Fourteenth ARM Science Team Meeting Proceedings, Albuquerque, New Mexico, March 22-26, 2004 Monitoring of Precipitable Water Vapor and Cloud Liquid Path from Scanning Microwave Radiometers During the 2003 Cloudiness Inter-Comparison Experiment V. Mattioli Department of Electronic and Information Engineering University of Perugia Perugia, Italy E. R. Westwater Cooperative Institute for Research in Environmental Sciences University of Colorado National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado V. Morris Pacific Northwest National Laboratory Richland, Washington Introduction Ground-based microwave radiometers (MWR) are widely used to measure atmospheric precipitable water vapor (PWV) and cloud liquid path (CLP). Comparisons of PWV derived from MWRs with water vapor retrievals from instruments like radiosondes, Global Positioning System (GPS) and Raman lidar are described in (Westwater 1993, Rocken et al. 1995, Basili et al. 2001, Han et al. 1994), but estimates of CLP are less characterized at present, since cloud liquid is not directly measured by RAOBs. Comparisons with aircraft in situ measurements have been made (Westwater et al. 2001), but further investigations are needed. This work is intended to explore the scanning capability of ground- based MWRs. MWR measurements were analyzed to retrieve the spatial distributions of PWV and CLP in the atmosphere, with the aim of improving the accuracy of parameterizations describing processes involved in the formation and evolution of clouds. Three dual-channel scanning MWRs at 23.8 and 31.4 GHz were continuously operated for two months (March and April 2003) during the Cloudiness Inter- Comparison Experiment (CIC) intensive operating period (IOP). The IOP was conducted at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site in north- central Oklahoma. Data from the three MWRs were compared during clear-sky condition to assess their agreement. Differences of the order of 0.3 K root mean square (rms) were obtained. Clear conditions were determined by using lidar measurements. Two different tipping calibration algorithms were applied, the Environmental Technology Laboratory (ETL) calibration method (Han and Westwater 2000) and the ARM calibration algorithm (Liljegren 1