using a 3-hourly cycled RR and AIRS radiance data with a 3-h time window (created from the Global Data Analysis System 6-h window AIRS observation files). Despite the sub-optimality of the radiance assimilation system, we have obtained modest forecast improvements from inclusion of the AIRS radiance data. Our retrospective testing work is complemented by an investigation of the weighting functions, as well as the temperature and water vapor Jacobians for the various channels. This analysis will help document deficiencies, facilitating more effectively use AIRS radiance data in the RR. Our work with the 3-hourly cycle is a prelude to examination of the more complex partially cycled hourly update used in the actual RR. One possible design reconfiguration for this system is to assimilate satellite data during the partial cycle, which would allow for a larger data cutoff period (3h or more). At the Symposium, we will describe results to date, ongoing work, and future plans.