A Multi-Sensor Approach to the Remote Sensing of Water Vapor Profiles in a Cloudy Atmosphere Project (Task 8)

This research project in the Center for Geosciences has reported good preliminary results over the ocean in the reports and papers. The research uses a new Bayesian retrieval algorithm and requires input from concurrent SSM/T2 and SSM/I data from DMSP satellites along with GOES imager data. Like Task 5, it definitely needs good validation data sets over land.

The tests we will seek during CLEX involve sampling diverse water vapor profiles along an orbit swath. For example, a classic "dry-line" situation which we hope to encounter in the Great Plains would be a good test of the new research. Because the methodology is designed to operate in the presence of non-precipitating cloud layers we will use CLEX airborne and/or ground-based observations to identify cloud tops, bases, and liquid water contents. Then the Task 8 team will use the CLEX cases to retrieve water vapor profiles and to improve their method and uncertainty limits. We expect several days of CLEX data collection under the "T2" observations from DMSP-F12.