The vertical distribution of atmospheric moisture is important to adequately characterize many meteorologically significant conditions. Although satellite measurements of humidity information has been assimilated to improve weather forecasting, typically only clear-sky data are used. This disregards cloudy satellite observations of many weather phenomenon and their potential cloudy precursors. The Regional Atmospheric Modeling and Data Assimilation System (RAMDAS) has been developed at CSU/CIRA to enable the assimilation of satellite radiances in clear and cloudy regions. An application using the Geostationary Operational Environmental Satellite (GOES) imager infrared channels has already revealed improvement in the cloud environment assimilation capabilities.

This work focuses on the use of the GOES sounder data which measures hourly radiances emerging from different vertical layers of the atmosphere to provide a moisture profiling capability. In preparation of assimilating this data into the RAMDAS system, a set of sensitivity analyses are performed using a cloudy observational operator called the visible-infrared observational operator (VISIROO). This provides an estimate of the potential impact of each channel within the data assimilation system. The experiments use GOES 8 and 10 sounder channels (channels 1-18) for a March 2000 case study that contains a variety of cloud conditions. These new GOES sounder sensitivity results will be presented and discussed, focusing on their potential use within the new all weather (cloudy and clear) data assimilation system.