An Algorithm for Drop-Size Distribution Retrieval From GPM Dual-Frequency Precipitation Radar

作者：Le Minda^*; Chandrasekar V

来源：IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(11): 7170-7185.

DOI：10.1109/TGRS.2014.2308475

• Drop-size distribution (DSD)
• dual-frequency precipitation radar (DPR)
• dual-frequency retrieval
• Global Precipitation Measurement (GPM)
• microphysics

The dual-frequency precipitation radar onboard the Global Precipitation Measurement (GPM) core satellite has reflectivity measurements at two independent frequencies, i.e., Ku-band and Ka-band. Dual-frequency retrieval algorithms have been developed traditionally through forward, backward, and recursive approaches. However, these algorithms suffer from a %26quot;dual value%26quot; problem when they retrieve median volume diameter D-0 from a dual-frequency ratio (DFR) in the rain region. It has been shown in the literature that a linear constraint of the drop-size distribution along the rain profile is a reasonable assumption to avoid the %26quot;dual value%26quot; problem. In this paper, a hybrid method is proposed to retrieve DSDs by combining the forward method and the linear constraint. The forward method is applied to ice and melting ice regions, whereas the linear constraint is applied to the rain region. The method is evaluated using data-based simulation. Different error sources, including sensitivity of snow density, system bias, and attenuation from nonprecipitating particles, are considered. The hybrid method is compared with the surface reference with weak constraint method and the Hitschfeld-Bordan DFR method and shows reasonable comparisons, particularly for medium-to-heavy precipitation. Retrieval examples for Hurricane Earl are shown using the hybrid method.

• 出版日期2014-11