This study finds improved ice water content estimates in deep convective systems, suggesting methods combining radar and radiometer measurements are effective.
Key Points
The retrieval method incorporates both a deep neural network and an optimal estimation technique, enhancing accuracy in measuring frozen hydrometeors.
Results show a significant reduction in retrieval errors when combining millimeter-wave radar and radiometer data compared to using radar alone.
The study demonstrates the algorithm's capability to accurately reproduce reflectivity and brightness temperatures from multiple radar observations.
Future research aims to extend these methods with new satellite missions, particularly focusing on enhancing the understanding of cloud ice properties.