Cloud Type Classification and Solid Precipitation Retrieval from Satellite Microwave Sensors

During previous decades the relationships between many geophysical variables and radiometric measurements in the microwaves were translated into several satellite-based algorithms. Recently, several studies have revealed a high correlation between the occurrence of solid precipitation in particular hail and the microwave brightness temperature depression in convective clouds. In this work, we propose a prototype method for cloud type classification and the detection of hailstorms on the basis of the AMSU-B/MHS brightness temperature variation. The method MicroWave Cloud Classification (MWCC) was originally developed for exploring the properties of the water vapor channels in the 183.31 GHz absorption band to classify the observed clouds in terms of stratiform and convective by evaluating the cloud top height. Using the results of the MWCC, deep convections were correlated with selected hailstorm events over Europe, South America and the US. The 10-year period (2000-2009) of the AMSU-B/MHS measurements co-located with surface hail observations were also employed to refine the algorithm criteria. The hail detector of the MWCC is based on a probabilistic model, which calculates the probability associated with each pixel by following the growth law of the hailstones. The validation results over the US have demonstrated the high correlation between the estimation of hail from the MWCC and the surface hail reports showing a remarkable agreement in terms of POD and FAR.