Global ice water content (IWC) measurements from CloudSat together with the Earth Observing System's (EOS) Microwave Limb Sounder (MLS) are used to assess the current status of climate models in simulating upper-tropospheric cloud physical processes. Comparisons are made with European Centre for Medium-Range Weather Forecasts analyses, NASA GMAO GEOS5 and simulations from several state-of-the-art global climate models (GCMs), including GSFC finite volume multiscale-modeling framework (fvMMF) cloud-resolving GCM. However, compatibility of the IWC between CloudSat retrieval and that represented by GCMs needs to be investigated before they can be applied for model evaluation. CloudSat and MLS total amount of retrieved IWC might be mixed with different types of frozen cloud condensate mass (e.g., cloud ice, snow and graupel) and sensitive to the assumptions made in the retrieval algorithm (e.g., particle size and shape). Moreover, GCMs use a range of parameterizations for cloud ice/condensate that includes diagnostic approaches, single moment approach with one prognostic for total cloud condensate mass or allow for more individual cloud condensate mass (e.g., cloud water, cloud ice, snow and graupel), for example fvMMF and CSUMMF. In this study, we will address compatibility of the classification and definition of cloud condensate mass between observations and GCM modeling to best ensure the use of CloudSat and MLS data for model evaluation. The effort is to evaluate the potential usefulness of this new data set for improving GCMs, particularly their upper level cloud microphysical parameterizations.