| description abstract | Global precipitation measurements from space-based radars and microwave radiometers have been the subject of numerous studies during the past decade. Rainfall retrievals over land from spaceborne microwave radiometers depend mainly on scattering from frozen hydrometeors. Unfortunately, the relationship between frozen hydrometeors and rainfall varies considerably. The large field of view and related beam filling of microwave radiometer footprints introduce additional difficulties. Some of these problems will be addressed by the improved sensors that will be placed on the Global Precipitation Measurement (GPM) core satellite. Two shuttle missions demonstrated that X-band synthetic aperture radar (X-SAR) could observe rainfall over land. Several X-band SARs that can provide such measurements will be launched in the coming decade. These include four Constellation of Small Satellites for Mediterranean Basin Observations (COSMO-SkyMed), two TerraSAR-X, and a fifth Korea Multipurpose Satellite (KOMPSAT-5) to be launched by the Italian, German, and Korean Space Agencies, respectively. Data from these satellites could augment the information available to the GPM science community. The present study presents computations of normalized radar cross sections (NRCS) that employed a simple, idealized two-layer cloud model that contained both rain and frozen hydrometeors. The modeled spatial distributions of these hydrometeors varied with height and horizontal distance. An exploratory algorithm was developed to retrieve the shape, width, and simple representations of the vertical profiles of frozen hydrometeors and rain from modeled NRCS scans. A discussion of uncertainties in the retrieval is presented. | |
