Ground-based multi-frequency microwave radiometry for rainfall remote sensing

Inversion algorithms for ground-based microwave radiometric retrieval of surface rain-rate, integrated cloud parameters, and slant-path attenuation are proposed and tested. The estimation methods are trained by numerical simulations of a radiative transfer model applied to microphysically-consistent precipitating cloud structures, representative of stratiform and convective rainy clouds. The discrete-ordinate method is used to solve the radiative transfer equation for plane-parallel seven-layer structures, including liquid, melted, and ice spherical hydrometeors. Besides ordinary multiple regression, a variance-constrained regression algorithm is developed and applied to synthetic data in order to evaluate its robustness to noise and its potentiality. Selection of optimal frequency sets and polynomial retrieval algorithms for rainfall parameters is carried out and discussed. Ground-based radiometric measurements at 13.0, 23.8, and 31.7 GHz are used for experimentally testing the retrieval algorithms. Comparison with rain-gauge data and rain path-attenuation measurements, derived from the three ITALSAT satellite beacons at 18.7, 39.6, and 49.5 GHz acquired at Pomezia (Rome, Italy), are performed for two selected cases of moderate and intense rainfall during 1998. Results show a fairly good agreement between retrieved and measured rainfall parameters, pointing out possible effects of nonhomogeneous beam filling at low frequencies when observing small convective cells.