<p><strong>Abstract.</strong> Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. A challenge is how to design strategies to best use these observations to understand the atmosphere and evaluate atmospheric numerical prediction models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution atmospheric models to emulate multi-wavelength, zenith-pointing, and scanning radar

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... s and multi-sensor (multi-radar and radar-lidar) integrated products. CR-SIM allows comparisons of the same variables between an atmospheric model simulation and remote sensing products using a forward modeling framework consistent with the microphysical assumptions used in the numerical model simulations. In this paper, we present several applications of CR-SIM for evaluation of a numerical model, quantification of retrieval uncertainty, and optimization of radar sampling strategy using observing system simulation experiments. These applications demonstrate that the application of CR-SIM as a virtual observatory operator on high-resolution model output helps interpret the differences between model results and observations and also improve under-standing of the representativeness errors due to the sampling limitations of the ground-based observatories. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are freely available to scientific community.</p>