Modeling and measurement of rainfall by ground-based multispectral microwave radiometry

The potential of ground-based multispectral microwave radiometers in retrieving rainfall parameters is investigated by coupling physically oriented models and retrieval methods with a large set of experimental data. Measured data come from rain events that occurred in the USA at Boulder, Colorado, and at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site in Lamont, OK. Rain cloud models are specified to characterize both nonraining clouds, stratiform and convective rainfall. Brightness temperature numerical simulations are performed for a set of frequencies from 20 to 60 GHz at zenith angle, representing the channels currently deployed on a commercially available ground-based radiometric system. Results are illustrated in terms of comparisons between measurements and model data in order to show that the observed radiometric signatures can be attributed to rainfall scattering and absorption. A new statistical inversion algorithm, trained by synthetic data and based on principal component analysis is also developed to classify the meteorological background, to identify the rain regime, and to retrieve rain rate from passive radiometric observations. Rain rate estimate comparisons with simultaneous rain gauge data and rain effect mitigation methods are also discussed.