Simulation of satellite lidar and radiometer retrievals of a general circulation model three-dimensional cloud data set

The inclusion of a backscatter lidar on a space platform for a radiation mission, as proposed by various space agencies, aims to bring new information on three-dimensional cloud distribution, with a special emphasis on optically thin cirrus clouds, which are presently poorly detected by passive sensors. Key issues for such cloud observational studies are the detection of multilayered cloud systems, thin cirrus, and fractional cloud cover, knowledge that would improve our understanding of the global radiation budget. To assess the impact of such lidar measurements on cloud climatology, a 1 month cloud data set has been simulated with a general circulation model (GCM). The cloud detection capability of a spaceborne scanning backscatter lidar is assessed with the use of two detection schemes, one based on limitations in the detected cloud optical depth and the other based on lidar signal-to-noise ratio. The cloud information retrieved from passive radiometric measurements using a procedure like that used in the International Satellite Cloud Climatology Project is also simulated from the same GCM cloud data set. It is shown that a spaceborne backscatter lidar can improve significantly the retrieval of thin cirrus clouds as well as underlying cloud layers. High-level cloud retrieval from a spaceborne lidar therefore appears as a powerful complement to radiometric measurements for improving our knowledge of actual cloud climatology.