Remote Sensing of Tropospheric Water Vapor and Cloud Liquid Water by Integrated Ground-Based Sensors

Abstract

A technique is presented for deriving tropospheric water vapor and cloud liquid water, as well as temperature, from a suite of ground-based sensors. Included in the suite are a dual-channel microwave radiometer, a ceilometer, a radio acoustic sounding system (RASS), and conventional surface meteorological instruments. A linear statistical inversion algorithm, combined with a data classification technique, is applied to retrieve water vapor and cloud liquid water profiles. The linear statistical inversion algorithm is also applied to derive temperature profiles from RASS virtual temperature measurements and surface meteorological parameters. A physical retrieval algorithm is then applied to retrieve integrated water vapor and liquid water. Finally, these two algorithms are coupled in a two-step iteration process. The technique is evaluated by comparing retrieved quantities with radiosonde measurements and by comparing this technique with the traditional technique based solely on dual-channel microwave radiometric measurements. Significant improvement is achieved in retrieving dominant structures in the water vapor profile when liquid clouds are present. This evaluation also predicts significant improvement in measuring integrated liquid water, but lack of ground truth prevented experimental verification.