Uncertainty in the treatment of clouds in climate models generates large uncertainty in predicting the climate response to greenhouse gas and aerosol forcing. By explicitly resolving the dynamics and thermodynamics of clouds and their interactions with the environment, Cloud Resolving Models (CRMs) are useful tools for developing physical understanding and parameterizations of cloud processes. In the Multi-scale Modeling Framework (MMF), CRMs are used to explicitly simulate clouds at the subgrid scale. Recognizing the increasingly important role of CRMs in climate modeling, this study aims to evaluate the ability of CRMs in simulating clouds and precipitation. Two sets of cloud resolving simulations are being performed for a three months period from May 1 – July 31, 2002 that covers the International H2O Project (IHOP 2002) field experiment. The Weather Research and Forecast (WRF) model is applied at 1 km horizontal spatial resolution over the U.S. Southern Great Plains. In the first set of simulation, WRF is applied in a weather forecast mode where simulations are initialized each day at 00Z and run for 24 hours. The second simulation is a continuous climate simulation initialized only once on May 1, 2002. Lateral boundary conditions for these simulations are provided by the Eta Regional Reanalysis at 32 km spatial resolution. These simulations will be evaluated using the IHOP 2002 data, which includes measurements collected from an extensive array of operational and experimental instruments. Analysis of observations and simulations will focus on the water cycle, particularly cloud, radiation, and land surface hydrology. Comparison of the two sets of simulations will contrast the ability of cloud resolving model in reproducing the temporal and spatial statistics of the water cycle and elucidate the impacts of cloud-radiation and land-atmosphere feedbacks.