Uncertainties in the representation of clouds and their sensitivities are largely responsible for the high degree of uncertainty associated with the magnitude of model-predicted climate change induced by human modification of aerosols, carbon dioxide, and other trace gases. Part of the reason is that cloud processes occur at scales much smaller than the grid size of climate models and they must be parameterized. In Brookhaven National Laboratory, we are attacking the cloud problem from two angles: observation and modeling. With the support from the DOE Atmospheric Radiation Measurement program, we have developed several novel remote sensing techniques to retrieve three-dimensional (3D) distribution of cloud liquid water. The first of these techniques is called "microwave cloud tomography", which uses multiple ground-based passive microwave sensor to probe cloud thermal emissions from distinct directions and locations and reconstruct 3D cloud structure using a tomographic approach (CT technique). We have also developed a technique that uses radar attenuation calculated from a dual-frequency cloud radar, instead of radar reflectivity (the sixth moment of size distribution) to determine cloud liquid water content. These 3D cloud observations can be used not only to derive cloud climatology but also to characterize subgrid-scale cloud variability and structure that are essential for the cloud and radiation transfer parameterization problems.
Branch Seminar Series Coordinators:Lazaros.Oraiopoulos@nasa.govCharles.K.Gatebe@nasa.gov