Cloud Type and Macrophysical Property Retrieval Using Multiple Remote Sensors

Abstract

A cloud detection algorithm based on ground-based remote sensors has been developed that can differentiate among various atmospheric targets such as ice and water clouds, virga, precipitation, and aerosol layers. Standard cloud type and macrophysical properties are identified by combining polarization lidar, millimeter-wave radar, infrared radiometer, and dual-channel microwave radiometer measurements. These algorithms are applied to measurements collected during 1998 from the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed site in north-central Oklahoma. The statistical properties of clouds for this year are presented, illustrating how extended-time remote sensing datasets can be converted to cloud properties of concern to climate research.