Evidence of rainfall signature on X-band spaceborne synthetic aperture radar response: models and measurements

Global precipitation measurements are needed by weather and climate modelers because the release of latent heating affects the performance of such models. Precipitation measurements are also required to facilitate management strategies for hydrology, transportation, and agriculture. Since the 1980s much of our understanding of global precipitation has been provided by space-borne passive microwave radiometers. Unfortunately, precipitation retrievals over land from microwave radiometer data have had limited success because they rely on the scattering properties of ice in the upper regions of precipitating clouds. Some of these limitations can be addressed by space-based radars operating at Ku band. The Ku-band Precipitation Radar (PR) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite has provided unprecedented and unique precipitation measurements over land. The high spatial resolution of Synthetic Aperture Radars (SARs) operating at X band can provide new insights into the structure of precipitating clouds. Indeed, the nominal spatial resolution of SAR (of the order of meters) is degraded by the turbulent motion of the storm hydrometeors (to the order of hundreds of meters) due to the broadening of the Doppler-frequency filters used in fixed-target imaging. Within the last decade it has been shown that the shorter wavelengths of X-SARs can enable them to respond to rainfall, even though the impact of the side-looking geometry and the coupling of backscattering and attenuation mechanisms are still open issues. Several X-SARs, that are currently or will soon be placed in orbit, provide a new opportunity to measure precipitation from space such as COSMO-SkyMed (CSK) and the TerraSAR-X (TSX). In order to interpret such X-SAR imagery, We have developed a theoretical and numerical framework to model spaceborne X-SAR response to precipitation systems, characterized by liquid and frozen hydrometeor distributions. The aim of this work is to show evidences of rainfall signatures on CASK and TSX imagery acquired during 2008 not only in a qualitative way, but also in a quantitative way by performing and validating rainfall retrieval from TSX and CSK data. The confirmation of these qualitative and quantitative evidences about CSK and TSX rain signatures can be effectively verified with co-registered weather radar (WR) imagery available during the TSX and CSK overpass. We will introduce basics of X-SAR response interpretation and qualitatively describe some case studies in terms of available CSK and TSX imagery and ground-based WR data. A quantitative correlation analysis will be performed and X-SAR data inversion algorithm will be developed and applied to retrieve rainfall fields.