Current satellite cloud retrievals are usually based on the assumption that all clouds consist of a homogenous single layer despite the frequent occurrence of cloud overlap. As such, cloud overlap will cause large errors in the retrievals of many cloud properties. To address this problem, a multilayered cloud retrieval system (MCRS) is developed by combining satellite visible and infrared radiances and surface microwave radiometer measurements. A two-layer cloud model was used to simulate ice-over-water cloud radiative characteristics. The radiances emanating from the combined low cloud and surface are estimated using the microwave liquid water with an assumption of effective droplet size. These radiances replace the background radiances traditionally used in single-layer cloud retrievals. The MCRS is applied to data from March through October 2000 over four Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) sites. The results are compared to the available retrievals of ice water path (IWP) from radar data and show that the MCRS clearly produces a more accurate retrieval of ice-over-water cloud properties. MCRS yields values of IWP that are closest to those from the radar retrieval. For ice-over-water cloud systems, on average, the optical depth and IWP are reduced, from original overestimates, by approximately 30%. The March--October mean cloud effective temperatures from the MCRS are decreased by 10 ¿ 12 K, which translates to an average height difference of ~1.4 km. These results indicate that ice-cloud height derived from traditional single-layer retrieval is underestimated, and the midlevel ice cloud coverage is over classified. Effective ice crystal particle sizes are increased by only a few percent with the new method. This new physically based technique should be robust and directly applicable when data are available simultaneously from a satellite imager and the appropriate satellite or surface microwave sensor.