Initial results show that the ability of CIP to correctly diagnose positive icing conditions (PODy) degrades as the age of METAR and satellite data increases. The volume of icing probability diagnosed by CIP is also higher in the cases using older data than those using the most up-to-date information, indicating a disconnect between that dataset and the other up-to-date datasets being blended together in CIP. These effects have been noted in the full CIP domain, but results suggest that they may be more pronounced near the edges of large cloud features. Identifying these regions to further investigate the impacts of older data may yield improved results. Older satellite and METAR data may incorrectly represent the existence of clouds over a particular gridpoint within the CIP domain. In reality that gridpoint may actually be clear due to clouds (or other favorable icing conditions) exiting the area. Identifying the frequency with which situations like this occur is a primary goal of this study. In addition to examining the impact of data age, variations in the icing intensity reports from voice PIREPs will also be evaluated. Voice PIREPs of in-flight icing currently offer the only in-situ observations of icing available to CIP. However, additional in-situ observations of parameters indicative of in-flight icing conditions do exist. These observations could provide additional benefit to the CIP, both for the identification of in-flight icing conditions and for the confirmation of ice-free airspace, if made available. The distribution of icing intensity values and concentration of in-flight icing observations will be varied to observe the impact on the resulting icing probability and severity diagnosis by the CIP.