An overview of the GLAS real-time atmospheric processing algorithms and results from the analysis of simulated GLAS data sets

A new era in atmospheric remote sensing is about to begin. Global monitoring of clouds and aerosols from space using a backscatter lidar system will greatly add to our knowledge in areas such as polar cloud climatology, aerosol loading and transport, and the planetary boundary layer. The Geoscience Laser Altimeter System (GLAS) will produce nearly 5 GB of data per day. A challenge is to create autonomous algorithms that will analyze the data in near-real time. This paper briefly discusses the algorithms and presents results of testing with simulated GLAS data sets.